Poot, D.H.J.

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

Microstructural changes observed with DKI in a transgenic Huntington rat model: Evidence for abnormal neurodevelopment (Article)

2012-01-16T00:00:00Z

Huntington Disease (HD) is a fatal neurodegenerative disorder, caused by a mutation in the Huntington gene. Although HD is most often diagnosed in mid-life, the key to its clinical expression may be found during brain maturation. In the present work, we performed in vivo diffusion kurtosis imaging (DKI) in order to study brain microstructure alterations in developing transgenic HD rat pups. Several developing brain regions, relevant for HD pathology (caudate putamen, cortex, corpus callosum, external capsule and anterior commissure anterior), were examined at postnatal days 15 (P15) and 30 (P30), and DKI results were validated with histology. At P15, we observed higher mean (MD) and radial (RD) diffusivity values in the cortex of transgenic HD rat pups. In addition, at the age of P30, lower axial kurtosis (AK) values in the caudate putamen of transgenic HD pups were found. At the level of the external capsule, higher MD values at P15 but lower MD and AD values at P30 were detected. The observed DKI results have been confirmed by myelin basic protein immunohistochemistry, which revealed a reduced fiber staining as well as less ordered fibers in transgenic HD rat pups. These results indicate that neuronal development in young transgenic HD rat pups occurs differently compared to controls and that the presence of mutant huntingtin has an influence on postnatal brain development. In this context, various diffusivity parameters estimated by the DKI model are a powerful tool to assess changes in tissue microstructure and detect developmental changes in young transgenic HD rat pups.

General and efficient super-resolution method for multi-slice MRI (Article)

2010-11-22T00:00:00Z

In this paper, a method is developed that reconstructs a high resolution image from an arbitrary set of multi-slice 3D MR images with a high in-plane resolution and a low through-plane resolution. Such images are often recorded to increase the efficiency of the acquisition. With a model of the acquisition of MR images, which is improved compared to previous super-resolution methods for MR images, a large system with linear equations is obtained. With the conjugated gradient method and this linear system, a high resolution image is reconstructed from MR images of an object. Also, a new and efficient method to apply an affine transformation to multi-dimensional images is presented. This method is used to efficiently reconstruction the high resolution image from multi-slice MR images with arbitrary orientations of the slices.