Open AccessTechnical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization
Author(s) -
Queiroz Cleiton Cavalcante,
Machado Marcos Antonio Dorea,
Ximenes Antonio Augusto Brito,
Pino Andre Gustavo Silva,
Netto Eduardo Martins
Publication year - 2022
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.13508
Subject(s) - computer science , single photon emission computed tomography , imaging phantom , photon counting , data acquisition , image resolution , artifact (error) , artificial intelligence , computer vision , algorithm , nuclear medicine , detector , medicine , telecommunications , operating system
Purpose Methodologies for optimization of SPECT image acquisition can be challenging due to imaging throughput, physiological bias, and patient comfort constraints. We evaluated a vendor‐independent method for simulating lower count image acquisitions. Methods We developed an algorithm that recombines the ECG‐gated raw data into reduced counting acquisitions. We then tested the algorithm to simulate reduction of counting statistics from phantom SPECT image acquisition, which was synchronized with an ECG simulator. The datasets were reconstructed with a resolution recovery algorithm and the summed stress score (SSS) was assessed by three readers (two experts and one automatic). Results The algorithm generated varying counting levels, simulating multiple examinations at the same time. The error between the expected and the simulated countings ranged from approximately 5% to 10% for the ungated simulations and 0% for the gated simulations. Conclusions The vendor‐independent algorithm successfully generated lower counting statistics datasets from single‐gated SPECT raw data. This method can be readily implemented for optimal SPECT research aiming to lower the injected activity and/ or to shorten the acquisition time.