BACKGROUND: Clinicians may order Octreoscan or positron emission tomography (PET) scan for staging patients with neuroendocrine tumors (NETs). (111)In-Octreoscan (Octreoscan) identifies tumors by radiolabeled targeting of somatostatin receptors, while 18F-fluorodeoxyglucose-positron emission tomography ((18)FDG-PET) measures differential tissue glucose transport. We assessed the sensitivity of both nuclear imaging modalities with pathologic correlation to define the best initial choice for NET staging after standard cross-sectional imaging. METHODS: We identified all patients diagnosed with NETs of gastrointestinal or pancreatic origin who underwent nuclear imaging staging by Octreoscan and/or PET from 2000 to 2013. Imaging results were correlated with tumor differentiation and grade of pathology specimens. RESULTS: Imaging and pathology results were identified for 153 patients. Of these, 131 underwent Octreoscan, 43 underwent PET, and 21 patients had both performed. Overall sensitivity of Octreoscan and PET for NET detection was similar (77 vs. 72 %; p = not significant). For well-differentiated NETs, Octreoscan (n = 124) demonstrated sensitivity of 80 vs. 60 % (p = 0.28) for PET (n = 30). For poorly-differentiated NETs, Octreoscan (n = 7) proved significantly less sensitive than PET (n = 13) (57 vs. 100 %; p = 0.02). The sensitivity of Octreoscan versus PET varied similarly when analyzed by WHO tumor grade: Grade 1 (79 vs. 52 %; p = 0.16), Grade 2 (85 vs. 86 %; p = not significant), and Grade 3 (57 vs. 100 %; p = 0.02). CONCLUSIONS: Tumor differentiation can be used to guide selection of nuclear imaging modalities for staging gastrointestinal and pancreatic NETs. Octreoscan appears more sensitive than (18)FDG-PET for well-differentiated NETs, whereas (18)FDG-PET demonstrates superior sensitivity for poorly-differentiated NETs.
BACKGROUND: Clinicians may order Octreoscan or positron emission tomography (PET) scan for staging patients with neuroendocrine tumors (NETs). (111)In-Octreoscan (Octreoscan) identifies tumors by radiolabeled targeting of somatostatin receptors, while 18F-fluorodeoxyglucose-positron emission tomography ((18)FDG-PET) measures differential tissue glucose transport. We assessed the sensitivity of both nuclear imaging modalities with pathologic correlation to define the best initial choice for NET staging after standard cross-sectional imaging. METHODS: We identified all patients diagnosed with NETs of gastrointestinal or pancreatic origin who underwent nuclear imaging staging by Octreoscan and/or PET from 2000 to 2013. Imaging results were correlated with tumor differentiation and grade of pathology specimens. RESULTS: Imaging and pathology results were identified for 153 patients. Of these, 131 underwent Octreoscan, 43 underwent PET, and 21 patients had both performed. Overall sensitivity of Octreoscan and PET for NET detection was similar (77 vs. 72 %; p = not significant). For well-differentiated NETs, Octreoscan (n = 124) demonstrated sensitivity of 80 vs. 60 % (p = 0.28) for PET (n = 30). For poorly-differentiated NETs, Octreoscan (n = 7) proved significantly less sensitive than PET (n = 13) (57 vs. 100 %; p = 0.02). The sensitivity of Octreoscan versus PET varied similarly when analyzed by WHO tumor grade: Grade 1 (79 vs. 52 %; p = 0.16), Grade 2 (85 vs. 86 %; p = not significant), and Grade 3 (57 vs. 100 %; p = 0.02). CONCLUSIONS:Tumor differentiation can be used to guide selection of nuclear imaging modalities for staging gastrointestinal and pancreatic NETs. Octreoscan appears more sensitive than (18)FDG-PET for well-differentiated NETs, whereas (18)FDG-PET demonstrates superior sensitivity for poorly-differentiated NETs.
Authors: James R Howe; Kenneth Cardona; Douglas L Fraker; Electron Kebebew; Brian R Untch; Yi-Zarn Wang; Calvin H Law; Eric H Liu; Michelle K Kim; Yusuf Menda; Brian G Morse; Emily K Bergsland; Jonathan R Strosberg; Eric K Nakakura; Rodney F Pommier Journal: Pancreas Date: 2017-07 Impact factor: 3.327
Authors: Ajaykumar C Morani; Shiva Gupta; Khaled M Elsayes; Ahmad I Mubarak; Ahmed M Khalaf; Priya R Bhosale; Jia Sun; Corey T Jensen; Vikas Kundra Journal: J Comput Assist Tomogr Date: 2022-03-04 Impact factor: 2.081
Authors: Tracey L Smith; Ziqiang Yuan; Marina Cardó-Vila; Carmen Sanchez Claros; Asha Adem; Min-Hui Cui; Craig A Branch; Juri G Gelovani; Steven K Libutti; Richard L Sidman; Renata Pasqualini; Wadih Arap Journal: Proc Natl Acad Sci U S A Date: 2016-02-16 Impact factor: 11.205