Prediction of knee pain improvement over two years for knee osteoarthritis using a dynamic nomogram based on MRI-derived radiomics: a proof-of-concept study

被引:17
|
作者
Lin, T. [1 ]
Peng, S. [2 ]
Lu, S. [1 ]
Fu, S. [2 ]
Zeng, D.
Li, J. [3 ]
Chen, T. [4 ]
Fan, T. [4 ]
Lang, C. [4 ]
Feng, S. [5 ]
Ma, J. [2 ]
Zhao, C. [6 ]
Antony, B. [7 ]
Cicuttini, F. [8 ]
Quan, X. [1 ]
Zhu, Z. [4 ]
Ding, C. [4 ,7 ]
机构
[1] Southern Med Univ, Zhujiang Hosp, Dept Radiol, Guangzhou 510282, Peoples R China
[2] Southern Med Univ, Sch Biomed Engn, Guangzhou 510515, Peoples R China
[3] Southern Med Univ, Nanfang Hosp, Dept Orthopaed, Div Orthopaed Surg, Guangzhou 510282, Peoples R China
[4] Southern Med Univ, Zhujiang Hosp, Clin Res Ctr, Guangzhou 510282, Peoples R China
[5] Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Hong Kong 999077, Peoples R China
[6] Philips China, Beijing 100000, Peoples R China
[7] Univ Tasmania, Menzies Inst Med Res, Hobart, Tas 7000, Australia
[8] Monash Univ, Dept Epidemiol & Prevent Med, Melbourne, Vic 3800, Australia
基金
中国国家自然科学基金; 英国医学研究理事会;
关键词
Osteoarthritis; Radiomics; Machine learning; Nomogram; MAGNETIC-RESONANCE; OLDER-ADULTS; STRUCTURAL-CHANGES; CARTILAGE VOLUME; SURVIVAL; ASSOCIATION; TEXTURE;
D O I
10.1016/j.joca.2022.10.014
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Objectives: To develop and validate a nomogram to detect improved knee pain in osteoarthritis (OA) by integrating magnetic resonance imaging (MRI) radiomics signature of subchondral bone and clinical characteristics. Methods: Participants were selected from the Vitamin D Effects on Osteoarthritis (VIDEO) study. The primary outcome was 20% improvement of knee pain score over 2 years in participants administrated either vitamin D or placebo. Radiomics features of subchondral bone and clinical characteristics from 216 participants were extracted and analyzed. The participants were randomly split into the training and validation cohorts at a ratio of 8:2. Least absolute shrinkage and selection operator (LASSO) regression was used to select features and generate radiomics signatures. The optimal radiomics signature and clinical indicators were fitted into a nomogram using multivariable logistic regression model. Results: The nomogram showed favorable discrimination performance [AUCtraining, 0.79 (95% CI: 0.72 -0.79), AUCvalidation, 0.83 (95% CI: 0.70-0.96)] as well as a good calibration. Additional contributing value of fusion radiomics signature to the nomogram was statistically significant (NRI, 0.23; IDI, 0.14, P < 0.001 in training cohort and NRI, 0.29; IDI, 0.18, P < 0.05 in validating cohort). Decision curve analysis confirmed the clinical usefulness of nomogram. Conclusion: The radiomics-based nomogram comprising the MR radiomics signature and clinical variables achieves a favorable predictive efficacy and accuracy in differentiating improvement in knee pain among OA patients. This proof-of-concept study provides a promising way to predict clinically meaningful outcomes. (c) 2022 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:267 / 278
页数:12
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