The ideal location of the male nipple-areolar complex: A pinpointing algorithm

Background: In the treatment of gender dysphoria, appropriate nipple-areola complex (NAC) positioning is essential for achieving a natural appearing male chest after subcutaneous mastectomy. An accurate predictive model for the ideal personalized position of the NAC is still lacking. The aim of this study is to determine the anthropometry of the male chest to create individualized guidelines for appropriate NAC positioning in the preoperative setting. Materials and methods: Cisgender male participants were recruited. Multiple chest measurements were manually recorded. Best subset regression using linear models was used to select predictors for the horizontal coordinate (nipple-nipple distance; NN) and vertical coordinate (sternal notch-nipple distance; SNN) of the NAC. Internal validation was assessed using bootstrapping. Furthermore, a cohort of transgender men who had received a mastectomy with replantation of nipples according to current practice was identified. Comparison testing between the algorithm and standard practice was performed to test the limitations of standard practice. Results: One hundred and fifty cis male participants were included (median age: 26, IQR: 22-34 years). Four predictors were found to predict NN (age, weight, chest circumference (CC), anterior-axillar fold to anterior-axillar fold (AUX-AUX)) and reads as follows: NN = 4.11 + 0.035*age + 0.041*weight + 0.093*CC + 0.140*AUX-AUX Two predictors were found to predict SNN (NN and weight), and reads as follows: SNN = 7.248 + 0.303*NN + 0.072*weight. Both models performed well (Bootstrapped R2: 0.63 (NN), 0.50 (SNN)) and outperformed previous models predicting NAC position. Ninety-six transgender men were eligible for evaluation of current practice and showed an average placement error of −0.9 cm for NN and +2.2 cm for SNN. Conclusion: The non-standardized approach of NAC repositioning results in a significant error of nipple placement. We suggest that the two predictive models for NN and SNN can be used to optimize NAC positioning on the masculinized chest wall. Supplemental data for this article is available online at https://doi.org/10.1080/26895269.2021.1884926.

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