人工智能辅助MRI方法用于定量膝关节软骨形态测量的开发、评估及多中心临床试验应用
Reliability assessment and multicenter clinical application of magnetic resonance methods for knee cartilage quantification
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中文总结 AI 辅助
本研究开发并评估了基于nnU-Net的AI辅助MRI方法，用于多中心膝骨关节炎试验的软骨形态定量测量，通过双阅片校正和3D射线技术实现高重复性，并验证了其疗效评估价值。
中文摘要 AI 辅助
目的：开发并评估一种人工智能辅助的MRI方法，用于多中心III期膝骨关节炎试验中的定量膝关节软骨形态测量。方法：AI预分割采用3D全分辨率nnU-Net。1.0版使用独立的股胫和髌骨软骨模型，而2.0版使用在黄金标准标注上训练的统一三分类模型。试验图像随后经过双阅片者校正和第三阅片者裁定。裁定后的掩膜被划分为内侧/外侧股骨和胫骨软骨以及髌骨软骨。软骨体积在物理坐标中测量，平均厚度通过3D射线追踪（3D-RT）测量，局部厚度<1.5 mm的表面积通过基于3D射线的面积方法（3D-RBA）测量。评估包括1,189次III期MRI检查、阅片者一致性、20个合成变薄模型，以及与3D-PMA和三种比较厚度方法的69名参与者纵向比较。结果：总体预分割Dice为0.964±0.030（中位数0.970），其中78.7%达到Dice≥0.95。软骨体积的阅片者间ICC为0.959-0.995。在69名参与者亚组中，总体积从V0时的14,184.366 mm³增加到V8时的15,359.345 mm³；3D-RBA和3D-PMA分别减少4.70%和6.88%，所有四种厚度测量在V8时最高。在20个几何实验中，MAPE为5.73%，CCC为0.822，Dice为0.956。该工作流程应用于来自416名参与者的1,188次MRI检查。从V0到V8，治疗组显示总体积+3.45%，平均厚度+2.46%，3D-RBA -4.54%，而对照组分别为-2.08%、-1.32%和+0.16%。结论：该工作流程为多中心KOA试验提供了可重复的MRI软骨评估框架。跨方法一致性和几何验证支持3D-RT和3D-RBA用于疗效评估。
英文摘要
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.
发表机构
- Academy for Clinical Innovation and Translation of Shanghai Co., Ltd. (ACITS)（上海临床创新与转化研究院有限公司）
- Shanghai IxCell Biotechnology Co., LTD（上海爱科百发生物科技有限公司）
- Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属第九人民医院）
- Nanyang Technological University（南洋理工大学）
- Renji Hospital, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属仁济医院）
- Shanghai Jiading District Central Hospital（上海市嘉定区中心医院）
机构由 AI 辅助整理，请以论文原文为准。
