Reliability assessment and multicenter clinical application of magnetic resonance methods for knee cartilage quantification
Abstract
Background: This study evaluated interreader agreement and longitudinal performance of MRI methods for knee cartilage volume, thickness, and defect-area quantification. Methods: AI-presegmented masks from 1,189 phase III examinations underwent independent correction by two readers and adjudication. Cartilage volume, three-dimensional ray-tracing thickness (3D-RT), and ray-based defect area (3D-RBA), defined by a 1.5-mm thickness threshold, were calculated. Agreement was assessed using segmentation metrics, intraclass correlation coefficients (ICCs), repeated-measures Bland-Altman analysis, and minimal detectable change at 95% confidence (MDC95). The 3D-RBA framework was evaluated in 120 digital-phantom experiments from 40 participants. Longitudinal analyses included 374 participants, alternative-method comparisons included 65, and retrospective phase II analysis included 24 participants with four visits. Results: Overall AI-to-adjudicated-mask Dice was 0.964 +/- 0.029. Interreader ICCs for volume, thickness, and defect area were 0.956, 0.904, and 0.932; corresponding MDC95 values were 1,596.9 mm^3, 0.227 mm, and 147.4 mm^2. Geometric mean absolute percentage error for defect area was 5.62%, with spatial Dice of 0.961. In 374 participants, volume changes correlated positively with thickness changes (rho=0.431) and negatively with defect-area changes (rho=-0.221). Within-participant phase II correlations followed the same directions in both groups. Conclusions: The workflow demonstrated good interreader agreement. Controlled geometric results and longitudinal associations supported the feasibility of threshold-based defect-area estimation. Volume, thickness, and defect area provide complementary measures of cartilage structure.
Related
- Multicenter Assessment of Combined Brain and Cervical Spinal cord 3T MP2RAGE T1 Measurements for Reliable Tissue Microstructure Quantification
- MRSIPrep: A Standardized Post-Quantification Framework for Preprocessing Whole-Brain Magnetic Resonance Spectroscopic Imaging
- Assessing the reliability of hippocampal single-voxel proton magnetic resonance spectroscopy through intra-class effect decomposition
- Open-Source Framework for the Visualization, Quantification, and Analysis of 4D Flow and High-Dimensional Magnetic Resonance Images
- Automated Cerebrospinal Fluid Flow Quantification in Hydrocephalus Using Phase‐Contrast Magnetic Resonance Imaging
BibTeX
@misc{yang2026reliability,
title = {{Reliability assessment and multicenter clinical application of magnetic resonance methods for knee cartilage quantification}},
author = {Binbin Yang and Yongmei Jian and Chenglei Liu and Rui Huang and Hongda Shao and Linjun Tong and Yuanjing Xu and Jingshu Wu and Chengzhang He and Suting Peng and Ming Xiao and Yinan Chen and Qi Duan},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.08081},
eprint = {2609.08081},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.08081},
}
RIS
TY - UNPB
TI - Reliability assessment and multicenter clinical application of magnetic resonance methods for knee cartilage quantification
AU - Binbin Yang
AU - Yongmei Jian
AU - Chenglei Liu
AU - Rui Huang
AU - Hongda Shao
AU - Linjun Tong
AU - Yuanjing Xu
AU - Jingshu Wu
AU - Chengzhang He
AU - Suting Peng
AU - Ming Xiao
AU - Yinan Chen
AU - Qi Duan
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2609.08081
UR - https://arxiv.org/abs/2609.08081
AB - Background: This study evaluated interreader agreement and longitudinal performance of MRI methods for knee cartilage volume, thickness, and defect-area quantification. Methods: AI-presegmented masks from 1,189 phase III examinations underwent independent correction by two readers and adjudication. Cartilage volume, three-dimensional ray-tracing thickness (3D-RT), and ray-based defect area (3D-RBA), defined by a 1.5-mm thickness threshold, were calculated. Agreement was assessed using segmentation metrics, intraclass correlation coefficients (ICCs), repeated-measures Bland-Altman analysis, and minimal detectable change at 95% confidence (MDC95). The 3D-RBA framework was evaluated in 120 digital-phantom experiments from 40 participants. Longitudinal analyses included 374 participants, alternative-method comparisons included 65, and retrospective phase II analysis included 24 participants with four visits. Results: Overall AI-to-adjudicated-mask Dice was 0.964 +/- 0.029. Interreader ICCs for volume, thickness, and defect area were 0.956, 0.904, and 0.932; corresponding MDC95 values were 1,596.9 mm^3, 0.227 mm, and 147.4 mm^2. Geometric mean absolute percentage error for defect area was 5.62%, with spatial Dice of 0.961. In 374 participants, volume changes correlated positively with thickness changes (rho=0.431) and negatively with defect-area changes (rho=-0.221). Within-participant phase II correlations followed the same directions in both groups. Conclusions: The workflow demonstrated good interreader agreement. Controlled geometric results and longitudinal associations supported the feasibility of threshold-based defect-area estimation. Volume, thickness, and defect area provide complementary measures of cartilage structure.
ER -