Patterns of cerebellar gray matter atrophy across Alzheimer's disease progression

The role of the cerebellum in cognitive function has been broadly investigated in the last decades from an anatomical, clinical, and functional point of view and new evidence points toward a significant contribution of the posterior lobes of the cerebellum in cognition in Alzheimer's disease (AD). In the present work we used SUIT-VBM (spatially unbiased infratentorial template, voxel-based morphometry) to perform an analysis of the pattern of cerebellar gray matter (GM) atrophy in amnestic mild cognitive impairment (a-MCI) and AD dementia patients compared to healthy subjects (HS), in order to follow the changes of non-motor features of cerebellar degeneration throughout disease progression. This template has been validated to guarantee a significant improvement in voxel-to-voxel alignment of the individual fissures and the deep cerebellar nuclei compared to Montreal Neurological Institute (MNI) whole-brain template. Our analysis shows a progression of cerebellar GM volume changes throughout a continuous spectrum from early to late clinical stages of AD. In particular vermis and paravermian areas of the anterior (I-V) and posterior (VI) lobes are involved since the a-MCI stage, with a later involvement of the hemispheric part of the posterior lobes (VI lobule) and Crus I in AD dementia patients only. These findings support the role of the cerebellum in higher-level functions, and whilst confirming previous data on the involvement of Crus I in AD dementia, provide new evidence of an involvement of the vermis in the early stages of the disease

An MRI-Derived Definition of MCI-to-AD Conversion for Long-Term, Automati c Prognosis of MCI Patients

Alzheimer's disease (AD) and mild cognitive impairment (MCI), continue to be widely studied. While there is no consensus on whether MCIs actually "convert" to AD, the more important question is not whether MCIs convert, but what is the best such definition. We focus on automatic prognostication, nominally using only a baseline image brain scan, of whether an MCI individual will convert to AD within a multi-year period following the initial clinical visit. This is in fact not a traditional supervised learning problem since, in ADNI, there are no definitive labeled examples of MCI conversion. Prior works have defined MCI subclasses based on whether or not clinical/cognitive scores such as CDR significantly change from baseline. There are concerns with these definitions, however, since e.g. most MCIs (and ADs) do not change from a baseline CDR=0.5, even while physiological changes may be occurring. These works ignore rich phenotypical information in an MCI patient's brain scan and labeled AD and Control examples, in defining conversion. We propose an innovative conversion definition, wherein an MCI patient is declared to be a converter if any of the patient's brain scans (at follow-up visits) are classified "AD" by an (accurately-designed) Control-AD classifier. This novel definition bootstraps the design of a second classifier, specifically trained to predict whether or not MCIs will convert. This second classifier thus predicts whether an AD-Control classifier will predict that a patient has AD. Our results demonstrate this new definition leads not only to much higher prognostic accuracy than by-CDR conversion, but also to subpopulations much more consistent with known AD brain region biomarkers. We also identify key prognostic region biomarkers, essential for accurately discriminating the converter and nonconverter groups

Strategic lesions in the anterior thalamic radiation and apathy in early Alzheimer's disease

BACKGROUND Behavioural disorders and psychological symptoms of Dementia (BPSD) are commonly observed in Alzheimer's disease (AD), and strongly contribute to increasing patients' disability. Using voxel-lesion-symptom mapping (VLSM), we investigated the impact of white matter lesions (WMLs) on the severity of BPSD in patients with amnestic mild cognitive impairment (a-MCI). METHODS Thirty-one a-MCI patients (with a conversion rate to AD of 32% at 2 year follow-up) and 26 healthy controls underwent magnetic resonance imaging (MRI) examination at 3T, including T2-weighted and fluid-attenuated-inversion-recovery images, and T1-weighted volumes. In the patient group, BPSD was assessed using the Neuropsychiatric Inventory-12. After quantitative definition of WMLs, their distribution was investigated, without an a priori anatomical hypothesis, against patients' behavioural symptoms. Unbiased regional grey matter volumetrics was also used to assess the contribution of grey matter atrophy to BPSD. RESULTS Apathy, irritability, depression/dysphoria, anxiety and agitation were shown to be the most common symptoms in the patient sample. Despite a more widespread anatomical distribution, a-MCI patients did not differ from controls in WML volumes. VLSM revealed a strict association between the presence of lesions in the anterior thalamic radiations (ATRs) and the severity of apathy. Regional grey matter atrophy did not account for any BPSD. CONCLUSIONS This study indicates that damage to the ATRs is strategic for the occurrence of apathy in patients with a-MCI. Disconnection between the prefrontal cortex and the mediodorsal and anterior thalamic nuclei might represent the pathophysiological substrate for apathy, which is one of the most common psychopathological symptoms observed in dementia

