MRI-based 3D models of the hip joint enables radiation-free computer-assisted planning of periacetabular osteotomy for treatment of hip dysplasia using deep learning for automatic segmentation

Abstract

Introduction Both Hip Dysplasia(DDH) and Femoro-acetabular-Impingement(FAI) are complex three-dimensional hip pathologies causing hip pain and osteoarthritis in young patients. 3D-MRI-based models were used for radiation-free computer-assisted surgical planning. Automatic segmentation of MRI-based 3D-models are preferred because manual segmentation is time-consuming. To investigate(1) the difference and(2) the correlation for femoral head coverage(FHC) between automatic MR-based and manual CT-based 3D-models and (3) feasibility of preoperative planning in symptomatic patients with hip diseases. Methods We performed an IRB-approved comparative, retrospective study of 31 hips(26 symptomatic patients with hip dysplasia or FAI). 3D MRI sequences and CT scans of the hip were acquired. Preoperative MRI included axial-oblique T1 VIBE sequence(0.8 mm 3 isovoxel) of the hip joint. Manual segmentation of MRI and CT scans were performed. Automatic segmentation of MRI-based 3D-models was performed using deep learning. Results (1)The difference between automatic and manual segmentation of MRI-based 3D hip joint models was below 1 mm(proximal femur 0.2 ± 0.1 mm and acetabulum 0.3 ± 0.5 mm). Dice coefficients of the proximal femur and the acetabulum were 98 % and 97 %, respectively. (2)The correlation for total FHC was excellent and significant(r = 0.975, p < 0.001) between automatic MRI-based and manual CT-based 3D-models. Correlation for total FHC (r = 0.979, p < 0.001) between automatic and manual MR-based 3D models was excellent. (3)Preoperative planning and simulation of periacetabular osteotomy was feasible in all patients(100 %) with hip dysplasia or acetabular retroversion. Conclusions Automatic segmentation of MRI-based 3D-models using deep learning is as accurate as CT-based 3D-models for patients with hip diseases of childbearing age. This allows radiation-free and patient-specific preoperative simulation and surgical planning of periacetabular osteotomy for patients with DDH.

Diagnosis of acetabular retroversion: Three signs positive and increased retroversion index have higher specificity and higher diagnostic accuracy compared to isolated positive cross over sign

“…This study has limitations. First, we did measure AV manually on 2D axial CT/MRI images, there was no 3D model available [34] . However, by using the same method of previous studies [25] , this allows for a direct comparison with the reported values from previous studies.…”

“…Recent validation studies showed comparable results for AV measurements between CT and MRI [32] , [33] . Previous studies used advanced methods for calculation of AV [34] or evaluated the influence of pelvic tilt [35] . Direct MR arthrography [36] was obtained according to a protocol-specific standardized technique.…”

Real-world analysis of artificial intelligence in musculoskeletal trauma

“…The DL based segmentation algorithms may have a role to play in automatic segmentation. A study by Zeng G. et al, 61 performed automatic segmentation of MRI-based 3D models utilising DL, which was at par in terms of accuracy with the CT-based 3D models for patients with hip diseases of childbearing age. Thus, DL enabled improved usage of MRI, which permits radiation-free and patienttailored preoperative simulation and surgical planning of periacetabular osteotomy in cases suffering from developmental dysplasia of the hip.…”

3D MRI Models of the Musculoskeletal System

“…7 In a study evaluating the accuracy of automatic deep learning segmentation of 3D MRI models for planning periacetabular osteotomy in hip dysplasia, there was excellent correlation for femoral head coverage anteversion and inclination between manual segmentation of CT-based and automatic segmentation of MRI-based 3D models. 47 Specific software developed for the planning of periacetabular osteotomy was used to calculate anterior, posterior, and total femoral head coverage, anteversion, inclination, and the extrusion index. 47 Femoral head coverage and anteversion are important diagnostic parameters to determine the need for and planning of surgical treatments of pincer impingement and hip dysplasia in patients who are candidates for arthroscopy and periacetabular osteotomy.…”

“…47 Specific software developed for the planning of periacetabular osteotomy was used to calculate anterior, posterior, and total femoral head coverage, anteversion, inclination, and the extrusion index. 47 Femoral head coverage and anteversion are important diagnostic parameters to determine the need for and planning of surgical treatments of pincer impingement and hip dysplasia in patients who are candidates for arthroscopy and periacetabular osteotomy. 34,36,37,41 In another study, 3D MRI was used to quantify femoral head deformity in patients with Legg-Calvé-Perthes disease (LCPD) using a 3D fat-suppressed spoiled GRE sequence and 3D postprocessing.…”