Functional imaging of neuroendocrine tumors with combined PET/CT using <sup>68</sup>Ga‐DOTATATE (DOTA‐<scp>D</scp>Phe<sup>1</sup>,Tyr<sup>3</sup>‐octreotate) and <sup>18</sup>F‐FDG

Irfan Kayani(University College Hospital), Jamshed Bomanji(University College Hospital), Ashley M. Groves(University College Hospital), Gerard S. Conway(Royal London Hospital), Sveto Gacinovic(University College Hospital), Thida Win(Lister Hospital), John Dickson(University College Hospital), Martyn Caplin(The Royal Free Hospital), Peter J. Ell(University College Hospital)
Cancer
March 28, 2008
Cited by 465Open Access
Full Text

Abstract

BACKGROUND: The aim was to assess the relevant distribution of the novel PET tracer (68)Ga-DOTATATE in neuroendocrine tumors (NETs) with combined positron emission tomography / computed tomography (PET/CT) and compare its performance with that of (18)F-FDG PET/CT. METHODS: The imaging findings with (68)Ga-DOTATATE and (18)F-FDG on 38 consecutive patients with a diagnosis of primary or recurrent NET were compared and correlated with tumor grade on histology based on ki67 and mitotic index. RESULTS: The sensitivity of (68)Ga-DOTATATE PET/CT was 82% (31 of 38) and that of (18)F-FDG PET/CT was 66% (25 of 38). The sensitivity of combined (68)Ga-DOTATATE and (18)F-FDG PET/CT was 92% (35 of 38). There was greater uptake of (68)Ga-DOTATATE than (18)F-FDG in low-grade NET (median SUV 29 vs 2.9, P < .001). In high-grade NET there was higher uptake of (18)F-FDG over (68)Ga-DOTATATE (median SUV 11.7 vs 4.4, P = .03). There was a significant correlation with predominant tumor uptake of (68)Ga-DOTATATE or (18)F-FDG and tumor grade on histology (P < .0001). CONCLUSIONS: (68)Ga-DOTATATE PET/CT is a useful novel imaging modality for NETs and is superior to (18)F-FDG for imaging well-differentiated NET. Functional imaging with both (68)Ga-DOTATATE and (18)F-FDG has potential for a more comprehensive tumor assessment in intermediate- and high-grade tumors.


Related Papers

No related papers found

Powered by citation graph analysis