Total lesion glycolysis by 18F-FDG PET/CT is a reliable predictor of prognosis in soft-tissue sarcoma View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-07-24

AUTHORS

Eun-Seok Choi, Seung-Gyun Ha, Han-Soo Kim, Jae Hong Ha, Jin Chul Paeng, Ilkyu Han

ABSTRACT

PurposePreoperative identification of aggressiveness is important for the establishment of a treatment strategy in patients with soft-tissue sarcoma (STS). We compared the predictive values of various metabolic parameters derived from PET/CT with 18F-FDG, including maximal standardized uptake value (SUVmax), total lesion glycolysis (TLG) and metabolic tumour volume (MTV).MethodsA total of 66 patients with STS who had undergone FDG PET/CT before tumour resection were reviewed retrospectively. We determined SUVmax, TLG and MTV to compare their value in predicting disease progression, which was defined as local recurrence and metastases. Receiver operating characteristic curve (ROC) analysis was used to compare the accuracy. Univariate and multivariate analyses of conventional clinicopathological variables were used to compare the reliability of the metabolic parameters.ResultsTLG exhibited greater accuracy than SUVmax or MTV in ROC analysis (area under curve, AUC, 0.802, 0.726 and 0.681, respectively). The cut-off values for disease progression derived from the AUC data were TLG 250; SUVmax 6.0, and MTV 40 cm3. In univariate analysis, TLG (>250) was a more significant predictive factor than SUVmax and MTV (P < 0.001, P = 0.031 and P = 0.022, respectively). TLG was the only meaningful metabolic parameter in the multivariate analysis (P = 0.008) other than presence of metastasis at diagnosis (P = 0.003).ConclusionTLG is a more accurate predictor of disease progression than SUVmax or MTV. TLG enables accurate preoperative assessment of aggressiveness comparable with conventional clinicopathological parameters. More... »

PAGES

1836-1842

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00259-013-2511-y

DOI

http://dx.doi.org/10.1007/s00259-013-2511-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039775122

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23880967


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