Acta Neurol Belg DOI 10.1007/s13760-014-0419-3

ORIGINAL ARTICLE

Hippocampal diffusion tensor imaging microstructural changes in vascular dementia Jelena Ostojic • Dusko Kozic • Aleksandra Pavlovic Marija Semnic • Aleksandar Todorovic • Kosta Petrovic • Nadezda Covickovic-Sternic



Received: 30 July 2014 / Accepted: 21 December 2014 Ó Belgian Neurological Society 2014

Abstract To explore microstructural integrity of hippocampus in vascular dementia (VD) using DTI. Twenty-five individuals with VD, without magnetic resonance imaging (MRI) evidence of gray matter pathology, and 25 matched healthy control (HC) individuals underwent a 3T MRI protocol including T2, FLAIR, and PD in the axial plane, 3D whole-brain T1-weighted with an isotropic resolution of 1 mm, and DTI acquired using 64 diffusion sensitizing directions, b value of 1,500 s/mm2, 65 axial slices, isotropic resolution of 1.8 mm. Images were processed to obtain indices of microstructural variations of bilateral hippocampi. Mean diffusivity (MD) in the hippocampus of patients with VD was significantly increased (p \ 0.05) bilaterally with respect to that of the group of HC examinees. In VD group left hippocampal MD (10-6 9 mm2/s) was 833.4 ± 92.8; in HC group left MD was 699.8 ± 56. In VD group, right hippocampal MD was 859.1 ± 69.8; in HC group right MD was 730.4 ± 40.2. No group differences were found in hippocampal FA. DTI shows microstructural hippocampal damage in VD in patients with

normal appearing gray matter structures on conventional MRI, indicating the need for further research on the link between VD and AD.

J. Ostojic (&)  K. Petrovic Center of Radiology, Clinical Center of Vojvodina, School of Medicine, University of Novi Sad, 1-7 Hajduk Veljkova Street, 21000 Novi Sad, Serbia e-mail: [email protected]; [email protected]

A. Pavlovic  N. Covickovic-Sternic Clinic of Neurology, Clinical Center of Serbia, School of Medicine, University of Belgrade, 6 Dr. Subotica Street, 11000 Belgrade, Serbia e-mail: [email protected].com

K. Petrovic e-mail: [email protected]

N. Covickovic-Sternic e-mail: [email protected]

D. Kozic  A. Todorovic Diagnostic Imaging Center, Institute of Oncology, School of Medicine, University of Novi Sad, 4 Institutski put, 21204 Sremska Kamenica, Serbia e-mail: [email protected]

M. Semnic Clinic for Neurology, Clinical Center of Vojvodina, School of Medicine, University of Novi Sad, 1-7 Hajduk Veljkova Street, 21000 Novi Sad, Serbia e-mail: [email protected]

Keywords Vascular dementia  Diffusion tensor imaging  Hippocampus  Mean diffusivity

Introduction Previous studies have shown microstructural alterations of the hippocampal formation as detected by diffusion tensor imaging (DTI) for patients with mild cognitive impairment and Alzheimer’s disease (AD). However, there is still a lack of knowledge and studies on the DTI of the hippocampus in vascular dementia (VD). Diffusion tensor imaging is a modality of magnetic resonance imaging (MRI) that quantifies the random water diffusion, giving the additional characterization on tissue architecture [1, 2]. Fractional anisotropy (FA) and

