Research Article: Enhanced prediction of gene mutation and risk stratification in non-small-cell lung cancer through dual-pathway fusion of radiomics and pathomics
Abstract:
This study aimed to develop and validate a multimodal combined model that integrated radiomics, pathomics and clinical features to precisely predict EGFR status and risk stratification in NSCLC.
We retrospectively analyzed 387 patients with NSCLC from two hospitals (the train cohort: n=193; the internal validation cohort: n=83; the external validation cohort: n=111). Radiomics models were developed using 3D CNN for the construction of deep learning radiomics (DLRadiomics). Weakly supervised learning and multi-instance learning were used to develop pathomics signature (Pathomics). We conducted an in-depth analysis of clinical features resulting in a clinical signature (Clinical). Finally, we integrated them into a comprehensive nomogram-Nomogram. The comparative analysis of all models was conducted through a comprehensive evaluation. The distribution of predictive features for Nomogram across different EGFR mutation subtypes was evaluated. The Kaplan-Meier curve was employed to assess the predictive capability of Nomogram in risk stratification among cases with survival outcomes.
In comparison to Clinical, DLRadiomics and Pathomics models, Nomogram exhibits superior predictive performance (the train cohort: AUC=0.986, 95%CI=0.969-1.000; the internal validation cohort: AUC=0.796, 95%CI=0.659-0.932; the external test cohort: AUC=0.850, 95%CI=0.719-0.981). Nomogram could also be used to predict effectively EGFR mutation subtype (P<0.05). In the validation and test cohorts, the log rank test proved the effectiveness of Nomogram in predicting risk stratification (P<0.05).
We demonstrated that Nomogram which integrated radiomics, pathomics and clinical features, could be served as a noninvasive and reusable tool to precisely predict EGFR status and risk stratification in NSCLC.
Introduction:
The latest cancer statistics indicate that lung cancer remains the primary cause of cancer-related deaths, particularly among individuals aged 50 and above. The annual number of fatalities due to lung cancer significantly outnumbers the combined totals of those from colorectal, breast, and prostate cancers ( 1 , 2 ). The proportion of non-small cell lung cancer (NSCLC) in lung cancer is approximately 80% ( 3 ). The rapid advancement of personalized precision therapy has increasingly benefited patients with NSCLC,…
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