Niessen, W.J.

Improving alignment in Tract-based spatial statistics: Evaluation and optimization of image registration (Article)

2013-08-01T00:00:00Z

Anatomical alignment in neuroimaging studies is of such importance that considerable effort is put into improving the registration used to establish spatial correspondence. Tract-based spatial statistics (TBSS) is a popular method for comparing diffusion characteristics across subjects. TBSS establishes spatial correspondence using a combination of nonlinear registration and a "skeleton projection" that may break topological consistency of the transformed brain images. We therefore investigated feasibility of replacing the two-stage registration-projection procedure in TBSS with a single, regularized, high-dimensional registration.To optimize registration parameters and to evaluate registration performance in diffusion MRI, we designed an evaluation framework that uses native space probabilistic tractography for 23 white matter tracts, and quantifies tract similarity across subjects in standard space. We optimized parameters for two registration algorithms on two diffusion datasets of different quality. We investigated reproducibility of the evaluation framework, and of the optimized registration algorithms. Next, we compared registration performance of the regularized registration methods and TBSS. Finally, feasibility and effect of incorporating the improved registration in TBSS were evaluated in an example study.The evaluation framework was highly reproducible for both algorithms (R20.993; 0.931). The optimal registration parameters depended on the quality of the dataset in a graded and predictable manner. At optimal parameters, both algorithms outperformed the registration of TBSS, showing feasibility of adopting such approaches in TBSS. This was further confirmed in the example experiment.

Automatic carotid artery distensibility measurements from CTA using nonrigid registration (Article)

2013-07-01T00:00:00Z

The distensibility of a blood vessel is a marker of atherosclerotic disease. In this paper we investigate the feasibility of measuring carotid artery distensibility on 4D CTA, both manually and using a new automatic method. On 4D CTA datasets manual (n= 38) and automatic (n= 76) measurements of the carotid distensibility were performed. A subset (n= 10) of the manual annotations were repeated by a second observer. The interobserver variability was assessed using a Bland-Altman analysis and appeared to be too large to reliably measure the distensibility using manual annotation. We compared two versions of the automatic method: one using 3D registration and one using a 4D registration method. The latter resulted in a more smooth deformation over time. The automatic method was evaluated using a synthetic deformation and by investigating whether known relations with cardiovascular risk factors could be reproduced. The relation between distensibility and cardiovascular risk factors was tested with a Mann-Whitney U test. Automatic measurements revealed an association with hypertension whereas the manual measurements did not. This relation has been found by other studies too. We conclude that carotid artery distensibility measurements should be performed automatically and that the method described in this paper is suitable for that.

The Relation of Uric Acid to Brain Atrophy and Cognition: The Rotterdam Scan Study. (Article)

2013-03-19T00:00:00Z

Background: Uric acid has been associated with focal vascular brain disease. However, it is unknown whether uric acid also relates to global brain changes such as brain atrophy. We therefore studied the relation of uric acid to brain atrophy and whether this is accompanied by worse cognitive function. Methods: In 814 persons of the population-based Rotterdam Study (mean age 62.0 years), we studied the relation of uric acid levels to brain tissue atrophy and cognition using linear regression models adjusted for age, sex and putative confounders. Brain atrophy was assessed using automated processing of magnetic resonance imaging. Cognition was assessed using a validated neuropsychological test battery and we computed compound scores of cognitive domains. Results: Higher uric acid levels were associated with white matter atrophy [difference in Z-score of white matter volume per standard deviation increase in uric acid: -0.07 (95% CI: -0.12; -0.01)], but not with gray matter atrophy. This was particularly marked when comparing hyperuricemic to normouricemic persons [Z-score difference: -0.27 (-0.43; -0.11)]. Worse cognition was primarily found in persons with hyperuricemia [-0.28 (-0.48; -0.08)]. Conclusions: Hyperuricemia is related to white matter atrophy and worse cognition. Copyright

Image registration improves human knee cartilage T1 mapping with delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) (Article)

2013-01-01T00:00:00Z

Objectives: To evaluate the effect of automated registration in delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) of the knee on the occurrence of movement artefacts on the T1 map and the reproducibility of region-of-interest (ROI)-based measurements. Methods: Eleven patients with early-stage knee osteoarthritis and ten healthy controls underwent dGEMRIC twice at 3 T. Controls underwent unenhanced imaging. ROIs were manually drawn on the femoral and tibial cartilage. T1 calculation was performed with and without registration of the T1-weighted images. Automated three-dimensional rigid registration was performed on the femur and tibia cartilage separately. Registration quality was evaluated using the square root Cramér-Rao lower bound (CRLBσ). Additionally, the reproducibility of dGEMRIC was assessed by comparing automated registration with manual slice-matching. Results: Automated registration of the T1-weighted images improved the T1 maps as the 90% percentile of the CRLBσwas significantly (P < 0.05) reduced with a median reduction of 55.8ms (patients) and 112.9ms (controls). Manual matching and automated registration of the re-imaged T1 map gave comparable intraclass correlation coefficients of respectively 0.89/0.90 (patients) and 0.85/0.85 (controls). Conclusions: Registration in dGEMRIC reduces movement artefacts on T1 maps and provides a good alternative to manual slice-matching in longitudinal studies. Key Points: • Quantitative MRI is increasingly used for biomedical assessment of knee articular cartilage • Image registration leads to more accurate quantification of cartilage quality and damage • Movement artefacts in delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) are reduced • Automated image registration successfully aligns baseline and follow-up dGEMRIC examinations • Reproducibility of dGEMRIC with registration is similar to that using manual slice-matching

Structural and diffusion MRI measures of the hippocampus and memory performance (Article)

2012-12-01T00:00:00Z

Hippocampal atrophy on MRI and changes in diffusion tensor imaging (DTI) measures of the hippocampus have been reported in patients with Alzheimer's disease. We examined the association between hippocampal volumes, DTI measures of the hippocampus and memory performance in 892 non-demented persons (age. ≥. 55. years) across different age groups. Hippocampal volume was segmented on 3D volumetric MRI scans. The segmentations were co-registered to mean diffusivity (MD) and fractional anisotropy (FA) maps to yield mean hippocampal MD and FA measurements. Higher MD of the hippocampus was associated with impaired verbal memory performance. In all persons ≥. 55. years, a higher MD of the hippocampus was associated with a worse memory performance. Hippocampal volumes were very weakly positively associated with delayed recall and only in persons >. 65. years. FA of the hippocampus was not associated with memory performance. Follow-up studies will be needed to determine whether higher MD of hippocampus at younger ages could be an earlier marker of incident Alzheimer's disease than hippocampal volume.

Determinants of cerebellar and cerebral volume in the general elderly population (Article)

2012-12-01T00:00:00Z

In a population-based study of 3962 community-dwelling nondemented elderly we investigated the relation of age, sex, cardiovascular risk factors, and the presence of infarcts with cerebellar volume, and its interrelationship with cerebral volumes. Cerebellar and cerebral gray and white matter were segmented using Freesurfer version 4.5 (http://surfer.nmr.mgh.harvard.edu/). We used linear regression analyses to model the relationship between age, sex, cardiovascular risk factors, brain infarcts, white matter lesions (WMLs) and cerebellar and cerebral volume. Smaller cerebellar volumes with increasing age were mainly driven by loss of white matter. Diabetes, higher serum glucose and lower cholesterol levels were related to smaller cerebellar volume. No association was found between hypertension, smoking, apolipoprotein E (ApoE) genotype, and cerebellar volume. Supratentorial lacunar infarcts and WMLs were related to smaller cerebellar volume. Infratentorial infarcts were related to smaller cerebellar white matter volume and total cerebral volume. This study suggests that determinants of cerebellar volume do not entirely overlap with those established for cerebral volume. Furthermore, presence of infarcts or WMLs in the cerebrum can affect cerebellar volume.

Vascular risk factors, apolipoprotein E, and hippocampal decline on magnetic resonance imaging over a 10-year follow-up (Article)

2012-01-12T00:00:00Z

Background: Decline of hippocampal volume on magnetic resonance imaging (MRI) may be considered as a surrogate biomarker of accumulating Alzheimer disease (AD) pathology. Previously, we showed in the prospective population-based Rotterdam Scan Study that a higher rate of decline of hippocampal volume on MRI precedes clinical AD or memory decline. We studied potential risk factors for decline of hippocampal volume. Methods: At baseline (1995-1996), 518 nondemented elderly subjects were included, and the cohort was re-examined in 1999 and in 2006. At each examination, hippocampal volume was determined using an automated segmentation procedure. In all, 301 persons had at least two three-dimensional MRI scans to assess decline in hippocampal volume. Results: Persons carrying the apolipoprotein E (APOE) e{open}4 allele had lower hippocampal volumes than persons with the e{open}3/e{open}3 genotype, but the rate of decline was not influenced by APOE genotype. In persons who did not use antihypertensive treatment, both a high (>90 mm Hg) and a low (<70 mm Hg) diastolic blood pressure were associated with a faster decline in hippocampal volume. Also, white matter lesions on baseline MRI were associated with a higher rate of decline in hippocampal volume. Conclusions: In a nondemented elderly population, persons with the APOE e{open}4 allele have a smaller hippocampal volume but not a higher rate of decline. Rate of decline of hippocampal volume was influenced by white matter lesions and diastolic blood pressure, supporting their hypothesized role in the pathogenesis of AD.

Global and focal brain volume in long-term breast cancer survivors exposed to adjuvant chemotherapy (Article)

2011-12-28T00:00:00Z

A limited number of studies have associated adjuvant chemotherapy with structural brain changes. These studies had small sample sizes and were conducted shortly after cessation of chemotherapy. Results of these studies indicate local gray matter volume decrease and an increase in white matter lesions. Up till now, it is unclear if non-CNS chemotherapy is associated with long-term structural brain changes. We compared focal and total brain volume (TBV) of a large set of non-CNS directed chemotherapy-exposed breast cancer survivors, on average 21 years post-treatment, to that of a population-based sample of women without a history of cancer. Structural MRI (1.5T) was performed in 184 chemotherapy-exposed breast cancer patients, mean age 64.0 (SD = 6.5) years, who had been diagnosed with cancer on average 21.1 (SD = 4.4) years before, and 368 age-matched cancer-free reference subjects from a population-based cohort study. Outcome measures were: TBV and total gray and white matter volume, and hippocampal volume. In addition, voxel based morphometry was performed to analyze differences in focal gray matter. The chemotherapy-exposed breast cancer survivors had significantly smaller TBV (-3.5 ml, P = 0.019) and gray matter volume (-2.9 ml, P = 0.003) than the reference subjects. No significant differences were observed in white matter volume, hippocampal volume, or local gray matter volume. This study shows that adjuvant chemotherapy for breast cancer is associated with long-term reductions in TBV and overall gray matter volume in the absence of focal reductions. The observed smaller gray matter volume in chemotherapy-exposed survivors was comparable to the effect of almost 4 years of age on gray matter volume reduction. These volume differences might be associated with the slightly worse cognitive performance that we observed previously in this group of breast cancer survivors.