A. Todorovic e-mail: [email protected]

123

Acta Neurol Belg

mean diffusivity (MD) are the two main parameters calculated from DTI. While FA is defined as a coefficient of variations of the eigenvalues, MD is compatible with the magnitude of the self-diffusion of water. Elevations of MD in degenerative brain tissue are assumed to result from the loss of barriers restricting water motion. Increased diffusivity has been associated with changes of water content, demyelinating, sclerotic and other processes, causing the consequent disruption and break-down of the tissue architecture [1]. Most studies have found MD changes in the white matter of different disorders, including dementia. However, structural involvement of the gray matter, associated with diffusivity alterations, has also been reported [3]. Several authors have shown the superiority of detected MD alterations of the hippocampus compared to volume measurements in patients with AD and in predicting dementia onset in mild cognitive impairment (MCI) patients [4–7]. To the best of our knowledge, there are no published data on the presence of hippocampal DTI abnormalities in patients with vascular dementia (VD). Hippocampus, the unique macroscopic and histologic structure, is a conspicuous part of the limbic system and plays a major role in short-term memory, mood regulations and perception of temporal ordering of events [4, 8]. Fu et al. have recently revealed that Alzheimer disease patients, compared to healthy controls and VD patients, had lower FA values in the anterior frontal lobe, temporal lobe and hippocampus, associated with higher ADC values in the temporal lobe and hippocampus. No differences were reported between VD patients and healthy controls [9]. Recent DTI studies found involvement of the other non-hippocampal structures of the medial temporal lobe in MCI and AD. Kiuchi et al. [10] evaluated gray and white matter DTI changes in patients with AD, MCI, subjective cognitive impairment (SCI) and healthy controls. No statistically significant differences were evident between healthy controls and patients with SCI. In patients with AD and MC, almost the same extent of DTI alterations was observed: elevated MD in the temporal lobe, frontal lobe and precuneus. In another study, Selnes et al. [11] revealed that DTI parameters were better predictor of disease progression in patients with cognitive impairment in comparison to the presence of cerebrospinal fluid biomarkers. Also, parahippocampal white matter DTI alternations were detected as useful for identifying patients with MCI at highest risk for conversion to AD [12]. Wang et al. [13] found that significant reductions of FA values in normal appearing white matter on conventional MRI in parietal lobes was observed in MCI, while the authors detected that MD values in the splenium of the corpus callosum could be used as a biomarker differentiating MCI and AD.

123

Materials and methods Participants The participants underwent a full clinical assessment and detailed neuropsychological evaluation, as previously reported [14]. Exclusion criteria were: any cause of stroke other than small vessel disease, including large artery stenosis or a cardioembolic source; cortical infarcts on neuroimaging; large subcortical infarcts (more than 15 mm maximum diameter) as these infarcts often have a large vessel or embolic etiology; and any history of previous neurological or psychiatric disease. Twenty-five individuals fulfilling NINDS-AIREN (National Institute of Neurologic Disorder and Stroke and Association Internationale pour la Recherche et l’Enseignement en Neurosciences) criteria, due to cerebral small vessel disease were recruited from the Belgrade Neurology Clinic. All VD patients had ischemic leukoaraiosis defined as diffuse confluent white matter hyperintensity on T2weighted MRI and lacunar infarctions. Twenty-five age-, education-, and gender-matched healthy volunteers, with no current or previous neurological or psychiatric disease, were recruited as control subjects (HC). Mean (SD) age was 69.5 (±8.8) years (range 50–84) in the group with VD, and 71.6 (±7.5) years (56–84) in HC group (p = 0.35). Mean (SD) duration of full-time education was 10.8 (±3.6) years in the VD group and 11.9 (±1.9) years in the control group (p = 0.16). Sixteen (64 %) of the VD group were male, compared to 15 (60 %) of the HC group (p = 0.8).Twenty (80 %) of the VD group had a history of hypertension. Four examinees of the VD group and one from the control group were diabetic. The institutional ethics committee approved the study and subjects gave informed, written consent. Image acquisition and processing We performed MRI using a 3T MR imaging scanner (Magnetom Trio, Siemens, Erlangen, Germany). The head was supported and immobilized within the head coil to minimize head movement and gradient noise. All participants underwent the same protocol, which included wholebrain T2, FLAIR, and PD in the axial plane, 3D wholebrain T1-weighted with an isotropic resolution of 1 mm, and DTI acquired using 64 diffusion sensitizing directions, b value of 1,500 s/mm2, 65 axial slices, isotropic resolution of 1.8 mm. Images were processed to obtain indices of microstructural variations of bilateral hippocampi. The diffusion tensor images were transferred to a dedicated workstation (Leonardo, Siemens Medical Solutions, Erlangen Germany), where the data were post-processed using the DTI Task Card (Massachusetts General Hospital

