Comparison of methods for measuring longitudinal brain change in cognitive impairment and dementia

Characteristics of Cortical Atrophy and White Matter Lesions Between Dementia With Lewy Bodies and Alzheimer's Disease: A Case-Control Study

Introduction: Currently, there is still clinical overlap between dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) patients, which may affect the accuracy of the early diagnosis of DLB. For better diagnosis and prognosis, further exploration of local cortical atrophy patterns and white matter lesions is needed.

Methods: We reviewed the outpatient medical records of 97 DLB patients and 173 AD patients from January 2018 to September 2020 along with 30 matched outpatient clinic normal elderly people. MRI visual rating scales, including medial temporal lobe atrophy (MTA), global cortical atrophy-frontal subscale (GCA-F), posterior atrophy (PA), Fazekas scale, Evans Index and cerebral microbleeds were evaluated and analyzed in DLB and AD patients with different severities and normal controls.

Results: Overall, patients with DLB had higher scores on all visual rating scales than the normal controls. Meanwhile, compared with AD, DLB had lower MTA scores in the mild to moderate groups (both p ≤ 0.001), but the GCA-F and PA scores were similar (all p > 0.05). The Fazekas scores in the moderate to severe DLB group were lower than those in the AD group (p = 0.024 and p = 0.027, respectively). In addition, the diagnostic performance and sensitivity of multiple imaging indicators for DLB were better than that of MTA alone (the combination of MTA, GCA-F, PA, Fazekas visual rating scales, AUC = 0.756, 95%CI: 0.700–0.813, sensitivity = 0.647, specificity = 0.804 and MTA visual rating scale, AUC = 0.726, 95%CI: 0.667–0.785, sensitivity = 0.497, specificity = 0.876, respectively).

Conclusion: The medial temporal lobe of DLB patients was relatively preserved, the frontal and parietal lobes were similarly atrophied to AD patients, and the white matter hyperintensity was lighter than that in AD patients. Combined multiple visual rating scales may provide a novel idea for the diagnosis of early DLB.

Leisure Activity Variety and Brain Volume Among Community-Dwelling Older Adults: Analysis of the Neuron to Environmental Impact Across Generations Study Data

Background: Recent findings indicate that leisure activity (LA) delays cognitive decline and reduces the risk of dementia. However, the association between LA and brain volume remains unclear. This study aimed to examine the association between LA variety and brain volume with a focus on the hippocampus and gray matter. Methods: Data were obtained from the baseline survey of the Neuron to Environmental Impact across Generations study, which had targeted community-dwelling older adults living in Niigata, Japan. We divided LAs into 10 categories, and counted the number of categories of activities in which the participants engaged. We classified them as follows: 0 (i.e., no activity), 1, 2, or ≥ 3 types. Brain volume was assessed through magnetic resonance imaging, and hippocampal and gray matter volumes were ascertained. Results: The sample size was 482. Multiple linear regression analysis showed that hippocampal and gray matter volumes were significantly greater among participants with ≥ 3 types of LAs than among their no-activity counterparts. Hippocampal volume was significantly greater among those who engaged in one type of LA than among those who engaged in no such activity. Sex-stratified analysis revealed that hippocampal volumes were significantly greater among males who engaged in ≥ 3 types of LAs and one type of LA. However, no such association was found among females. Conclusion: The present findings suggest that engaging in a wide range of LAs is related to hippocampal and gray matter volumes. Furthermore, there was a sex difference in the association between LA variety and brain volume.

Brain structure changes over time in normal and mildly impaired aged persons

Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70–78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a cerebrospinal fluid (CSF) expansion rate of 2.97 ± 0.07 ml/year (0.22 ± 0.04%/year). Hippocampal volume loss rate was higher than the GM and CSF global rates, 0.0114 ± 0.0004 ml/year (0.49 ± 0.04%/year). Regions of greatest GM loss were posterior inferior frontal lobe, medial parietal lobe and dorsal cerebellum. Rates of GM loss and CSF expansion were on the low end of the range of other published values, perhaps due to the relatively good health of the elder volunteers in this study. An additional smaller group of 6 subjects diagnosed with MCI at baseline were followed as well, and comparisons were made with the normal group in terms of both global and regional GM loss and CSF expansion rates. An increased rate of GM loss was found in the hippocampus bilaterally for the MCI group.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Associations among amyloid status, age, and longitudinal regional brain atrophy in cognitively unimpaired older adults

The goal of this study was to compare regional brain atrophy patterns in cognitively unimpaired (CU) older adults with and without brain accumulation of amyloid-β (Aβ) to elucidate contributions of Aβ, age, and other variables to atrophy rates. In 80 CU participants from the Alzheimer's Disease Neuroimaging Initiative, we determined effects of Aβ and age on longitudinal, regional atrophy rates, while accounting for confounding variables including sex, APOE ε4 genotype, white matter lesions, and cerebrospinal fluid total and phosphorylated tau levels. We not only found overlapping patterns of atrophy in Aβ+ versus Aβ- participants but also identified regions where atrophy pattern differed between the 2 groups. Higher Aβ load was associated with increased longitudinal atrophy in the entorhinal cortex, amygdala, and hippocampus, even when accounting for age and other variables. Age was associated with atrophy in insula, fusiform gyrus, and isthmus cingulate, even when accounting for Aβ. We found age by Aβ interactions in the postcentral gyrus and lateral orbitofrontal cortex. These results elucidate the separate and related effects of age, Aβ, and other important variables on longitudinal brain atrophy rates in CU older adults.

