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J Nucl Med ; 53(9): 1345-51, 2012 Sep.
Article in English | MEDLINE | ID: mdl-22797376

ABSTRACT

UNLABELLED: Modern multidisciplinary therapy for colorectal liver metastases (CRLM) is associated with significant morbidity and must be adapted to the patient's relative risk. The tools currently available to risk-stratify patients are limited. This study assessed the prognostic utility of metabolic measurements derived from(18)F-FDG PET compared with previously proposed prognostic scoring systems. METHODS: Preoperative (18)F-FDG PET/CT studies from a series of 30 patients who underwent liver resection for CRLM after neoadjuvant chemotherapy were evaluated. Quantitative (18)F-FDG PET analysis calculated the maximum and mean standardized uptake value, metabolic tumor volume (MTV), and tumor glycolytic volume (TGV) as measures of the metabolic activity of tumors. The predictive value of these parameters was compared with that of 4 prognostic scores developed by Fong, Iwatsuki, Nordlinger, and Rees. RESULTS: High MTV and TGV in patients before metastasectomy were significantly associated with poorer overall survival (MTV: P = 0.001; TGV: P = 0.004) and recurrence-free survival (MTV: P = 0.001, TGV; P = 0.002). Maximum and mean standardized uptake value did not show any significant predictive ability. Of the prognostic scores, prediction of outcome was most accurate using the Basingstoke index (area under the curve, 0.898). CONCLUSION: Assessment of metabolic tumor burden with volumetric (18)F-FDG PET parameters appears to be a valuable adjunct in determining the biology of CRLM before surgical resection and may enable better risk stratification of patients.


Subject(s)
Colorectal Neoplasms/pathology , Fluorodeoxyglucose F18 , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/secondary , Multimodal Imaging , Positron-Emission Tomography , Tomography, X-Ray Computed , Adult , Aged , Aged, 80 and over , Biological Transport , Glycolysis , Humans , Liver Neoplasms/metabolism , Liver Neoplasms/pathology , Male , Middle Aged , Prognosis , ROC Curve , Retrospective Studies , Survival Analysis , Tumor Burden
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