2D-3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models (Article)

2011-12-01T00:00:00Z

Three-dimensional patient specific bone models are required in a range of medical applications, such as pre-operative surgery planning and improved guidance during surgery, modeling and simulation, and in vivo bone motion tracking. Shape reconstruction from a small number of X-ray images is desired as it lowers both the acquisition costs and the radiation dose compared to CT. We propose a method for pose estimation and shape reconstruction of 3D bone surfaces from two (or more) calibrated X-ray images using a statistical shape model (SSM). User interaction is limited to manual initialization of the mean shape. The proposed method combines a 3D distance based objective function with automatic edge selection on a Canny edge map. Landmark-edge correspondences are weighted based on the orientation difference of the projected silhouette and the corresponding image edge. The method was evaluated by rigid pose estimation of ground truth shapes as well as 3D shape estimation using a SSM of the whole femur, from stereo cadaver X-rays, in vivo biplane fluoroscopy image-pairs, and an in vivo biplane fluoroscopic sequence. Ground truth shapes for all experiments were available in the form of CT segmentations. Rigid registration of the ground truth shape to the biplane fluoroscopy achieved sub-millimeter accuracy (0.68. mm) measured as root mean squared (RMS) point-to-surface (P2S) distance. The non-rigid reconstruction from the biplane fluoroscopy using the SSM also showed promising results (1.68. mm RMS P2S). A feasibility study on one fluoroscopic time series illustrates the potential of the method for motion and shape estimation from fluoroscopic sequences with minimal user interaction.

Replication study of Chr17q25 with cerebral white matter lesion volume (Article)

2011-11-01T00:00:00Z

BACKGROUND AND PURPOSE-: Recently, the first genomewide association study on cerebral white matter lesion burden identified chr17q25 to be significantly associated with white matter lesions. We report on the first independent replication study of this genetic association. METHODS-: In a population-based cohort study, we investigated the association between the 6 genomewide significant single nucleotide polymorphisms at that locus and cerebral white matter lesion volume on MRI, measured quantitatively, adjusted for age, sex, and intracranial volume. Adjustments for ApoE4 carriership and cardiovascular risk factors were evaluated separately. Finally, we performed a meta-analysis of all published data for the single most significant single nucleotide polymorphism, rs3744028. RESULTS-: The risk alleles of all the 6 single nucleotide polymorphisms were significantly associated with white matter lesion volume with P=1.1*10 for rs3744028, adjusted for age, sex, and intracranial volume. Additional adjustments only had minor influence on these associations. A meta-analysis with all published data for rs3744028 resulted in a probability value of 5.3*10. CONCLUSIONS-: This study further establishes chr17q25 as a novel genetic locus for WML volume.

Calcium scoring in unenhanced and enhanced CT data of the aorta-iliacal arteries: Impact of image acquisition, reconstruction, and analysis parameter settings (Article)

2011-11-01T00:00:00Z

Background: Several studies have been published on the matter of abdominal aortic and iliac calcifications and the association to clinical entities such as diabetes mellitus and renal failure. However, comparing of these studies is questionable since quantification methods for atherosclerosis differ. Purpose: To evaluate the effect of image acquisition settings, reconstruction parameters, and analysis methods on calcium quantification in the abdominal aorta. Material and Methods: Calcium scores were retrospectively determined on standardized abdominal CT scans of 15 patients. Two researchers obtained calcium scores with 10 different lower thresholds (LT) (130, 145, 160, 175, 200, 300, 400, 500, 600, 1000) in CT scans with and without contrast enhancement, with slice thicknesses (ST) varying between 2.0-5.0 mm for the non-contrast-enhanced series and between 1.0-5.0 mm for the contrast-enhanced series. In addition calcium scores obtained with two convolution kernels (B10f, B20f) were compared. Inter-observer variability was calculated. Results: Calcium scoring at higher STs is overestimated compared to smaller STs and this effect was more pronounced with increasing calcium loads. Concerning the convolution kernel, scores obtained with kernel B10f were overestimated compared to kernel B20f. Increase of LT resulted in a decrease of the calcium score and scoring in contrast-enhanced series resulted in higher scores compared to non-contrast-enhanced series. These effects are more apparent in patients with higher calcium loads. Calcium scoring reproducibility with the reference standard is limited for the aorta-iliac trajectory, whereas scoring with the remaining settings is reproducible. Conclusion: Scores obtained with different settings cannot be compared. The inter-observer reproducibility was limited using the reference standard and practical difficulties were substantial. Scoring with higher LT, ST, and contrast enhancement is faster and has less practical difficulties.

Genetic determination of human facial morphology: Links between cleft-lips and normal variation (Article)

2011-11-01T00:00:00Z

Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and other previous studies showed distinctly differing facial distance measurements when comparing unaffected relatives of NSCL/P patients with normal controls. Here, we test the hypothesis that genetic loci involved in NSCL/P also influence normal variation in facial morphology. We tested 11 SNPs from 10 genomic regions previously showing replicated evidence of association with NSCL/P for association with normal variation of nose width and bizygomatic distance in two cohorts from Germany (N=529) and the Netherlands (N=2497). The two most significant associations found were between nose width and SNP rs1258763 near the GREM1 gene in the German cohort (P=6 × 10 4), and between bizygomatic distance and SNP rs987525 at 8q24.21 near the CCDC26 gene (P=0.017) in the Dutch sample. A genetic prediction model explained 2% of phenotype variation in nose width in the German and 0.5% of bizygomatic distance variation in the Dutch cohort. Although preliminary, our data provide a first link between genetic loci involved in a pathological facial trait such as NSCL/P and variation of normal facial morphology. Moreover, we present a first approach for understanding the genetic basis of human facial appearance, a highly intriguing trait with implications on clinical practice, clinical genetics, forensic intelligence, social interactions and personal identity.

Trans-dimensional MCMC methods for fully automatic motion analysis in tagged MRI (Article)

2011-10-11T00:00:00Z

Tagged magnetic resonance imaging (tMRI) is a well-known noninvasive method allowing quantitative analysis of regional heart dynamics. Its clinical use has so far been limited, in part due to the lack of robustness and accuracy of existing tag tracking algorithms in dealing with low (and intrinsically time-varying) image quality. In this paper, we propose a novel probabilistic method for tag tracking, implemented by means of Bayesian particle filtering and a trans-dimensional Markov chain Monte Carlo (MCMC) approach, which efficiently combines information about the imaging process and tag appearance with prior knowledge about the heart dynamics obtained by means of non-rigid image registration. Experiments using synthetic image data (with ground truth) and real data (with expert manual annotation) from preclinical (small animal) and clinical (human) studies confirm that the proposed method yields higher consistency, accuracy, and intrinsic tag reliability assessment in comparison with other frequently used tag tracking methods.

The Rotterdam Scan Study: Design and update up to 2012 (Article)

2011-10-01T00:00:00Z

Neuroimaging plays an important role in etiologic research on neurological diseases in the elderly. The Rotterdam Scan Study was initiated as part of the ongoing Rotterdam Study with the aim to unravel causes of neurological disease by performing neuroimaging in a population-based longitudinal setting. In 1995 and 1999 random subsets of the Rotterdam Study underwent neuroimaging, whereas from 2005 onwards MRI has been implemented into the core protocol of the Rotterdam Study. In this paper, we discuss the background and rationale of the Rotterdam Scan Study. We also describe the imaging protocol and post-processing techniques, and highlight the main findings to date. Finally, we make recommendations for future research, which will also be the main focus of investigation in the Rotterdam Scan Study.

Facilitating tumor functional assessment by spatially relating 3D tumor histology and In Vivo MRI: Image registration approach (Article)

2011-08-29T00:00:00Z

Background: Magnetic resonance imaging (MRI), together with histology, is widely used to diagnose and to monitor treatment in oncology. Spatial correspondence between these modalities provides information about the ability of MRI to characterize cancerous tissue. However, registration is complicated by deformations during pathological processing, and differences in scale and information content. Methodology/Principal Findings: This study proposes a methodology for establishing an accurate 3D relation between histological sections and high resolution in vivo MRI tumor data. The key features of the methodology are: 1) standardized acquisition and processing, 2) use of an intermediate ex vivo MRI, 3) use of a reference cutting plane, 4) dense histological sampling, 5) elastic registration, and 6) use of complete 3D data sets. Five rat pancreatic tumors imaged by T2*-w MRI were used to evaluate the proposed methodology. The registration accuracy was assessed by root mean squared (RMS) distances between manually annotated landmark points in both modalities. After elastic registration the average RMS distance decreased from 1.4 to 0.7 mm. The intermediate ex vivo MRI and the reference cutting plane shared by all three 3D images (in vivo MRI, ex vivo MRI, and 3D histology data) were found to be crucial for the accurate co-registration between the 3D histological data set and in vivo MRI. The MR intensity in necrotic regions, as manually annotated in 3D histology, was significantly different from other histologically confirmed regions (i.e., viable and hemorrhagic). However, the viable and the hemorrhagic regions showed a large overlap in T2*-w MRI signal intensity. Conclusions: The established 3D correspondence between tumor histology and in vivo MRI enables extraction of MRI characteristics for histologically confirmed regions. The proposed methodology allows the creation of a tumor database of spatially registered multi-spectral MR images and multi-stained 3D histology.

Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading (Article)

2011-08-01T00:00:00Z

This paper describes an evaluation framework that allows a standardized and objective quantitative comparison of carotid artery lumen segmentation and stenosis grading algorithms. We describe the data repository comprising 56 multi-center, multi-vendor CTA datasets, their acquisition, the creation of the reference standard and the evaluation measures. This framework has been introduced at the MICCAI 2009 workshop 3D Segmentation in the Clinic: A Grand Challenge III, and we compare the results of eight teams that participated. These results show that automated segmentation of the vessel lumen is possible with a precision that is comparable to manual annotation. The framework is open for new submissions through the website http://cls2009.bigr.nl.

Body-mass index, abdominal adiposity, and cardiovascular risk (Article)

2011-07-16T00:00:00Z

Incidence, treatment, and case-fatality of non-traumatic subarachnoid haemorrhage in the Netherlands (Article)

2011-07-01T00:00:00Z

Background: Non-traumatic subarachnoid haemorrhage (SAH) is a devastating disorder and in the majority of cases it is caused by rupture of an intracranial aneurysm. No actual data are available on the incidence of non-traumatic SAH and aneursymal SAH (aSAH) in the Netherlands and little is known about treatment patterns of aSAH. Our purpose was therefore to assess the incidence, treatment patterns, and case-fatality of non-traumatic (a)SAH within the Dutch general population. Methods: Two population based data sources were used for this retrospective cohort study. One was the nationwide hospital discharge registry (National Medical Registration, LMR). Cases were patients hospitalized for SAH (ICD-9-code 430) in 2001-2005. The second source was the Integrated Primary Care Information (IPCI) database, a medical record database allowing for case validation. Cases were patients with validated non-traumatic (a)SAH in 1996-2006. Incidence, treatment, and case-fatality were assessed. Results: The incidence rate (IR) of non-traumatic SAH was 7.12 per 100,000 PY (95%CI: 6.94-7.31) and increased with age. The IR of aSAH was 3.78 (95%CI: 2.98-4.72). Women had a twofold increased risk of non-traumatic SAH; this difference appeared after the fourth decade. Non-traumatic SAH fatality was 30% (95%CI: 29-31%). Of aSAH patients 64% (95%CI: 53-74%) were treated with a clipping procedure, and 26% (95%CI: 17-37%) with coiling. Conclusion: Non-traumatic SAH is a rare disease with substantial case-fatality; rates in the Netherlands are similar to other countries. Case-fatality is also similar as well as age and sex patterns in incidence.

