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Related Experiment Video

Updated: Mar 31, 2026

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
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Pilli Kai Score: A Proposed Digital Twin Framework Integrating Radiomics and Biomarkers for Enhanced Lung Nodule Risk

Zain Khalpey1, Suchitra Pilli2

  • 1Cardiothoracic Surgery Department, HonorHealth, Scottsdale, USA.

Cureus
|March 30, 2026
PubMed
Summary

The Pilli Kai Score is a new digital twin framework to assess lung nodule malignancy risk. It integrates multiple data types for improved accuracy and personalized lung cancer care.

Keywords:
blood biomarkersclinical utilitycost-effectivenessdigital twinlung cancer riskpet-ctprediction modelpulmonary nodulesradiomicsrisk stratification

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Area of Science:

  • Pulmonary medicine and diagnostic imaging.
  • Artificial intelligence in healthcare.
  • Biomarker discovery and application.

Background:

  • Indeterminate pulmonary nodules are common and difficult to diagnose.
  • Current models for malignancy risk lack precision, especially for intermediate-risk patients.
  • Accurate risk stratification is crucial to avoid unnecessary invasive procedures.

Purpose of the Study:

  • To introduce the Pilli Kai Score, a novel digital twin framework for lung nodule malignancy risk assessment.
  • To integrate diverse data sources including clinical variables, radiomics, biomarkers, and PET data.
  • To enhance diagnostic accuracy and personalize lung cancer patient management.

Main Methods:

  • Development of a multi-modal digital twin framework (Pilli Kai Score).
  • Integration of clinical data, standardized radiomics, blood biomarkers, and PET imaging data.
  • Proposed validation targets include calibration, ROC AUC > 0.85, and high negative predictive value.

Main Results:

  • The Pilli Kai Score framework is proposed, integrating multiple data types for malignancy risk estimation.
  • Illustrative figures demonstrate the workflow and anticipated performance benchmarks.
  • No patient-level data were analyzed in this technical report.

Conclusions:

  • The Pilli Kai Score framework has the potential to improve diagnostic accuracy for indeterminate pulmonary nodules.
  • Successful validation could reduce unnecessary invasive procedures and enable personalized lung cancer care.
  • Further multi-center studies are required to validate the framework's performance in real-world settings.