Neuroscience Letters 616 (2016) 11–18
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Research paper
Non-Gaussian diffusion alterations on diffusion kurtosis imaging in patients with early Alzheimer’s disease Lixiang Yuan a , Man Sun a,b , Yuanyuan Chen c , Miaomiao Long a , Xin Zhao c , Jianzhong Yin a , Xu Yan d , Dongxu Ji a , Hongyan Ni a,∗ a
Department of Radiology, Tianjin First Central Hospital, Tianjin 300192, China First Central Clinical institution, Tianjin Medical University, Tianjin 300192, China c Department of Biomedical Engineering, Tianjin University, Tianjin 300072, China d MR Collaboration NE Asia, Siemens Healthcare, Shanghai 201318, China b
h i g h l i g h t s • • • •
MR diffusion imaging has advantage in studying brain microstructural changes of AD. The Gaussian model, diffusion tensor imaging (DTI) has its drawback in biological tissues. Diffusion kurtosis imaging (DKI) can solve those problems. This voxel-based DKI study of the AD whole brain showed that early AD patients already have microstructural changes in both white matter (WM) and gray matter (GM). • DKI can provide supplementary information in reflecting these changes and may be more sensitive than DTI in diagnosing early AD.
a r t i c l e
i n f o
Article history: Received 24 August 2015 Received in revised form 9 January 2016 Accepted 13 January 2016 Available online 18 January 2016 Keywords: Alzheimer’s disease Diffusion kurtosis imaging Voxel-based analysis Non-Gaussian
a b s t r a c t Objective: To evaluate non-Gaussian diffusion changes of the whole-brain and its correlation with cognitive performance in patients with early Alzheimer’s disease (AD), using diffusion kurtosis imaging (DKI). Methods: Twenty-six patients with early AD and twenty-six normal controls underwent diffusion imaging. Seven parametric maps were calculated from multiple b-value diffusion data, including mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD) and radial diffusivity (RD). Voxel-based analyses were performed to evaluate the group difference between the AD patients and normal controls. Then correlation between the diffusion parameters (MK, FA and MD) and cognitive performance were analyzed in AD patients. Results: For AD patients, increased MD, AxD and RD were found in white matter (WM), including the genu of corpus callosum, bilateral cingulate bundle, bilateral temporal and frontal WM, and were also found in gray matter (GM), including the bilateral temporal GM, parahippocampal gyrus, hippocampus, cingulate gyrus, thalamus, and amygdala. These regions were partially overlapped with those showing decreased FA, MK, AK and RK. However, only kurtosis indices could detect the significant differences in the lentiform nucleus between AD patients and health control. DKI indices in AD patients significantly correlated with the clinical scores in genu of CC, cingulate bundle, temporal and frontal lobe, while the voxel number showing significant correlation with MK was more than that with FA and MD. Conclusions: Early AD patients already have microstructural changes in both WM and GM. DKI can provide supplementary information in reflecting these changes and may be sensitive in diagnosing early AD. © 2016 Elsevier Ireland Ltd. All rights reserved.
1. Introduction
∗ Corresponding author. Fax: +86 2223621365. E-mail address: [email protected] (H. Ni). http://dx.doi.org/10.1016/j.neulet.2016.01.021 0304-3940/© 2016 Elsevier Ireland Ltd. All rights reserved.
Alzheimer’s disease (AD) is the most common type of dementia. At present, various neuroimaging techniques have been applied to find an easily applicable, noninvasive and cost-effective method to help the early diagnosis of AD.
12
L. Yuan et al. / Neuroscience Letters 616 (2016) 11–18
Table 1 Demographic and neuropsychological data of AD and NC groups.
Age (years) Female/male Education (years) MMSE MOCA CDR * **
AD (n = 26)
NC (n = 26)
P value
67.65 ± 6.899 14/12 10.92 ± 2.841 20.46 ± 2.248 18.23 ± 3.241 0.84 ± 0.235
65.54 ± 6.041 15/11 11.31 ± 3.564 28.85 ± 0.925 27.04 ± 1.509 0
0.245* 0.780** 0.669* 0.000* 0.000* 0.000*
Two-sample t test (p < 0.05). Chi-square test (p < 0.05).
