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Background: Biochemical MRI of hip cartilage such as delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) and T2 mapping is increasingly used to judge cartilage quality in the assessment of femoroacetabular impingement (FAI). The current evidence is sparse about which of these techniques yields a stronger correlation with histologic cartilage degeneration because of the difficulty in validating biochemical MRI techniques against histology in the clinical setting. Recently, an experimental ovine FAI model was established that induces chondrolabral damage and offers a validated platform to address these limitations., Questions/purposes: In a sheep model, we asked: (1) Do dGEMRIC and/or T2 values of acetabular and femoral cartilage correlate with histologic cartilage degeneration as assessed with the Mankin score? (2) Do simultaneously measured dGEMRIC and T2 values correlate in an experimental ovine FAI model?, Methods: We performed an experimental pilot study on five female Swiss Alpine sheep (10 hips) that underwent postmortem MRI, including biochemical cartilage sequences, after a staged FAI correction had been performed on one side. No surgery was performed on the contralateral side, which served as a healthy control. In these sheep, an extraarticular intertrochanteric varus osteotomy was performed to rotate the naturally aspherical ovine femoral head into the acetabulum to induce cam-type FAI and chondrolabral damage comparable to human beings. After a 70-day ambulation period, femoral osteochondroplasty was performed and all sheep were euthanized after a total observation period of 210 days. Before they were euthanized, the sheep received a contrast agent and roamed and walked for at least 45 minutes. Hips were prepared to fit in a knee coil and MRI was performed at 3 T including a three-dimensional (3-D) dGEMRIC sequence, a two-dimensional (2-D) radial T2 mapping sequence, and a 2-D radial proton density-weighted sequence for morphologic cartilage assessment. Using specifically developed software, the 3-D dGEMRIC images and T2 maps were coregistered on the 2-D morphologic radial images. This enabled us to simultaneously measure dGEMRIC and T2 values using the identical regions of interest. dGEMRIC and T2 values of the acetabular and femoral cartilage were measured circumferentially using anatomic landmarks. After MRI, bone-cartilage samples were taken from the acetabulum and the femur and stained with toluidine blue for assessment of the histologic cartilage degeneration using the Mankin score, which was assessed in consensus by two observers. Spearman's rank correlation coefficient was used to (1) correlate dGEMRIC values and T2 values with the histologic Mankin score of femoroacetabular cartilage; and to (2) correlate dGEMRIC values and T2 values of femoroacetabular cartilage., Results: A moderate to fair correlation between overall dGEMRIC values of the acetabular cartilage (R = -0.430; p = 0.003) and the femoral cartilage (R = -0.334; p = 0.003) versus the histologic Mankin score was found. A moderate correlation (R = -0.515; p = 0.010) was found among peripheral dGEMRIC values of the acetabulum, the superior femoral cartilage (R = -0.500; p = 0.034), and the histologic Mankin score, respectively. No correlation between overall and regional femoroacetabular T2 values and the histologic Mankin scores was found. No correlation between overall and regional femoroacetabular dGEMRIC values and T2 values was found., Conclusions: In this recently established sheep model, we found dGEMRIC values correlated well with histologic evidence of cartilage degeneration in the hip. This combination of a robust animal model and an accurate imaging technique appears to offer a noninvasive means to study the natural course of FAI and to compare the effectiveness of potential surgical options to treat it., Clinical Relevance: This translational study supports the continuing use of dGEMRIC as a biomarker for prearthritic cartilage degeneration with the ultimate goal to identify patients who will benefit most from corrective FAI surgery. The value of T2 imaging of hip cartilage warrants further investigation.

