Abstract
Background: It was difficult to distinguish the cartilage thinning of an entire knee joint and to track the evolution of cartilage morphology alongside ages in the general population, which was of great significance for studying osteoarthritis until big imaging data and artificial intelligence are fused. The purposes of our study are (1) to explore the cartilage thickness in anatomical regions of the knee joint among a large collection of healthy knees, and (2) to investigate the relationship between the thinning pattern of the cartilages and the increasing ages.Methods: In this retrospective study, 2,481 healthy knees (subjects ranging from 15 to 64 years old, mean age: 35 ± 10 years) were recruited. With magnetic resonance images of knees acquired on a 3-T superconducting scanner, we automatically and precisely segmented the cartilage via deep learning and calculated the cartilage thickness in 14 anatomical regions. The thickness readings were compared using ANOVA by considering the factors of age, sex, and side. We further tracked the relationship between the thinning pattern of the cartilage thickness and the increasing ages by regression analysis.Results: The cartilage thickness was always thicker in the femur than corresponding regions in the tibia (p < 0.05). Regression analysis suggested cartilage thinning alongside ages in all regions (p < 0.05) except for medial and lateral anterior tibia in both females and males (p > 0.05). The thinning speed of men was faster than women in medial anterior and lateral anterior femur, yet slower in the medial patella (p < 0.05).Conclusion: We established the calculation method of cartilage thickness using big data and deep learning. We demonstrated that cartilage thickness differed across individual regions in the knee joint. Cartilage thinning alongside ages was identified, and the thinning pattern was consistent in the tibia while inconsistent in patellar and femoral between sexes. These findings provide a potential reference to detect cartilage anomaly.
Highlights
Osteoarthritis (OA) is a chronic, disabling joint disease with a total incidence of 15% in populations [1, 2]
medial patella (PM) owned the highest cartilage thickness (2.18 ± 0.32 mm; for convenience, the “mm” unit would be skipped in the following thickness reading)
When comparing corresponding A/C/P regions between femur and tibia (i.e., medial anterior femur (FMA) vs. TMA, medial central femur (FMC) vs. medial central tibia (TMC), etc.), femur always led in the reading {FMA vs. TMA: 2.06 ± 0.20 vs. 1.48 ± 0.10 [difference of means 0.58 ± 0.01, 95% confidence interval (CI) 0.56–0.59], FMC vs. TMC: 1.75 ± 0.12 vs. 1.60 ± 0.12 (0.15 ± 0.01, 0.13–0.16); p < 0.05 in all above tests}
Summary
Osteoarthritis (OA) is a chronic, disabling joint disease with a total incidence of 15% in populations [1, 2]. OA causes prevalent damages to many parts of the knee joint, including articular cartilage and subchondral bone, which seriously impair the quality of life of middle-aged and older people [3, 4]. It was difficult to distinguish the cartilage thinning of an entire knee joint and to track the evolution of cartilage morphology alongside ages in the general population, which was of great significance for studying osteoarthritis until big imaging data and artificial intelligence are fused. The purposes of our study are [1] to explore the cartilage thickness in anatomical regions of the knee joint among a large collection of healthy knees, and [2] to investigate the relationship between the thinning pattern of the cartilages and the increasing ages
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