Quantification of patellofemoral cartilage deformation and contact area changes in response to static loading via high‐resolution MRI with prospective motion correction. Issue 5 (23rd March 2019)

• Record Type: Journal Article
• Authors: Lange, Thomas; Taghizadeh, Elham; Knowles, Benjamin R.; Südkamp, Norbert P.; Zaitsev, Maxim; Meine, Hans; Izadpanah, Kaywan
• Is Part Of: Journal of magnetic resonance imaging. Volume 50:Issue 5(2019)
• Page Start: 1561
• Page End: 1570
• Publication Date: 2019-03-23
• Subjects: magnetic resonance imaging -- prospective motion correction -- loading -- patellofemoral cartilage -- thickness -- contact area; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.26724
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Background: Higher‐resolution MRI of the patellofemoral cartilage under loading is hampered by subject motion since knee flexion is required during the scan. Purpose: To demonstrate robust quantification of cartilage compression and contact area changes in response to in situ loading by means of MRI with prospective motion correction and regularized image postprocessing. Study Type: Cohort study. Subjects: Fifteen healthy male subjects. Field Strength: 3 T. Sequence: Spoiled 3D gradient‐echo sequence augmented with prospective motion correction based on optical tracking. Measurements were performed with three different loads (0/200/400 N). Assessment: Bone and cartilage segmentation was performed manually and regularized with a deep‐learning approach. Average patellar and femoral cartilage thickness and contact area were calculated for the three loading situations. Reproducibility was assessed via repeated measurements in one subject. Statistical Tests: Comparison of the three loading situations was performed by Wilcoxon signed‐rank tests. Results: Regularization using a deep convolutional neural network reduced the variance of the quantified relative load‐induced changes of cartilage thickness and contact area compared to purely manual segmentation (average reduction of standard deviation by ∼50%) and repeated measurements performed on the same subject demonstrated high reproducibility of the method. For the three loading situations (0/200/400 N), the patellofemoral cartilage contact area as well as the mean patellar and femoral cartilage thickness were significantly different from each other ( P < 0.05). While the patellofemoral cartilage contact area increased under loading (by 14.5/19.0% for loads of 200/400 N), patellar and femoral cartilage thickness exhibited a load‐dependent thickness decrease (patella: –4.4/–7.4%, femur: –3.4/–7.1% for loads of 200/400 N). Data Conclusion: MRI with prospective motion correction enables quantitative evaluation of patellofemoral cartilage deformation and contact area changes in response to in situ loading. Regularizing the manual segmentations using a neural network enables robust quantification of the load‐induced changes. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1561–1570.