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A Journal on Nuclear Medicine and Molecular Imaging
Affiliated to the and to the International Research Group of Immunoscintigraphy
Indexed/Abstracted in: Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index (SciSearch), Scopus
Impact Factor 2,413
Online ISSN 1827-1936
Yeon H. HAN, Hwan J. JEONG, Myung H. SOHN, Seok T. LIM
Department of Nuclear Medicine, Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Cyclotron Research Center, Molecular Imaging and Therapeutic Medicine Research Center, Chonbuk National University Medical School and Hospital, Jeonju, Jeonbuk, Republic of Korea
BACKGROUND: The aim of this study was to find a reliable predictor of recurrence in patients with locally advanced colorectal cancer.
METHODS: We enrolled 96 patients for this retrospective study. We investigated metabolic (SUVmax, metabolic tumor volume, total lesion glycolysis, and heterogeneity), clinical (age, sex, stage, and CEA level) and pathologic (Ki-67, p53, CD31, COX-2, E-cadherin and EGFR) parameters. The coefficient of variation (COV) was chosen to assess heterogeneity of [18F]FDG uptake by dividing the standard deviation of the SUV by SUVmean. Recurrence-free survival was compared with each metabolic, clinical and pathologic parameters by using univariate and multivariate survival analysis.
RESULTS: Among 96 patients, 19 patients (19.8%) showed disease recurrence. In the ROC analysis, the optimal cutoff values of SUVmax, metabolic tumor volume (cm3), total lesion glycolysis (cm3), and metabolic heterogeneity were determined as 17.6, 10.05, 232.46, and 0.48, respectively. In univariate analysis, probability of recurrence was statistically increased in those with metabolic tumor volume >10.05 (P=0.045), and those with metabolic heterogeneity > 0.48 (P=0.031). In multivariate analysis, metabolic heterogeneity was the only independent prognostic factor (HR 4.56, 95 % CI 1.57-13.23, P=0.006).
CONCLUSIONS: Intratumoral metabolic heterogeneity assessed by COV is a reliable predictive factor for disease recurrence in patients with locally advanced colorectal cancer. Therefore, its application could be an important step for personalized management of colorectal cancer.