Feasibility of shortening the 18F-FDG Patlak scan time in a high-sensitivity short-axial field-of-view positron emission tomography-computed tomography system for oncological studies using deep learning denoising algorithms

Key Points

• Abbreviated protocols provide acceptable ki values from short-axial pet/ct systems for oncological purposes, improving efficiency.
• The 20-minute protocol, enhanced by deep learning-based denoising, shows potential for clinical application in ki analysis.
• This analysis uses data from a high-sensitivity short-axial pet/ct system, confirming denoising algorithms enhance imaging protocols.
• Highlights a feasible approach to shorten scan times, suggesting further exploration into clinical applicability and validation.

Abstract