Evaluation of the difference-correction effect of the gamma camera systems used by easy Z-score Imaging System (eZIS) an
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ORIGINAL ARTICLE
Evaluation of the difference-correction effect of the gamma camera systems used by easy Z-score Imaging System (eZIS) analysis Yasushi Yamamoto • Masahisa Onoguchi • Kazunori Kawakami • Masuo Haramoto • Rei Wake • Jun Horiguchi • Hajime Kitagaki
Received: 1 November 2012 / Accepted: 21 December 2013 Ó The Author(s) 2014. This article is published with open access at Springerlink.com
Abstract Objective We examined the difference of the effect by data to revise a gamma camera difference. The differencecorrection method of the camera is incorporated in eZIS analysis. Methods We acquired single photon emission computed tomography (SPECT) data from the three-dimensional (3D) Hoffman brain phantom (Hoffman), the threedimensional brain phantom (3D-Brain), Pool phantom
Y. Yamamoto M. Haramoto Department of Radiology, Shimane University Hospital, 89-1 Enya-cho, Izumo, Shimane 693-8501, Japan e-mail: [email protected] M. Haramoto e-mail: [email protected] Y. Yamamoto M. Onoguchi (&) Department of Quantum Medical Technology, Graduate School of Medical Science, Kanazawa University, Kodatsuno 5-11-80, Kanazawa, Ishikawa 920-0942, Japan e-mail: [email protected] K. Kawakami R. Wake J. Horiguchi Department of Psychiatry, Shimane University School of Medicine, 89-1 Enya-cho, Izumo, Shimane 693-8501, Japan e-mail: [email protected] R. Wake e-mail: [email protected] J. Horiguchi e-mail: [email protected] H. Kitagaki Department of Radiology, Shimane University Faculty of Medicine, 89-1 Enya-cho, Izumo, Shimane, Japan e-mail: [email protected]
(pool) and from normal subjects (Normal-SPECT) to investigate compensating for a difference in gamma camera systems. We compared SPECT counts of standard camera with the SPECT counts that revised the difference of the gamma camera system (camera). Furthermore, we compared the ‘‘Z-score map (Z-score)’’. To verify the effect of the compensation, we examined digitally simulated data designed to represent a patient with Alzheimer’s dementia. We carried out both eZIS analysis and ‘‘Specific Volume of interest Analysis (SVA)’’. Results There was no great difference between the correction effect using Hoffman phantom data and that using 3D-Brain phantom data. Furthermore, a good compensation effect was obtained only over a limited area. The compensation based on the pool was found to be less satisfactory than any of the other compensations according to all results of the measurements examined in the study. The compensation based on the Normal-SPECT data resulted in a Z-score map (Z-score) for the result that approximated that from the standard camera. Therefore, we concluded that the effect of the compensation based on Normal-SPECT data was the best of the four methods tested. Conclusions Based on eZIS analysis, the compensation using the pool data was inferior to the compensations using the other methods tested. Based on the results of the SAV analysis, the effect of the compensation using the Hoffman data was bet
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