The anteroposterior and primary-to-posterior limbic ratios as MRI-derived volumetric markers of Alzheimer's disease

BACKGROUND/AIMS

Alzheimer's disease (AD) shows a characteristic pattern of brain atrophy, with predominant involvement of posterior limbic structures, and relative preservation of rostral limbic and primary cortical regions. We aimed to investigate the diagnostic utility of two gray matter volume ratios based on this pattern, and to develop a fully automated method to calculate them from unprocessed MRI files.

PATIENTS AND METHODS

Cross-sectional study of 118 subjects from the ADNI database, including normal controls and patients with mild cognitive impairment (MCI) and AD. Clinical variables and 3T T1-weighted MRI files were analyzed. Regional gray matter and total intracranial volumes were calculated with a shell script (gm_extractor) based on FSL. Anteroposterior and primary-to-posterior limbic ratios (APL and PPL) were calculated from these values. Diagnostic utility of variables was tested in logistic regression models using Bayesian model averaging for variable selection. External validity was evaluated with bootstrap sampling and a test set of 60 subjects.

RESULTS

gm_extractor showed high test-retest reliability and high concurrent validity with FSL's FIRST. Volumetric measurements agreed with the expected anatomical pattern associated with AD. APL and PPL ratios were significantly different between groups, and were selected instead of hippocampal and entorhinal volumes to differentiate normal from MCI or cognitively impaired (MCI plus AD) subjects.

CONCLUSION

APL and PPL ratios may be useful components of models aimed to differentiate normal subjects from patients with MCI or AD. These values, and other gray matter volumes, may be reliably calculated with gm_extractor.

Variables associated with hippocampal atrophy rate in normal aging and mild cognitive impairment

The goal of this study was to identify factors contributing to hippocampal atrophy rate (HAR) in clinically normal older adults (NC) and participants with mild cognitive impairment (MCI). Longitudinal HAR was measured on T1-weighted magnetic resonance imaging, and the contribution of age, gender, apolipoprotein E (ApoE) ε4 status, intracranial volume, white matter lesions, and β-amyloid (Aβ) levels to HAR was determined using linear regression. Age-related effects of HAR were compared in Aβ positive (Aβ+) and Aβ negative (Aβ-) participants. Age and Aβ levels had independent effects on HAR in NC, whereas gender, ApoE ε4 status, and Aβ levels were associated with HAR in MCI. In multivariable models, Aβ levels were associated with HAR in NC; ApoE ε4 and Aβ levels were associated with HAR in MCI. In MCI, age was a stronger predictor of HAR in Aβ- versus Aβ+ participants. HAR was higher in Aβ+ participants, but most of the HAR was because of factors other than Aβ status. Age-related effects on HAR did not differ between NC versus MCI participants with the same Aβ status. Therefore, we conclude that even when accounting for other covariates, Aβ status, and not age, is a significant predictor of HAR; and that most of the HAR is not accounted for by Aβ status in either NC or MCI.

FMRI activation during executive function predicts response to cognitive behavioral therapy in older, depressed adults

OBJECTIVES

To test our hypothesis that pre-treatment executive function and brain regional activation during executive function would discriminate between responders and non-responders to cognitive behavioral therapy (CBT) in elderly depressed outpatients.

DESIGN

Clinical cohort study.

SETTING

University-affiliated hospital.

PARTICIPANTS

Sixty outpatients (age 59 years and older) completed 12 weeks of CBT between July 2010 and December 2011. Forty-four completed fMRI procedures.

MEASUREMENTS

The main outcome consisted of a conversion from a clinical diagnosis (Mini-International Neuropsychiatric Interview) of depression to no clinical diagnosis of depression or a significant improvement in diagnostic criteria. Brain activation measured by functional magnetic resonance imaging during the Wisconsin Card Sorting task (WCST) was the primary predictor variable.

RESULTS

67% of patients had a positive response to CBT. Decreased activation in the left inferior frontal triangle and right superior frontal gyrus as well as increased activity in the right middle frontal gyrus and left superior frontal gyrus predicted a positive response to CBT. Demographic and neurocognitive measures of WCST performance were not significant predictors of a positive CBT outcome, whereas the measure of WCST-induced activity in the prefrontal cortex was a significant predictor.