Genome-wide association studies of cerebral white matter lesion burden (Article)

2011-07-01T00:00:00Z

Objective: White matter hyperintensities (WMHs) detectable by magnetic resonance imaging are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMHs are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified. Methods: We performed a meta-analysis of genome-wide association studies (GWASs) for WMH burden in 9,361 stroke-free individuals of European descent from 7 community-based cohorts. Significant findings were tested for replication in 3,024 individuals from 2 additional cohorts. Results: We identified 6 novel risk-associated single nucleotide polymorphisms (SNPs) in 1 locus on chromosome 17q25 encompassing 6 known genes including WBP2, TRIM65, TRIM47, MRPL38, FBF1, and ACOX1. The most significant association was for rs3744028 (pdiscovery= 4.0 × 10-9; preplication= 1.3 × 10-7; pcombined= 4.0 × 10-15). Other SNPs in this region also reaching genome-wide significance were rs9894383 (p = 5.3 × 10-9), rs11869977 (p = 5.7 × 10-9), rs936393 (p = 6.8 × 10-9), rs3744017 (p = 7.3 × 10-9), and rs1055129 (p = 4.1 × 10-8). Variant alleles at these loci conferred a small increase in WMH burden (4-8% of the overall mean WMH burden in the sample). Interpretation: This large GWAS of WMH burden in community-based cohorts of individuals of European descent identifies a novel locus on chromosome 17. Further characterization of this locus may provide novel insights into the pathogenesis of cerebral WMH. Copyright

Estimating 3D lumen centerlines of carotid arteries in free-hand acquisition ultrasound (Article)

2011-06-29T00:00:00Z

Purpose: The purpose of this paper is to present a methodology to estimate the carotid artery lumen centerlines in ultrasound (US) images obtained in a free-hand examination. Challenging aspects here are speckle noise in US images, artifacts, and the lack of contrast in the direction orthogonal to the US beam direction. Method: An algorithm based on a rough lumen segmentation obtained by robust ellipse fitting was developed to deal with these conditions and estimate the lumen center in 2D B-mode scans. In a free-hand sweep examination, continuous image acquisitions are performed through time when the radiologist moves the probe on the patient's neck. The result is a series of images that show 2D cross-sections of the carotid's morphology. A tracking sensor (Flock of Birds) was attached to the probe and both were connected to a PC executing the Stradwin software, which relates spatial information to the acquisition data of the US probe. The spatial information was combined with the 2D lumen center estimates to provide a centerline in 3D. For validation, 19 carotid scans from 15 different patients were scanned, their centerlines calculated by the algorithm and compared with results acquired by manual annotations. Results: The average Euclidean distance between both among all the examinations was 0.82 mm. For each examination, the percentage of these Euclidean distances below 2 mm was calculated; the average over all examinations was 92%. Conclusion: Automated 3D estimation of carotid artery lumen centerlines in free-hand real-time ultrasound is feasible and can be performed with high accuracy. The algorithm is robust enough to keep the centerlines inside the vessel, even in the absence of contrast in parts of the vessel wall.

Multispectral MRI centerline tracking in carotid arteries (Article)

2011-06-09T00:00:00Z

We propose a minimum cost path approach to track the centerlines of the internal and external carotid arteries in multispectral MR data. User interaction is limited to the annotation of three seed points. The cost image is based on both a measure of vessel medialness and lumen intensity similarity in two MRA image sequences: Black Blood MRA and Phase Contrast MRA. After intensity inhomogeneity correction and noise reduction, the two images are aligned using affine registration. The two parameters that control the contrast of the cost image were determined in an optimization experiment on 40 training datasets. Experiments on the training datasets also showed that a cost image composed of a combination of gradient-based medialness and lumen intensity similarity increases the tracking accuracy compared to using only one of the constituents. Furthermore, centerline tracking using both MRA sequences outperformed tracking using only one of these MRA images. An independent test set of 152 images from 38 patients served to validate the technique. The centerlines of 148 images were successfully extracted using the parameters optimized on the training sets. The average mean distance to the reference standard, manually annotated centerlines, was 0.98 mm, which is comparable to the in-plane resolution. This indicates that the proposed method has a high potential to replace the manual centerline annotation.

Region based level set segmentation of the outer wall of the carotid bifurcation in CTA (Article)

2011-06-09T00:00:00Z

This paper presents a level set based method for segmenting the outer vessel wall and plaque components of the carotid artery in CTA. The method employs a GentleBoost classification framework that classifies pixels as calcified region or not, and inside or outside the vessel wall. The combined result of both classifications is used to construct a speed function for level set based segmentation of the outer vessel wall; the segmented lumen is used to initialize the level set. The method has been optimized on 20 datasets and evaluated on 80 datasets for which manually annotated data was available as reference. The average Dice similarity of the outer vessel wall segmentation was 92%, which compares favorably to previous methods.

Automated versus manual segmentation of atherosclerotic carotid plaque volume and components in CTA: associations with cardiovascular risk factors (Article)

2011-05-26T00:00:00Z

The purpose of this study was to validate automated atherosclerotic plaque measurements in carotid arteries from CT angiography (CTA). We present an automated method (three initialization points are required) to measure plaque components within the carotid vessel wall in CTA. Plaque components (calcifications, fibrous tissue, lipids) are determined by different ranges of Hounsfield Unit values within the vessel wall. On CTA scans of 40 symptomatic patients with atherosclerotic plaque in the carotid artery automatically segmented plaque volume, calcified, fibrous and lipid percentages were 0.97 ± 0.51 cm3, 10 ± 11%, 63 ± 10% and 25 ± 5%; while manual measurements by first observer were 0.95 ± 0.60 cm3, 14 ± 16%, 63 ± 13% and 21 ± 9%, respectively and manual measurement by second observer were 1.05 ± 0.75 cm3, 11 ± 12%, 61 ± 11% and 27 ± 10%. In 90 datasets, significant associations were found between age, gender, hypercholesterolemia, diabetes, smoking and previous cerebrovascular disease and plaque features. For both automated and manual measurements, significant associations were found between: age and calcium and fibrous tissue percentage; gender and plaque volume and lipid percentage; diabetes and calcium, smoking and plaque volume; previous cerebrovascular disease and plaque volume. Significant associations found only by the automated method were between age and plaque volume, hypercholesterolemia and plaque volume and diabetes and fibrous tissue percentage. Significant association found only by the manual method was between previous cerebrovascular disease and percentage of fibrous tissue. Automated analysis of plaque composition in the carotid arteries is comparable with the manual analysis and has the potential to replace it.

Nonrigid registration of dynamic medical imaging data using nD+t B-splines and a groupwise optimization approach (Article)

2011-04-01T00:00:00Z

A registration method for motion estimation in dynamic medical imaging data is proposed. Registration is performed directly on the dynamic image, thus avoiding a bias towards a specifically chosen reference time point. Both spatial and temporal smoothness of the transformations are taken into account. Optionally, cyclic motion can be imposed, which can be useful for visualization (viewing the segmentation sequentially) or model building purposes. The method is based on a 3D (2D. +. time) or 4D (3D. +. time) free-form B-spline deformation model, a similarity metric that minimizes the intensity variances over time and constrained optimization using a stochastic gradient descent method with adaptive step size estimation. The method was quantitatively compared with existing registration techniques on synthetic data and 3D. +. t computed tomography data of the lungs. This showed subvoxel accuracy while delivering smooth transformations, and high consistency of the registration results. Furthermore, the accuracy of semi-automatic derivation of left ventricular volume curves from 3D. +. t computed tomography angiography data of the heart was evaluated. On average, the deviation from the curves derived from the manual annotations was approximately 3%. The potential of the method for other imaging modalities was shown on 2D. +. t ultrasound and 2D. +. t magnetic resonance images. The software is publicly available as an extension to the registration package elastix.

Statistical analysis of minimum cost path based structural brain connectivity (Article)

2011-03-15T00:00:00Z

Diffusion MRI can be used to study the structural connectivity within the brain. Brain connectivity is often represented by a binary network whose topology can be studied using graph theory. We present a framework for the construction of weighted structural brain networks, containing information about connectivity, which can be effectively analyzed using statistical methods. Network nodes are defined by segmentation of subcortical structures and by cortical parcellation. Connectivity is established using a minimum cost path (mcp) method with an anisotropic local cost function based directly on diffusion weighted images. We refer to this framework as Statistical Analysis of Minimum cost path based Structural Connectivity (SAMSCo) and the weighted structural connectivity networks as mcp-networks. In a proof of principle study we investigated the information contained in mcp-networks by predicting subject age based on the mcp-networks of a group of 974 middle-aged and elderly subjects. Using SAMSCo, age was predicted with an average error of 3.7. years. This was significantly better than predictions based on fractional anisotropy or mean diffusivity averaged over the whole white matter or over the corpus callosum, which showed average prediction errors of at least 4.8. years. Additionally, we classified subjects, based on the mcp-networks, into groups with low and high white matter lesion load, while correcting for age, sex and white matter atrophy. The SAMSCo classification outperformed the classification based on the diffusion measures with a classification accuracy of 76.0% versus 63.2%. We also performed a classification in groups with mild and severe atrophy, correcting for age, sex and white matter lesion load. In this case, mcp-networks and diffusion measures yielded similar classification accuracies of 68.3% and 67.8% respectively. The SAMSCo prediction and classification experiments indicate that the mcp-networks contain information regarding age, white matter lesion load and white matter atrophy, and that in case of age and white matter lesion load the mcp-network based models outperformed the predictions based on diffusion measures.

Platelet aggregation inhibitors, vitamin K antagonists and risk of subarachnoid hemorrhage (Article)

2011-03-01T00:00:00Z

Background: Use of platelet aggregation inhibitors and vitamin K antagonists has been associated with an increased risk of intracranial hemorrhage (ICH). Whether the use of these antithrombotic drugs is associated with an increased risk of subarachnoid hemorrhage (SAH) remains unclear, especially as confounding by indication might play a role. Objective: The aim of the present study was to investigate whether use of platelet aggregation inhibitors or vitamin K antagonists increase the risk of SAH. Methods: We applied population-based case-control, case-crossover and case-time-control designs to estimate the risk of SAH while addressing issues both of confounding by indication and time varying exposure within the PHARMO Record Linkage System database. This system includes drug dispensing records from community pharmacies and hospital discharge records of more than 3million community-dwelling inhabitants in the Netherlands. Patients were considered a case if they were hospitalized for a first SAH (ICD-9-CM code 430) in the period between 1st January 1998 and 31st December 2006. Controls were selected from the source population, matched on age, gender and date of hospitalization. Conditional logistic regression was used to estimate multivariable adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of SAH during use of platelet aggregation inhibitors or vitamin K antagonists. In the case-crossover and case-time-control designs we selected 11 control periods preceding the index date in successive steps of 1month in the past. Results: In all, 1004 cases of SAH were identified. In the case-control analysis the adjusted OR for the risk of SAH in current use of platelet aggregation inhibitors was 1.32 (95% CI: 1.02-1.70) and in current use of vitamin K antagonists 1.29 (95% CI: 0.89-1.87) compared with no use. In the case-crossover analysis the ORs for the risk of SAH in current use of platelet aggregation inhibitors and vitamin K antagonists were 1.04 (95% CI: 0.56-1.94) and 2.46 (95% CI: 1.04-5.82), respectively. In the case-time-control analysis the OR for platelet aggregation inhibitors was 0.50 (95% CI: 0.26-0.98) and for vitamin K antagonists 1.98 (95% CI: 0.82-4.76). Conclusion: The use of platelet aggregation inhibitors was not associated with an increased SAH risk; the modest increase observed in the case-control analysis could be as a result of confounding. The use of vitamin K antagonists seemed to be associated with an increased risk of SAH. The increase was most pronounced in the case-crossover analysis and therefore cannot be explained by unmeasured confounding.