Anatomical and Functional Deficits in Patients with Amnestic Mild Cognitive Impairment

Background: Anatomical and functional deficits have been studied in patients with amnestic mild cognitive impairment (MCI). However, it is unclear whether and how the anatomical deficits are related to the functional alterations. Present study aims to characterize the association between anatomical and functional deficits in MCI patients. Methods: Seventeen amnestic MCI patients and 18 healthy aging controls were scanned using a T1 Weighted MPRAGE sequence and a gradient-echo echo-planar imaging sequence. Clinical severity of MCI patients was evaluated by usin

Quantitative MRI Brain Studies in Mild Cognitive Impairment and Alzheimer's disease: A Methodological Review

Classifying and predicting Alzheimer's disease (AD) in individuals with memory disorders through clinical and psychometric assessment is challenging especially in Mild Cognitive Impairment (MCI) subjects. Quantitative structural Magnetic Resonance Imaging (MRI) acquisition methods in combination with Computer-Aided Diagnosis (CAD) are currently being used for the assessment AD. These acquisitions methods include: i) Voxel-based Morphometry (VBM), ii) volumetric measurements in specific Regions of Interest (ROIs), iii) cortical thickness measurements, iv) shape analysis and v) texture analysis. This review evaluates the aforementioned methods in the classification of cases into one of the following 3 groups: Normal Controls (NC), MCI and AD subjects. Furthermore, the performance of the methods is assessed on the prediction of conversion from MCI to AD. In parallel, it is also assessed which ROIs are preferred in both classification and prognosis through the different states of the disease. Structural changes in the early stages of the disease are more pronounced in the Medial Temporal Lobe (MTL) especially in the entorhinal cortex, whereas with disease progression both entorhinal cortex and hippocampus offer similar discriminative power. However, for the conversion from MCI subjects to AD, entorhinal cortex provides better predictive accuracies rather than other structures, such as the hippocampus

β-Amyloid (1–42) Levels in Cerebrospinal Fluid and Cerebral Atrophy in Mild Cognitive Impairment and Alzheimer's Disease

Background: Recent studies consistently reported Alzheimer’s disease (AD) and, to a lower extent, mild cognitive impairment (MCI) to be accompanied by reduced cerebrospinal fluid (CSF) levels of β-amyloid. However, how these changes are related to brain morphological alterations is so far only partly understood. Methods: CSF levels of β-amyloid (1–42) were examined with respect to cerebral atrophy in 23 subjects with MCI, 16 patients with mild-to-moderateAlzheimer’s disease (AD) and 15 age-matched controls by using magnetic resonance imaging and voxel-based morphometry (VBM). Results: When contrasted with the controls, β-amyloid (1–42) levels were significantly lower (p Conclusion: Our finding confirms the results of previous studies and suggests that both the decrease in β-amyloid (1–42) and the development of hippocampal atrophy coincide in the disease process

Magnetic resonance imaging In Alzheimer’s disease, mild cognitive impairment and normal aging : Multi-template tensor-based morphometry and visual rating

