경도인지장애와 알츠하이머병 환자의 18F-fludeoxyglucose PET 표준섭취계수율에 대한 체적 및 피질 표면 기반 관심영역 분석
Region of Interest Analysis for Standardized Uptake Value Ratio of 18F-fludeoxyglucose PET: Mild Cognitive Impairment and Alzheimer’s Disease
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18F-fludeoxyglucose PET (FDG-PET) can help finding an abnormal metabolic activity in brain. In this study, we evaluated an efficiency of volume- and cortical surface-based analysis which were used to determine whether standardized uptake value ratio (SUVR) of FDG-PET was different among Alzheimer’s disease (AD), mild cognitive impairment (MCI), and healthy control (HC). Each PET image was rigidly co-registered to the corresponding magnetic resonance imaging (MRI) using mutual information. All voxels of the co-registered PET images were divided by the mean FDG uptake of the cerebellum cortex which was thresholded by partial volume effect (>0.9). Also, the SUVR value of each vertex was linearly interpolated from volumetric SUVR image which was thresholded by gray matter partial volume effect (>0.1). Lobar mean values were calculated from both volume- and cortical surface-based SUVRs. Statistical analysis was conducted to compare two measures for AD, MCI and HC groups. Even though the results of volume (SUVR_vol) and cortical surface-based SUVR (SUVR_surf) analysis were not significantly different from each other, the latter would be better for detecting group differences in SUVR of PET.
Abstract
18F-fludeoxyglucose PET (FDG-PET) can help finding an abnormal metabolic activity in brain. In this study, we evaluated an efficiency of volume- and cortical surface-based analysis which were used to determine whether standardized uptake value ratio (SUVR) of FDG-PET was different among Alzheimer’s disease (AD), mild cognitive impairment (MCI), and healthy control (HC). Each PET image was rigidly co-registered to the corresponding magnetic resonance imaging (MRI) using mutual information. All voxels of the co-registered PET images were divided by the mean FDG uptake of the cerebellum cortex which was thresholded by partial volume effect (>0.9). Also, the SUVR value of each vertex was linearly interpolated from volumetric SUVR image which was thresholded by gray matter partial volume effect (>0.1). Lobar mean values were calculated from both volume- and cortical surface-based SUVRs. Statistical analysis was conducted to compare two measures for AD, MCI and HC groups. Even though the results of volume (SUVR_vol) and cortical surface-based SUVR (SUVR_surf) analysis were not significantly different from each other, the latter would be better for detecting group differences in SUVR of PET.
참고문헌 (26)
- C. Marcus, "Brain PET in the diagnosis of Alzheimer’s disease", Clinical nuclear medicine, 39, pp.e413~ (2014)
- V. J. Lowe, "Comparison of 18F-FDG and PiB PET in cognitive impairment", Journal of Nuclear Medicine, 50, pp.878~886 (2009)
- 18F□FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI), "N. Smailagic", The Cochrane Library, ~ (2015)
- H. Barthel, "Cerebral amyloid-β PET with florbetaben (18 F) in patients with Alzheimer's disease and healthy controls:a multicentre phase 2 diagnostic study", The Lancet Neurology, 10, pp.424~435 (2011)
- C. R. Jack, "Brain β-amyloid load approaches a plateau", Neurology, 80, pp.890~896 (2013)
- B. S. Ye, "Hippocampal and cortical atrophy in amyloid-negative mild cognitive impairments: comparison with amyloidpositive mild cognitive impairment", Neurobiology of aging, 35, pp.291~300 (2014)
- A. D. Joshi, "Performance characteristics of amyloid PET with florbetapir F 18 in patients with Alzheimer’s disease and cognitively normal subjects", Journal of Nuclear Medicine, 53, pp.378~384 (2012)
- K. E. Pike, "β-amyloid imaging and memory in nondemented individuals: evidence for preclinical Alzheimer’s disease", Brain, 130, pp.2837~2844 (2007)
- J. Tohka, "Fast and robust parameter estimation for statistical partial volume models in brain MRI", Neuroimage, 23, pp.84~97 (2004)
- H.-J. Park, "Cortical surface-based analysis of 18F-FDG PET:measured metabolic abnormalities in schizophrenia are affected by cortical structural abnormalities", Neuroimage, 31, pp.1434~1444 (2006)
- J. G. Sled, "A nonparametric method for automatic correction of intensity nonuniformity in MRI data", IEEE transactions on medical imaging, 17, pp.87~97 (1998)
- A. P. Zijdenbos, "Automatic 'pipeline' analysis of 3-D MRI data for clinical trials: application to multiple sclerosis", IEEE transactions on medical imaging, 21, pp.1280~1291 (2002)
- S. M. Smith, "Fast robust automated brain extraction", Human brain mapping, 17, pp.143~155 (2002)
- D. L. Collins, "Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space", Journal of computer assisted tomography, 18, pp.192~205 (1994)
- J. S. Kim, "Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification", Neuroimage, 27, pp.210~221 (2005)
- O. Lyttelton, "An unbiased iterative group registration template for cortical surface analysis", Neuroimage, 34, pp.1535~1544 (2007)
- K. Im, "Brain size and cortical structure in the adult human brain", Cerebral Cortex, 18, pp.2181~2191 (2008)
- U. Yoon, "Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia", Neuroimage, 34, pp.1405~1415 (2007)
- FDG PET, "European journal of nuclear medicine and molecular imaging", 2012, 990~1000
- S. Minoshima, "Alzheimer’s disease versus dementia with Lewy bodies: cerebral metabolic distinction with autopsy confirmation", Annals of neurology, 50, pp.358~365 (2001)
- L. Mosconi, "PET in the Evaluation of Alzheimer’s Disease and Related Disorders", pp.49~65 (2009), Springer
- K. Chen, "Twelve-month metabolic declines in probable Alzheimer's disease and amnestic mild cognitive impairment assessed using an empirically pre-defined statistical region-of-interest: findings from the Alzheimer's Disease Neuroimaging Initiative", Neuroimage, 51, pp.654~664 (2010)
- S. Morbelli, "Mapping brain morphological and functional conversion patterns in amnestic MCI: a voxelbased MRI and FDG-PET study", European journal of nuclear medicine and molecular imaging, 37, pp.36~ (2010)
- J. C. Patterson, "Early detection of brain pathology suggestive of early AD using objective evaluation of FDG-PET scans", International Journal of Alzheimer’s Disease, 2011 (2011)
- A. Tucholka, "An empirical comparison of surface-based and volume-based group studies in neuroimaging", Neuroimage, 63, pp.1443~1453 (2012)
- D. Riviere, "Automatic recognition of cortical sulci of the human brain using a congregation of neural networks", Medical image analysis, 6, pp.77~92 (2002)