Association between carotid artery plaque ulceration and plaque composition evaluated with multidetector CT angiography (Article)

2011-02-01T00:00:00Z

Background and Purpose- Symptomatic carotid artery plaque ulceration is associated with distinct plaque components such as a large lipid-rich necrotic core (LR-NC) in ischemic stroke patients with a 50% carotid stenosis. We evaluated the associations between carotid artery plaque ulceration and plaque characteristics in ischemic stroke patients with 50% stenosis, as well as in those with a low degree of stenosis (0% to 49%). Methods- Consecutive patients (n=346) with symptoms in the anterior circulation were evaluated with multidetector CT angiography (MDCTA) for the presence of atherosclerotic plaque, degree of stenosis, and plaque ulceration in the symptomatic carotid artery. Plaque volume and plaque component proportions of LR-NC, fibrous tissue, and calcification were measured. The associations between plaque ulceration and plaque characteristics were analyzed using logistic regression. Results- Atherosclerotic plaque was present in 185 patients. Plaque ulcerations were present in 38 (21%) patients, of which half had a low degree stenosis (0% to 49%). Plaque volume was significantly larger in ulcerated plaques. After adjustment for age, sex, and degree of stenosis, LR-NC proportion was strongly associated with plaque ulceration (odds ratio, 2.21; 95% CI, 1.49 to 3.27), whereas calcification proportion was inversely associated with plaque ulceration (odds ratio, 0.60; 95% CI, 0.40 to 0.89). These associations remained significant in patients with a low degree stenosis (0% to 49%). CONCLUSION-: Plaque volume, degree of stenosis, and LR-NC proportion evaluated noninvasively with MDCTA are associated with carotid artery plaque ulceration, even in patients with a low degree stenosis (0% to 49%). Plaque volume and composition analysis with MDCTA may identify rupture prone plaques and improve risk stratification in ischemic stroke patients.

Genetic risk factors for cerebral small-vessel disease in hypertensive patients from a genetically isolated population (Article)

2011-01-01T00:00:00Z

Background: Asymptomatic cerebral lesions on MRI such as white matter lesions (WML), lacunes and microbleeds are commonly seen in older people. We examined the role of a series of candidate genes involved in blood pressure regulation and amyloid metabolism. Materials and Methods: The study was embedded in a family-based cohort sampled from a Dutch genetically isolated population. We selected individuals between 55 and 75 years of age with hypertension (N=129). Volumes of WML and presence of lacunes and microbleeds were assessed with MRI. We studied three genes involved in blood pressure regulation (angiotensin, angiotensin II type 1 receptor, α-adducin) and two genes involved in the amyloid pathway (apolipoprotein E (APOE) and sortilin-related receptor gene (SORL1)). Results: All participants had WML (median volume, 3.1 ml; interquartile range, 1.5e6.5 ml); lacunar infarcts were present in 15.5% and microbleeds in 23.3%. Homozygosity for the APOE ε4 allele was associated with lacunes (OR, 4.8; 95% CI, 1.2 to 19.3). Individuals carrying two copies of the variant allele of four single nucleotide polymorphism (SNPs) located at the 3'-end of SORL1 (rs1699102, rs3824968, rs2282649, rs1010159) had significantly more often microbleeds (highest OR, 6.87; 95% CI, 1.78 to 26.44). Conclusion: The association of SORL1 with microbleeds suggests that the amyloid cascade is involved in the aetiology of microbleeds in populations with hypertension.

Robust CTA lumen segmentation of the atherosclerotic carotid artery bifurcation in a large patient population (Article)

2010-12-01T00:00:00Z

We propose and validate a semi-automatic method for lumen segmentation of the carotid bifurcation in computed tomography angiography (CTA). First, the central vessel axis is obtained using path tracking between three user-defined points. Second, starting from this path, the segmentation is automatically obtained using a level set. The cost and speed functions for path tracking and segmentation make use of intensity and homogeneity slice-based image features. The method is validated on a large data set of 234 carotid bifurcations of 129 ischemic stroke patients with atherosclerotic disease. The results are compared to manually obtained lumen segmentations. Parameter optimization is carried out on a subset of 30 representative carotid bifurcations. With the optimized parameter settings the method successfully tracked the central vessel paths in 201 of the remaining 204 bifurcations (99%) which were not part of the training set. Comparison with manually drawn segmentations shows that the average overlap between the method and observers is similar (for the inter-observer set the results were 92% vs. 87% and for the intra-observer set 94% vs. 94%). Therefore the method has potential to replace the manual procedure of lumen segmentation of the atherosclerotic bifurcation in CTA. © 2010 Elsevier B.V.

Coronary segmentation based motion corrected cardiac CT reconstruction (Article)

2010-12-01T00:00:00Z

A method to obtain motion artifact-free reconstructed images of the coronary arteries is proposed and evaluated. The method relies on the integration of coronary motion estimation in an iterative computed tomography reconstruction technique. Coronary motion fields are derived from a set of coronary centerlines extracted at multiple cardiac phases within the R-R interval. Start and end points are provided by the user in one time-frame only. Corresponding centerline positions are used to determine the motion fields from phase to phase. Finally, dense motion fields are achieved by thin-plate-spline interpolation and are used to perform a motion-corrected iterative reconstruction of a selected region of interest, which results in an effective improvement of the reconstructed image quality.

Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: A large-scale, multicenter, and multivendor study (Article)

2010-12-01T00:00:00Z

Purpose: Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data. Methods: A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patient's CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation. Results: The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94±1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26±1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method. Conclusions: A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/ multivendor data sets.

Intracranial aneurysm segmentation in 3D CT angiography: Method and quantitative validation (Article)

2010-12-01T00:00:00Z

Accurately quantifying aneurysm shape parameters is of clinical importance, as it is an important factor in choosing the right treatment modality (i.e. coiling or clipping), in predicting rupture risk and operative risk and for pre-surgical planning. The first step in aneurysm quantification is to segment it from other structures that are present in the image. As manual segmentation is a tedious procedure and prone to inter- and intra-observer variability, there is a need for an automated method which is accurate and reproducible. In this paper a novel semi-automated method for segmenting aneurysms in Computed Tomography Angiography (CTA) data based on Geodesic Active Contours is presented and quantitatively evaluated. Three different image features are used to steer the level set to the boundary of the aneurysm, namely intensity, gradient magnitude and variance in intensity. The method requires minimum user interaction, i.e. clicking a single seed point inside the aneurysm which is used to estimate the vessel intensity distribution and to initialize the level set. The results show that the developed method is reproducible, and performs in the range of interobserver variability in terms of accuracy.

Correspondence free 3D statistical shape model fitting to sparse X-ray projections (Article)

2010-12-01T00:00:00Z

In this paper we address the problem of 3D shape reconstruction from sparse X-ray projections. We present a correspondence free method to fit a statistical shape model to two X-ray projections, and illustrate its performance in 3D shape reconstruction of the femur. The method alternates between 2D segmentation and 3D shaoe reconstruction, where 2D segmentation is guided by dynamic programming along the model projection on the X-ray plane. 3D reconstruction is based on the iterative minimization of the 3D distance between a set of support points and the back-projected silhouette with respect to the pose and model parameters. We show robustness of the reconstruction on simulated X-ray projection data of the femur, varying the field of view; and in a pilot study on cadaveric femora.

A semi-automatic method for segmentation of the carotid bifurcation and bifurcation angle quantification on black blood MRA (Article)

2010-11-22T00:00:00Z

Quantitative information about the geometry of the carotid artery bifurcation may help in predicting the development of atherosclerosis. A geodesic active contours based segmentation method combining both gradient and intensity information was developed for semi-automatic, accurate and robust quantification of the carotid bifurcation angle in Black Blood MRA data. The segmentation method was evaluated by comparing its accuracy to inter and intra observer variability on a large dataset that has been acquired as part of a longitudinal population study which investigates the natural progression of carotid atherosclerosis. Furthermore, the method is shown to be robust to initialization differences. The bifurcation angle obtained from the segmented lumen corresponds well with the angle derived from the manual lumen segmentation, which demonstrates that the method has large potential to replace manual segmentations for extracting the carotid bifurcation angle from Black Blood MRA data.

Conditional shape models for cardiac motion estimation (Article)

2010-11-22T00:00:00Z

We propose a conditional statistical shape model to predict patient specific cardiac motion from the 3D end-diastolic CTA scan. The model is built from 4D CTA sequences by combining atlas based segmentation and 4D registration. Cardiac motion estimation is, for example, relevant in the dynamic alignment of pre-operative CTA data with intra-operative X-ray imaging. Due to a trend towards prospective electrocardiogram gating techniques, 4D imaging data, from which motion information could be extracted, is not commonly available. The prediction of motion from shape information is thus relevant for this purpose. Evaluation of the accuracy of the predicted motion was performed using CTA scans of 50 patients, showing an average accuracy of 1.1 mm.

Statistical analysis of structural brain connectivity (Article)

2010-11-22T00:00:00Z

We present a framework for statistical analysis in large cohorts of structural brain connectivity, derived from diffusion weighted MRI. A brain network is defined between subcortical gray matter structures and a cortical parcellation obtained with FreeSurfer. Connectivity is established through minimum cost paths with an anisotropic local cost function and is quantified per connection. The connectivity network potentially encodes important information about brain structure, and can be analyzed using multivariate regression methods. The proposed framework can be used to study the relation between connectivity and e.g. brain function or neurodegenerative disease. As a proof of principle, we perform principal component regression in order to predict age and gender, based on the connectivity networks of 979 middle-aged and elderly subjects, in a 10-fold cross-validation. The results are compared to predictions based on fractional anisotropy and mean diffusivity averaged over the white matter and over the corpus callosum. Additionally, the predictions are performed based on the best predicting connection in the network. Principal component regression outperformed all other prediction models, demonstrating the age and gender information encoded in the connectivity network.

Coronary motion estimation from CTA using probability atlas and diffeomorphic registration (Article)

2010-11-09T00:00:00Z

In this paper, we present a method for coronary artery motion estimation from 4D cardiac CT angiogram (CTA) data sets. The proposed method potentially allows the construction of patient-specific 4D coronary motion model from pre-operative CTA which can be used for guiding totally endoscopic coronary artery bypass surgery (TECAB). The proposed approach consists of three steps: Firstly, prior to motion tracking, we form a coronary probability atlas from manual segmentations of the CTA scans of a number of subjects. Secondly, the vesselness response image is calculated and enhanced for end-diastolic and end-systolic CTA images in each 4D sequence. Thirdly, we design a special purpose registration framework for tracking the highly localized coronary motion. It combines the coronary probability atlas, the intensity information from the CTA image and the corresponding vesselness response image to fully automate the coronary motion tracking procedure and improve its accuracy. We performed pairwise 3D registration of cardiac time frames by using a multi-channel implementation of the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework, where each channel contains a given level of description of the registered shapes. For validation, we compare the automatically tracked coronaries with those segmented manually at end-diastolic phase for each subject.