Alzheimer's disease (AD) is the most common neurodegenerative disease preceded by a stage of mild cognitive impairment (MCI). The structural brain changes in AD can be detected more than 20 years before symptoms appear. If we are to reveal early brain changes in AD process, it is important to develop new diagnostic methods. Magnetic resonance imaging (MRI) is an imaging technique used in the diagnosis and monitoring of neurodegenerative diseases. Magnetic resonance imaging can detect the typical signs of brain atrophy of degenerative diseases, but similar changes can also be seen in normal aging. Visual rating methods (VRM) have been developed for visual evaluation of atrophy in dementia. A computer-based tensor-based morphometry (TBM) analysis is capable of assessing the brain volume changes typically encountered in AD. This study compared the VRM and TBM analysis in MCI and AD subjects by cross-sectional and longitudinal examination. The working hypothesis was that TBM analysis would be better than the visual methods in detecting atrophy in the brain. TBM was also used to analyze volume changes in the deep gray matter (DGM). Possible associations between TBM changes and neuropsychological tests performances were examined. This working hypothesis was that the structural DGM changes would be associated with impairments in cognitive functions. In the cross-sectional study, TBM distinguished the MCI from controls more sensitively than VRM, but the methods were equally effective in differentiating AD from MCI and controls. In the longitudinal study, both methods were equally good in the evaluation of atrophy in MCI, if the groups were sufficiently large and the disease progressed to AD. Volume changes were found in DGM structures, and the atrophy of DGM structures was related to cognitive impairment in AD. Based on these results, a TBM analysis is more sensitive in detecting brain changes in early AD as compared to VRM. In addition, the study produced information about the involvement of the deep gray matter in cognitive impairment in AD.Magneettikuvaus Alzheimerin taudissa, lievässä muistihäiriössä ja normaalissa ikääntymisessä: Tensoripohjainen muotoanalyysi ja visuaalinen arviointimenetelmä Alzheimerin tauti (AT) on yleisin dementoiva sairaus, jota edeltää yleensä lievä muistitoimintojen heikentyminen. AT:n aivomuutoksia voidaan todeta yli 20 vuotta ennen sairastumista. Jotta vielä varhaisempia AT:n aivomuutoksia voidaan todeta, on tärkeää kehittää uusia diagnostisia menetelmiä. Magneettikuvausta (MK) käytetään rappeuttavien aivosairauksien diagnostiikassa ja seurannassa. MK:lla voidaan havaita aivorappeumasairauksille tyypillistä kutistumista, mutta samanlaisia muutoksia voi esiintyä myös normaalissa ikääntymisessä. Aivorappeuman arviointiin on kehitetty silmämääräisiä arviointimenetelmiä. Tietokoneperusteinen tensoripohjainen muotoanalyysi (TPM) laskee esimerkiksi AT:lle tyypillisiä aivojen tilavuusmuutoksia. Tämä tutkimus vertaili silmämääräisiä arvioitimenetelmiä ja TPM:ä lievässä muistitoimintojen heikentymisessä ja AT:ssa poikittais- ja pitkittäistutkimuksella. TPM:n oletettiin olevan silmämääräisiä menetelmiä parempi tunnistamaan aivojen kutistumismuutoksia. Lisäksi TPM:llä tutkittiin AT:iin liittyviä aivojen syvän harmaan aiheen muutoksia, joita verrattiin neuropsykologisten testien tuloksiin. Syvän harmaan aineen kutistumisen oletettiin olevan yhteydessä tietojenkäsittelyn heikentymiseen. Tulosten perustella TPM tunnisti AT:iin liittyviä aivomuutoksia silmämääräistä menetelmää paremmin jo lievän muistitoimintojen heikentymisen vaiheessa. AT:iin liittyviä aivomuutoksia löytyi myös aivojen syvästä harmaasta aineesta ja ne olivat osittain yhteydessä neuropsykologisten testien tuloksiin. Tutkimuksen perusteella TPM voi parantaa AT:n varhaisdiagnostiikkaa verrattuna silmämääräisiin arviointimenetelmiin. Tutkimus antoi myös tietoa aivojen syvän harmaan aineen osallisuudesta ihmisen tietojenkäsittelyyn