CONCLUSIONS

These data are among the first to suggest that measures of prefrontal brain activation during executive functioning predict response to CBT in older adults. Further exploration of the specific underlying processes that these prefrontal cortical regions are engaging that contributes to better CBT outcomes is warranted in larger, randomized studies.

Mild cognitive impairment in adult: A neuropsychological review

Mild cognitive impairment (MCI) is associated with an increased risk of developing dementia. This is clinically relevant overt dementia can be prevented if treatment strategies are devised for MCI. Neuropsychological deficits in this condition are very common and are important clinically for treatment and outcomes. We aimed to review various neuropsychological deficits in MCI. Further, we have presented the current evidence for nosological status, neuroanatomical basis, and clinical outcome of this heterogeneous construct. All published papers on the topic of neuropsychological deficits in MCI on Medline and other databases were reviewed. A wide range of memory and executive function deficits are common in MCI patients. However, several studies are limited by either improper designs or inadequate sample sizes. Several neuropsychological impairments like memory function and executive functions can be diagnosed in MCI. The evidence base for the exact neuroanatomical basis of MCI is not robust yet. However, given the wide range of outcomes, controversies and debates exist regarding the nosological significance of the deficits. Hence, more studies are needed to specifically locate the impairments and further delineate the construct of MCI.

Evolution of hippocampal shapes across the human lifespan

Aberrant hippocampal morphology plays an important role in the pathophysiology of aging. Volumetric analysis of the hippocampus has been performed in aging studies; however, the shape morphometry--which is potentially more informative in terms of related cognition--has yet to be examined. In this paper, we employed an advanced brain mapping technique, large deformation diffeomorphic metric mapping (LDDMM), and a dimensionality reduction approach, locally linear diffeomorphic metric embedding (LLDME), to explore age-related changes in hippocampal shape as delineated from magnetic resonance (MR) images of 302 healthy adults aged from 18 to 94 years. Compared with the hippocampal volumes, the hippocampal shapes clearly showed the nonlinear trajectory of biological aging across the human lifespan, where the variation of hippocampal shapes by age was characterized by a cubic polynomial. By integrating of LDDMM and LLDME, we were also able to illustrate the average hippocampal shapes in each individual decade. In addition, LDDMM and LLDME facilitated the identification of 63 years as a threshold beyond which hippocampal morphological changes were accelerated. Adults over 63 years of age showed the inward-deformation bilaterally in the head of the hippocampi and the left subiculum regardless of hippocampal volume reduction when compared to adults younger than 63. Hence, we demonstrated that the shape of anatomical structures added another dimension of structural morphological quantification beyond the volume in understanding aging.

Mapping Dynamic Changes in Ventricular Volume onto Baseline Cortical Surfaces in Normal Aging, MCI, and Alzheimer's Disease

Ventricular volume (VV) is a powerful global indicator of brain tissue loss on MRI in normal aging and dementia. VV is used by radiologists in clinical practice and has one of the highest obtainable effect sizes for tracking brain change in clinical trials, but it is crucial to relate VV to structural alterations underlying clinical symptoms. Here we identify patterns of thinner cortical gray matter (GM) associated with dynamic changes in lateral VV at 1-year (N=677) and 2-year (N=536) intervals, in the ADNI cohort. People with faster VV loss had thinner baseline cortical GM in temporal, inferior frontal, inferior parietal, and occipital regions (controlling for age, sex, diagnosis). These findings show the patterns of relative cortical atrophy that predict later ventricular enlargement, further validating the use of ventricular segmentations as biomarkers. We may also infer specific patterns of regional cortical degeneration (and perhaps functional changes) that relate to VV expansion.

CSF and brain structural imaging markers of the Alzheimer's pathological cascade

Cerebral spinal fluid (CSF) and structural imaging markers are suggested as biomarkers amended to existing diagnostic criteria of mild cognitive impairment (MCI) and Alzheimer's disease (AD). But there is no clear instruction on which markers should be used at which stage of dementia. This study aimed to first investigate associations of the CSF markers as well as volumes and shapes of the hippocampus and lateral ventricles with MCI and AD at the baseline and secondly apply these baseline markers to predict MCI conversion in a two-year time using the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Our results suggested that the CSF markers, including Aβ42, t-tau, and p-tau, distinguished MCI or AD from NC, while the Aβ42 CSF marker contributed to the differentiation between MCI and AD. The hippocampal shapes performed better than the hippocampal volumes in classifying NC and MCI, NC and AD, as well as MCI and AD. Interestingly, the ventricular volumes were better than the ventricular shapes to distinguish MCI or AD from NC, while the ventricular shapes showed better accuracy than the ventricular volumes in classifying MCI and AD. As the CSF markers and the structural markers are complementary, the combination of them showed great improvements in the classification accuracies of MCI and AD. Moreover, the combination of these markers showed high sensitivity but low specificity for predicting conversion from MCI to AD in two years. Hence, it is feasible to employ a cross-sectional sample to investigate dynamic associations of the CSF and imaging markers with MCI and AD and to predict future MCI conversion. In particular, the volumetric information may be good for the early stage of AD, while morphological shapes should be considered as markers in the prediction of MCI conversion to AD together with the CSF markers.