Prediction of dementia by hippocampal shape analysis (Article)

2010-10-25T00:00:00Z

This work investigates the possibility of predicting future onset of dementia in subjects who are cognitively normal, using hippocampal shape and volume information extracted from MRI scans. A group of 47 subjects who were non-demented normal at the time of the MRI acquisition, but were diagnosed with dementia during a 9 year follow-up period, was selected from a large population based cohort study. 47 Age and gender matched subjects who stayed cognitively intact were selected from the same cohort study as a control group. The hippocampi were automatically segmented and all segmentations were inspected and, if necessary, manually corrected by a trained observer. From this data a statistical model of hippocampal shape was constructed, using an entropy-based particle system. This shape model provided the input for a Support Vector Machine classifier to predict dementia. Cross validation experiments showed that shape information can predict future onset of dementia in this dataset with an accuracy of 70%. By incorporating both shape and volume information into the classifier, the accuracy increased to 74%.

3D fusion of intravascular ultrasound and coronary computed tomography for in-vivo wall shear stress analysis: A feasibility study (Article)

2010-10-01T00:00:00Z

Wall shear stress, the force per area acting on the lumen wall due to the blood flow, is an important biomechanical parameter in the localization and progression of atherosclerosis. To calculate shear stress and relate it to atherosclerosis, a 3D description of the lumen and vessel wall is required. We present a framework to obtain the 3D reconstruction of human coronary arteries by the fusion of intravascular ultrasound (IVUS) and coronary computed tomography angiography (CT). We imaged 23 patients with IVUS and CT. The images from both modalities were registered for 35 arteries, using bifurcations as landmarks. The IVUS images together with IVUS derived lumen and wall contours were positioned on the 3D centerline, which was derived from CT. The resulting 3D lumen and wall contours were transformed to a surface for calculation of shear stress and plaque thickness. We applied variations in selection of landmarks and investigated whether these variations influenced the relation between shear stress and plaque thickness. Fusion was successfully achieved in 31 of the 35 arteries. The average length of the fused segments was 36.4 ± 15.7 mm. The length in IVUS and CT of the fused parts correlated excellently (R2= 0.98). Both for a mildly diseased and a very diseased coronary artery, shear stress was calculated and related to plaque thickness. Variations in the selection of the landmarks for these two arteries did not affect the relationship between shear stress and plaque thickness. This new framework can therefore successfully be applied for shear stress analysis in human coronary arteries.

Nonrigid registration and template matching for coronary motion modeling from 4D CTA (Article)

2010-08-12T00:00:00Z

In this paper, we present a method for coronary artery motion tracking in 4D cardiac CT angiogram data sets. The proposed method allows the construction of patient-specific 4D coronary motion model from pre-operative CTA which can be used for guiding totally endoscopic coronary artery bypass surgery (TECAB). The proposed approach consists of three steps: Firstly, the coronary arteries are extracted in the end-diastolic time frame using a minimal cost path approach. To achieve this, the start and end points of the coronaries are identified interactively and the minimal cost path between the start and end points is computed using A*graph search algorithm. Secondly, the cardiac motion is estimated throughout the cardiac cycle by using a non-rigid image registration technique based on a free-form B-spline transformation model and maximization of normalized mutual information. Finally, coronary arteries are tracked automatically through all other phases of the cardiac cycle. This is estimated by deforming the extracted coronaries at end-diastole to all other time frames according the motion field acquired in second step. The estimated coronary centerlines are then refined by template matching algorithm to improve the accuracy. We compare the proposed approach with two alternative approaches: The first approach is based on the minimal cost path extraction of the coronaries with start and end points manually identified in each time frame while the second approach is based on propagating the extracted coronaries from the end-diastolic time frame to other time frames using image-based non-rigid registration only. Our results show that the proposed approach performs more robustly than the non-rigid registration based method and that the resulting motion model is comparable to the motion model constructed from semi-automatic extractions of the coronaries in all time frames.

Automated analysis of time-lapse fluorescence microscopy images: From live cell images to intracellular foci (Article)

2010-08-11T00:00:00Z

Motivation: Complete, accurate and reproducible analysis of intracellular foci from fluorescence microscopy image sequences of live cells requires full automation of all processing steps involved: cell segmentation and tracking followed by foci segmentation and pattern analysis. Integrated systems for this purpose are lacking. Results: Extending our previous work in cell segmentation and tracking, we developed a new system for performing fully automated analysis of fluorescent foci in single cells. The system was validated by applying it to two common tasks: intracellular foci counting (in DNA damage repair experiments) and cell-phase identification based on foci pattern analysis (in DNA replication experiments). Experimental results show that the system performs comparably to expert human observers. Thus, it may replace tedious manual analyses for the considered tasks, and enables high-content screening.

Three-dimensional registration of histology of human atherosclerotic carotid plaques to in-vivo imaging (Article)

2010-08-01T00:00:00Z

An accurate spatial relationship between 3D in-vivo carotid plaque and lumen imaging and histological cross sections is required to study the relationship between biomechanical parameters and atherosclerotic plaque components. We present and evaluate a fully three-dimensional approach for this registration problem, which accounts for deformations that occur during the processing of the specimens. By using additional imaging steps during tissue processing and semi-automated non-linear registration techniques, a 3D-reconstruction of the histology is obtained.The methodology was evaluated on five specimens obtained from patients, operated for severe atherosclerosis in the carotid bifurcation. In more than 80% of the histology slices, the quality of the semi-automated registration with computed tomography angiography (CTA) was equal to or better than the manual registration. The inter-observer variability was between one and two in-vivo CT voxels and was equal to the manual inter-observer variability. Our technique showed that the angles between the normals of the registered histology slices and the in-vivo CTA scan direction ranged 6-56°, indicating that proper 3D-registration is crucial for establishing a correct spatial relation with in-vivo imaging modalities. This new 3D-reconstruction technique of atherosclerotic plaque tissue opens new avenues in the field of biomechanics as well as in the field of image processing, where it can be used for validation purposes of segmentation algorithms.

Accuracy and reproducibility study of automatic MRI brain tissue segmentation methods (Article)

2010-07-01T00:00:00Z

The ability to study changes in brain morphometry in longitudinal studies majorly depends on the accuracy and reproducibility of the brain tissue quantification. We evaluate the accuracy and reproducibility of four previously proposed automatic brain tissue segmentation methods: FAST, SPM5, an automatically trained k-nearest neighbor (kNN) classifier, and a conventional kNN classifier based on a prior training set. The intensity nonuniformity correction and skull-stripping mask were the same for all methods. Evaluations were performed on MRI scans of elderly subjects derived from the general population. Accuracy was evaluated by comparison to two manual segmentations of MRI scans of six subjects (mean age 65.9 ± 4.4. years). Reproducibility was assessed by comparing the automatic segmentations of 30 subjects (mean age 57.0 ± 3.7. years) who were scanned twice within a short time interval. All methods showed good accuracy and reproducibility, with only small differences between methods. The conventional kNN classifier was the most accurate method with similarity indices of 0.82/0.90/0.94 for cerebrospinal fluid/gray matter/white matter, but it showed the lowest reproducibility. FAST yielded the most reproducible segmentation volumes with volume difference standard deviations of 0.55/0.49/0.38 (percentage of intracranial volume) respectively. The results of the reproducibility experiment can be used to calculate the required number of subjects in the design of a longitudinal study with sufficient power to detect changes over time in brain (tissue) volume. Example sample size calculations demonstrate a rather large effect of the choice of segmentation method on the required number of subjects.

A 10-year follow-up of hippocampal volume on magnetic resonance imaging in early dementia and cognitive decline (Article)

2010-04-01T00:00:00Z

Hippocampal atrophy is frequently observed on magnetic resonance images from patients with Alzheimer's disease and persons with mild cognitive impairment. Even in asymptomatic elderly, a small hippocampal volume on magnetic resonance imaging is a risk factor for developing Alzheimer's disease. However, not everyone with a small hippocampus develops dementia. With the increased interest in the use of sequential magnetic resonance images as potential surrogate biomarkers of the disease process, it has also been shown that the rate of hippocampal atrophy is higher in persons with Alzheimer's disease compared to those with mild cognitive impairment and the healthy elderly. Whether a higher rate of hippocampal atrophy also predicts Alzheimer's disease or subtle cognitive decline in non-demented elderly is unknown. We examine these associations in a group of 518 elderly (age 60-90 years, 50 female), taken from the population-based Rotterdam Scan Study. A magnetic resonance imaging examination was performed at baseline in 1995-96 that was repeated in 1999-2000 (in 244 persons) and in 2006 (in 185 persons). Using automated segmentation procedures, we assessed hippocampal volumes on all magnetic resonance imaging scans. All persons were free of dementia at baseline and followed over time for cognitive decline and incident dementia. Persons had four repeated neuropsychological tests at the research centre over a 10-year period. We also continuously monitored the medical records of all 518 participants for incident dementia. During a total follow-up of 4360 person-years, (mean 8.4, range 0.1-11.3), 50 people developed incident dementia (36 had Alzheimer's disease). We found an increased risk to develop incident dementia per standard deviation faster rate of decline in hippocampal volume [left hippocampus 1.6 (95 confidence interval 1.2-2.3, right hippocampus 1.6 (95 confidence interval 1.2-2.1)]. Furthermore, decline in hippocampal volume predicted onset of clinical dementia when corrected for baseline hippocampal volume. In people who remained free of dementia during the whole follow-up period, we found that decline in hippocampal volume paralleled, and preceded, specific decline in delayed word recall. No associations were found in this sample between rate of hippocampal atrophy, Mini Mental State Examination and tests of executive function. Our results suggest that rate of hippocampal atrophy is an early marker of incipient memory decline and dementia, and could be of additional value when compared with a single hippocampal volume measurement as a surrogate biomarker of dementia.

Intracranial aneurysm segmentation in 3D CT angiography: Method and quantitative validation with and without prior noise filtering (Article)

2010-03-25T00:00:00Z

Intracranial aneurysm volume and shape are important factors for predicting rupture risk, for pre-surgical planning and for follow-up studies. To obtain these parameters, manual segmentation can be employed; however, this is a tedious procedure, which is prone to inter- and intra-observer variability. Therefore there is a need for an automated method, which is accurate, reproducible and reliable. This study aims to develop and validate an automated method for segmenting intracranial aneurysms in Computed Tomography Angiography (CTA) data. Also, it is investigated whether prior smoothing improves segmentation robustness and accuracy. The proposed segmentation method is implemented in the level set framework, more specifically Geodesic Active Surfaces, in which a surface is evolved to capture the aneurysmal wall via an energy minimization approach. The energy term is composed of three different image features, namely; intensity, gradient magnitude and intensity variance. The method requires minimal user interaction, i.e. a single seed point inside the aneurysm needs to be placed, based on which image intensity statistics of the aneurysm are derived and used in defining the energy term. The method has been evaluated on 15 aneurysms in 11 CTA data sets by comparing the results to manual segmentations performed by two expert radiologists. Evaluation measures were Similarity Index, Average Surface Distance and Volume Difference. The results show that the automated aneurysm segmentation method is reproducible, and performs in the range of inter-observer variability in terms of accuracy. Smoothing by nonlinear diffusion with appropriate parameter settings prior to segmentation, slightly improves segmentation accuracy.

