Radiomic nomogram based on lumbar spine magnetic resonance images to diagnose osteoporosis

Author:

Kang Si-ru1ORCID,Wang Kai2

Affiliation:

1. Department of Radiology, Xiaogan Hospital Affiliated to Wuhan University of Science and Technology, Xiaogan, PR China

2. Department of Orthopedics, Xiaogan Hospital Affiliated to Wuhan University of Science and Technology, Xiaogan, PR China

Abstract

Background We aimed to establish a novel model using a radiomics analysis of magnetic resonance (MR) images for predicting osteoporosis. Purpose To investigate the effectiveness of a radiomics approach utilizing magnetic resonance imaging (MRI) of the lumbar spine in identifying osteoporosis. Material and Methods In this retrospective study, a total of 291 patients who underwent MRI were analyzed. Radiomics features were extracted from the MRI scans of all 1455 lumbar vertebrae, and build the radiomics model based on T2-weighted (T2W), T1-weighted (T1W), and T2W + T1W imaging. The performance of the combined model was assessed using metrics such as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. The AUCs of these models were compared using the DeLong test. Their clinical usefulness was assessed using a decision curve analysis. Results T2W, T1W, and T1W + T2W imaging retained 27, 27, and 17 non-zero coefficients, respectively. The AUCS about radiomics scores based on T2W, T1W, and T1W + T2W imaging were 0.894, 0.934, and 0.945, respectively, which all performed better than the clinical model significantly. The rad-signatures based on T1W + T2W imaging, which exhibited a stronger predictive power, were included in the creation of the nomogram for osteoporosis diagnosis, and the AUC was 0.965 (95% confidence interval (CI)=0.944–0.986) in the training cohort and 0.917 (95% CI=0.738–1.000) in the test cohort. The calibration curve indicated that the radiomics nomogram had considerable clinical usefulness in prediction, observation, and decision curve analysis. Conclusion A reliable and powerful tool for identifying osteoporosis can be provided by the nomogram that combines the T1W and T2W imaging radiomics score with clinical risk factors.

Publisher

SAGE Publications

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3