The potential of MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations: a systematic review and meta-analysis.

IF 2.9 4区 医学 Q3 ENGINEERING, BIOMEDICAL BioMedical Engineering OnLine Pub Date : 2025-01-17 DOI:10.1186/s12938-025-01331-6
Linyong Wu, Dayou Wei, Songhua Li, Shaofeng Wu, Yan Lin, Lifei Chen
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Abstract

Background: Epidermal growth factor receptor (EGFR) gene mutations can lead to distant metastasis in non-small cell lung cancer (NSCLC). When the primary NSCLC lesions are removed or cannot be sampled, the EGFR status of the metastatic lesions are the potential alternative method to reflect EGFR mutations in the primary NSCLC lesions. This review aimed to evaluate the potential of magnetic resonance imaging (MRI) radiomics based on extrapulmonary metastases in predicting EGFR mutations through a systematic reviews and meta-analysis.

Materials and methods: A systematic review of the studies on MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations. The area under the curve (AUC), sensitivity (SNEC), and specificity (SPEC) of each study were separately extracted for comprehensive evaluation of MRI radiomics in predicting EGFR mutations in primary or metastatic NSCLC.

Results: Thirteen studies were ultimately included, with 2369 cases of metastatic NSCLC, including five studies predicting EGFR mutations in primary NSCLC, eight studies predicting EGFR mutations in metastatic NSCL. In terms of EGFR mutations in the primary lesion of NSCLC, the pooled AUC was 0.90, with SENC and SPEC of 0.80 and 0.85, respectively, which seems superior to the radiomics meta-analysis based on NSCLC primary lesions. In terms of EGFR mutations in NSCLC metastases, the pooled AUC was 0.86, with SENC and SEPC of 0.79 and 0.79, respectively, indicating moderate evaluation performance.

Conclusions: MRI radiomics helps to predict the EGFR mutation status in the primary or metastatic lesions of NSCLC, serve as a high-precision supplement to current molecular detection methods.

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基于肺外转移的MRI放射组学预测EGFR突变的潜力:系统回顾和荟萃分析。
背景:表皮生长因子受体(EGFR)基因突变可导致非小细胞肺癌(NSCLC)远处转移。当原发性NSCLC病变被切除或无法采样时,转移灶的EGFR状态是反映原发性NSCLC病变中EGFR突变的潜在替代方法。本综述旨在通过系统回顾和荟萃分析,评估基于肺外转移的磁共振成像(MRI)放射组学在预测EGFR突变方面的潜力。材料和方法:系统回顾了基于肺外转移的MRI放射组学预测EGFR突变的研究。分别提取每项研究的曲线下面积(AUC)、敏感性(SNEC)和特异性(SPEC),以综合评价MRI放射组学预测原发性或转移性NSCLC中EGFR突变的能力。结果:最终纳入13项研究,2369例转移性NSCLC,其中5项研究预测原发性NSCLC的EGFR突变,8项研究预测转移性NSCLC的EGFR突变。在NSCLC原发病变中EGFR突变的汇总AUC为0.90,SENC和SPEC分别为0.80和0.85,似乎优于基于NSCLC原发病变的放射组学荟萃分析。NSCLC转移灶中EGFR突变的汇总AUC为0.86,SENC和SEPC分别为0.79和0.79,评价效果中等。结论:MRI放射组学有助于预测NSCLC原发性或转移性病变中EGFR突变状态,是对现有分子检测方法的高精度补充。
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来源期刊
BioMedical Engineering OnLine
BioMedical Engineering OnLine 工程技术-工程:生物医学
CiteScore
6.70
自引率
2.60%
发文量
79
审稿时长
1 months
期刊介绍: BioMedical Engineering OnLine is an open access, peer-reviewed journal that is dedicated to publishing research in all areas of biomedical engineering. BioMedical Engineering OnLine is aimed at readers and authors throughout the world, with an interest in using tools of the physical and data sciences and techniques in engineering to understand and solve problems in the biological and medical sciences. Topical areas include, but are not limited to: Bioinformatics- Bioinstrumentation- Biomechanics- Biomedical Devices & Instrumentation- Biomedical Signal Processing- Healthcare Information Systems- Human Dynamics- Neural Engineering- Rehabilitation Engineering- Biomaterials- Biomedical Imaging & Image Processing- BioMEMS and On-Chip Devices- Bio-Micro/Nano Technologies- Biomolecular Engineering- Biosensors- Cardiovascular Systems Engineering- Cellular Engineering- Clinical Engineering- Computational Biology- Drug Delivery Technologies- Modeling Methodologies- Nanomaterials and Nanotechnology in Biomedicine- Respiratory Systems Engineering- Robotics in Medicine- Systems and Synthetic Biology- Systems Biology- Telemedicine/Smartphone Applications in Medicine- Therapeutic Systems, Devices and Technologies- Tissue Engineering
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