Brain tissue volumes in relation to cognitive function and risk of dementia (Article)

2010-03-01T00:00:00Z

We investigated in a population-based cohort study the association of global and lobar brain tissue volumes with specific cognitive domains and risk of dementia. Participants (n = 490; 60-90 years) were non-demented at baseline (1995-1996). From baseline brain MRI-scans we obtained global and lobar volumes of CSF, GM, normal WM, white matter lesions and hippocampus. We performed neuropsychological testing at baseline to assess information processing speed, executive function, memory function and global cognitive function. Participants were followed for incident dementia until January 1, 2005. Larger volumes of CSF and WML were associated with worse performance on all neuropsychological tests, and an increased risk of dementia. Smaller WM volume was related to poorer information processing speed and executive function. In contrast, smaller GM volume was associated with worse memory function and increased risk of dementia. When investigating lobar GM volumes, we found that hippocampal volume and temporal GM volume were most strongly associated with risk of dementia, even in persons without objective and subjective cognitive deficits at baseline, followed by frontal and parietal GM volumes.

Small coronary calcifications are not detectable by 64-slice contrast enhanced computed tomography (Article)

2010-01-01T00:00:00Z

Recently, small calcifications have been associated with unstable plaques. Plaque calcifications are both in intravascular ultrasound (IVUS) and multi-slice computed tomography (MSCT) easily recognized. However, smaller calcifications might be missed on MSCT due to its lower resolution. Because it is unknown to which extent calcifications can be detected with MSCT, we compared calcification detection on contrast enhanced MSCT with IVUS. The coronary arteries of patients with myocardial infarction or unstable angina were imaged by 64-slice MSCT angiography and IVUS. The IVUS and MSCT images were registered and the arteries were inspected on the presence of calcifications on both modalities independently. We measured the length and the maximum circumferential angle of each calcification on IVUS. In 31 arteries, we found 99 calcifications on IVUS, of which only 47 were also detected on MSCT. The calcifications missed on MSCT (n = 52) were significantly smaller in angle (27° ± 16° vs. 59° ± 31°) and length (1.4 ± 0.8 vs. 3.7 ± 2.2 mm) than those detected on MSCT. Calcifications could only be detected reliably on MSCT if they were larger than 2.1 mm in length or 36° in angle. Half of the calcifications seen on the IVUS images cannot be detected on contrast enhanced 64-slice MSCT angiography images because of their size. The limited resolution of MSCT is the main reason for missing small calcifications.

Vascular brain disease and depression in the elderly (Article)

2010-01-01T00:00:00Z

Background: Cross-sectional studies have shown an association between vascular brain disease and depression. Longitudinal data are scarce. In a population-based study we investigated this relationship both cross-sectionally and longitudinally. Methods: Brain MRIs were administered to 479 persons aged 60-90 years at baseline (1995-1996). Brain atrophy, white matter lesions and brain infarcts are all markers of vascular brain disease. At baseline and at follow-up examinations, we also identified persons with depressive symptoms and syndromes using the Center for Epidemiological Studies Depression Scale and psychiatric interviews. Medical records were continuously monitored to identify incident depression. Follow-up was complete until October 2005. Results: At baseline, 36 persons had depressive symptoms. Brain atrophy, white matter lesions, and infarcts were associated with presence of depressive symptoms. During follow-up, 92 persons developed depressive symptoms, 35 of whom were categorized as having depressive syndrome. There was no association of any MRI marker with incident depressive symptoms or syndromes. Conclusions: Markers of vascular brain disease were associated with depression cross-sectionally. However, when these markers and risk of depression were assessed longitudinally, no relationship was found.

International Journal of Computer Vision: Editorial (Article)

2009-12-01T00:00:00Z

Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms (Article)

2009-10-01T00:00:00Z

Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.

Coronary lumen segmentation using graph cuts and robust kernel regression (In Book)

2009-09-21T00:00:00Z

This paper presents a novel method for segmenting the coronary lumen in CTA data. The method is based on graph cuts, with edge-weights depending on the intensity of the centerline, and robust kernel regression. A quantitative evaluation in 28 coronary arteries from 12 patients is performed by comparing the semi-automatic segmentations to manual annotations. This evaluation showed that the method was able to segment the coronary arteries with high accuracy, compared to manually annotated segmentations, which is reflected in a Dice coefficient of 0.85 and average symmetric surface distance of 0.22 mm.

Withdrawal of statins and risk of subarachnoid hemorrhage (Article)

2009-08-01T00:00:00Z

BACKGROUND AND PURPOSE-: Vascular endothelium, which can be affected by statins, is believed to play a substantial role in subarachnoid hemorrhage (SAH). Our objective was to estimate the association between use and withdrawal of statins and the risk of SAH. METHODS-: We conducted a population-based case-control study within the PHARMO database. A case was defined as a person hospitalized for SAH (ICD-9-CM code 430) in the period January 1, 1998 to December 31, 2006. Ten randomly chosen controls were matched to each case on age, gender, and calendar date. RESULTS-: During the study period 1004 incident cases of SAH were identified. Current use of statins did not significantly decrease the risk of SAH (OR=0.77, 95% CI 0.55 to 1.07). The odds ratio for recent withdrawal compared to nonusers was 1.62 (95% CI 0.96 to 2.73). Compared to current use, recent withdrawal was associated with an increased risk of SAH (OR=2.34, 95% CI 1.35 to 4.05). Interaction analysis showed that the effect of statin withdrawal was highest in patients who had also recently stopped antihypertensive drugs (OR=6.77, 95% CI 2.10 to 21.8). CONCLUSIONS-: Current use of statins seems to lower the risk of SAH, although the reduction was not significant in new users. Statin withdrawal increased the risk of SAH by a factor 2, even more in patients who had also recently stopped their antihypertensive treatment.

White Matter microstructural integrity and cognitive function in a general elderly population (Article)

2009-05-01T00:00:00Z

Context: The role of macrostructural white matter changes, such as atrophy and white matter lesions, in cognitive decline is increasingly being recognized. However, in the elderly population, these macrostructural changes do not account for all variability in cognition. Measures reflecting white matter microstructural integrity may provide additional information to investigate the relation between white matter changes and cognition. Objective: To study the relation between white matter integrity and cognition in the general elderly population, using diffusion tensor imaging and taking into account macrostructural white matter changes. Design: Cross-sectional population-based study. Setting: A general community in the Netherlands. Participants: A population-based sample of 860 persons, older than 60 years, free of dementia. We performed multisequence magnetic resonance imaging, which included diffusion tensor imaging, and extensive neuropsychological testing. Fractional anisotropy, mean diffusivity, and directional diffusivities were measured globally in white matter lesions and normal-appearing white matter. Main Outcome Measures: Performance on neuro- psychological tests in the following cognitive domains: memory, executive function, information processing speed, global cognition, and motor speed. Results: Regardless of macrostructural white matter changes, a higher mean diffusivity or higher axial and radial diffusivities within white matter lesions or normal- appearing white matter were related to worse performance on tasks assessing information processing speed and global cognition. In addition, diffusivity within white matter lesions related to memory, while in normal-appearing white matter, it furthermore related to executive function. Lower mean fractional anisotropy in white matter lesions or normal-appearing white matter related to worse information processing speed and motor speed. Conclusions: Microstructural integrity of both white matter lesions and normal-appearing white matter is associated with cognitive function, regardless of white matter atrophy and white matter lesion volume. This suggests that measuring white matter integrity has added value beyond macrostructural assessment of white matter changes to study the relation between white matter and cognition.

White matter lesion extension to automatic brain tissue segmentation on MRI (Article)

2009-05-01T00:00:00Z

A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.

Selective deblurring for improved calcification visualization and quantification in carotid CT angiography: Validation using micro-CT (Article)

2009-03-01T00:00:00Z

Visualization and quantification of small structures with computed tomography (CT) is hampered by the limited spatial resolution of the system. Histogram-based selective deblurring (HiSD) is a deconvolution method that restores small high-density structures, i.e., calcifications, of a CT image, using the high-intensity voxel information of the deconvolved image, while preserving the original hounsfield Units (HUs) in the remaining tissues. In this study, high resolution micro-CT data are used to validate the potential of HiSD to improve calcium visualization and quantification in the carotid arteries on in vivo contrast-enhanced CTA data. The evaluation is performed qualitatively and quantitatively on 15 atherosclerotic plaques obtained from ten different patients. HiSD in combination with vessel segmentation significantly improves calcification visualization and quantification on in vivo contrast-enhanced CT images. Calcification blur is reduced, while avoiding noise amplification and edge-ringing artifacts in the surrounding tissues. Calcification quantification errors are reduced by 23.5% on average. © 2006 IEEE.

Coronary lumen segmentation using graph cuts and robust kernel regression. (Article)

2009-01-01T00:00:00Z

Motion compensated iterative reconstruction of a region of interest in cardiac cone-beam CT (Article)

2009-01-01T00:00:00Z

A method for motion compensated iterative CT reconstruction of a cardiac region-of-interest is presented. The algorithm is an ordered subset maximum likelihood approach with spherically symmetric basis functions, and it uses an ECG for gating. Since the straightforward application of iterative methods to CT data has the drawback that a field-of-view has to be reconstructed, which covers the complete volume contributing to the absorption, region-of-interest reconstruction is applied here. Despite gating, residual object motion within the reconstructed gating window leads to motion blurring in the reconstructed image. To limit this effect, motion compensation is applied. Hereto, a gated 4D reconstruction at multiple phases is generated for the region-of-interest, and a limited set of vascular landmarks are manually annotated throughout the cardiac phases. A dense motion vector field is obtained from these landmarks by scattered data interpolation. The method is applied to two clinical data sets at strongest motion phases. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improved reconstruction quality.

Multiple object tracking in molecular bioimaging by Rao-Blackwellized marginal particle filtering (Article)

2008-12-01T00:00:00Z

Time-lapse fluorescence microscopy imaging has rapidly evolved in the past decade and has opened new avenues for studying intracellular processes in vivo. Such studies generate vast amounts of noisy image data that cannot be analyzed efficiently and reliably by means of manual processing. Many popular tracking techniques exist but often fail to yield satisfactory results in the case of high object densities, high noise levels, and complex motion patterns. Probabilistic tracking algorithms, based on Bayesian estimation, have recently been shown to offer several improvements over classical approaches, by better integration of spatial and temporal information, and the possibility to more effectively incorporate prior knowledge about object dynamics and image formation. In this paper, we extend our previous work in this area and propose an improved, fully automated particle filtering algorithm for the tracking of many subresolution objects in fluorescence microscopy image sequences. It involves a new track management procedure and allows the use of multiple dynamics models. The accuracy and reliability of the algorithm are further improved by applying marginalization concepts. Experiments on synthetic as well as real image data from three different biological applications clearly demonstrate the superiority of the algorithm compared to previous particle filtering solutions.

Averaging centerlines: Mean shift on paths (Article)

2008-12-01T00:00:00Z

Generation of a reference standard from multiple manually annotated datasets is a non-trivial problem. This paper discusses the weighted averaging of 3D open curves, which we used to generate a reference standard for vessel tracking data. We show how weighted averaging can be implemented by applying the Mean Shift algorithm to paths, and discuss the details of our implementation. Our approach can handle cases where the observer centerlines take different branches in a natural way. The method has been evaluated on synthetic data, and has been used to generate reference centerlines for evaluation of vessel tracking algorithms.

Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts (Article)

2008-12-01T00:00:00Z

Since hippocampal volume has been found to be an early biomarker for Alzheimer's disease, there is large interest in automated methods to accurately, robustly, and reproducibly extract the hippocampus from MRI data. In this work we present a segmentation method based on the minimization of an energy functional with intensity and prior terms, which are derived from manually labelled training images. The intensity energy is based on a statistical intensity model that is learned from the training images. The prior energy consists of a spatial and regularity term. The spatial prior is obtained from a probabilistic atlas created by registering the training images to the unlabelled target image, and deforming and averaging the training labels. The regularity prior energy encourages smooth segmentations. The resulting energy functional is globally minimized using graph cuts. The method was evaluated using image data from a population-based study on diseases among the elderly. Two set of images were used: a small set of 20 manually labelled MR images and a larger set of 498 images, for which manual volume measurements were available, but no segmentations. This data was previously used in a volumetry study that found significant associations between hippocampal volume and cognitive decline and incidence of dementia. Cross-validation experiments with the labelled set showed similarity indices of 0.852 and 0.864 and mean surface distances of 0.40 and 0.36 mm for the left and right hippocampus. 83% of the automated segmentations of the large set were rated as 'good' by a trained observer. Also, the proposed method was used to repeat the manual hippocampal volumetry study. The automatically obtained hippocampal volumes showed significant associations with cognitive decline and dementia, similar to the manually measured volumes. Finally, direct quantitative and qualitative comparisons showed that the proposed method outperforms a multi-atlas based segmentation method.

White matter atrophy and lesion formation explain the loss of structural integrity of white matter in aging (Article)

2008-11-15T00:00:00Z

The importance of macrostructural white matter changes, including white matter lesions and atrophy, in intact brain functioning is increasingly being recognized. Diffusion tensor imaging (DTI) enables measurement of the microstructural integrity of white matter. Loss of white matter integrity in aging has been reported, but whether this is inherent to the aging process itself or results from specific white matter pathology is unknown. In 832 persons aged 60 years and older from the population-based Rotterdam Study, we measured fractional anisotropy (FA) and directional diffusivities in normal-appearing white matter using DTI. All subjects' DTI measures were projected onto a common white matter skeleton to enable robust voxelwise comparison. With increasing age, multiple regions showed significant decreases in FA or increases in axial or radial diffusivity in normal-appearing white matter. However, nearly all of these regional changes were explained by either white matter atrophy or by white matter lesions; each of which related to changes in distinct brain regions. These results indicate that loss of white matter integrity in aging is primarily explained by atrophy and lesion formation and not by the aging process itself. Furthermore, white matter atrophy and white matter lesion formation relate to loss of integrity in distinct brain regions, indicating the two processes are pathophysiologically different.

Total cerebral blood flow in relation to cognitive function: The Rotterdam Scan study (Article)

2008-10-01T00:00:00Z

Cerebral hypoperfusion has been associated with worse cognitive function. We investigated the association between cerebral blood flow and cognition and whether this association is independent of brain volume. In 892 participants, aged 60 to 91 years, of the population-based Rotterdam Scan study, we measured total cerebral blood flow (tCBF) and brain volume using magnetic resonance imaging. Lower tCBF was associated with worse information-processing speed, executive function, and global cognition. However, after correcting tCBF for brain volume, these associations disappeared. The association between tCBF and cognition may be mediated or confounded by brain atrophy. Future studies on tCBF should take into account brain atrophy.

A new detection scheme for multiple object tracking in fluorescence microscopy by joint probabilistic data association filtering (In Proceedings)

2008-09-10T00:00:00Z

Tracking of multiple objects in biological image data is a challenging problem due largely to poor imaging conditions and complicated motion scenarios. Existing tracking algorithms for this purpose often do not provide sufficient robustness and/or are computationally expensive. In this paper we propose a new object detection scheme, based on importance sampling from image intensity distributions, and show how it can be easily incorporated into a probabilistic tracking framework based on Kalman or particle filtering. Experiments on synthetic as well as real fluorescence microscopy image data from different biological studies show that the resulting tracking algorithm yields smaller localization errors at much lower execution times compared to other available methods.

Advanced level-set based multiple-cell segmentation and tracking in time-lapse fluorescence microscopy images (In Proceedings)

2008-09-10T00:00:00Z

Segmentation and tracking of cells in fluorescence microscopy image sequences is an important task in many biological studies into cell migration as well as intracellular dynamics. The growing size and complexity of biological image data sets precludes manual analysis, and calls for increasingly advanced automatic algorithms that are generic enough to be easily tunable to different applications, yet robust enough to deal with different cell types and strongly varying imaging conditions. Active-contour based algorithms have proven to be very suitable for this purpose but still suffer from several short-comings that limit their segmentation accuracy and tracking robustness. In addition, these algorithms are generally rather computationally expensive. In this paper, we present an advanced level-set based multiple-cell segmentation and tracking algorithm, which implements seven modifications compared to earlier algorithms that considerably improve its performance. Preliminary experiments on three different time-lapse fluorescence microscopy images demonstrate the potential of the new algorithm.

Automatic image-driven segmentation of the ventricles in cardiac cine MRI (Article)

2008-08-01T00:00:00Z

Purpose: To propose and to evaluate a novel method for the automatic segmentation of the heart's two ventricles from dynamic ("cine") short-axis "steady state free precession" (SSFP) MR images. This segmentation task is of significant clinical importance. Previously published automated methods have various disadvantages for routine clinical use. Materials and Methods: The proposed method is primarily image-driven: it exploits the spatiotemporal information provided by modern 3D+time SSFP cardiac MRI, and makes only few and plausible assumptions about the image acquisition and about the imaged heart. Specifically, the method does not require previously trained statistical shape models or gray-level appearance models, as often used by other methods. Results: The performance of the segmentation method was demonstrated through a qualitative visual validation on 32 clinical exams: no gross failures for the left-ventricle (right-ventricle) on 31 (29) of the exams were found. A validation of resulting quantitative cardiac functional parameters showed good agreement with a manual quantification of 19 clinical exams. Conclusion: The proposed method is feasible, fast, and robust against anatomical variability and image contrast variations.

Cerebral arteries: Fully automated segmentation from ct angiography - A feasibility study (Article)

2008-06-01T00:00:00Z

The purpose of this study was to retrospectively assess the feasibility of a fully automated image postprocessing tool for the segmentation of the arterial cerebrovasculature from computed tomographic (CT) angiography in 27 patients (nine men, 18 women; mean age, 55 years; age range, 33-76 years) with subarachnoid hemorrhage. The institutional review board approved this study, and informed consent was waived. The proposed method, which does not require the acquisition of an additional CT scan for bone suppression, consists of the following: (a) automatic detection of the main arteries for initialization, (b) segmentation of these arteries through the skull base, and (c) suppression of the large veins near the skull. The parameters of this method were optimized on the training subset of nine patients, and the method was successful at segmentation of the arteries in 15 (83%) of the 18 remaining patients. The difference between automatic and manual diameter measurements was 0.0 mm ± 0.4 (standard deviation). The study results showed that fully automated segmentation of the cerebral arteries is feasible.

Brain tissue volumes in the general elderly population. The Rotterdam Scan Study (Article)

2008-06-01T00:00:00Z

We investigated how volumes of cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) varied with age, sex, small vessel disease and cardiovascular risk factors in the Rotterdam Scan Study. Participants (n = 490; 60-90 years) were non-demented and 51.0% had hypertension, 4.9% had diabetes mellitus, 17.8% were current smoker and 54.0% were former smoker. We segmented brain MR-images into GM, normal WM, white matter lesion (WML) and CSF. Brain infarcts were rated visually. Volumes were expressed as percentage of intra-cranial volume. With increasing age, volumes of total brain, normal WM and total WM decreased; that of GM remained unchanged; and that of WML increased, in both men and women. Excluding persons with infarcts did not alter these results. Persons with larger load of small vessel disease had smaller brain volume, especially normal WM volume. Diastolic blood pressure, diabetes mellitus and current smoking were also related to smaller brain volume. In the elderly, higher age, small vessel disease and cardiovascular risk factors are associated with smaller brain volume, especially WM volume.

Volume preserving image registration via a post-processing stage (Article)

2008-05-19T00:00:00Z

In this paper a method to remove the divergence from a vector field is presented. When applied to a displacement field, this will remove all local compression and expansion. The method can be used as a post-processing step for (unconstrained) registered images, when volume changes in the deformation field are undesired. The method involves solving Poisson's equation for a large system. Algorithms to solve such systems include Fourier analysis and Cyclic Reduction. These solvers are vastly applied in the field of fluid dynamics, to compensate for numerical errors in calculated velocity fields. The application to medical image registration as described in this paper, has to our knowledge not been done before. To show the effect of the method, it is applied to the registration of both synthetic data and dynamic MR series of the liver. The results show that the divergence in the displacement field can be reduced by a factor of 10 - 1000 and that the accuracy of the registration increases.

Prevalence and risk factors of cerebral microbleeds: The Rotterdam Scan Study (Article)

2008-04-01T00:00:00Z

BACKGROUND: Cerebral microbleeds are focal deposits of hemosiderin that can be visualized with MRI. Little is known on their prevalence in the general population and on their etiology. It has been suggested that, in analogy to spontaneous intracranial hemorrhage, the etiology of microbleeds differs according to their location in the brain, with lobar microbleeds being caused by cerebral amyloid angiopathy and deep or infratentorial microbleeds resulting from hypertension and atherosclerosis. We investigated the prevalence of and risk factors for microbleeds in the general population aged 60 years and older. METHODS: This study is based on 1,062 persons (mean age 69.6 years) from the population-based Rotterdam Scan Study. MRI was performed at 1.5 T and included a sequence optimized to increase the conspicuity of microbleeds. We assessed the relation of APOE genotype, cardiovascular risk factors, and markers of small vessel disease to the presence and location of microbleeds with multiple logistic regression. RESULTS: Overall prevalence of cerebral microbleeds was high and increased with age from 17.8% in persons aged 60-69 years to 38.3% in those over 80 years. APOE ε4 carriers had significantly more often strictly lobar microbleeds than noncarriers. In contrast, cardiovascular risk factors and presence of lacunar infarcts and white matter lesions were associated with microbleeds in a deep or infratentorial location but not in a lobar location. CONCLUSION: The prevalence of cerebral microbleeds is high. Our data support the hypothesis that strictly lobar microbleeds are related to cerebral amyloid angiopathy, whereas microbleeds in a deep or infratentorial location result from hypertensive or atherosclerotic microangiopathy.

Assessment of atherosclerotic carotid plaque volume with multidetector computed tomography angiography (Article)

2008-03-31T00:00:00Z

Purpose: The amount of atherosclerotic plaque and its components (calcifications, fibrous tissue, and lipid core) could be better predictors of acute events than the now currently used degree of stenosis. Therefore, we evaluated a dedicated software tool for volume measurements of atherosclerotic carotid plaque and its components in multidetector computed tomography angiography (MDCTA) images. Materials and Methods: Data acquisition was approved by the Institutional Review Board and all patients gave written informed consent. MDCTA images of 56 carotid arteries were analyzed by three observers. Plaque volumes were assessed by manual drawing of the outer vessel contour. The luminal boundary was determined based on a Hounsfield-Unit (HU) threshold. The contribution of different components was measured by the number of voxels within defined ranges of HU-values (calcification >130 HU, fibrous tissue 60-130 HU, lipid core <60 HU). Interobserver variability (IOV) was assessed. Results: Plaque volume was 1,259 ± 621 mm3. The calcified, fibrous and lipid volumes were 238 ± 252 mm3, 647± 277 mm3 and 376± 283 mm3, respectively. IOV was moderate with interclass correlation coefficients (ICC) ranging from 0.76 to 0.99 and coefficients of variation (COV) ranging from 3% to 47%. Conclusion: Atherosclerotic carotid plaque volume and plaque component volumes can be assessed with MDCTA with a reasonable observer variability.