Functional magnetic resonance imaging in aging and dementia: detection of age-related cognitive changes and prediction of cognitive decline

Functional magnetic resonance imaging (fMRI) allows for dynamic observation of the neural substrates of cognitive processing, which makes it a valuable tool for studying brain changes that may occur with both normal and pathological aging. fMRI studies have revealed that older adults frequently exhibit a greater magnitude and extent activation of the blood-oxygen-level-dependent signal compared to younger adults. This additional activation may reflect compensatory recruitment associated with functional and structural deterioration of neural resources. Increased activation has also been associated with several risk factors for Alzheimer's disease (AD), including the apolipoprotein ε4 allele. Longitudinal studies have also demonstrated that fMRI may have predictive utility in determining which individuals are at the greatest risk of developing cognitive decline. This chapter will review the results of a number of task-activated fMRI studies of older adults, focusing on both healthy aging and neuropathology associated with AD. We also discuss models that account for cognitive aging processes, including the hemispheric asymmetry reduction in older adults (HAROLD) and scaffolding theory of aging and cognition (STAC) models. Finally, we discuss methodological issues commonly associated with fMRI research in older adults.

Functional magnetic resonance imaging of semantic memory as a presymptomatic biomarker of Alzheimer's disease risk

Extensive research efforts have been directed toward strategies for predicting risk of developing Alzheimer's disease (AD) prior to the appearance of observable symptoms. Existing approaches for early detection of AD vary in terms of their efficacy, invasiveness, and ease of implementation. Several non-invasive magnetic resonance imaging strategies have been developed for predicting decline in cognitively healthy older adults. This review will survey a number of studies, beginning with the development of a famous name discrimination task used to identify neural regions that participate in semantic memory retrieval and to test predictions of several key theories of the role of the hippocampus in memory. This task has revealed medial temporal and neocortical contributions to recent and remote memory retrieval, and it has been used to demonstrate compensatory neural recruitment in older adults, apolipoprotein E ε4 carriers, and amnestic mild cognitive impairment patients. Recently, we have also found that the famous name discrimination task provides predictive value for forecasting episodic memory decline among asymptomatic older adults. Other studies investigating the predictive value of semantic memory tasks will also be presented. We suggest several advantages associated with the use of semantic processing tasks, particularly those based on person identification, in comparison to episodic memory tasks to study AD risk. Future directions for research and potential clinical uses of semantic memory paradigms are also discussed. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies

There is consistent evidence that brain volume changes in early and late life. Most longitudinal studies usually only span a few years and include a limited number of participants. In this review, we integrate findings from 56 longitudinal magnetic resonance imaging (MRI) studies on whole brain volume change in healthy individuals. The individual longitudinal MRI studies describe only the development in a limited age range. In total, 2,211 participants were included. Age at first measurement varied between 4 and 88 years of age. The studies included in this review were performed using a large range of methods (e.g., different scanner protocols and different acquisition parameters). We applied a weighted regression analysis to estimate the age dependency of the rate of relative annual brain volume change across studies. The results indicate that whole brain volume changes throughout the life span. A wave of growth occurs during childhood/adolescence, where around 9 years of age a 1% annual brain growth is found which levels off until at age 13 a gradual volume decrease sets in. During young adulthood, between ∼18 and 35 years of age, possibly another wave of growth occurs or at least a period of no brain tissue loss. After age 35 years, a steady volume loss is found of 0.2% per year, which accelerates gradually to an annual brain volume loss of 0.5% at age 60. The brains of people over 60 years of age show a steady volume loss of more than 0.5%. Understanding the mechanisms underlying these plastic brain changes may contribute to distinguishing progressive brain changes in psychiatric and neurological diseases from healthy aging processes. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc.

Age-related changes in the mesial temporal lobe: the parahippocampal white matter region

The perforant pathway originates from cells in the entorhinal cortex and relays sensory information from the neocortex to the hippocampus, a region critical for memory function. Imaging studies have demonstrated structural alterations in the parahippocampal white matter in the region of the perforant pathway in people at risk for developing Alzheimer's disease. It is not clear, however, if changes noted in this region are indicative of pathological aging or are a function of the normal aging process. We compared magnetic resonance imaging (MRI)-derived mesial temporal lobe volumes in 51 healthy older individuals and 40 young participants, with an emphasis on the parahippocampal white matter. Yearly clinical evaluations showed that 9 of the older cohort declined in cognitive function. Parahippocampal white matter, hippocampal, and entorhinal cortex volumes were significantly reduced in healthy older people who remained stable over time compared with young participants. These findings suggest that volume differences in mesial temporal lobe gray and white matter structures may take place as a result of the normative aging process.

Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort

Atrophic changes in early Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI) have been proposed as biomarkers for detection and monitoring. We analyzed magnetic resonance imaging (MRI) atrophy rate from baseline to 1 year in 4 groups of participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI): AD (n = 152), converters from MCI to probable AD (MCI-C, n = 60), stable MCI (MCI-S, n = 261), and healthy controls (HC, n = 200). Scans were analyzed using multiple methods, including voxel-based morphometry (VBM), regions of interest (ROIs), and automated parcellation, permitting comparison of annual percent change (APC) in neurodegeneration markers. Effect sizes and the sample required to detect 25% reduction in atrophy rates were calculated. The influence of APOE genotype on APC was also evaluated. AD patients and converters from MCI to probable AD demonstrated high atrophy APCs across regions compared with minimal change in healthy controls. Stable MCI subjects showed intermediate atrophy rates. APOE genotype was associated with APC in key regions. In sum, APC rates are influenced by APOE genotype, imminent MCI to AD conversion, and AD-related neurodegeneration.

Prediction of cognitive decline in healthy older adults using fMRI

Few studies have examined the extent to which structural and functional MRI, alone and in combination with genetic biomarkers, can predict future cognitive decline in asymptomatic elders. This prospective study evaluated individual and combined contributions of demographic information, genetic risk, hippocampal volume, and fMRI activation for predicting cognitive decline after an 18-month retest interval. Standardized neuropsychological testing, an fMRI semantic memory task (famous name discrimination), and structural MRI (sMRI) were performed on 78 healthy elders (73% female; mean age = 73 years, range = 65 to 88 years). Positive family history of dementia and presence of one or both apolipoprotein E (APOE) ε4 alleles occurred in 51.3% and 33.3% of the sample, respectively. Hippocampal volumes were traced from sMRI scans. At follow-up, all participants underwent a repeat neuropsychological examination. At 18 months, 27 participants (34.6%) declined by at least 1 SD on one of three neuropsychological measures. Using logistic regression, demographic variables (age, years of education, gender) and family history of dementia did not predict future cognitive decline. Greater fMRI activity, absence of an APOE ε4 allele, and larger hippocampal volume were associated with reduced likelihood of cognitive decline. The most effective combination of predictors involved fMRI brain activity and APOE ε4 status. Brain activity measured from task-activated fMRI, in combination with APOE ε4 status, was successful in identifying cognitively intact individuals at greatest risk for developing cognitive decline over a relatively brief time period. These results have implications for enriching prevention clinical trials designed to slow AD progression.

Gray matter atrophy rate as a marker of disease progression in AD

Global gray matter (GM) atrophy rates were quantified from magnetic resonance imaging (MRI) over 6- and 12-month intervals in 37 patients with Alzheimer's disease (AD) and 19 controls using: (1) nonlinear registration and integration of Jacobian values, and (2) segmentation and subtraction of serial GM volumes. Sample sizes required to power treatment trials using global GM atrophy rate as an outcome measure were estimated and compared between the 2 techniques, and to global brain atrophy measures quantified using the boundary shift integral (brain boundary shift integral; BBSI) and structural image evaluation, using normalization, of atrophy (SIENA). Increased GM atrophy rates (approximately 2% per year) were observed in patients compared with controls. Although mean atrophy rates provided by Jacobian integration were smaller than those from segmentation and subtraction of GM volumes, measurement variance was reduced. The number of patients required per treatment arm to detect a 20% reduction in GM atrophy rate over a 12-month follow-up (90% power) was 202 (95% confidence interval [CI], 118–423) using Jacobian integration and 2047 (95% CI 271 to > 10 000) using segmentation and subtraction. Comparable sample sizes for whole brain atrophy were 240 (95% CI, 142–469) using the BBSI and 196 (95% CI, 110–425) using SIENA. Jacobian integration could be useful for measuring GM atrophy rate in Alzheimer's disease as a marker of disease progression and treatment efficacy.

Registration of longitudinal image sequences with implicit template and spatial-temporal heuristics

Accurate measurement of longitudinal changes of anatomical structure is important and challenging in many clinical studies. Also, for identification of disease-affected regions due to the brain disease, it is extremely necessary to register a population data to the common space simultaneously. In this paper, we propose a new method for simultaneous longitudinal and groupwise registration of a set of longitudinal data acquired from multiple subjects. Our goal is to 1) consistently measure the longitudinal changes from a sequence of longitudinal data acquired from the same subject; and 2) jointly align all image data (acquired from all time points of all subjects) to a hidden common space. To achieve these two goals, we first introduce a set of temporal fiber bundles to explore the spatial-temporal behavior of anatomical changes in each longitudinal data of the same subject. Then, a probabilistic model is built upon the hidden state of spatial smoothness and temporal continuity on the fibers. Finally, the transformation fields that connect each time-point image of each subject to the common space are simultaneously estimated by the expectation maximization (EM) approach, via the maximum a posterior (MAP) estimation of probabilistic models. Promising results are obtained to quantitatively measure the longitudinal changes of hippocampus volume, indicating better performance of our method than the conventional pairwise methods.

