The contribution of voxel-based morphometry in staging patients with mild cognitive impairment

Bozzali, Marco; Filippi, Massimo; Magnani, Giuseppe; Cercignani, Mara; Franceschi, M.; Schiatti, E; Castiglioni, S.; Mossini, R.; Falautano, Monica; Scotti, Giuseppe; Comı, Gıancarlo; Falini, Andrea

doi:10.1212/01.wnl.0000228243.56665.c2

Cited by 163 publications

(137 citation statements)

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“…Most of the literature on cortical atrophy in MCI has focused on exploratory mapping of atrophy in MCI compared to controls or patients with AD, 6,25,26 or in MCI converters to mild AD dementia compared to nonconverters. 8,9,27 In the former studies of atrophy in MCI in which the diagnostic outcome is unknown, atrophy patterns are largely similar to, although of lesser magnitude, than those of mild AD dementia. Of the previous investigations that have followed patients clinically after scanning, two demonstrated distributed atrophy patterns in the MCI progressors that are typical of those of patients with AD when comparing MCI progressors to controls, 7 but surprisingly one study showed more widespread atrophy when comparing MCI progressors to nonprogressors, 7 while the other showed much less widespread differences involving only supramarginal, inferior frontal, and hippocampal regions.…”

Section: And Thinning In Cortical Rois In Patients With Questionable mentioning

confidence: 99%

“…Of the previous investigations that have followed patients clinically after scanning, two demonstrated distributed atrophy patterns in the MCI progressors that are typical of those of patients with AD when comparing MCI progressors to controls, 7 but surprisingly one study showed more widespread atrophy when comparing MCI progressors to nonprogressors, 7 while the other showed much less widespread differences involving only supramarginal, inferior frontal, and hippocampal regions. 9 A third investigation identi- fied focal ventromedial temporal atrophy. 8 There are no previous comparable data regarding the magnitude of atrophy (% difference) between progressors vs nonprogressors.…”

Section: And Thinning In Cortical Rois In Patients With Questionable mentioning

confidence: 99%

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The cortical signature of prodromal AD

Bakkour¹,

Morris²,

Dickerson³

2009

Neurology

275

243

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Objective:We previously used exploratory analyses across the entire cortex to determine that mild Alzheimer disease (AD) is reliably associated with a cortical signature of thinning in specific limbic and association regions. Here we investigated whether the cortical signature of AD-related thinning is present in individuals with questionable AD dementia (QAD) and whether a greater degree of regional cortical thinning predicts mild AD dementia. Methods: Results:Longitudinal clinical follow-up revealed that 20 participants converted to mild AD dementia (progressors) while 29 remained stable (nonprogressors) approximately 2.5 years after scanning. At baseline, QAD participants showed a milder degree of cortical thinning than typically seen in mild AD, and CDR Sum-of-Boxes correlated with thickness in temporal and parietal ROIs. Compared to nonprogressors, progressors showed temporal and parietal thinning. Using receiver operating characteristic curves, the thickness of an aggregate measure of these regions predicted progression to mild AD with 83% sensitivity and 65% specificity.Conclusions: Thinning in specific cortical areas known to be affected by Alzheimer disease (AD) is detectable in individuals with questionable AD dementia (QAD) and predicts conversion to mild AD dementia. This method could be useful for identifying individuals at relatively high risk for imminent progression from QAD to mild AD dementia, which may be of value in clinical trials. CDR-SB ϭ CDR Sum-of-Boxes; eTIV ϭ estimated total intracranial volume; EV ϭ entorhinal volume; HV ϭ hippocampal volume; MCI ϭ mild cognitive impairment; MCT ϭ mean cortical thickness; MMSE ϭ Mini-Mental State Examination; MTL ϭ medial temporal lobe; MTLT ϭ medial temporal lobe thickness; OC ϭ older controls; QAD ϭ questionable AD dementia; ROC ϭ receiver operating characteristic; ROI ϭ region of interest; WBV ϭ whole brain volume.Anatomic abnormalities of brain regions known to be early sites of Alzheimer disease (AD) pathology, such as medial temporal lobe (MTL) regions including the entorhinal cortex and hippocampal formation, can be detected in prodromal AD prior to dementia. 1-3 Although it is well known that early in its clinical course AD affects non-MTL neocortical association regions, 4,5 there has been little investigation of neocortical anatomy in prodromal AD prior to dementia. The few investigations of cortical anatomic abnormalities in mild cognitive impairment (MCI) 6 or prodromal AD 7-9 have used techniques that involve exploratory mapping of

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Section: And Thinning In Cortical Rois In Patients With Questionable mentioning

confidence: 99%

Section: And Thinning In Cortical Rois In Patients With Questionable mentioning

confidence: 99%

The cortical signature of prodromal AD

Bakkour¹,

Morris²,

Dickerson³

2009

Neurology

275

243

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“…A variety of VBM-type methods exist (Ashburner and Friston, 2000;Chung et al, 2001;Davatzikos et al, 2001;Davatzikos et al, 1996;Thompson et al, 2001), which generally fall under the umbrella of the field of computational neuroanatomy (Ashburner et al, 2003;Miller et al, 1997). VBM studies have confirmed that complex spatial patterns of brain atrophy can be measured in MCI and AD (Bozzali et al, 2006;Chetelat et al, 2002; Davatzikos et al, in press, 2006;Karas et al, 2004;Pennanen et al, 2005a;Saykin et al, 2006;Thompson et al, 2001;Whitwell et al, 2007;Xie et al, 2006). However, VBM analyses are of limited value for individual diagnosis, since they measure group differences and are not equipped to classify individuals.…”

