Alzheimer's Disease and PET Imaging(Ⅰ)
Value of visual analysis and SUVR during 18F-AV45 PET/CT imaging in the diagnosis of mild cognitive impairment and Alzheimer′s disease
Zhang Chenpeng, Wang Cheng, Xin Mei, Xia Qian, Wan Liangrong, Qiu Ju, Xu Qun, Yue Ling, Xiao Shifu, Liu Jianjun
Published 2020-04-25
Cite as Chin J Nucl Med Mol Imaging, 2020, 40(4): 201-206. DOI: 10.3760/cma.j.cn321828-20200225-00067
Abstract
ObjectiveTo evaluate the value of visual analysis and standardized uptake value ratio (SUVR) during 18F-florbetapir (AV45) PET/CT brain imaging in diagnosis of β-amyloid (Aβ) deposition in patients with mild cognitive impairment (MCI) and Alzheimer′s disease (AD), and to explore the clinical ancillary value of the two indexes.
MethodsFrom December 2018 to July 2019, a total of 47 subjects, including 5 (3 males, 2 females, age (58±13) years) normal controls (NC), 8 (2 males, 6 females, age (66±10) years) patients with AD and 34 (16 males, 18 females, age (70±7) years) patients with MCI were enrolled. All subjects underwent 18F-AV45 PET/CT scan. All images were evaluated by visual analysis and SUVR were calculated. The diagnostic efficiencies of visual analysis and SUVR were compared by McNemar test and Kappa test. One-way analysis of variance and Welch test were used to compare data differences. The best threshold value of SUVR was obtained by receiver operating characteristic (ROC) curve analysis.
ResultsThe positive rate of Aβ deposition for all subjects was 46.81%(22/47) by SUVR analysis, and 38.30%(18/47) by visual analysis. There was no significant difference between the two methods (χ2=33.15, P>0.05), and the consistency was good (Kappa=0.83). Considering the clinical diagnosis as the"gold standard", the Aβ deposition obtained by visual analysis and SUVR analysis can effectively distinguish AD from NC, and the sensitivities were 7/8vs 8/8, respectively, both specificities were 5/5(χ2=9.48, P>0.05), with good consistency (Kappa=0.84). SUVR quantitative analysis could distinguish AD from NC, AD from MCI (F values: 3.99-8.79, all P<0.01), but could not distinguish NC from MCI (allP>0.05). ROC curve analysis showed that the best threshold value of precuneus′ SUVR was 1.08 for the differential diagnosis of AD and NC; for the differential diagnosis of AD and MCI, the best threshold value of lateral temporal′s SUVR was 1.06.
ConclusionVisual analysis was consistent with SUVR′s qualitative determination during 18F-AV45 PET/CT imaging for brain Aβ deposition, while SUVR quantitative analysis could assist in the differential diagnosis of AD and NC, AD and MCI.
Key words:
Alzheimer Disease; Cognition disorders; Amyloidogenic proteins; Positron-emission tomography; Tomography, X-ray computed
Contributor Information
Zhang Chenpeng
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Wang Cheng
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Xin Mei
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Xia Qian
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Wan Liangrong
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Qiu Ju
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Xu Qun
Department of Neurology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
Yue Ling
Department of Geriatric Psychiatry, Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University
Alzheimer′s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
Xiao Shifu
Department of Geriatric Psychiatry, Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University
Alzheimer′s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai 200030, China
Liu Jianjun
Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
