CT-defined Visceral Pleural Invasion in T1 Lung Adenocarcinoma: Lack of Relationship to Disease-Free Survival
Hyungjin Kim, Jin Mo Goo, Young Tae Kim, Chang Min Park
Seoul National University New Generation University College Seoul National University Hospital
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Background Pathologic visceral pleural invasion (pVPI) leads to upstaging from T1 to T2. However, it is unclear whether the CT features for pVPI can be reliably used as a clinical T2 descriptor for preoperative staging. Purpose To validate the diagnostic accuracy and analyze the prognostic value of CT findings for the prediction of pVPI in patients with resected node-negative lung adenocarcinoma. Materials and Methods This retrospective cohort study included clinical T1N0M0 adenocarcinomas resected between 2009 and 2015. The diagnostic CT findings suggestive of pVPI were evaluated by a thoracic radiologist. The accuracy of diagnostic CT findings in relation to pVPI and accuracy for disease-free survival (DFS) were evaluated by using test performance metrics and multivariable Cox regression analysis, respectively. Results The authors analyzed 695 patients (median age, 63 years; 411 women). Data for pVPI were not available in six patients. The accuracy of CT features for pVPI ranged from 62.7% (432 of 689 patients) to 72.3% (498 of 689 patients). Positive predictive values ranged from 44.1% (173 of 392 patients) to 56.4% (88 of 156 patients), which indicated that about half of the CT-based predictions were false-positive. Multivariable Cox regression models showed that none of the combinations of CT findings were independent predictors of DFS (adjusted hazard ratios, 1.40, 1.48, 1.06, and 1.21 for each combination; P > .05 for all). In addition, pVPI was not an independent prognostic factor (adjusted hazard ratio, 1.27; P = .26), whereas age and clinical T category were independent prognostic factors in all Cox models (P < .05 for all). Conclusion CT features of pathologic visceral pleural invasion (pVPI) have an accuracy of 62.7%–72.3%. CT features of pVPI were not independent prognostic factors for disease-free survival in clinical T1 lung adenocarcinomas. This argues against the use of CT features of visceral pleural invasion as T2 descriptors in the clinical staging of lung cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.
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生物医学Lung Cancer Diagnosis and Treatment
Pleural and Pulmonary Diseases · Radiomics and Machine Learning in Medical Imaging
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