Related Experiment Video For Lung adenocarcinoma
Updated: Feb 13, 2026

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
Published on: January 10, 2025
Qualitative CT Criterion for Subsolid Nodule Subclassification: Improving Interobserver Agreement and Pathologic
Po An Chen1, Eric P Huang1, Lu Yang Shih2
1Department of Radiology, Kaohsiung Veterans General Hospital, No. 386, Ta-Chung 1st Road, Kaohsiung, 81362, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan.
Rationale And Objectives:
The main aim of this study was to evaluate the clinical validity and correlation with pathologic invasiveness in the pulmonary adenocarcinoma spectrum based on the novel qualitative computed tomography criterion for subsolid nodule (SSN) classification, which classified SSN into pure ground-glass nodule, heterogeneous ground-glass nodule, and part-solid nodule. In addition, we compared the performance of the conventional and novel classifications.
Materials And Methods:
The computed tomography images of 41 SSN nodules were interpreted by six observers independently, and the SSN characteristics were classified according to both the conventional and the novel classification systems. Each observer assessed 41 nodules in two different classifications separated by a minimum of 8 weeks. The kappa (κ) coefficient test was used to determine the reliability. The correlation between pulmonary adenocarcinoma spectrum and the SSN classification was analyzed with Spearman correlation coefficients.
Results:
Interobserver agreement (κ) was 0.702 (range 0.42-0.89) and 0.707 (range 0.58-0.88) for the conventional and the novel classifications for SSN, respectively, and intraobserver agreement (κ) was 0.92 and 0.88 for the conventional and the novel classifications for SSN, respectively. The novel SSN classification (correlation coefficient range 0.622-0.732) is more strongly correlated with the pathologic invasiveness degree of lesions in adenocarcinoma spectrum than the conventional SSN classification (correlation coefficient range 0.458-0.644).
Conclusions:
The agreement between observers on the novel SSN classification system was good and had better correlation with pathologic invasiveness than the conventional SSN classification. Further studies are needed to confirm these results on interobserver agreement.
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