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A CT-Based Radiomics Nomogram to Predict Complete Ablation of Pulmonary Malignancy: A Multicenter Study
Guozheng Zhang1, Hong Yang2, Xisong Zhu1
1Department of Radiology, The Quzhou Affiliated Hospital of Wenzhou Medical University (Quzhou People's Hospital), Quzhou, China.
Frontiers in Oncology
|February 28, 2022
Summary
This study developed a computed tomography (CT)-based radiomics nomogram to predict complete pulmonary malignancy ablation. The tool offers accurate, objective intraoperative assessment, aiding clinical decision-making for thermal ablation procedures.
Area of Science:
- Medical Imaging
- Oncology
- Radiology
Background:
- Thermal ablation is a minimally invasive treatment for pulmonary malignancy.
- Current methods for assessing complete tumor ablation lack quantitative criteria, relying on subjective clinical judgment.
Purpose of the Study:
- To develop and validate an intraoperative computed tomography (CT)-based radiomics nomogram.
- To predict complete ablation of pulmonary malignancy using quantitative imaging features.
Main Methods:
- Radiomics features were extracted from CT images of 104 pulmonary lesions (92 patients).
- Feature selection was performed using mRMR and LASSO, followed by logistic regression to build a prediction model.
- Model performance was evaluated using AUC, accuracy, sensitivity, specificity, ROC curves, calibration curves, and DCA.
Main Results:
- A CT-based radiomics nomogram integrating radiomics signature and clinical predictors achieved AUCs of 0.88 (training) and 0.87 (validation).
- The nomogram demonstrated good calibration and high consistency with complete tumor ablation.
- Decision curve analysis confirmed the nomogram's clinical utility.
Conclusions:
- A CT-based radiomics nomogram provides reliable intraoperative prediction of complete pulmonary malignancy ablation.
- This tool can assist clinicians in making informed decisions during thermal ablation procedures.