Acta Neurol Belg

and Harvard Medical School Boston, MA). Mean diffusivity (MD) and fractional anisotropy (FA) were calculated from the DTI metrics on a voxel-by-voxel basis and displayed as two-dimensional color and gray-scale images. From these images, the average metric values were measured in specific regions of interest (ROIs). Our analysis was based on manual selection of the ROI as a region in the center of the anterior hippocampus in all patients and healthy subjects. The FA and MD values were measured in the Head of the Hippocampus on both sides. For each subject, FA maps were superimposed onto the threedimensional 3D T1-weighted image. To achieve standardized data collection and to avoid contamination of the data by adjacent structures, the size of ROI was fixed to five pixels. The circular five-pixel ROIs were selected on 3D DTI direction maps in color overlaid onto the 3D T1 MPRAGE anatomy reconstructed in three orthogonal directions and displayed together in 3D (Fig. 1a, b). A small distance was maintained between the ROIs and the

edge of the hippocampus in three planes to minimize volume averaging with the adjacent CSF. Subsequently, the ROIs were copied on MD and FA maps in DTI Evaluation package for quantitative evaluation (Fig. 1c, d). A single experienced neuroradiologist who was blinded to clinical data placed ROI areas three times into the head of each hippocampus, under the supervision of MRI Physicist. By applying repeated-measures analysis as described previously [8], intraregional variability of MD and FA were not statistically significant (p [ 0.1) for three measurements in all participants. To investigate further, factor analysis was applied to choose one measurement that best correlated with the two other measurements. We calculated Coefficient of variation to estimate inter-individual variability for MD and FA. Using multivariate analysis of variance (MANOVA) and discriminant analysis (DA) the overall differences were tested among VD and HC groups and between hemispheres. When MANOVA was significant, analysis of

Fig. 1 Placement of the regions of interest (ROI) in the hippocampus

123

Acta Neurol Belg

variance (ANOVA) and Student’s t test were applied to evaluate the difference in MD and FA between groups. Regions-of-interest were drawn manually on co-registered FA maps and 3D T1-weighted high resolution structural images (a, b). The measurements of FA and MD were obtained in the head of the hippocampus on both sides, across the previously defined ROIs (c, d).

Results According to the descriptive and dispersion parameters, the sampling distribution was normal for diffusion measures in both hippocampi. There was no significant inter-individual variability for MD and FA in HC and VD groups. The Coefficient of variation, CV in HC group was 8.5 and 9 for MD; 18.7 and 15.1 for FA in left and right hippocampus, respectively. The Coefficient of variation, CV in VD group was 11 and 12 for MD; 13.2 and 15.3 for FA in left and right hippocampus, respectively. The overall differences among VD and HC groups were significant in both hemispheres (MANOVA, p \ 0.001; DA, p \ 0.001). ANOVA showed significant difference for MD (p \ 0.001) in both hippocampi. Comparing the confidence intervals, MD values in VD patients were found to be increased in the hippocampus in both sides. No significant group differences for FA were found in left (ANOVA, p = 0.646; DA, p = 0.057) and right hippocampus (ANOVA, p = 0.854; DA, p = 0.022). The results of the paired sample t test for comparing diffusion measures are listed in Table 1. There were no significant differences between hemispheres in either HC (MANOVA, p = 0.644; DA, p = 0.627) and VD (MANOVA, p = 0.531; DA, p = 0.582) group (see Fig. 2).

Fig. 2 Confidence ellipses for the left hippocampus. The graph illustrates marked difference between healthy control (1) and vascular dementia (2) groups

follow-up of neurodegenerative process. Numerous studies showed patterns of white matter abnormalities in patients with different types of dementia [4, 15, 16]. DTI was found to be able to detect microstructural alterations in AD, before morphological changes on conventional MRI became visible [17]. The underlying pathology associated with normal-appearing white matter on routine imaging examinations has come into main focus of research. DTI, as a novel modality of neuroimaging, has enabled promising results in recent years in confirming further connections between cerebrovascular disease (CVD) and AD. Atherosclerotic changes have been found to be associated with a higher risk of AD, while cerebrovascular risk factors were significantly related to clinically diagnosed AD [18– 21]. The role of DTI is markedly increased since studies in patient groups with small vessel disease have detected rather weak correlations between the lesion load on T2weighted sequence and the degree of cognitive impairment. This lack of significant correlation decreases the usefulness of conventional MRI, since high signal intensity on T2

Discussion Over the past several years, there has been a huge amount of investigations in the field of dementia biomarkers that have a potential role in the early diagnosis and periodic Table 1 Results of paired sample t test for comparing MD and FA between vascular dementia and control group in left and right hippocampus

Hippocampus

Control group (HC)

Vascular dementia (VD)

