A Framework for Three-dimensional Statistical Shape Modeling of the Proximal Femur in Legg-Calvé-Perthes Disease

Overview

Journal Int J Comput Assist Radiol Surg

Publisher Springer

Specialties General Surgery
Radiology

Date 2024 Oct 8

PMID 39377856

Authors

Luke G Johnson

Joseph D Mozingo

Penny R Atkins

Seaton Schwab

Alan Morris

Shireen Y Elhabian

David R Wilson

Harry K W Kim

Andrew E Anderson

Affiliations

Soon will be listed here.

Abstract

Purpose: The pathomorphology of Legg-Calvé-Perthes disease (LCPD) is a key contributor to poor long-term outcomes such as hip pain, femoroacetabular impingement, and early-onset osteoarthritis. Plain radiographs, commonly used for research and in the clinic, cannot accurately represent the full extent of LCPD deformity. The purpose of this study was to develop and evaluate a methodological framework for three-dimensional (3D) statistical shape modeling (SSM) of the proximal femur in LCPD.

Methods: We developed a framework consisting of three core steps: segmentation, surface mesh preparation, and particle-based correspondence. The framework aims to address challenges in modeling this rare condition, characterized by highly heterogeneous deformities across a wide age range and small sample sizes. We evaluated this framework by producing a SSM from clinical magnetic resonance images of 13 proximal femurs with LCPD deformity from 11 patients between the ages of six and 12 years.

Results: After removing differences in scale and pose, the dominant shape modes described morphological features characteristic of LCPD, including a broad and flat femoral head, high-riding greater trochanter, and reduced neck-shaft angle. The first four shape modes were chosen for the evaluation of the model's performance, together describing 87.5% of the overall cohort variance. The SSM was generalizable to unfamiliar examples with an average point-to-point reconstruction error below 1mm. We observed strong Spearman rank correlations (up to 0.79) between some shape modes, 3D measurements of femoral head asphericity, and clinical radiographic metrics.

Conclusion: In this study, we present a framework, based on SSM, for the objective description of LCPD deformity in three dimensions. Our methods can accurately describe overall shape variation using a small number of parameters, and are a step toward a widely accepted, objective 3D quantification of LCPD deformity.

References

Kim H . Legg-Calvé-Perthes disease. J Am Acad Orthop Surg. 2010; 18(11):676-86. DOI: 10.5435/00124635-201011000-00005. View

Paley D . The treatment of femoral head deformity and coxa magna by the Ganz femoral head reduction osteotomy. Orthop Clin North Am. 2011; 42(3):389-99, viii. DOI: 10.1016/j.ocl.2011.04.006. View

Clohisy J, Nepple J, Ross J, Pashos G, Schoenecker P . Does surgical hip dislocation and periacetabular osteotomy improve pain in patients with Perthes-like deformities and acetabular dysplasia?. Clin Orthop Relat Res. 2015; 473(4):1370-7. PMC: 4353550. DOI: 10.1007/s11999-014-4115-7. View

Dagenais S, Garbedian S, Wai E . Systematic review of the prevalence of radiographic primary hip osteoarthritis. Clin Orthop Relat Res. 2008; 467(3):623-37. PMC: 2635466. DOI: 10.1007/s11999-008-0625-5. View

OConnor J, Hill J, Beverland D, Dunne N, Lennon A . Influence of preoperative femoral orientation on radiographic measures of femoral head height in total hip replacement. Clin Biomech (Bristol). 2020; 81:105247. DOI: 10.1016/j.clinbiomech.2020.105247. View

Lechler P, Frink M, Gulati A, Murray D, Renkawitz T, Bucking B . The influence of hip rotation on femoral offset in plain radiographs. Acta Orthop. 2014; 85(4):389-95. PMC: 4105770. DOI: 10.3109/17453674.2014.931196. View

