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Utility of Metabolic Parameters on FDG PET/CT in the Classification of Early-Stage Lung Adenocarcinoma

Authors :
Katsuhiko Kato
Shinichiro Kamiya
Shinji Ito
Shinji Naganawa
Shingo Iwano
Rintaro Ito
Source :
Clinical Nuclear Medicine. 44:560-565
Publication Year :
2019
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2019.

Abstract

PURPOSE This paper aims to explore the role of a metabolic parameter on F-FDG-PET/CT for clinical T-classification in early-stage adenocarcinoma. PATIENTS AND METHODS One hundred six surgically resected pathological TNM stage (p-stage) 0/I lung adenocarcinomas were retrospectively reviewed. The solid size (SS) measured on thin-section CT and the pathological invasive size (IS) of tumors were recorded. The SUVmax and metabolic tumor volume with SUV ≥1.0 (MTV1.0) derived from PET/CT data were measured on a workstation, and the metabolic tumor diameter with SUV ≥1.0 (MTD1.0) was calculated automatically from MTV1.0. For the correlations between the IS and the SS, MTD1.0, or SUVmax, Pearson's correlation coefficients were compared using the Meng-Rosenthal-Rubin method. Additionally, the reproducibility between the clinical TNM stage (c-stage), based on the SS or MTD1.0, and the p-stage was analyzed using the kappa coefficient (k). RESULTS For the correlations between the IS and the other parameters, Pearson correlation coefficient was 0.630 for the SS, 0.600 for the SUVmax, and 0.725 for MTD1.0. MTD1.0 correlated significantly and more strongly with the IS than the SS and the SUVmax did (P = 0.040, and P = 0.008, respectively). The reproducibility between p-stage and c-stage based on the SS was moderate (k = 0.529, P < 0.001), whereas that between p-stage and c-stage based on MTD1.0 was substantial (k = 0.676, P < 0.001). CONCLUSIONS MTD1.0 on FDG-PET/CT was correlated significantly and more strongly with the pathological IS in lung adenocarcinomas than with the SS on thin-section CT. FDG-PET/CT could classify more precisely early-stage lung adenocarcinoma than the presently used T-classification based on thin-section CT findings.

Details

ISSN :
15360229 and 03639762
Volume :
44
Database :
OpenAIRE
Journal :
Clinical Nuclear Medicine
Accession number :
edsair.doi.dedup.....e412993133012fbc2d3d6b0571049339