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Computed tomography versus frozen sections for distinguishing lung adenocarcinoma: A cohort study of concordance rate.

Authors :
Lv YL
Zhang J
Xu K
Jin XY
Zhang XB
Yang HH
Fan XH
Zhang YJ
Li M
Zheng ZC
Huang J
Ye XD
Tao GY
Han YC
Ye B
Source :
Asian journal of surgery [Asian J Surg] 2022 Nov; Vol. 45 (11), pp. 2172-2178. Date of Electronic Publication: 2022 Mar 26.
Publication Year :
2022

Abstract

Background: Computed tomography (CT) imaging can help to predict the pathological invasiveness of early-stage lung adenocarcinoma and guide surgical resection. This retrospective study investigated whether CT imaging could distinguish pre-invasive lung adenocarcinoma from IAC. It also compared final pathology prediction accuracy between CT imaging and intraoperative frozen section analysis.<br />Methods: This study included 2093 patients with early-stage peripheral lung adenocarcinoma who underwent CT imaging and intraoperative frozen section analysis between March 2013 and November 2014. Nodules were classified as ground-glass (GGNs), part-solid (PSNs), and solid nodules according to CT findings; they were classified as pre-IAC and IAC according to final pathology. Univariate, multivariate, and receiver operating characteristic (ROC) curve analyses were performed to evaluate whether CT imaging could distinguish pre-IAC from IAC. The concordance rates of CT imaging and intraoperative frozen section analyses with final pathology were also compared to determine their accuracies.<br />Results: Multivariate analysis identified tumor size as an independent distinguishing factor. ROC curve analyses showed that the optimal cut-off sizes for distinguishing pre-IAC from IAC for GGNs, PSNs, and solid nodules were 10.79, 11.48, and 11.45 mm, respectively. The concordance rate of CT imaging with final pathology was significantly greater than the concordance rate of intraoperative frozen section analysis with final pathology (P = 0.041).<br />Conclusion: CT imaging could distinguish pre-IAC from IAC in patients with early-stage lung adenocarcinoma. Because of its accuracy in predicting final pathology, CT imaging could contribute to decisions associated with surgical extent. Multicenter standardized trials are needed to confirm the findings in this study.<br />Competing Interests: Declaration of competing interest None.<br /> (Copyright © 2022 Asian Surgical Association and Taiwan Robotic Surgery Association. Published by Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
0219-3108
Volume :
45
Issue :
11
Database :
MEDLINE
Journal :
Asian journal of surgery
Publication Type :
Academic Journal
Accession number :
35346584
Full Text :
https://doi.org/10.1016/j.asjsur.2022.03.001