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Related Experiment Video

Updated: Jun 16, 2025

Predictive Immune Modeling of Solid Tumors
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Baseline Radiomics as a Prognostic Tool for Clinical Benefit from Immune Checkpoint Inhibition in Inoperable NSCLC

Fedor Moiseenko1,2, Marko Radulovic3, Nadezhda Tsvetkova1

  • 1N.P Napalkov Saint Petersburg Clinical Research and Practical Centre for Specialized Types of Medical Care (Oncological), Leningradskaya Str. 68A, 197758 Saint Petersburg, Russia.

Cancers
|June 13, 2025
PubMed
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This study developed a radiomics approach to predict durable survival in non-small cell lung cancer (NSCLC) patients receiving immunotherapy. The method accurately identifies patients likely to benefit, improving treatment selection and reducing costs.

Area of Science:

  • Radiology
  • Oncology
  • Artificial Intelligence

Background:

  • Checkpoint inhibitors (ICIs) are vital for non-small cell lung cancer (NSCLC) but current selection methods are insensitive.
  • Many NSCLC patients incur costs from ineffective immunotherapy treatments.

Purpose of the Study:

  • To predict durable survival (≥24 months) in NSCLC patients undergoing immunotherapy.
  • To enhance patient selection for immunotherapy and improve treatment outcomes.

Main Methods:

  • A comprehensive ensemble radiomics approach was applied to pretreatment CT scans of 220 NSCLC patients.
  • 1680 models were built using various normalization, feature selection, and classification techniques.
  • Clinicopathological (CP) and radiomics features were evaluated for predicting overall survival (OS) and progression-free survival (PFS).
Keywords:
NSCLCcheckpoint inhibitorsensembleimmunotherapymachine learningpredictionprognosisradiomics

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Main Results:

  • The combined CP and radiomics ensemble model achieved the highest accuracy (85%) for predicting 24-month OS (AUC = 0.863).
  • Radiomics-only models showed strong performance (82% accuracy, AUC = 0.796) for 24-month OS.
  • Predictive performance for shorter PFS endpoints was lower.

Conclusions:

  • The developed radiomics pipeline significantly improves patient selection for NSCLC immunotherapy.
  • This approach can help avoid unnecessary toxicity and costs for non-responders.
  • Radiomics offers a promising tool for personalized NSCLC treatment strategies.