Literature DB >> 18092131

Pre-operative estimation of esophageal tumor metabolic length in FDG-PET images with surgical pathology confirmation.

Marcelo Mamede1, Georges El Fakhri, Paula Abreu-e-Lima, William Gandler, Vânia Nosé, Victor H Gerbaudo.   

Abstract

OBJECTIVE: The aim of this study was to evaluate a 3D tumor segmentation method for fluorodeoxyglucose positron emission tomography (FDG-PET) in the context of noninvasive estimation of tumor metabolic length (Lm), as it correlates with surgical pathology and phantom results.
METHODS: Thirty-four patients (7 women, 27 men) with esophageal cancer were retrospectively evaluated. All patients underwent FDG-PET-computed tomography (CT) imaging following endoscopic ultrasound (EUS). Seventeen patients had esophagectomy after PET/CT, without prior neoadjuvant therapy. Tumor length was assessed by EUS (Le, n=31) and histopathology (Lp, n=17). Images were evaluated quantitatively with a 3D threshold-based region-growing program (Medical Image Processing Analysis and Visualization). Lm, total metabolic volume (Vm), maximum standardized uptake value (SUVmax), and average SUV (SUVa) over the entire tumor were obtained for several threshold values (mean activity in the liver plus 0-, 1-, 2-, 3-, and 4-SD of the activity in the liver).
RESULTS: Lm showed a good correlation with Lp for all thresholds (best correlation for Lm(2-SD), r=0.74, P<0.001). A positive nonsignificant correlation was observed between Lp and Le (r=0.30, P=0.29). Lm(2-SD) correlated well with Le (r=0.71, P<0.001). Good correlations were also observed between Lm(2-SD) and Vm(2-SD) (r=0.89, P<0.001) and SUVa(2-SD) (r=0.38, P<0.05). Vm(2-SD) also had a significant correlation with Lp (r=0.61, P<0.05) and Le (r=0.57, P<0.001).
CONCLUSIONS: FDG-PET-derived tumor metabolic length of untreated esophageal carcinomas correlates well with surgical pathology results, and provides preliminary evidence that noninvasive delineation of the superior and inferior extent of viable tumor involvement might be feasible using computer-generated metabolic length measurements.

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Year:  2007        PMID: 18092131     DOI: 10.1007/s12149-007-0040-0

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


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