Mean

Mean

SD

SD

CI

p

CI

Left MD 9 10-6mm2/s

699.79

55.98

668.78

730.80

833.36

92.77

795.06

871.66

\0.001

FA 9 10-3

184.11

51.43

155.62

212.59

177.40

39.62

161.04

193.76

0.646

Right SD standard deviation, CI confidence interval

123

MD 9 10-6mm2/s

730.41

40.16

708.16

752.65

859.10

69.76

830.30

887.91

\0.001

FA 9 10-3

174.83

33.76

156.13

193.54

172.66

45.96

153.68

191.63

0.854

Acta Neurol Belg

weighted and fluid attenuated inversion recovery (FLAIR) sequences may reflect a wide spectrum of conditions, ranging from complete axonal damage to relatively benign conditions with preserved fibre architecture. However, the changes in normal appearing white matter detected with DTI correlated with cognitive performance [22]. Along with cortical abnormalities, histologically proven white matter changes were well-characterized in AD [23]. But for the long time, it remained unclear whether white matter damage in AD is secondarily associated to gray matter abnormalities, reflects primary white matter degenerative process or is compatible with a combination of the two mentioned conditions. More recent DTI studies suggested that observed white matter changes in patients with AD were mainly reflective of the secondary degenerative process, but direct effect of amyloid b on white matter tissue could not be excluded [24]. Although DTI has been mainly used to investigate regional changes in both normal and abnormally appearing white matter on conventional MRI, it became clear that this method could be also used to highlight microstructural alterations of gray matter, including hippocampal formation [7, 25, 26]. Several authors detected increased sensitivity of DTI compared to hippocampal volume in evaluation of patients with AD. The absence of positive correlation between hippocampal volume and memory performance in patients younger than 65 years, suggested that in younger age these volume differences more likely reflected inborn variations than the degree of Alzheimer pathology [2, 26, 27]. Since DTI abnormalities have been observed in both white and gray matter in AD and in ischemic white matter disease, our goal was to investigate potential hippocampal involvement in VD, to detect potential stronger connections between AD and CVD using the different path of research in comparison to prior studies. Increased MD in hippocampal formations in our patients with VD might reflect direct pathological damage due to global ischemia and hypoperfusion, or secondary degeneration due to disruption of white matter tracts, linking them to hippocampi with consequent affection of both synaptic and extrasynaptic transmission. In DTI-estimation of white matter integrity in patients with dementia, alterations in both FA and MD were evident. In our study, no statistically significant relations were observed for FA. In the gray matter tissue, the presence of multiple crossing axonal fibers lowers the FA compared to white matter tissue, and makes the measure more difficult to interpret [2, 28, 29]. Unlike MD, FA showed low sensitivity to detect hippocampal neurodegenerative alterations in MCI patients. This is explained by heterogenous organization of the hippocampus which contains gray and white matter regions and different orientation of white

matter tracts, which have a marked impact on FA values [4, 30]. In conclusion, the major implication of our results is the presence of microstructural hippocampal damage indicating the need for further research on the link between VD and AD. These data encourage the additional use of multiple diffusion indices as important modalities for the diagnosis of coexisting microscopic changes in hippocampi associated with structural changes of the white matter in patients with VD. Further follow-up studies are needed to confirm the prognostic value of concomitant gray matter involvement in patients with leukoaraiosis for the early detection of cognitive deterioration in patients with VD. Acknowledgments The study was supported by grant from the Ministry of Science of the Republic of Serbia (grant number 175022). The authors thank the patients and volunteers for participating in the study. Conflict of interest of interest.

