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

Prediction of Pathological Invasive Size

Iwano, Shingo, MD*; Ito, Shinji, MD*; Kamiya, Shinichiro, MD*; Ito, Rintaro, MD*; Kato, Katsuhiko, MD; Naganawa, Shinji, MD*

doi: 10.1097/RLU.0000000000002591
Original Articles

Purpose This paper aims to explore the role of a metabolic parameter on 18F-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.

From the Departments of *Radiology, and

Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.

Received for publication February 2, 2019; revision accepted March 10, 2019.

Conflicts of interest and sources of funding: This work was supported by Grants-in-Aid for Scientific Research (C) (KAKENHI grant number 15 K09919) from the Japanese Ministry of Education, Culture, Sports, Science and Technology.

Correspondence to: Shingo Iwano, MD, Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466–8550, Japan. E-mail:

Online date: April 23, 2019

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