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18F- FDG PET/CT-derived parameters predict clinical stage and prognosis of esophageal cancer

Authors :
Styliani Mantziari
Anastasia Pomoni
John O. Prior
Michael Winiker
Pierre Allemann
Nicolas Demartines
Markus Schäfer
Source :
BMC Medical Imaging, Vol 20, Iss 1, Pp 1-10 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract Background Although 18F- FDG PET/CT is validated in baseline workup of esophageal cancer to detect distant metastases, it remains underused in assessing local staging and biology of the primary tumor. This study aimed to evaluate the association between 18F- FDG PET/CT-derived parameters of esophageal cancer, and its clinico-pathological features and prognosis. Methods All patients (n = 86) with esophageal adenocarcinoma or squamous cell cancer operated between 2005 and 2014 were analyzed. Linear regression was used to identify clinico-pathologic features of esophageal cancer associated with the tumor’s maximal Standardized Uptake Value (SUVmax), Total Lesion Glycolysis (TLG) and Metabolic Tumor Volume (MTV). ROC curve analysis was performed to precise the optimal cutoff of each variable associated with a locally advanced (cT3/4) status, long-term survival and recurrence. Kaplan Meier curves and Cox regression were used for survival analyses. Results High baseline SUVmax was associated with cT3/4 status and middle-third tumor location, TLG with a cT3/4 and cN+ status, whereas MTV only with active smoking. A cT3/4 status was significantly predicted by a SUVmax > 8.25 g/mL (p 41.7 (p 10.70 cm3 (p 12.7 g/mL was associated with an early tumor recurrence and a poor disease-free survival (median 13 versus 56 months, p = 0.030), particularly in squamous cell cancer. Conclusions Baseline 18F- FDG PET/CT has a high predictive value of preoperative cT stage, as its parameters SUVmax, TLG and MTV can predict a locally advanced tumor with high accuracy. A SUVmax > 12.7 g/mL may herald early tumor recurrence and poor disease-free survival.

Details

Language :
English
ISSN :
14712342
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Imaging
Publication Type :
Academic Journal
Accession number :
edsdoj.778fdd388ed3495fa56d400140a77fb0
Document Type :
article
Full Text :
https://doi.org/10.1186/s12880-019-0401-x