The authors declare that there are no conflicts

References 1. Le Bihan D, Johansen-Berg H (2012) Diffusion MRI at 25: exploring brain tissue structure and function. Neuroimage 61:324–341 2. Den Heijer T, van der Lijn F, Vernooij MW et al (2012) Structural and diffusion MRI measures of the hippocampus and memory performance. Neuroimage 63:1782–1789 3. Bhagat YA, Hussain MS, Stobbe RW et al (2008) Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study. Magn Reson Imaging 26:683–693 4. Fellgiebel A, Dellani P, Greverus D, Scheurich A, Stoeter P, Muller MJ (2006) Predicting conversion to dementia in mild cognitive impairment by volumetric and diffusivity measurements of hippocampus. Psychiatry Res 146:283–287 5. Muller M, Greverus D, Dellani P et al (2005) Functional implications of hippocampal volume and diffusivity in mild cognitive impairment. Neuroimage 28:1033–1042 6. Kantarci K, Petersen R, Boeve B et al (2005) DWI predicts future progression to Alzheimer disease in amnestic mild cognitive impairment. Neurology 64:902–904 7. Cherubini A, Peran P, Spoletini I et al (2010) Combined volumetry and DTI in subcortical structures of mild cognitive impairment and Alzheimer’s disease patients. J Alzheimers Dis 19(4):1273–1282 8. Ostojic J, Kozic D, Konstantinovic J et al (2010) Three-dimensional multivoxel spectroscopy of the healthy hippocampus—are metabolic differences related to the location? Clin Radiol 65(4):302–307 9. Fu JL, Zhang T, Chang C, Zhang YZ, Li WB (2012) The value of diffusion tensor imaging in the differential diagnosis of subcortical ischemic vascular dementia and Alzheimer’s disease in patients with only mild white matter alterations on T2-weighted images. Acta Radiol 53(3):312–317 10. Kiuchi K, Kitamura S, Taoka T et al (2014) Gray and white matter changes in subjective cognitive impairment, amnestic mild cognitive impairment and Alzheimer’s disease: a voxel-based analysis study. PLoS One 9(8):e104007. doi:10.1371/journal. pone.0104007

123

Acta Neurol Belg 11. Selnes P, Aarsland D, Bjørnerud A et al (2013) Diffusion tensor imaging surpasses cerebrospinal fluid as predictor of cognitive decline and medial temporal lobe atrophy in subjective cognitive impairment and mild cognitive impairment. J Alzheimers Dis 33(3):723–736. doi:10.3233/JAD-2012-121603 12. Solodkin A, Chen EE, Van Hoesen GW et al (2013) In vivo parahippocampal white matter pathology as a biomarker of disease progression to Alzheimer’s disease. J Comp Neurol 521(18):4300–4317 13. Wang JH, Lv PY, Wang HB et al (2013) Diffusion tensor imaging measures of normal appearing white matter in patients who are aging, or have amnestic mild cognitive impairment, or Alzheimer’s disease. J Clin Neurosci 20(8):1089–1094 14. Pavlovic AM, Pekmezovic T, Zidverc-Trajkovic J et al (2011) What are the differences between younger and older patients with symptomatic small vessel disease? Clin Neuro Neurosurg 113(9):762–767 15. Chen TF, Lin CC, Chen YF et al (2009) Diffusion tensor changes in patients with amnestic mild cognitive impairment and various dementias. Psychiatry Res 173:15–21 16. Yoshiura T, Mihara F, Ogomori K, Tanaka A, Kaneko K, Masuda K (2002) Diffusion tensor in posterior cingulare girus: correlation with cognitive decline in Alzheimer’s disease. Neuro Report 13:2299–2302 17. Varghese T, Sheelakumari R, James JS, Mathuranath PS (2013) A review of neuroimaging biomarkers of Alzheimer’s disease. Neurol Asia 18(3):239–248 18. Korczyn AD (2005) The underdiagnosis of the vascular contribution to dementia. J Neurol Sci 229–230:3–6 19. Alves GS, Sudo FK, Alves CE, Ericeira-Valente L, Moreira DM, Engelhardt E, Laks J (2012) Diffusion tensor imaging studies in vascular disease. Dement Neuropsychol 6(3):158–163 20. Hardiman O, Doherty CP (eds) (2011) Neurodegenerative disorders: a clinical guide. Springer, London 21. Otsuka Y, Yamauchi H, Sawarnoto N, Iseki K, Tomimoto H, Fukuyama H (2012) Diffuse tract damage in the hemispheric

123

22.

23.

24.

25.

26.

27.

28.

29.

30.

