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DOI: 10.1055/a-2710-7001
Experimental approach for optimizing dose regimen of 68Ga-DOTATATE PET/CT for neuroendocrine tumor (NET) imaging in current high sensitivity scanners: Phantom and Patient Study
Experimenteller Ansatz zur Optimierung des Dosierungsschemas von 68Ga-DOTATATE PET/CT für die Bildgebung neuroendokriner Tumore (NET) in aktuellen hochempfindlichen Scannern: Phantom- und PatientenstudieAuthors
Supported by: Tehran University of Medical Sciences and Health Services 49402
Abstract
Aim
This study aimed to determine the optimized scan time and injected activity regimen for clinical 68Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.
Methods
A NEMA PET body phantom was used with Ga-68 to simulate a 9:1 sphere-to-background ratio. PET data were acquired on a high-sensitivity scanner at various scan times (15–300 s/bed). For each scan time, coefficient of variation (COV) and contrast-to-noise ratio (CNR) were calculated. The minimum scan time (Tmin) needed to meet the Rose Criterion (CNR > 5) for the smallest sphere was identified. This Tmin was then applied to patient scans with neuroendocrine tumors (originally acquired at 120 s/bed) to evaluate image quality and determine an optimized activity regimen for clinical 68Ga-DOTATATE PET imaging.
Results
Phantom experiments showed that a COVmax of 20% is the highest acceptable noise level for detecting the smallest lesions, corresponding to a minimum scan time of about 1 minute per bed position. Patient image analysis confirmed that all tumors visible at routine scan times were still detectable at this minimum duration. This supports the use of a lower activity regimen (~1 MBq/kg), which can reduce patient radiation exposure compared to the standard 1.85 MBq/kg protocol.
Conclusion
This work demonstrated that scan time and activity for 68Ga-DOTATATE NET imaging can be significantly minimized without compromising image interpretation and quantification.
Publication History
Received: 03 May 2025
Accepted after revision: 25 September 2025
Article published online:
26 November 2025
© 2025. Thieme. All rights reserved.
Georg Thieme Verlag KG
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