Evaluation of the Effect of Acquisition Time on Image Quality of Adrenal Carcinoma PET/CT Scans
Year: 2025
Type: article
Abstract: Purpose: Adrenal adenomas are best detected and understood using a Positron Emission Tomography/Computed Tomography (PET/CT) scanner. When doing PET scans, the acquisition time of 18-Fluorodeoxyglucose (18FDG) absorption is crucial as it determines the diagnostic accuracy and quality of the images. This study aimed to investigate the effects of various acquisition periods to assess the efficacy of PET/CT in identifying adrenal adenomas (1.5 vs. 3 minutes). Materials and Methods: The research included 30 patients who were thought to have adrenal adenomas. Following the 18FDG injection, PET/CT imaging was performed on each patient using one of two distinct acquisition times: 1.5 or 3 minutes. The image quality was objectively evaluated using a 5-point Likert scale. Experienced nuclear medicine professionals used consensus reading to assess diagnostic performance for adrenal adenoma identification. Results: The preliminary findings showed that compared to the 1.5-minute acquisition technique, PET/CT imaging with a 3-minute duration after 18FDG injection produced considerably superior image quality (p < 0.05). In addition, the longer acquisition time significantly increased the chance of detecting the lesion more precisely, improving the visualisation and characterisation of adrenal adenomas. With greater sensitivity and specificity, the 3-minute acquisition methodology showed better diagnostic accuracy for adrenal adenoma identification than the 1.5-minute approach. Conclusion: The study suggests that extending the acquisition time to 3 minutes improves image quality and diagnostic performance for adrenal adenoma detection, potentially improving patient care by facilitating accurate diagnosis and treatment planning.
Authors: Hiba Al-Hameed, Zainab Raad Salman, Hayder Kadhim Essa, Mustafa Ibrahim Ahmed Aldulaimy, Hiyam A. Altaii
Institutions: University of Baghdad, Ministry of Health, University of Mosul
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414810045
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