deep white matter may correlate with global cognitive impairment and callosal atrophy in patients with extensive leukoaraiosis. Am J Neuroradiol 33:726–732 O’Sullivan M, Morris RG, Huckstep B, Jones DK, Willisms SCR, Markus HS (2012) Diffusion tensor MRI correlates with executive dysfunction in patients with ischemic leukoaraiosis. J Neurol Neurosurg Psychiatry 75:441–447 Bronge L, Bogdanovic N, Wahlund IO (2002) Postmortem MRI and histopathology of white matter changes in Alzheimer brains: a quantitative, comparative study. Dement Geriatr Cogn Disord 13(4):205–212 Agosta F, Pievani M, Sala S, Geroldi C, Galluzzi S, Frisoni G, Filippi M (2011) White matter damage in Alzheimer disease and its relationship to gray matter atrophy. Radiology 258(3): 853–863 Carlesimo GA, Piras F, Assogna F, Pontieri FE, Caltagirone C, Spalletta G (2012) Hippocampal abnormalities and memory deficits in Parkinson disease. Neurology 78(24):1939–1945 Carlesimo GA, Cherubini A, Caltagirone C, Spalletta G (2010) Hippocampal mean diffusivity and memory in healthy elderly individuals: a cross-sectional study. Neurology 74:194–200 Rodrigue KM, Raz N (2004) Shrinkage of the entorhinal cortex over the five years predicts memory performance in healthy adults. J Neurosci 24:956–963 Gerdes JS, Keller SS, Schwindt W, Evers S, Mohammadi S, Deppe M (2012) Progression of microstructural putamen alterations in a case of symptomatic recurrent seizures using diffusion tensor imaging. Seizure 21(6):478–481 Bohanna I, Georgiou-Karistianis N, Egan GF (2011) Connectivity-based segmentation of the striatum in Huntington’s disease: vulnerability of motor pathways. Neurobiol Dis 42:475–481 Fellgiebel A, Wille P, Muller MJ, Winterer G, Scheurich A, Vucurevic G, Schmidt LG, Stoeter P (2004) Ultrastructural hippocampal and white matter alterations in mild cognitive impairment: a diffuse tensor imaging study. Dement Geriatr Cogn Disord 18(1):101–110

Hippocampal diffusion tensor imaging microstructural changes in vascular dementia.

To explore microstructural integrity of hippocampus in vascular dementia (VD) using DTI. Twenty-five individuals with VD, without magnetic resonance i...
591KB Sizes 0 Downloads 19 Views

Recommend Documents


Longitudinal diffusion tensor imaging in frontotemporal dementia.
Novel biomarkers for monitoring progression in neurodegenerative conditions are needed. Measurement of microstructural changes in white matter (WM) using diffusion tensor imaging (DTI) may be a useful outcome measure. Here we report trajectories of W

Diffusion tensor imaging of hippocampal network plasticity.
Diffusion tensor imaging (DTI) has become a valuable tool to investigate white matter integrity in the brain. DTI also gives contrast in gray matter, which has been relatively little explored in studies assessing post-injury structural abnormalities.

Diffusional kurtosis and diffusion tensor imaging reveal different time-sensitive stroke-induced microstructural changes.
Diffusion MRI is a promising, clinically feasible imaging technique commonly used to describe white matter changes after stroke. We investigated the sensitivity of diffusion MRI to detect microstructural alterations in gray matter after sensorimotor

Microstructural changes of the whole brain in patients with comitant strabismus: evidence from a diffusion tensor imaging study.
The aim of this study was to investigate the fractional anisotropy (FA) and mean diffusivity (MD) using a diffusion tensor imaging technique and whole-brain voxel-based analysis in patients with comitant strabismus.

Longitudinal cerebellar diffusion tensor imaging changes in posterior fossa syndrome.
Posterior fossa syndrome is a severe transient loss of language that frequently complicates resection of tumors of the cerebellum. The associated pathophysiology and relevant anatomy to this language deficit remains controversial. We performed a retr

Microstructural abnormalities in children with post-traumatic stress disorder: a diffusion tensor imaging study at 3.0T.
Posttraumatic stress disorder (PTSD) is a severe anxiety disorder characterized by re-experiencing, avoidance and hyperarousal. Brain microstructure abnormalities in PTSD, especially in children, are not yet well characterized. The aim of this study

Unique white matter microstructural patterns in ADHD presentations-a diffusion tensor imaging study.
Attention-deficit/hyperactivity disorder predominantly inattentive (ADHD-PI) and combined (ADHD-C) presentations are likely distinct disorders that differ neuroanatomically, neurochemically, and neuropsychologically. However, to date, little is known

Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study.
This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson's disease who were enrolled in the Parkinson's progression marker ini

Cerebral Microstructural Alterations after Radiation Therapy in High-Grade Glioma: A Diffusion Tensor Imaging-Based Study.
To investigate radiation therapy-induced microstructural damage of white matter in patients with high-grade glioma by diffusion tensor imaging (DTI).