Diffusion tensor imaging (DTI) can estimate the integrity of white matter (WM) tracts. A meta-analysis showed that DTI was better than hippocampal volumetry in differentiating normal aging from AD [1]. But DTI is inadequate to accurately describe the actual diffusion process of water molecules in biological tissues. Moreover, it is incapable of probing multiple WM structures within an individual voxel as well as the microstructural changes in the gray matter (GM) [2]. Diffusion kurtosis imaging (DKI) is a complementary technique for the conventional DTI, and can overcome the limitations of conventional DTI in both WM and GM [2]. Moreover, DKI has already shown its greater promise in detecting brain’s microstructural changes compared with the conventional DTI [3,4]. Region of interests (ROI) analysis is often used to probe the brain’s microstructure alterations. But it is a human dependent method and can only be used to evaluate the predetermined regions. Alternatively, only a few voxel-based analysis (VBA) DKI analyses in AD patients have been reported [5–8]. Benitez et al. used the novel white matter tract integrity metrics to detect the underlying WM pathological mechanisms in AD [8]. A recent study using tract-based spatial statistics and ROI analyses showed a great potential in differentiating AD patients from subjects with mild cognitive impairment (MCI) or normal controls [5]. But both these studies did not take the whole brain into consideration. The purpose of this study was to characterize the non-Gaussian diffusion patterns of the whole brain in patients with early AD by using DKI. Our hypothesis was that DKI might be helpful in detecting the microstructural changes in AD. 2. Materials and methods 2.1. Subjects This study was approved by the local ethics committee, and informed consent was obtained from each subject. Finally, twenty-six early AD patients and twenty-six age-matched normal controls (NC) were analyzed. Early AD group fulfilled: (1) the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria for AD, (2) 18 < Mini-Mental State Examination (MMSE, Chinese version, education corrected) ≤ 23, (3) Montreal Cognitive Assessment (MOCA) < 26, (4) 0.5 ≤ Clinical Dementia Rating (CDR) ≤ 1; NC group fulfilled: (1) no evidence of dementia or MCI, (2) MMSE score ≥27, (3) MOCA ≥26, (4) CDR = 0. In addition to above conditions, Hachinski Ischemic Score (HIS)
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Research paper
Non-Gaussian diffusion alterations on diffusion kurtosis imaging in patients with early Alzheimer’s disease Lixiang Yuan a , Man Sun a,b , Yuanyuan Chen c , Miaomiao Long a , Xin Zhao c , Jianzhong Yin a , Xu Yan d , Dongxu Ji a , Hongyan Ni a,∗ a
Department of Radiology, Tianjin First Central Hospital, Tianjin 300192, China First Central Clinical institution, Tianjin Medical University, Tianjin 300192, China c Department of Biomedical Engineering, Tianjin University, Tianjin 300072, China d MR Collaboration NE Asia, Siemens Healthcare, Shanghai 201318, China b
h i g h l i g h t s • • • •
MR diffusion imaging has advantage in studying brain microstructural changes of AD. The Gaussian model, diffusion tensor imaging (DTI) has its drawback in biological tissues. Diffusion kurtosis imaging (DKI) can solve those problems. This voxel-based DKI study of the AD whole brain showed that early AD patients already have microstructural changes in both white matter (WM) and gray matter (GM). • DKI can provide supplementary information in reflecting these changes and may be more sensitive than DTI in diagnosing early AD.
a r t i c l e
i n f o
Article history: Received 24 August 2015 Received in revised form 9 January 2016 Accepted 13 January 2016 Available online 18 January 2016 Keywords: Alzheimer’s disease Diffusion kurtosis imaging Voxel-based analysis Non-Gaussian
a b s t r a c t Objective: To evaluate non-Gaussian diffusion changes of the whole-brain and its correlation with cognitive performance in patients with early Alzheimer’s disease (AD), using diffusion kurtosis imaging (DKI). Methods: Twenty-six patients with early AD and twenty-six normal controls underwent diffusion imaging. Seven parametric maps were calculated from multiple b-value diffusion data, including mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD) and radial diffusivity (RD). Voxel-based analyses were performed to evaluate the group difference between the AD patients and normal controls. Then correlation between the diffusion parameters (MK, FA and MD) and cognitive performance were analyzed in AD patients. Results: For AD patients, increased MD, AxD and RD were found in white matter (WM), including the genu of corpus callosum, bilateral cingulate bundle, bilateral temporal and frontal WM, and were also found in gray matter (GM), including the bilateral temporal GM, parahippocampal gyrus, hippocampus, cingulate gyrus, thalamus, and amygdala. These regions were partially overlapped with those showing decreased FA, MK, AK and RK. However, only kurtosis indices could detect the significant differences in the lentiform nucleus between AD patients and health control. DKI indices in AD patients significantly correlated with the clinical scores in genu of CC, cingulate bundle, temporal and frontal lobe, while the voxel number showing significant correlation with MK was more than that with FA and MD. Conclusions: Early AD patients already have microstructural changes in both WM and GM. DKI can provide supplementary information in reflecting these changes and may be sensitive in diagnosing early AD. © 2016 Elsevier Ireland Ltd. All rights reserved.
