ArticleQuantitative imaging in medicine and surgery2025
Assessment of intratumor heterogeneity in non-small cell lung cancer by unsupervised K-means clustering of radiomics features based on multiphase computed tomography images.
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Intratumor heterogeneity (ITH) is a key determinant of tumor progression, drug resistance, and poor survival in patients with cancer. This study aimed to examine ITH in non-small cell lung cancer (NSCLC) via unsupervised K-means clustering based on multiphase computed tomography (CT) radiomics features. Methods: This study retrospectively included 452 patients with NSCLC across three cohorts from two centers. Multiphase CT images [including unenhanced CT (UECT) and contrast-enhanced CT arterial phase (CECT-AP) and -venous phase (CECT-VP)], clinicopathological characteristics, and short-term immunotherapy responses of patients were collected. A total of 104 radiomics features were extracted from lung cancer regions segmented on CT images. Unsupervised K-means clustering was then employed to quantify ITH in NSCLC, with results visualized through ITH distribution heatmaps. The degree of ITH was quantified and termed ITH-Radscore. We assessed the difference in ITH-Radscores derived from UECT and CECT images. Furthermore, we analyzed the associations of ITH-Radscores with the clinicopathological characteristics and immunotherapeutic efficacy for NSCLC to validate the accuracy and effectiveness of our proposed method. Results: By viewing ITH distribution heatmaps of unsupervised K-means clustering based on multiphase CT images, we identified two distinct high-order ITH imaging patterns, designated as the tree-ring pattern and diffuse pattern. ITH-Radscores for the tree-ring and diffuse patterns were significantly different, with values of 0.643-0.768 and 0.921-0.967, respectively. ITH-Radscores derived from UECT images were significantly higher than those from CECT images (all P values <0.001). ITH-Radscores derived from CECT-AP and CECT-VP showed limited diagnostic value for high-grade patterns in lung adenocarcinoma (P=0.209 and P=0.501, respectively), while those derived from UECT images demonstrated significant predictive capability (P=0.019). ITH-Radscores derived from multiphase CT images were significantly associated with the clinical stage, histological grade, lymphovascular invasion, angiogenesis expression, and short-term immunotherapy efficacy for NSCLC (all P values <0.05). Conclusions: Multiphase CT-based unsupervised radiomics analysis effectively revealed ITH in NSCLC, especially on UECT images. ITH-Radscore demonstrated potential as a noninvasive imaging biomarker associated with the clinicopathological characteristics and immunotherapy outcomes of NSCLC, offering valuable insights for precision oncology.
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