A diffusion tensor MRI study of patients with MCI and AD with a 2-year clinical follow-up

Scola, Elisa; Bozzali, Marco; Agosta, Federica; Magnani, Giuseppe; Franceschi, M.; Sormani, Maria Pia; Cercignani, Mara; Pagani, Elisabetta; Falautano, Monica; Filippi, Massimo; Falini, Andrea

doi:10.1136/jnnp.2009.189639

Cited by 84 publications

(68 citation statements)

References 43 publications

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“…For example, DTI has been shown to differentiate AD patients from cognitively healthy controls with accuracy rates on par with gray matter volume estimates obtained using structural MRI [7]. In fact, some studies [8] found no predictive value in volumetry data for conversion to AD from its prodrome, mild cognitive impairment (MCI), in the short-term (2 years), whereas DTI measures were predictive. Diffusivity in the hippocampus, a key region for memory formation that is particularly susceptible to AD-related neurodegeneration [9], may predict progression from MCI to AD more accurately than hippocampal atrophy measured by structural MRI [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the hippocampus, MD is also elevated in other brain regions in those with AD versus healthy controls or MCI controls, including entorhinal cortex [19], temporal [19], parietal [8,19], frontal [19], and occipital lobe regions [8] as well as lateral temporal and parietal lobe association cortices [18]. Such findings of increased MD are assumed to result from the degeneration of physiological barriers to diffusion (i.e., reduced cellular membrane in neurons from stunted axons and dendrites, neuron loss) [20,21].…”

Section: Introductionmentioning

confidence: 99%

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In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer’s Disease with Diffusion Tensor Imaging

Snow

Dale

O’Brien-Moran

et al. 2017

JAD

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Abstract.A diagnosis of Alzheimer's disease (AD), a neurodegenerative disorder accompanied by severe functional and cognitive decline, is based on clinical findings, with final confirmation of the disease at autopsy by the presence of amyloid-␤ (A␤) plaques and neurofibrillary tangles. Given that microstructural brain alterations occur years prior to clinical symptoms, efforts to detect brain changes early could significantly enhance our ability to diagnose AD sooner. Diffusion tensor imaging (DTI), a type of MRI that characterizes the magnitude, orientation, and anisotropy of the diffusion of water in tissues, has been used to infer neuropathological changes in vivo. Its utility in AD, however, is still under investigation. The current study used DTI to examine brain regions susceptible to AD-related pathology; the cerebral cortex, entorhinal cortex, and hippocampus, in 12-14-month-old 3xTg AD mice that possess both A␤ plaques and neurofibrillary tangles. Mean diffusivity did not differ between 3xTg and control mice in any region. Decreased fractional anisotropy (p < 0.01) and axial diffusivity (p < 0.05) were detected only in the hippocampus, in which both congophilic A␤ plaques and hyperphosphorylated tau accumulation, consistent with neurofibrillary tangle formation, were detected. Pathological tau accumulation was seen in the cortex. The entorhinal cortex was largely spared from AD-related neuropathology. This is the first study to demonstrate DTI abnormalities in gray matter in a mouse model of AD in which both pathological hallmarks are present, suggesting the feasibility of DTI as a non-invasive means of detecting brain pathology in vivo in early-stage AD.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer’s Disease with Diffusion Tensor Imaging

Snow

Dale

O’Brien-Moran

et al. 2017

JAD

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“…44 Some studies satisfied both NINCDS-ADRDA and DSM-IV criteria, 22,23,[26][27][28]31,38 and others used only one set of criteria. Some studies that used NINCDS-ADRDA criteria adopted probable AD, 10,12,14,17,[19][20][21]23,[26][27][28][29]32,33 whereas other studies did not indicate the diagnosis as probable or possible AD. Our study excluded other types of dementia, not AD.…”

Section: Discussionmentioning

confidence: 99%

P1‐149: Structural MRI and amyloid PET imaging for prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment: A meta‐analysis