MR venography of the human brain using susceptibility weighted imaging at very high field strength (Article)

2008-03-01T00:00:00Z

Objective: We investigate the implications of high magnetic field strength on MR venography based on susceptibility-weighted imaging (SWI) and estimate the optimum echo time to obtain maximum contrast between blood and brain tissue. Materials and methods: We measured tissue contrast and T*2relaxation times at 7 T of gray matter, white matter, and venous blood in vivo. Results: T*2relaxation times of gray matter, white matter, and venous blood in vivo yielded 32.9 ± 2.3, 27.7 ± 4.3, and 7.4 ± 1.4 ms, respectively. Optimum TE was found to be 15 ms which is supported by theoretical considerations. Using this optimum TE, we acquired 3D high resolution datasets with a large volume coverage in a short measurement time that show very detailed microanatomical structures of the human brain such as intracortical veins and laminar cortical substructures. Conclusions: By applying optimised vessel filters (vesselness filter and vessel enhancing diffusion) whole brain MR venograms can be obtained at 7 T with a significantly reduced measurement time compared to 3 T.

Kidney function is related to cerebral small vessel disease (Article)

2008-01-01T00:00:00Z

BACKGROUND AND PURPOSE - Poor kidney function, as measured by glomerular filtration rate (GFR), is closely associated with presence of glomerular small vessel disease. Given the hemodynamic similarities between the vascular beds of the kidney and the brain, we hypothesized an association between kidney function and markers of cerebral small vessel disease on MRI. We investigated this association in a population-based study of elderly persons. METHODS - We measured GFR using the Cockcroft-Gault equation in 484 participants (60 to 90 years of age) from the Rotterdam Scan Study. Using automated MRI-analysis we measured global as well as lobar and deep volumes of gray matter and white matter, and volume of WML. Lacunar infarcts were rated visually. Volumes of deep white matter and WML and presence of lacunar infarcts reflected cerebral small vessel disease. We used linear and logistic regression models to investigate the association between GFR and brain imaging parameters. Analyses were adjusted for age, sex, and additionally for cardiovascular risk factors. RESULTS - Persons with lower GFR had less deep white matter volume (difference in standardized volume per SD decrease in GFR: -0.15 [95% CI -0.26 to -0.04]), more WML (difference per SD decrease in GFR: 0.14 [95% CI 0.03 to 0.25]), and more often lacunar infarcts, although the latter was not significant. GFR was not associated with gray matter volume or lobar white matter volume. Additional adjustment for cardiovascular risk factors yielded similar results. CONCLUSIONS - Impaired kidney function is associated with markers of cerebral small vessel disease as assessed on MRI.

Incidental findings on brain MRI in the general population (Article)

2007-11-01T00:00:00Z

Background: Magnetic resonance imaging (MRI) of the brain is increasingly used both in research and in clinical medicine, and scanner hardware and MRI sequences are continually being improved. These advances are likely to result in the detection of unexpected, asymptomatic brain abnormalities, such as brain tumors, aneurysms, and subclinical vascular pathologic changes. We conducted a study to determine the prevalence of such incidental brain findings in the general population. Methods: The subjects were 2000 persons (mean age, 63.3 years; range, 45.7 to 96.7) from the population-based Rotterdam Study in whom high-resolution, structural brain MRI (1.5 T) was performed according to a standardized protocol. Two trained reviewers recorded all brain abnormalities, including asymptomatic brain infarcts. The volume of white-matter lesions was quantified in milliliters with the use of automated post-processing techniques. Two experienced neuroradiologists reviewed all incidental findings. All diagnoses were based on MRI findings, and additional histologic confirmation was not obtained. Results: Asymptomatic brain infarcts were present in 145 persons (7.2%). Among findings other than infarcts, cerebral aneurysms (1.8%) and benign primary tumors (1.6%), mainly meningiomas, were the most frequent. The prevalence of asymptomatic brain infarcts and meningiomas increased with age, as did the volume of white-matter lesions, whereas aneurysms showed no age-related increase in prevalence. Conclusions: Incidental brain findings on MRI, including subclinical vascular pathologic changes, are common in the general population. The most frequent are brain infarcts, followed by cerebral aneurysms and benign primary tumors. Information on the natural course of these lesions is needed to inform clinical management. Copyright

Advances in Radiologic Image Analysis From MICCAI 2006 (Article)

2007-11-01T00:00:00Z

Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification (Article)

2007-08-01T00:00:00Z

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.

Evaluation of an improved technique for lumen path definition and lumen segmentation of atherosclerotic vessels in CT angiography (Article)

2007-07-01T00:00:00Z

Vessel image analysis is crucial when considering therapeutical options for (cardio-) vascular diseases. Our method, VAMPIRE (Vascular Analysis using Multiscale Paths Inferred from Ridges and Edges), involves two parts: a user defines a start- and endpoint upon which a lumen path is automatically defined, and which is used for initialization; the automatic segmentation of the vessel lumen on computed tomographic angiography (CTA) images. Both parts are based on the detection of vessel-like structures by analyzing intensity, edge, and ridge information. A multi-observer evaluation study was performed to compare VAMPIRE with a conventional method on the CTA data of 15 patients with carotid artery stenosis. In addition to the start- and endpoint, the two radiologists required on average 2.5 (SD: 1.9) additional points to define a lumen path when using the conventional method, and 0.1 (SD: 0.3) when using VAMPIRE. The segmentation results were quantitatively evaluated using Similarity Indices, which were slightly lower between VAMPIRE and the two radiologists (respectively 0.90 and 0.88) compared with the Similarity Index between the radiologists (0.92). The evaluation shows that the improved definition of a lumen path requires minimal user interaction, and that using this path as initialization leads to good automatic lumen segmentation results.

Histogram-based selective deblurring to improve computed tomography imaging of calcifications (Article)

2007-01-01T00:00:00Z

OBJECTIVES: Computed tomography (CT) imaging of small high-density structures, eg, calcifications, is hampered by image blur. This study aims to deconvolve calcifications in the transverse and longitudinal directions while avoiding noise amplification and edge-ringing artifacts in the surrounding low-density structures. MATERIALS AND METHODS: A method referred to as histogram-based selective deblurring (HiSD) has been developed to generate a restored image by combining the low-intensity (ie, Hounsfield Units) information of the original image with the high-intensity information of the deconvolved image. HiSD is evaluated on phantom and in vitro atherosclerotic plaque CT images by comparing the original and restored images with their corresponding reference micro-CT images both qualitatively and quantitatively. RESULTS: HiSD reduces calcification blur in the transverse and longitudinal directions without introducing noise and ringing-artifacts in the surrounding tissues. Calcification area and volume measurements are significantly improved in the restored images (reducing on average overestimation by 32% and 83%, respectively). CONCLUSIONS: HiSD significantly improves CT visualization and quantification of small high-density structures imaged in vitro.

Vessel Axis Tracking Using Topology Constrained Surface Evolution (Article)

2007-01-01T00:00:00Z

An approach to three-dimensional vessel axis tracking based on surface evolution is presented. The main idea is to guide the evolution of the surface by analyzing its skeleton topology during evolution, and imposing shape constraints on the topology. For example, the intermediate topology can be processed such that it represents a single vessel segment, a bifurcation, or a more complex vascular topology. The evolving surface is then re-initialized with the newly found topology. Re-initialization is a crucial step since it creates probing behavior of the evolving front, encourages the segmentation process to extract the vascular structure of interest and reduces the risk on leaking of the curve into the background. The method was evaluated in two computed tomography angiography applications: (i) extracting the internal carotid arteries including the region in which they traverse through the skull base, which is challenging due to the proximity of bone structures and overlap in intensity values, and (ii) extracting the carotid bifurcations including many cases in which they are severely stenosed and contain calcifications. The vessel axis was found in 90% (18/20 internal carotids in ten patients) and 70% (14/20 carotid bifurcations in a different set of ten patients) of the cases.

Beeldenstorm in de Geneeskunde (Inaugural Lecture)

2006-01-13T00:00:00Z

De Dikke van Dale|1 kent aan het woord “Beeldenstorm” twee gangbare betekenissen toe. De beeldenstorm is met name bekend als een belangrijk moment in onze vaderlandse geschiedenis, en refereert aan de “calvinistische volksbeweging in 1566, vooral in Vlaanderen en Brabant, tegen het vereren van beelden in kerken”. Deze beeldenstorm ging gepaard met “gewelddadige vernieling en verwoesting van beelden, schilderijen en andere kostbaarheden en kunstwerken in kerken”. Hoewel er ook zeker politieke en sociale oorzaken aan de beeldenstorm ten grondslag lagen, waren de motieven voor de beeldenstorm dus met name van ideële, religieuze aard. De volksbeweging zette zich af tegen de verering van beelden, en de protserige rijkdom van de Rooms-katholieke kerk. De gevolgen van de beeldenstorm waren voor de Nederlanden verstrekkend. De gebeurtenissen leidden ertoe dat Filips II de hertog van Alva naar de Nederlanden stuurde, om een strafexpeditie uit te voeren, er het katholieke geloof op te leggen, en het bestuur te centraliseren. Weerstand tegen dit regime leidde tot de tachtigjarige oorlog. Indirect kan de beeldenstorm dus worden gezien als aanleiding voor de tachtigjarige oorlog. Het zich afzetten tegen de gevestigde orde vinden we terug in de tweede betekenis die de Dikke van Dale aan het woord “beeldenstorm” toekent: “Bestrijding van geijkte instellingen, conventies, gevestigde opvattingen”. Met deze rede sluit ik me graag aan bij deze tweede, figuurlijke betekenis van het woord beeldenstorm. Want het zijn met name beelden die de geneeskunde de laatste eeuwen ingrijpend hebben veranderd. En het zijn met name beelden die tot belangrijke nieuwe inzichten hebben geleid, zowel op het gebied van de menselijke anatomie en fysiologie, als in het begrip van ziekteprocessen. Dit is niet zo verwonderlijk, gezien de kracht van het beeld. We kennen niet voor niets de uitdrukking: “Eerst zien, dan geloven”. We leren door te zien. Er bestaat geen krachtiger middel om gevestigde opinies te bestrijden dan beelden te tonen die met deze opinies in strijd zijn. En er bestaat geen krachtiger middel om nieuwe inzichten te verwerven in een systeem dan door de processen die zich in het systeem afspelen af te beelden. Zo ook in de geneeskunde.

Vessel enhancing diffusion: a scale space representation of vessel (Article)

2006-01-01T00:00:00Z

A method is proposed to enhance vascular structures within the framework of scale space theory. We combine a smooth vessel filter which is based on a geometrical analysis of the Hessian's eigensystem, with a non-linear anisotropic diffusion scheme. The amount and orientation of diffusion depend on the local vessel likeliness. Vessel enhancing diffusion (VED) is applied to patient and phantom data and compared to linear, regularized Perona-Malik, edge and coherence enhancing diffusion. The method performs better than most of the existing techniques in visualizing vessels with varying radii and in enhancing vessel appearance. A diameter study on phantom data shows that VED least affects the accuracy of diameter measurements. It is shown that using VED as a preprocessing step improves level set based segmentation of the cerebral vasculature, in particular segmentation of the smaller vessels of the vasculature.