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Eur J Nucl Med Mol Imaging. 2014 Nov;41(11):2051-7. doi: 10.1007/s00259-014-2831-6. Epub 2014 Jul 3.

Metabolic parameters using ¹⁸F-FDG PET/CT correlate with occult lymph node metastasis in squamous cell lung carcinoma.

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  • 1Department of Nuclear Medicine, Kyungpook National University School of Medicine and Hospital, 50, Samduk 2-ga, Jung Gu, Daegu, Republic of Korea, 700-721,



The aim of this study was to investigate predictability of occult lymph node metastasis (OLM) using metabolic parameters on pretreatment (18)F-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET)/CT in squamous cell non-small cell lung carcinoma (SC-NSCLC) patients who were clinically node negative (cN0) before surgery.


A total of 63 cN0 SC-NSCLC patients (M/F = 61/2, mean age 64.1 ± 8.0) who underwent curative surgery with lymph node dissection were enrolled in this study. Metabolic tumor volume (MTV) of the primary tumor was obtained with a standardized uptake value (SUV) threshold of 2.5. Total lesion glycolysis (TLG) was calculated by multiplication of the MTV and its SUVmean. Metabolic parameters (SUVmax, MTV, and TLG) and clinicopathological factors were analyzed for OLM.


Of 63 patients, 12 (19.0 %) had OLM. Significantly higher SUVmax, MTV, TLG, and pathological tumor size were observed in patients with OLM. The optimal cutoff values for prediction of OLM determined using a receiver-operating characteristic (ROC) curve were 8.8 for SUVmax, 18.9 cm(3) for MTV, 88.4 for TLG, and 2.8 cm for pathological tumor size. Univariate analysis showed correlation of SUVmax, MTV, and TLG with the rate of OLM. In multivariate analyses, high SUVmax and MTV showed an association with an increased risk of OLM, after adjusting for age, sex, pathological tumor size, T stage, and location.


Metabolic parameters on pretreatment (18)F-FDG PET/CT were significant predictors for OLM in cN0 SC-NSCLC patients. Surgical planning can be tailored based on the parameters in order to reduce the risk of hidden residual lymph node metastases in patients.

[PubMed - indexed for MEDLINE]
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