Background: The time-consuming and user-dependent postprocessing of biochemical cartilage MRI has limited the use of delayed gadolinium-enhanced MRI of cartilage (dGEMRIC). An automated analysis of biochemical three-dimensional (3-D) images could deliver a more time-efficient and objective evaluation of cartilage composition, and provide comprehensive information about cartilage thickness, surface area, and volume compared with manual two-dimensional (2-D) analysis., Questions/purposes: (1) How does the 3-D analysis of cartilage thickness and dGEMRIC index using both a manual and a new automated method compare with the manual 2-D analysis (gold standard)? (2) How does the manual 3-D analysis of regional patterns of dGEMRIC index, cartilage thickness, surface area and volume compare with a new automatic method? (3) What is the interobserver reliability and intraobserver reproducibility of software-assisted manual 3-D and automated 3-D analysis of dGEMRIC indices, thickness, surface, and volume for two readers on two time points?, Methods: In this IRB-approved, retrospective, diagnostic study, we identified the first 25 symptomatic hips (23 patients) who underwent a contrast-enhanced MRI at 3T including a 3-D dGEMRIC sequence for intraarticular pathology assessment due to structural hip deformities. Of the 23 patients, 10 (43%) were male, 16 (64%) hips had a cam deformity and 16 (64%) hips had either a pincer deformity or acetabular dysplasia. The development of an automated deep-learning-based approach for 3-D segmentation of hip cartilage models was based on two steps: First, one reader (FS) provided a manual 3-D segmentation of hip cartilage, which served as training data for the neural network and was used as input data for the manual 3-D analysis. Next, we developed the deep convolutional neural network to obtain an automated 3-D cartilage segmentation that we used as input data for the automated 3-D analysis. For actual analysis of the manually and automatically generated 3-D cartilage models, a dedicated software was developed. Manual 2-D analysis of dGEMRIC indices and cartilage thickness was performed at each "full-hour" position on radial images and served as the gold standard for comparison with the corresponding measurements of the manual and the automated 3-D analysis. We measured dGEMRIC index, cartilage thickness, surface area, and volume for each of the four joint quadrants and compared the manual and the automated 3-D analyses using mean differences. Agreement between the techniques was assessed using intraclass correlation coefficients (ICC). The overlap between 3-D cartilage volumes was assessed using dice coefficients and means of all distances between surface points of the models were calculated as average surface distance. The interobserver reliability and intraobserver reproducibility of the software-assisted manual 3-D and the automated 3-D analysis of dGEMRIC indices, thickness, surface and volume was assessed for two readers on two different time points using ICCs., Results: Comparable mean overall difference and almost-perfect agreement in dGEMRIC indices was found between the manual 3-D analysis (8 ± 44 ms, p = 0.005; ICC = 0.980), the automated 3-D analysis (7 ± 43 ms, p = 0.015; ICC = 0.982), and the manual 2-D analysis.Agreement for measuring overall cartilage thickness was almost perfect for both 3-D methods (ICC = 0.855 and 0.881) versus the manual 2-D analysis. A mean difference of -0.2 ± 0.5 mm (p < 0.001) was observed for overall cartilage thickness between the automated 3-D analysis and the manual 2-D analysis; no such difference was observed between the manual 3-D and the manual 2-D analysis.Regional patterns were comparable for both 3-D methods. The highest dGEMRIC indices were found posterosuperiorly (manual: 602 ± 158 ms; p = 0.013, automated: 602 ± 158 ms; p = 0.012). The thickest cartilage was found anteroinferiorly (manual: 5.3 ± 0.8 mm, p < 0.001; automated: 4.3 ± 0.6 mm; p < 0.001). The smallest surface area was found anteroinferiorly (manual: 134 ± 60 mm; p < 0.001, automated: 155 ± 60 mm; p < 0.001). The largest volume was found anterosuperiorly (manual: 2343 ± 492 mm; p < 0.001, automated: 2294 ± 467 mm; p < 0.001). Mean average surface distance was 0.26 ± 0.13 mm and mean Dice coefficient was 86% ± 3%. Intraobserver reproducibility and interobserver reliability was near perfect for overall analysis of dGEMRIC indices, thickness, surface area, and volume (ICC range, 0.962-1)., Conclusions: The presented deep learning approach for a fully automatic segmentation of hip cartilage enables an accurate, reliable and reproducible analysis of dGEMRIC indices, thickness, surface area, and volume. This time-efficient and objective analysis of biochemical cartilage composition and morphology yields the potential to improve patient selection in femoroacetabular impingement (FAI) surgery and to aid surgeons with planning of acetabuloplasty and periacetabular osteotomies in pincer FAI and hip dysplasia. In addition, this validation paves way to the large-scale use of this method for prospective trials which longitudinally monitor the effect of reconstructive hip surgery and the natural course of osteoarthritis., Level of Evidence: Level III, diagnostic study.