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Differentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value. | LitMetric

Differentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value.

Nucl Med Commun

Departments of aDiagnostic Radiology bObstetrics and Gynaecology, Queen Mary Hospital, University of Hong Kong, Pokfulam Road, Hong Kong.

Published: December 2013

Objective: The aim of the study was to elucidate the differential metabolic activities in aggressive and indolent subtypes of uterine sarcomas, which may aid in managing these heterogeneous tumours.

Methods: We retrospectively analysed the PET/computed tomography scans of consecutive patients (N=18) diagnosed with uterine sarcoma at our unit. The patients were divided into indolent (N=4) and aggressive (N=14) tumour groups, and the maximum standardized uptake values (SUV max) of all lesions (n=134) were measured. The SUV max of the lesions were compared between the two tumour groups using the Mann-Whitney U-test. We calculated the optimal cutoff value as determined by receiver operating characteristic analysis. A P-value less than 0.05 was considered statistically significant.

Results: The mean SUV max of aggressive (n=104) and indolent tumours (n=30) were significantly different (8.0 ± 7.3 vs. 1.9 ± 0.9 respectively; P<0.001). A cutoff of SUV max greater than 4.0 was able to exclude indolent tumours, with 100% specificity and positive predictive value (sensitivity 72%, negative predictive value 50% and accuracy 78%; area under the curve 97%). By applying this same cutoff value on the most metabolic active lesion in each patient, we were able to correctly classify all but one patient into either the aggressive or indolent tumour group with 100% specificity and positive predictive value (sensitivity 93%, negative predictive value 80% and accuracy 94%).

Conclusion: Aggressive and indolent uterine sarcoma subtypes have differential metabolic activities that can be used to classify them and this can aid in patient management for preoperative surgical planning and treatment stratification.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3815224PMC
http://dx.doi.org/10.1097/MNM.0000000000000005DOI Listing

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