Peritumoral radiomics increases the efficiency of classification of pure ground-glass lung nodules: a multicenter study

• Published in: Journal of cardiothoracic surgery Vol. 19; no. 1; pp. 505 - 9
• Main Authors: Zeng, Ying, Zhou, Xiao, Zhou, Tianzhi, Liu, Haibo, Zhou, Yingjun, Lin, Shanyue, Zhang, Wei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 30-08-2024; BioMed Central; BMC
• Subjects: Adenocarcinoma of Lung - classification; Adenocarcinoma of Lung - diagnostic imaging; Adenocarcinoma of Lung - pathology; Aged; Classification; Collaboration; Comparative analysis; Computed tomography; CT imaging; Diagnostic systems; Efficiency; Feature extraction; Female; Hospitals; Humans; IASLC system; Lung cancer; Lung Neoplasms - classification; Lung Neoplasms - diagnostic imaging; Lung Neoplasms - pathology; Lung nodules; Male; Medical imaging; Medical imaging equipment; Medical prognosis; Middle Aged; Multiple Pulmonary Nodules - classification; Multiple Pulmonary Nodules - diagnostic imaging; Multiple Pulmonary Nodules - pathology; Neoplasm Grading; Nodules; Patients; Performance evaluation; Peritumoral; pGGNs; Radiology; Radiomics; Regression analysis; Retrospective Studies; Thoracic surgery; Tomography, X-Ray Computed - methods; Tumor Burden; Tumors; China; IASLC system; Peritumoral; Efficiency; pGGNs; Radiomics
• ISSN: 1749-8090; 1749-8090
• DOI: 10.1186/s13019-024-03008-y

We aimed to evaluate the efficiency of computed tomography (CT) radiomic features extracted from gross tumor volume (GTV) and peritumoral volumes (PTV) of 5, 10, and 15 mm to identify the tumor grades corresponding to the new histological grading system proposed in 2020 by the Pathology Committee of the International Association for the Study of Lung Cancer (IASLC).
A total of 151 lung adenocarcinomas manifesting as pure ground-glass lung nodules (pGGNs) were included in this randomized multicenter retrospective study. Four radiomic models were constructed from GTV and GTV + 5/10/15-mm PTV, respectively, and compared. The diagnostic performance of the different models was evaluated using receiver operating characteristic curve analysis RESULTS: The pGGNs were classified into grade 1 (117), 2 (34), and 3 (0), according to the IASLC grading system. In all four radiomic models, pGGNs of grade 2 had significantly higher radiomic scores than those of grade 1 (P < 0.05). The AUC of the GTV and GTV + 5/10/15-mm PTV were 0.869, 0.910, 0.951, and 0.872 in the training cohort and 0.700, 0.715, 0.745, and 0.724 in the validation cohort, respectively.
The radiomic features we extracted from the GTV and PTV of pGGNs could effectively be used to differentiate grade-1 and grade-2 tumors. In particular, the radiomic features from the PTV increased the efficiency of the diagnostic model, with GTV + 10 mm PTV exhibiting the highest efficacy.