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Femoroacetabular impingement (FAI) cam morphology is routinely assessed usingtwo-dimensional alpha angles which do not provide specific data on cam sizecharacteristics. The purpose of this study is to implement a novel, automatedthree-dimensional (3D) pipeline, CamMorph, for segmentation and measurement ofcam volume, surface area and height from magnetic resonance (MR) images inpatients with FAI. The CamMorph pipeline involves two processes: i) proximalfemur segmentation using an approach integrating 3D U-net with focused shapemodelling (FSM); ii) use of patient-specific anatomical information from 3D FSMto simulate healthy femoral bone models and pathological region constraints toidentify cam bone mass. Agreement between manual and automated segmentation ofthe proximal femur was evaluated with the Dice similarity index (DSI) andsurface distance measures. Independent t-tests or Mann-Whitney U rank testswere used to compare the femoral head volume, cam volume, surface area andheight data between female and male patients with FAI. There was a mean DSIvalue of 0.964 between manual and automated segmentation of proximal femurvolume. Compared to female FAI patients, male patients had a significantlylarger mean femoral head volume (66.12cm3 v 46.02cm3, p<0.001). Compared tofemale FAI patients, male patients had a significantly larger mean cam volume(1136.87mm3 v 337.86mm3, p<0.001), surface area (657.36mm2 v 306.93mm2 ,p<0.001), maximum-height (3.89mm v 2.23mm, p<0.001) and average-height (1.94mmv 1.00mm, p<0.001). Automated analyses of 3D MR images from patients with FAIusing the CamMorph pipeline showed that, in comparison with female patients,male patients had significantly greater cam volume, surface area and height.

Automated volumetric and statistical shape assessment of cam-type morphology of the femoral head-neck region from 3D magnetic resonance images