Park

Kim

Park

et al. 2015

Alzheimer's & Dementia

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Alzheimer's disease (AD) has an insidious onset with a slowly progressive course. Mild cognitive impairment (MCI) is an intermediate stage between cognitively normal and AD. In particular, amnestic MCI is considered as a prodromal stage of AD. MCI may therefore be a target for the prediction of who will develop AD prediction. Several markers during the prodromal MCI stage, including neuropsychological tests, have been proposed for the prediction of AD. However, no Print ISSN 1738-3684 / On-line ISSN 1976 OPEN ACCESS Copyright © 2017 Korean Neuropsychiatric Association 205single study has included enough data to provide a reliable predictor of AD. The International Working Group (IWG) and National Institute on Aging Alzheimer's Association (NIA-AA) has proposed several biomarkers as diagnostic criteria for MCI, including cerebro spinal fluid (CSF) amyloid beta (Aβ) and tau, atrophy on MRI, glucose metabolism on [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) and fibrillar Aβ burden on amyloid PET. 1,2 FDG-PET has been suggested to be the strongest predictor for progression from MCI to AD, 3 however, its high costs may limit its widespread adoption. A CSF assessment requires a lumbar puncture, which is regarded an invasive procedure, although it is widely implemented without problems in the elderly. In contrast, MRI is noninvasive, widely used in clinical settings and also could be easily performed. Atrophy measurements on MRI have been used to predict the progression to AD inpatients with MCI since the 1990s. Most studies have

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“…Thus, our sample is more heterogeneous than the MCI subgroups in other studies Fellgiebel et al, 2006;Müller et al, 2007;Scola et al, 2010). Second, in our study, we applied the previously validated CSF contamination model by Koo et al (2009).…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies on GM MD in AD reported increases of hippocampal MD and whole brain GM MD in subjects with mild cognitive impairment (MCI) as compared to healthy controls Eustache et al, 2016;Fellgiebel et al, 2004;Müller et al, 2005;Scola et al, 2010), as well as in MCI patients that converted to AD compared to MCI subjects that remained stable over a period of several years (Douaud et al, 2013;Fellgiebel et al, 2006;Scola et al, 2010;van Uden et al, 2016). In some studies, hippocampal diffusivity even demonstrated a higher diagnostic and prognostic accuracy than hippocampal volume (Fellgiebel et al, 2006;Kantarci et al, 2005;Müller et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

[IC‐P‐161]: MEAN DIFFUSIVITY IN CORTICAL GRAY MATTER IN ALZHEIMER's DISEASE: THE IMPORTANCE OF PARTIAL VOLUME CORRECTION

Henf

Grothe

Teipel

et al. 2017

Alzheimer's & Dementia

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Mean diffusivity (MD) measured by diffusion tensor imaging can reflect microstructural alterations of the brain's gray matter (GM). Therefore, GM MD may be a sensitive marker of neurodegeneration related to Alzheimer's Disease (AD). However, due to partial volume effects (PVE), differences in MD may be overestimated because of a higher degree of brain atrophy in AD patients and in cases with mild cognitive impairment (MCI). Here, we evaluated GM MD changes in AD and MCI compared with healthy controls, and the effect of partial volume correction (PVC) on diagnostic utility of MD.We determined region of interest (ROI) and voxel-wise group differences and diagnostic accuracy of MD and volume measures between matched samples of 39 AD, 39 MCI and 39 healthy subjects before and after PVC. Additionally, we assessed whether effects of GM MD values on diagnosis were mediated by volume.ROI and voxel-wise group differences were reduced after PVC. When using these ROIs for predicting group separation in logistic models, both PVE corrected and uncorrected GM MD values yielded a poorer diagnostic accuracy in single predictor models than regional volume. For the discrimination of AD patients and healthy controls, the effect of GM MD on diagnosis was significantly mediated by volume of hippocampus and posterior cingulate ROIs.Our results suggest that GM MD measurements are strongly confounded by PVE in the presence of brain atrophy, underlining the necessity of PVC when using these measurements as specific metrics of microstructural tissue degeneration. Independently of PVC, regional MD was not superior to regional volume in separating prodromal and clinical stages of AD from healthy controls.

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A diffusion tensor MRI study of patients with MCI and AD with a 2-year clinical follow-up

Cited by 84 publications

References 43 publications

In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer’s Disease with Diffusion Tensor Imaging

In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer’s Disease with Diffusion Tensor Imaging

P1‐149: Structural MRI and amyloid PET imaging for prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment: A meta‐analysis

[IC‐P‐161]: MEAN DIFFUSIVITY IN CORTICAL GRAY MATTER IN ALZHEIMER's DISEASE: THE IMPORTANCE OF PARTIAL VOLUME CORRECTION

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