Gallant A, Harding A, Johnson C, Steenbeek A, Curran J . Identifying H1N1 and COVID-19 vaccine hesitancy or refusal among health care providers: a scoping review. JBI Evid Synth. 2023; 21(5):913-951. PMC: 10173945. DOI: 10.11124/JBIES-22-00112. View

Harris M, Datar M, Whitaker R, Jurrus E, Peters C, Anderson A . Statistical shape modeling of cam femoroacetabular impingement. J Orthop Res. 2013; 31(10):1620-6. PMC: 4137561. DOI: 10.1002/jor.22389. View

Turmezei T, Treece G, Gee A, Sigurdsson S, Jonsson H, Aspelund T . Quantitative 3D imaging parameters improve prediction of hip osteoarthritis outcome. Sci Rep. 2020; 10(1):4127. PMC: 7058047. DOI: 10.1038/s41598-020-59977-2. View

10.

Atkins P, Shin Y, Agrawal P, Elhabian S, Whitaker R, Weiss J . Which Two-dimensional Radiographic Measurements of Cam Femoroacetabular Impingement Best Describe the Three-dimensional Shape of the Proximal Femur?. Clin Orthop Relat Res. 2018; 477(1):242-253. PMC: 6345307. DOI: 10.1097/CORR.0000000000000462. View

11.

Chan E, Farnsworth C, Klisch S, Hosalkar H, Sah R . 3-dimensional metrics of proximal femoral shape deformities in Legg-Calvé-Perthes disease and slipped capital femoral epiphysis. J Orthop Res. 2017; 36(5):1526-1535. PMC: 6538305. DOI: 10.1002/jor.23791. View

12.

Standefer K, Dempsey M, Jo C, Kim H . 3D MRI Quantification of Femoral Head Deformity in Legg-Calvé-Perthes Disease. J Orthop Res. 2016; 35(9):2051-2058. DOI: 10.1002/jor.23484. View

13.

Pienkowski D, Resig J, Talwalkar V, Tylkowski C . Novel three-dimensional MRI technique for study of cartilaginous hip surfaces in Legg-Calvé-Perthes disease. J Orthop Res. 2009; 27(8):981-8. DOI: 10.1002/jor.20909. View

14.

Memis A, Varli S, Bilgili F . A novel approach for computerized quantitative image analysis of proximal femur bone shape deformities based on the hip joint symmetry. Artif Intell Med. 2021; 115:102057. DOI: 10.1016/j.artmed.2021.102057. View

15.

Goparaju A, Iyer K, Bone A, Hu N, Henninger H, Anderson A . Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. Med Image Anal. 2022; 76:102271. PMC: 8792348. DOI: 10.1016/j.media.2021.102271. View

16.

Cates J, Fletcher P, Styner M, Shenton M, Whitaker R . Shape modeling and analysis with entropy-based particle systems. Inf Process Med Imaging. 2007; 20:333-45. PMC: 2768473. DOI: 10.1007/978-3-540-73273-0_28. View

17.

Joseph B, Varghese G, Mulpuri K, Rao K, Nair N . Natural evolution of Perthes disease: a study of 610 children under 12 years of age at disease onset. J Pediatr Orthop. 2003; 23(5):590-600. DOI: 10.1097/00004694-200309000-00005. View

18.

Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J, Pujol S . 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012; 30(9):1323-41. PMC: 3466397. DOI: 10.1016/j.mri.2012.05.001. View

19.

Anderson A, Peters C, Tuttle B, Weiss J . Subject-specific finite element model of the pelvis: development, validation and sensitivity studies. J Biomech Eng. 2005; 127(3):364-73. DOI: 10.1115/1.1894148. View

20.

Whitmarsh T, Humbert L, De Craene M, Del Rio Barquero L, Frangi A . Reconstructing the 3D shape and bone mineral density distribution of the proximal femur from dual-energy X-ray absorptiometry. IEEE Trans Med Imaging. 2011; 30(12):2101-14. DOI: 10.1109/TMI.2011.2163074. View