1. Introduction
∗ Corresponding author. Fax: +86 2223621365. E-mail address: [email protected] (H. Ni). http://dx.doi.org/10.1016/j.neulet.2016.01.021 0304-3940/© 2016 Elsevier Ireland Ltd. All rights reserved.
Alzheimer’s disease (AD) is the most common type of dementia. At present, various neuroimaging techniques have been applied to find an easily applicable, noninvasive and cost-effective method to help the early diagnosis of AD.
12
L. Yuan et al. / Neuroscience Letters 616 (2016) 11–18
Table 1 Demographic and neuropsychological data of AD and NC groups.
Age (years) Female/male Education (years) MMSE MOCA CDR * **
AD (n = 26)
NC (n = 26)
P value
67.65 ± 6.899 14/12 10.92 ± 2.841 20.46 ± 2.248 18.23 ± 3.241 0.84 ± 0.235
65.54 ± 6.041 15/11 11.31 ± 3.564 28.85 ± 0.925 27.04 ± 1.509 0
0.245* 0.780** 0.669* 0.000* 0.000* 0.000*
Two-sample t test (p < 0.05). Chi-square test (p < 0.05).
Diffusion tensor imaging (DTI) can estimate the integrity of white matter (WM) tracts. A meta-analysis showed that DTI was better than hippocampal volumetry in differentiating normal aging from AD [1]. But DTI is inadequate to accurately describe the actual diffusion process of water molecules in biological tissues. Moreover, it is incapable of probing multiple WM structures within an individual voxel as well as the microstructural changes in the gray matter (GM) [2]. Diffusion kurtosis imaging (DKI) is a complementary technique for the conventional DTI, and can overcome the limitations of conventional DTI in both WM and GM [2]. Moreover, DKI has already shown its greater promise in detecting brain’s microstructural changes compared with the conventional DTI [3,4]. Region of interests (ROI) analysis is often used to probe the brain’s microstructure alterations. But it is a human dependent method and can only be used to evaluate the predetermined regions. Alternatively, only a few voxel-based analysis (VBA) DKI analyses in AD patients have been reported [5–8]. Benitez et al. used the novel white matter tract integrity metrics to detect the underlying WM pathological mechanisms in AD [8]. A recent study using tract-based spatial statistics and ROI analyses showed a great potential in differentiating AD patients from subjects with mild cognitive impairment (MCI) or normal controls [5]. But both these studies did not take the whole brain into consideration. The purpose of this study was to characterize the non-Gaussian diffusion patterns of the whole brain in patients with early AD by using DKI. Our hypothesis was that DKI might be helpful in detecting the microstructural changes in AD. 2. Materials and methods 2.1. Subjects This study was approved by the local ethics committee, and informed consent was obtained from each subject. Finally, twenty-six early AD patients and twenty-six age-matched normal controls (NC) were analyzed. Early AD group fulfilled: (1) the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria for AD, (2) 18 < Mini-Mental State Examination (MMSE, Chinese version, education corrected) ≤ 23, (3) Montreal Cognitive Assessment (MOCA) < 26, (4) 0.5 ≤ Clinical Dementia Rating (CDR) ≤ 1; NC group fulfilled: (1) no evidence of dementia or MCI, (2) MMSE score ≥27, (3) MOCA ≥26, (4) CDR = 0. In addition to above conditions, Hachinski Ischemic Score (HIS)
