Predicting EGFR mutation status in non-small cell lung cancer patients with brain metastases based on MRI radiomics: A systematic review and meta-analysis.

INTRODUCTION This study evaluates the quality and diagnostic accuracy of Magnetic Resonance Imaging (MRI) radiomics-based prediction of epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients with brain metastasis. METHODS Six databases (PubMed, Embase, Web of Science, Cochrane Library, Scopus, and IEEE Xplore) were systematically searched up to June 2025. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and Radiomics Quality Score (RQS). The predictive performance of MRI radiomics was quantitatively analyzed by pooling sensitivity (SEN), specificity (SPE), positive/negative likelihood ratios (PLR/NLR), diagnostic odds ratio (DOR), and area under the curve (AUC). RESULTS 15 studies were included in the systematic review, of which 11 reported sufficient data for meta-analysis (10 training cohorts and 7 validation cohorts). QUADAS-2 indicated that the overall quality of the studies was considered acceptable. The mean RQS score of the included studies was 14.47 (40.19 % of the maximum). Training cohorts achieved the pooled sensitivity, specificity, PLR, NLR, DOR and AUC of MRI-based radiomics for predicting EGFR mutation status were 0.82 [95 % CI: 0.75-0.87], 0.85 [95 % CI: 0.77-0.90], 6.69 [95 % CI: 3.53-12.69], 0.13 [95 % CI: 0.06-0.18], 52.79 [95 % CI: 14.90-187.03], and 0.94 [95 % CI: 0.92-0.96], respectively. For the validation cohorts, these values were 0.77 [95 % CI: 0.69-0.84], 0.83 [95 % CI: 0.78-0.88], 4.64 [95 % CI: 3.45-6.25], 0.27 [95 % CI: 0.20-0.38], 16.69 [95 % CI: 9.85-29.19], and 0.85 [95 % CI: 0.81-0.88]. CONCLUSION MRI radiomics-based models may be useful in predicting the EGFR mutation status in patients with brain metastases from NSCLC. However, the analysis revealed limitations including the retrospective design of most studies, geographic bias, and relatively low methodological quality. IMPLICATIONS FOR PRACTICE MRI radiomics may offer a promising non-invasive diagnostic approach for clinical use, providing valuable insights to guide clinical decision-making before obtaining pathological results.

• Publication year

  2025

• Venue

  Radiography

• Publication date

  2025-08-01

• Fields of study

  Medicine

• Identifiers
  DOI 10.1016/j.radi.2025.103113PMID 40829998
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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