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Preoperative prediction power of radiomics and non-radiomics methods based on MRI for early recurrence in hepatocellular carcinoma: a systemic review and meta-analysis. | LitMetric

AI Article Synopsis

  • Study aimed to compare the effectiveness of radiomics vs. non-radiomics methods in predicting early recurrence of hepatocellular carcinoma (HCC) post-surgery.
  • Analysis included 10 studies with 1857 patients, finding that radiomics had better diagnostic accuracy, sensitivity, and lower negative likelihood ratio compared to non-radiomics.
  • Significant heterogeneity and potential publication bias were noted in the radiomics data, suggesting that while radiomics is more effective, further research is needed to ensure its reliability.

Article Abstract

Objective: To compare radiomics and non-radiomics in predicting early recurrence (ER) in patients with hepatocellular carcinoma (HCC) after curative surgery.

Methods: We systematically searched PubMed and Embase databases. Studies with clear reference criteria were selected. Data were extracted and assessed for quality using the quality in prognosis studies tool (QUIPS) by two independent authors. All included radiomics studies underwent radiomics quality score (RQS) assessment. We calculated sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) using random or fixed models with a 95%CI. Forest maps visualized the data, and summary receiver operating characteristic (sROC) curves with the area under the curve (AUC) were generated. Meta-regression and subgroup analyses explored sources of heterogeneity. We compared sensitivity, specificity, PLR, and NLR using the z-test and compared AUC values using the Delong test.

Results: Our meta-analysis included 10 studies comprising 1857 patients. For radiomics, the pooled sensitivity, specificity, AUC of sROC, PLR and NLR were 0.84(95%CI: 0.78-0.89), 0.80(95%CI: 0.75-0.85), 0.89(95%CI: 0.86-0.91), 4.28(95%CI: 3.48-5.27) and 0.20(95%CI: 0.14-0.27), respectively, but with significant heterogeneity (I = 60.78% for sensitivity, I = 55.79% for specificity) and potential publication bias (P = 0.04). The pooled sensitivity, specificity, AUC of sROC, PLR, NLR for non-radiomics were 0.75(95%CI:0.68-0.81), 0.78(95%CI:0.72-0.83), 0.83(95%CI: 0.80-0.86), 3.45(95%CI: 2.68-4.44) and 0.32(95%CI: 0.24-0.41), respectively. There was no significant heterogeneity in this group (I = 0% for sensitivity, I = 17.27% for specificity). Radiomics showed higher diagnostic accuracy (AUC: 0.89 vs. 0.83, P = 0.0456), higher sensitivity (0.84 vs. 0.75, P = 0.0385) and lower NLR (0.20 vs. 0.32, P = 0.0287).

Conclusion: The radiomics from preoperative MRI effectively predicts ER of HCC and has higher diagnostic accuracy than non-radiomics. Due to potential publication bias and suboptimal RQS scores in radiomics, these results should be interpreted cautiously.

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Source
http://dx.doi.org/10.1007/s00261-024-04356-yDOI Listing

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