Age-related differences in regional brain volumes: a comparison of optimized voxel-based morphometry to manual volumetry

Regional manual volumetry is the gold standard of in vivo neuroanatomy, but is labor-intensive, can be imperfectly reliable, and allows for measuring limited number of regions. Voxel-based morphometry (VBM) has perfect repeatability and assesses local structure across the whole brain. However, its anatomic validity is unclear, and with its increasing popularity, a systematic comparison of VBM to manual volumetry is necessary. The few existing comparison studies are limited by small samples, qualitative comparisons, and limited selection and modest reliability of manual measures. Our goal was to overcome those limitations by quantitatively comparing optimized VBM findings with highly reliable multiple regional measures in a large sample (N=200) across a wide agespan (18-81). We report a complex pattern of similarities and differences. Peak values of VBM volume estimates (modulated density) produced stronger age differences and a different spatial distribution from manual measures. However, when we aggregated VBM-derived information across voxels contained in specific anatomically defined regions (masks), the patterns of age differences became more similar, although important discrepancies emerged. Notably, VBM revealed stronger age differences in the regions bordering CSF and white matter areas prone to leukoaraiosis, and VBM was more likely to report nonlinearities in age-volume relationships. In the white matter regions, manual measures showed stronger negative associations with age than the corresponding VBM-based masks. We conclude that VBM provides realistic estimates of age differences in the regional gray matter only when applied to anatomically defined regions, but overestimates effects when individual peaks are interpreted. It may be beneficial to use VBM as a first-pass strategy, followed by manual measurement of anatomically defined regions.

Hippocampal atrophy rates in Alzheimer disease: added value over whole brain volume measures

OBJECTIVE

To investigate the added value of hippocampal atrophy rates over whole brain volume measurements on MRI in patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and controls.

METHODS

We included 64 patients with AD (67 +/- 9 years; F/M 38/26), 44 patients with MCI (71 +/- 6 years; 21/23), and 34 controls (67 +/- 9 years; 16/18). Two MR scans were performed (scan interval: 1.8 +/- 0.7 years; 1.0 T), using a coronal three-dimensional T1-weighted gradient echo sequence. At follow-up, 3 controls and 23 patients with MCI had progressed to AD. Hippocampi were manually delineated at baseline. Hippocampal atrophy rates were calculated using regional, nonlinear fluid registration. Whole brain baseline volumes and atrophy rates were determined using automated segmentation and registration tools.

RESULTS

All MRI measures differed between groups (p < 0.005). For the distinction of MCI from controls, larger effect sizes of hippocampal measures were found compared to whole brain measures. Between MCI and AD, only whole brain atrophy rate differed significantly. Cox proportional hazards models (variables dichotomized by median) showed that within all patients without dementia, hippocampal baseline volume (hazard ratio [HR]: 5.7 [95% confidence interval: 1.5-22.2]), hippocampal atrophy rate (5.2 [1.9-14.3]), and whole brain atrophy rate (2.8 [1.1-7.2]) independently predicted progression to AD; the combination of low hippocampal volume and high atrophy rate yielded a HR of 61.1 (6.1-606.8). Within patients with MCI, only hippocampal baseline volume and atrophy rate predicted progression.

CONCLUSION

Hippocampal measures, especially hippocampal atrophy rate, best discriminate mild cognitive impairment (MCI) from controls. Whole brain atrophy rate discriminates Alzheimer disease (AD) from MCI. Regional measures of hippocampal atrophy are the strongest predictors of progression to AD.

The cortical signature of Alzheimer's disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals

Alzheimer's disease (AD) is associated with neurodegeneration in vulnerable limbic and heteromodal regions of the cerebral cortex, detectable in vivo using magnetic resonance imaging. It is not clear whether abnormalities of cortical anatomy in AD can be reliably measured across different subject samples, how closely they track symptoms, and whether they are detectable prior to symptoms. An exploratory map of cortical thinning in mild AD was used to define regions of interest that were applied in a hypothesis-driven fashion to other subject samples. Results demonstrate a reliably quantifiable in vivo signature of abnormal cortical anatomy in AD, which parallels known regional vulnerability to AD neuropathology. Thinning in vulnerable cortical regions relates to symptom severity even in the earliest stages of clinical symptoms. Furthermore, subtle thinning is present in asymptomatic older controls with brain amyloid binding as detected with amyloid imaging. The reliability and clinical validity of AD-related cortical thinning suggests potential utility as an imaging biomarker. This "disease signature" approach to cortical morphometry, in which disease effects are mapped across the cortical mantle and then used to define ROIs for hypothesis-driven analyses, may provide a powerful methodological framework for studies of neuropsychiatric diseases.

