JOURNAL ARTICLE

A meta-analysis of MRI radiomics-based diagnosis for BI-RADS 4 breast lesions

Jie LinHao ZhengQiyu JiaJingjing ShiShiwei WangJunna WangMin Ge

Year: 2024 Journal:   Journal of Cancer Research and Clinical Oncology Vol: 150 (5)Pages: 254-254   Publisher: Springer Science+Business Media

Abstract

Abstract Objective The aim of this study is to conduct a systematic evaluation of the diagnostic efficacy of Breast Imaging Reporting and Data System (BI-RADS) 4 benign and malignant breast lesions using magnetic resonance imaging (MRI) radiomics. Methods A systematic search identified relevant studies. Eligible studies were screened, assessed for quality, and analyzed for diagnostic accuracy. Subgroup and sensitivity analyses explored heterogeneity, while publication bias, clinical relevance and threshold effect were evaluated. Results This study analyzed a total of 11 studies involving 1,915 lesions in 1,893 patients with BI-RADS 4 classification. The results showed that the combined sensitivity and specificity of MRI radiomics for diagnosing BI-RADS 4 lesions were 0.88 (95% CI 0.83–0.92) and 0.79 (95% CI 0.72–0.84). The positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 4.2 (95% CI 3.1–5.7), 0.15 (95% CI: 0.10–0.22), and 29.0 (95% CI 15–55). The summary receiver operating characteristic (SROC) analysis yielded an area under the curve (AUC) of 0.90 (95% CI 0.87–0.92), indicating good diagnostic performance. The study found no significant threshold effect or publication bias, and heterogeneity among studies was attributed to various factors like feature selection algorithm, radiomics algorithms, etc. Overall, the results suggest that MRI radiomics has the potential to improve the diagnostic accuracy of BI-RADS 4 lesions and enhance patient outcomes. Conclusion MRI-based radiomics is highly effective in diagnosing BI-RADS 4 benign and malignant breast lesions, enabling improving patients’ medical outcomes and quality of life.

Keywords:
Diagnostic odds ratio Medicine Meta-analysis Breast MRI Receiver operating characteristic Radiomics BI-RADS Magnetic resonance imaging Likelihood ratios in diagnostic testing Radiology Odds ratio Subgroup analysis Breast imaging Diagnostic accuracy Area under the curve Publication bias Breast cancer Internal medicine Cancer Mammography

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4
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38
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0.85
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Citation History

Topics

Radiomics and Machine Learning in Medical Imaging
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
MRI in cancer diagnosis
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
Medical Imaging Techniques and Applications
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
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