Qin QJ, Hou MY, Tian JJ, Sun YZ, Jing XH, Zuo TY. Immediate post-microwave ablation computed tomography model may better predict short-term response of stage I non-small cell lung cancer. World J Radiol 2026; 18(9): 124658 [DOI: 10.4329/wjr.124658]
Corresponding Author of This Article
Tai-Yang Zuo, MD, Department of Oncology Intervention, Central Hospital Affiliated to Shandong First Medical University, No. 105 Jiefang Road, Jinan 250013, Shandong Province, China. zuotaiyang001@163.com
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
research-article
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Qing-Jin Qin, Ming-Yuan Hou, Yan-Zhuo Sun, Tai-Yang Zuo, Department of Oncology Intervention, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, China
Ming-Yuan Hou, Department of Medical Imaging, Qufu Hospital of Traditional Chinese Medicine, Jining 273100, Shandong Province, China
Juan-Juan Tian, Department of Clinical Laboratory, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, China
Xiao-Han Jing, School of Radiology, Shandong First Medical University, Jinan 250013, Shandong Province, China
Co-first authors: Qing-Jin Qin and Ming-Yuan Hou.
Author contributions: Qin QJ performed statistical analysis and drafted the original manuscript; Qin QJ and Hou MY contributed equally to this article, they are the co-first authors of this manuscript; Qin QJ, Hou MY, and Zuo TY contributed to study conception and design, project supervision, and manuscript revision; Hou MY and Jing XH completed quantitative radiomic image analysis; Tian JJ and Sun YZ collected clinical patient data; Zuo TY provided technical support; and all authors thoroughly reviewed and endorsed the final manuscript.
AI contribution statement: Portions of this manuscript were edited using AI tools solely for language refinement. The authors carefully reviewed and verified all AI-assisted outputs and take full responsibility for the scientific content of the manuscript.
Supported by Shandong Provincial Medical and Health Science and Technology Program, No. 202309031576; Science and Technology Development Program of Jinan Municipal Health Commission, No. 2022-2-15; and Jining Key Research and Development Program (Soft Science Projects), No. 2025JNZC186 and 2025JNZC187.
Institutional review board statement: This study was approved by the Medical Ethics Committee of Central Hospital Affiliated to Shandong First Medical University, approval No. 20241111004.
Informed consent statement: We had acquired the written informed consent of all participants with lung tumors before they received computed tomography-guided percutaneous microwave ablation.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data supporting this study’s findings are available from the corresponding author upon reasonable request.
Corresponding author: Tai-Yang Zuo, MD, Department of Oncology Intervention, Central Hospital Affiliated to Shandong First Medical University, No. 105 Jiefang Road, Jinan 250013, Shandong Province, China. zuotaiyang001@163.com
Received: June 23, 2026 Revised: July 22, 2026 Accepted: August 28, 2026 Published online: September 28, 2026 Processing time: 99 Days and 14.4 Hours
Abstract
BACKGROUND
Microwave ablation (MWA) is indicated for treating inoperable early-stage non-small cell lung cancer.
AIM
To evaluate its therapeutic effect by developing multimodal models that integrate computed tomography (CT) radiomics features and simple clinical characteristics.
METHODS
This study enrolled 50 patients with stage I non-small cell lung cancer who were treated with MWA. Corresponding CT images were collected before and after the MWA, and radiomics features were extracted using the 3D-slicer software platform. In the study, statistical analyses were performed using R studio software. Firstly, radiomics features related to local tumor progression (LTP) at 6 months were screened from the pre-MWA and immediate post-MWA CT radiomics features by the max-relevance and min-redundancy features. This study aimed to evaluate its therapeutic effect by developing multimodal models that integrate CT radiomics features and simple clinical characteristics. Based on the selected radiomics features, prediction models for 6-month LTP were constructed. These models’ performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC).
RESULTS
Three pre-MWA CT radiomics features and three post-MWA CT radiomics features were confirmed to be correlated with the LTP. For the ROC curves that only covered the pre-MWA CT radiomics, AUC was 0.689. For the ROC curves integrating the pre-MWA CT radiomics plus simple clinical characteristics, AUC was 0.849. For the ROC curves that only covered the immediate post-MWA CT radiomics features, AUC was 0.849. For the ROC curves integrating the immediate post-MWA CT features plus simple clinical characteristics, AUC was 0.907.
CONCLUSION
This exploratory preliminary analysis revealed that the predictive model integrating immediate post-microwave-ablation CT radiomic features and clinical indicators yields superior prognostic performance relative to the model constructed solely from preoperative CT radiomic features.
Core Tip: This exploratory study constructed predictive models based on preoperative and immediate post-microwave ablation computed tomography radiomic features as well as simple clinical characteristics from patients with stage I non-small cell lung cancer (NSCLC), and verified that the immediate postoperative multimodal model may exhibit favorable predictive performance for the risk of local tumor progression at 6 months. This model can assist clinicians in rapid patient risk stratification, guide the formulation of individualized surveillance schedules, facilitate early salvage local interventions, and coordinate subsequent systemic therapy. It effectively improves the refined management paradigm after microwave ablation for early-stage NSCLC and provides novel imaging evidence to support precise implementation of minimally invasive comprehensive treatment for NSCLC.