Towards an accurate and robust method based on fuzzy logic principles for the reconstruction and quantification of large volumes from MR and CT images

The authors have previously evaluated a new method of volume reconstruction and quantification from MR images, based on fuzzy logic (FL) principles. The technique is evaluated here for larger and more complex structures by investigating its accuracy and robustness using MR and CT images. Four large (50-71 cm(3)) and complex (e.g. mimicking a prostate) structures were created and imaged on MR and CT scanners, both with increasing slice thickness. Contours were delineated to generate 112 volumes. MR and CT images were processed using the FL method and a "classical" method of reconstruction on research software. In addition, the CT images were also processed on commercial virtual simulation software. Calculated volumes were compared with actual volumes. The mean +/- standard deviation of the relative variations in calculated target volume using the FL method was found to be 4.4%+/-2.8%, whereas with the "classical" method it was 23.7%+/-6% from axial MR images and 23.3%+/-9.8% from CT images. With the "classical" method, the relative variations in calculated volumes rise with increasing slice thickness, and the displayed volumes show deformations in the longitudinal direction. With the FL method, the volume calculation is not sensitive to the slice thickness and so the deformations are minimal. When used with MR images, our FL method of volume reconstruction is accurate and robust with respect to changes in slice thickness. For CT images, the results are encouraging but some work is still needed to improve the accuracy of the FL method.

APOE related hippocampal shape alteration in geriatric depression

Late-onset depression often precedes the onset of dementia associated with the hippocampal degeneration. Using large deformation diffeomorphic metric mapping (LDDMM), we evaluated apolipoprotein E epsilon-4 allele (apoE E4) effects on hippocampal volume and shape in 38 depressed patients without the apoE E4, 14 depressed patients with one apoE E4, and 31 healthy comparison subjects without the apoE E4. The hippocampal volumes were manually assessed. We applied a diffeomorphic template generation procedure for creating the hippocampal templates based on a subset of the population. The LDDMM mappings were used to generate the hippocampal shape of each subject and characterize the surface deformation of each hippocampus relative to the template. Such deformation was modeled as random field characterized by the Laplace-Beltrami basis functions in the template coordinates. Linear regression was used to examine group differences in the hippocampal volume and shape. We found that there were significant hippocampal shape alternations in both depressed groups while the groups of depressed patients and the group of healthy subjects did not differ in the hippocampal volume. The depressed patients with one apoE E4 show more pronounced shape inward-compression in the anterior CA1 than the depressed patients without the apoE E4 when compared with the healthy controls without the apoE E4. Thus, hippocampal shape abnormalities in late-onset depressed patients with one apoE E4 may indicate future conversion of this group to AD at higher risk than depressed patients without the apoE E4.

Rate of entorhinal and hippocampal atrophy in incipient and mild AD: relation to memory function

In the present study, as part of a more extensive longitudinal investigation of the in vivo anatomical markers of early and incipient AD in our laboratory, three groups of elderly participants were followed with yearly clinical evaluations and high resolution MRI scans over a 6-year period (baseline and 5 years of follow-up). At baseline, participants consisted of: (1) 35 old subjects with no cognitive impairment (controls); (2) 33 participants with amnestic mild cognitive impairment (MCI); and (3) 14 patients with very mild AD. 11 participants with amnestic MCI received a diagnosis of AD over the follow-up period and 9 controls declined in cognitive function. T1 weighted MRI scans were acquired using a 3D SPGR pulse sequence. At baseline, both the amnestic MCI and mild AD groups differed from the controls in hippocampal and entorhinal cortex volume, but not from each other. Longitudinal analyses showed that the rate of atrophy of the entorhinal cortex and hippocampus for the stable controls differed significantly from MCI participants who converted to AD and the AD groups. Furthermore, longitudinal decreases in hippocampal and entorhinal volume were related to longitudinal decline in declarative memory performance. These findings suggest that the rate of atrophy of mesial temporal lobe structures can differentiate healthy from pathological aging.

MRI measures of temporoparietal regions show differential rates of atrophy during prodromal AD

BACKGROUND

MRI studies have demonstrated differential rates of atrophy in the entorhinal cortex and hippocampus during the prodromal phase of Alzheimer disease (AD). The current study was designed to determine whether a broader set of temporoparietal regions show differential rates of atrophy during the evolution of AD.

METHODS

Sixteen regions of interest (ROIs) were analyzed on MRI scans obtained at baseline and follow-up in 66 subjects comprising three groups: controls = individuals who were cognitively normal at both baseline and follow-up; nonconverters = subjects with mild cognitive impairment (MCI) at both baseline and follow-up; converters had MCI at baseline but had progressed to AD at follow-up.