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confidence: 99%

Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study

et al. 2008

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This work builds upon previous studies that reported high sensitivity and specificity in classifying individuals with mild cognitive impairment (MCI), which is often a prodromal phase of Alzheimer's Disease (AD), via pattern classification of MRI scans. The current study integrates MRI and PET 15 O water scans from 30 participants in the Baltimore Longitudinal Study of Aging, and tests the hypothesis that joint evaluation of structure and function can yield higher classification accuracy than either alone. Classification rates of up to 100% accuracy were achieved via leave-one-out cross validation, whereas conservative estimates of generalization performance in new scans, evaluated via bagging cross-validation, yielded an area under the receiver operating characteristic (ROC) curve equal to 0.978 (97.8%), indicating excellent diagnostic accuracy. Spatial maps of regions determined to contribute the most to the classification implicated many temporal, prefrontal, orbitofrontal, and parietal regions. Detecting complex patterns of brain abnormality in early stages of cognitive impairment has pivotal importance for the detection and management of AD. KeywordsAlzheimer's Disease; MCI; high-dimensional Pattern Classification; MRI; PET; voxel-based analysis; diagnosis of AD Amnestic mild cognitive impairment (MCI) is often a prodromal stage to Alzheimer's Disease (AD), as individuals with MCI may convert to AD at an annual rate as high as 15% . Therefore, MCI is frequently considered to be a good target for early AD diagnosis, and for therapeutic interventions. MRI and PET imaging can potentially be used as diagnostic tools that assess brain structure and function in a direct and objective way and have potential utility for diagnosis, prognosis, and evaluation of disease progression and treatment effects.Many imaging studies have found loss of grey matter (GM) and metabolic abnormalities in MCI. Most of the earlier studies were based on volumetric measurements of regions of interest (ROI's) (Chetelat et al., 2002;Convit et al., 2000;Dickerson et al., 2001;Fox et al., 1996a;Kaye et al., 1997;Killiany et al., 2000), such as the hippocampus and the entorhinal cortex, and have confirmed GM atrophy in regions that are known to be affected by AD. However, the pattern of AD pathology is complex and evolves as the disease progresses, starting mainly in the hippocampus and entorhinal cortex, and subsequently spreading throughout temporal and orbitofrontal cortex, posterior cingulate, and association cortex generally (Braak et al., 1998). Therefore, measuring volumes or average PET signals of a few structures cannot capture Voxel-based morphometry (VBM) has been proposed by a number of investigators as a more comprehensive way of measuring the spatial distribution of brain atrophy in MCI and AD, by evaluating images region by region instead of making a priori assumptions about specific ROIs. A variety of VBM-type methods exist (Ashburner and Friston, 2000;Chung et al., 2001;Davatzikos et al., 2001;Davatzikos et al., 1996...

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“…Thus, in agreement with clinical observations that place MCI between normal cognitive aging and AD based on atrophy severity, MCI likewise appears to be intermediate between normal aging and AD. [37][38][39] Progressive brain atrophy has been documented in MCI subjects who have declined (and even in those who have remained stable), providing evidence for a neurodegenerative etiology and advancing disease pathology in the latter as well. 40 Whole brain size and ventricular size are powerful predictors of future cognitive decline throughout the spectrum of normal aging to onset of AD.…”

Section: Figmentioning

confidence: 99%

Brain Mapping as a Tool to Study Neurodegeneration

Apostolova

Thompson

2007

Neurotherapeutics

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Summary: Alzheimer's disease (AD) is the most common neurodegenerative disorder for those 65 years or older; it currently affects 4.5 million in the United States and is predicted to rise to 13.2 million by the year 2050. Neuroimaging and brain mapping techniques offer extraordinary power to understand AD, providing spatially detailed information on the extent and trajectory of the disease as it spreads in the living brain. Computational anatomy techniques, applied to large databases of brain MRI scans, reveal the dynamic sequence of cortical and hippocampal changes with disease progression and how these relate to cognitive decline and future clinical outcomes. People who are mildly cognitively impaired, in particular, are at a fivefold increased risk of imminent conversion to dementia, and they show specific structural brain changes that are predictive of imminent disease onset. We review the principles and key findings of several new methods for assessing brain degeneration, including voxel-based morphometry, tensor-based morphometry, cortical thickness mapping, hippocampal atrophy mapping, and automated methods for mapping ventricular anatomy. Applications to AD and other dementias are discussed, with a brief review of related findings in other neurological and neuropsychiatric illnesses, including epilepsy, HIV/AIDS, schizophrenia, and disorders of brain development.

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The contribution of voxel-based morphometry in staging patients with mild cognitive impairment

Abstract: Different patterns of gray matter density distribution in patients with mild cognitive impairment may be associated to different rates of conversion to Alzheimer disease.

Cited by 163 publications

References 25 publications

The cortical signature of prodromal AD

The cortical signature of prodromal AD

Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study

Brain Mapping as a Tool to Study Neurodegeneration

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