Author:
Zhong Jingyu,Xing Yue,Zhang Guangcheng,Hu Yangfan,Ding Defang,Ge Xiang,Pan Zhen,Yin Qian,Zhang Huizhen,Yang Qingcheng,Zhang Huan,Yao Weiwu
Abstract
Abstract
Purpose
To systematically assess the quality of radiomics research in giant cell tumor of bone (GCTB) and to test the feasibility of analysis at the level of radiomics feature.
Methods
We searched PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data to identify articles of GCTB radiomics until 31 July 2022. The studies were assessed by radiomics quality score (RQS), transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement, checklist for artificial intelligence in medical imaging (CLAIM), and modified quality assessment of diagnostic accuracy studies (QUADAS-2) tool. The radiomic features selected for model development were documented.
Results
Nine articles were included. The average of the ideal percentage of RQS, the TRIPOD adherence rate and the CLAIM adherence rate were 26%, 56%, and 57%, respectively. The risk of bias and applicability concerns were mainly related to the index test. The shortness in external validation and open science were repeatedly emphasized. In GCTB radiomics models, the gray level co-occurrence matrix features (40%), first order features (28%), and gray-level run-length matrix features (18%) were most selected features out of all reported features. However, none of the individual feature has appeared repeatably in multiple studies. It is not possible to meta-analyze radiomics features at present.
Conclusion
The quality of GCTB radiomics studies is suboptimal. The reporting of individual radiomics feature data is encouraged. The analysis at the level of radiomics feature has potential to generate more practicable evidence for translating radiomics into clinical application.
Funder
Yangfan Project of Science and Technology Commission of Shanghai Municipality
Research Fund of Tongren Hospital, Shanghai Jiao Tong University School of Medicine
National Natural Science Foundation of China
Medicine and Engineering Combination Project of Shanghai Jiao Tong University
Guangci Innovative Technology Launch Plan of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
Publisher
Springer Science and Business Media LLC
Subject
Orthopedics and Sports Medicine,Surgery
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