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基于临床三维磁共振图像的股骨头颈区域凸轮型形态的自动容积和统计形状评估

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

作者信息

Bugeja Jessica M, Xia Ying, Chandra Shekhar S, Murphy Nicholas J, Eyles Jillian, Spiers Libby, Crozier Stuart, Hunter David J, Fripp Jurgen, Engstrom Craig

机构信息

School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia.

Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Health and Biosecurity, Herston, Australia.

出版信息

Quant Imaging Med Surg. 2022 Oct;12(10):4924-4941. doi: 10.21037/qims-22-332.

Abstract

BACKGROUND

Femoroacetabular impingement (FAI) cam morphology is routinely assessed using manual measurements of two-dimensional (2D) alpha angles which are prone to high rater variability and do not provide direct three-dimensional (3D) data on these osseous formations. We present CamMorph, a fully automated 3D pipeline for segmentation, statistical shape assessment and measurement of cam volume, surface area and height from clinical magnetic resonance (MR) images of the hip in FAI patients.

METHODS

The novel CamMorph pipeline involves two components: (I) accurate proximal femur segmentation generated by combining the 3D U-net to identify both global (region) and local (edge) features in clinical MR images and focused shape modelling to generate a 3D anatomical model for creating patient-specific proximal femur models; (II) patient-specific anatomical information from 3D focused shape modelling to simulate 'healthy' femoral bone models with cam-affected region constraints applied to the anterosuperior femoral head-neck region to quantify cam morphology in FAI patients. The CamMorph pipeline, which generates patient-specific data within 5 min, was used to analyse multi-site clinical MR images of the hip to measure and assess cam morphology in male (n=56) and female (n=41) FAI patients.

RESULTS

There was excellent agreement between manual and CamMorph segmentations of the proximal femur as demonstrated by the mean Dice similarity index (DSI; 0.964±0.006), 95% Hausdorff distance (HD; 2.123±0.876 mm) and average surface distance (ASD; 0.539±0.189 mm) values. Compared to female FAI patients, male patients had a significantly larger median cam volume (969.22 272.97 mm, U=240.0, P<0.001), mean surface area [657.36 306.93 mm, t(95)=8.79, P<0.001], median maximum-height (3.66 2.15 mm, U=407.0, P<0.001) and median average-height (1.70 0.86 mm, U=380.0, P<0.001).

CONCLUSIONS

The fully automated 3D CamMorph pipeline developed in the present study successfully segmented and measured cam morphology from clinical MR images of the hip in male and female patients with differing FAI severity and pathoanatomical characteristics.

摘要

背景

股骨髋臼撞击症(FAI)的凸轮形态通常通过手动测量二维(2D)α角来评估,这种方法容易出现较高的评分者变异性,并且无法提供这些骨性结构的直接三维(3D)数据。我们提出了CamMorph,这是一种用于从FAI患者的髋关节临床磁共振(MR)图像中进行分割、统计形状评估以及测量凸轮体积、表面积和高度的全自动3D流程。

方法

新颖的CamMorph流程包括两个部分:(I)通过结合3D U-net以识别临床MR图像中的全局(区域)和局部(边缘)特征,并进行聚焦形状建模以生成3D解剖模型,从而创建患者特异性近端股骨模型,实现准确的近端股骨分割;(II)利用3D聚焦形状建模得到的患者特异性解剖信息,在应用于股骨头-颈前上区域的凸轮影响区域约束条件下,模拟“健康”股骨模型,以量化FAI患者的凸轮形态。CamMorph流程可在5分钟内生成患者特异性数据,用于分析髋关节的多部位临床MR图像,以测量和评估男性(n = 56)和女性(n = 41)FAI患者的凸轮形态。

结果

股骨近端的手动分割与CamMorph分割之间具有极好的一致性,平均骰子相似性指数(DSI;0.964±0.006)、95%豪斯多夫距离(HD;2.123±0.876 mm)和平均表面距离(ASD;0.539±0.189 mm)值证明了这一点。与女性FAI患者相比,男性患者的凸轮体积中位数显著更大(969.22±272.97 mm³,U = 240.0,P < 0.001)、平均表面积[657.36±306.93 mm²,t(95)= 8.79,P < 0.001]、最大高度中位数(3.66±2.15 mm,U = 407.0,P < 0.001)和平均高度中位数(1.70±0.86 mm,U = 380.0,P < 0.001)。

结论

本研究中开发的全自动3D CamMorph流程成功地从具有不同FAI严重程度和病理解剖特征的男性和女性患者的髋关节临床MR图像中分割并测量了凸轮形态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/241a/9511434/7de6679b4026/qims-12-10-4924-f1.jpg

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