| Literature DB >> 31361207 |
Hyungjin Kim1, Jin Mo Goo1, Young Tae Kim1, Chang Min Park1.
Abstract
BackgroundPathologic 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.PurposeTo 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 MethodsThis 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.ResultsThe 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).ConclusionCT 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, 2019Online supplemental material is available for this article.See also the editorial by Nishino in this issue.Entities:
Year: 2019 PMID: 31361207 DOI: 10.1148/radiol.2019190297
Source DB: PubMed Journal: Radiology ISSN: 0033-8419 Impact factor: 11.105