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Diagnostic performance of a whole-body dynamic (68)GA-DOTATOC PET/CT acquisition to differentiate physiological uptake of pancreatic uncinate process from pancreatic neuroendocrine tumor
To evaluate the diagnostic performance of net influx rate (Ki) values from a whole-body dynamic (WBD) (68)Ga-DOTATOC-PET/CT acquisition to differentiate pancreatic neuroendocrine tumors (pNETs) from physiological uptake of pancreatic uncinate process (UP). Patients who were benefited from a WBD acqu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437793/ https://www.ncbi.nlm.nih.gov/pubmed/32871968 http://dx.doi.org/10.1097/MD.0000000000020021 |
Sumario: | To evaluate the diagnostic performance of net influx rate (Ki) values from a whole-body dynamic (WBD) (68)Ga-DOTATOC-PET/CT acquisition to differentiate pancreatic neuroendocrine tumors (pNETs) from physiological uptake of pancreatic uncinate process (UP). Patients who were benefited from a WBD acquisition for the assessment of a known well-differentiated neuroendocrine tumor (NET)/suspicion of disease in the prospective GAPET-NET cohort were screened. Only patients with a confirmed pNET/UP as our gold standard were included. The positron emission tomography (PET) procedure consisted in a single-bed dynamic acquisition centered on the heart, followed by a whole-body dynamic acquisition and then a static acquisition. Dynamic (Ki calculated according to Patlak method), static (SUVmax, SUVmean, SUVpeak) parameters, and tumor-to-liver and tumor-to-spleen ratio (TLRKi and TSRKi (according to hepatic/splenic Ki)), tumor SUVmax to liver SUVmax (TM/LM), tumor SUVmax to liver SUVmean (TM/Lm), tumor SUVmax to spleen SUVmax (TM/SM), and tumor SUVmax to spleen SUVmean (TM/Sm) (according to hepatic/splenic SUVmax and SUVmean respectively) were calculated. A Receiver Operating Characteristic (ROC) analysis was performed to evaluate their diagnostic performance to distinguish UP from pNET. One hundred five patients benefited from a WBD between July 2018 and July 2019. Eighteen (17.1%) had an UP and 26 (24.8%) a pNET. For parameters alone, the Ki and SUVpeak had the best sensitivity (88.5%) while the Ki, SUVmax, and SUVmean had the best specificity (94.4%). The best diagnostic accuracy was obtained with Ki (90.9%). For ratios, the TLRKi and the TSRKi had the best sensitivity (95.7%) while the TM/SM and TM/Sm the best specificity (100%). TLRKi had the best diagnostic accuracy (95.1%) and the best area under the curve (AUC) (0.990). Our study is the first one to evaluate the interest of a WBD acquisition to differentiate UP from pNETs and shows excellent diagnostic performances of the Ki approach. |
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