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Multi-Institutional CT Scan-Based Radiomics for Predicting Tumor PD-L1 Expression in Patients with Advanced and

Ralph Saber1,2, Marion Tonneau2,3, Olivier Salko2

  • 1MedICAL Laboratory, Polytechnique Montreal, Montreal, QC H3T 1J4, Canada.

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|February 27, 2026
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Summary
This summary is machine-generated.

A novel radiomics algorithm using CT scans can predict programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC). This non-invasive approach shows promise as a biomarker for immune checkpoint inhibitor (ICI) therapy, potentially improving patient outcomes.

Keywords:
immune checkpoint blockadenon-small cell lung cancernoninvasive biomarkerprogrammed death-ligand 1radiomics

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Area of Science:

  • Oncology
  • Radiology
  • Artificial Intelligence

Background:

  • Immune checkpoint inhibitors (ICIs) have transformed advanced non-small cell lung cancer (NSCLC) treatment.
  • However, 70% of patients experience disease progression, necessitating predictive biomarkers.
  • Programmed death-ligand 1 (PD-L1) expression is a key biomarker, but its assessment is invasive.

Purpose of the Study:

  • To develop a non-invasive radiomics surrogate for PD-L1 expression (rad-PDL1) using computed tomography (CT) imaging.
  • To compare the predictive value of rad-PDL1 with traditional pathological assessments.
  • To evaluate the generalizability of rad-PDL1 across advanced and limited-stage NSCLC.

Main Methods:

  • Radiomics features from pretreatment CT scans were analyzed using a Transformer model-based pipeline.
  • The algorithm classified tumors as high vs. low PD-L1 expression.
  • Validation was performed on 482 advanced NSCLC patients and an independent cohort of 51 limited-stage NSCLC patients.

Main Results:

  • The radiomics pipeline demonstrated strong predictive performance with AUCs of 0.75 and 0.68 in primary and independent validation, respectively.
  • Accuracy was 0.73 and 0.69, indicating good generalizability across disease stages.
  • Higher rad-PDL1 expression correlated with longer progression-free survival.

Conclusions:

  • A CT-based radiomic surrogate for PD-L1 expression is feasible.
  • The approach showed partial generalization to an independent neoadjuvant cohort.
  • Larger prospective, multi-site validation is required before clinical implementation.