LAUSR

Objective The easy Z-score imaging system (eZIS) analysis is used for the diagnosis of dementia by cerebral blood flow on single photon emission computed tomography (SPECT). Differences in the acquisition and reconstruction conditions in SPECT may affect the eZIS analysis results. The present study aimed to construct our institutional normal database (NDB) and Alzheimer’s disease (AD)-specific volumes of interest (VOIs) in eZIS analysis, and to compare the differential diagnostic ability between healthy controls (HC) and patients with AD in the image reconstruction filtered back projection (FBP) and ordered subset expectation maximization (OSEM) methods. Methods An NDB was constructed at our institution from 30 healthy individual using the FBP and OSEM reconstruction methods. We divided 51 HC and 51 AD patients into two groups, one for AD disease-specific VOI construction (HC, AD) and the other for NDB verification (HC, AD); image reconstruction was performed using FBP and OSEM. The areas of reduced blood flow in AD patients were compared with those of HC using the two types of image reconstruction methods. We used AD disease-specific VOI and NDB from each reconstruction method in eZIS analysis and compared the differential diagnostic ability for HC and AD with the different reconstruction methods. Results Comparing the areas of reduced blood flow in AD patients using the different image reconstruction methods, OSEM showed decreased blood flow in the medial region of the temporal lobes compared to FBP. Comparing the differential diagnostic ability for HC and AD using eZIS, the Severity, Extent, and Ratio showed higher values in the analysis performed using OSEM image reconstruction compared to FBP. Conclusion With the 99m Tc-ECD SPECT, the eZIS analysis equipped with our institutional AD-specific VOI and NDB using OSEM image reconstruction could distinguish HC from AD better than eZIS analysis using FBP image reconstruction. This study is registered in UMIN Clinical Trials Registry (UMIN-CTR) as UMIN study ID: UMIN000042362.