RESULTS

Annualized percent change was analyzed with multivariate analysis of variance (MANOVA), covaried for age. The MANOVA demonstrated an effect of group (p = 0.004). Post hoc comparisons demonstrated greater rates of atrophy for converters vs nonconverters for six ROIs: hippocampus, entorhinal cortex, temporal pole, middle temporal gyrus, fusiform gyrus, and inferior temporal gyrus. Converters showed differentially greater rates of atrophy than controls in five of the same ROIs (and inferior parietal lobule). Rates of change in clinical status were correlated with the atrophy rates in these regions. Comparisons between controls and nonconverters demonstrated no differences.

CONCLUSION

These results demonstrate that temporoparietal regions show differential rates of atrophy on MRI during prodromal Alzheimer disease (AD). MRI data correlate with measures of clinical severity and cognitive decline, suggesting the potential of these regions of interest as antemortem markers of prodromal AD.

Ventricular enlargement as a possible measure of Alzheimer's disease progression validated using the Alzheimer's disease neuroimaging initiative database

Ventricular enlargement may be an objective and sensitive measure of neuropathological change associated with mild cognitive impairment (MCI) and Alzheimer's disease (AD), suitable to assess disease progression for multi-centre studies. This study compared (i) ventricular enlargement after six months in subjects with MCI, AD and normal elderly controls (NEC) in a multi-centre study, (ii) volumetric and cognitive changes between Apolipoprotein E genotypes, (iii) ventricular enlargement in subjects who progressed from MCI to AD, and (iv) sample sizes for multi-centre MCI and AD studies based on measures of ventricular enlargement. Three dimensional T(1)-weighted MRI and cognitive measures were acquired from 504 subjects (NEC n = 152, MCI n = 247 and AD n = 105) participating in the multi-centre Alzheimer's Disease Neuroimaging Initiative. Cerebral ventricular volume was quantified at baseline and after six months using semi-automated software. For the primary analysis of ventricle and neurocognitive measures, between group differences were evaluated using an analysis of covariance, and repeated measures t-tests were used for within group comparisons. For secondary analyses, all groups were dichotomized for Apolipoprotein E genotype based on the presence of an epsilon 4 polymorphism. In addition, the MCI group was dichotomized into those individuals who progressed to a clinical diagnosis of AD, and those subjects that remained stable with MCI after six months. Group differences on neurocognitive and ventricle measures were evaluated by independent t-tests. General sample size calculations were computed for all groups derived from ventricle measurements and neurocognitive scores. The AD group had greater ventricular enlargement compared to both subjects with MCI (P = 0.0004) and NEC (P < 0.0001), and subjects with MCI had a greater rate of ventricular enlargement compared to NEC (P = 0.0001). MCI subjects that progressed to clinical AD after six months had greater ventricular enlargement than stable MCI subjects (P = 0.0270). Ventricular enlargement was different between Apolipoprotein E genotypes within the AD group (P = 0.010). The number of subjects required to demonstrate a 20% change in ventricular enlargement was substantially lower than that required to demonstrate a 20% change in cognitive scores. Ventricular enlargement represents a feasible short-term marker of disease progression in subjects with MCI and subjects with AD for multi-centre studies.

Imaging of mild cognitive impairment and early dementia

The concept of mild cognitive impairment (MCI) has been introduced to describe older individuals who cognitively lie between normal ageing and dementia. Nowadays, there is a particular interest in MCI because this syndrome is thought to be a transitional stage to Alzheimer's disease (AD) that may define a window for effective therapeutic interventions. However, not all patients with MCI will go on to develop AD. Imaging offers an extraordinary opportunity to study MCI. We will review key findings of brain imaging studies in MCI, including structural brain changes studied with MRI, white matter changes with diffusion tensor imaging and altered brain activity and blood flow studied with various imaging modalities, such as positron emission tomography, single-photon emission computed tomography and arterial spin labelling MRI, a non-invasive approach to measure cerebral blood flow. The strength and limitations of each modality for diagnosis of MCI, prediction of MCI outcome and assessment of drug efficacy will be discussed.

Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images

The evaluation of atrophy quantification methods based on magnetic resonance imaging have been usually hindered by the lack of realistic gold standard data against which to judge these methods or to help refine them. Recently [Camara, O., Schweiger, M., Scahill, R., Crum, W., Sneller, B., Schnabel, J., Ridgway, G., Cash, D., Hill, D., Fox, N., 2006. Phenomenological model of diffuse global and regional atrophy using finite-element methods. IEEE Trans. Med.l Imaging 25, 1417-1430], we presented a technique in which atrophy is realistically simulated in different tissue compartments or neuroanatomical structures with a phenomenological model. In this study, we have generated a cohort of realistic simulated Alzheimer's disease (AD) images with known amounts of atrophy, mimicking a set of 19 real controls and 27 probable AD subjects, with an improved version of our atrophy simulation methodology. This database was then used to assess the accuracy of several well-known computational anatomy methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of longitudinal atrophy in brain structures using MR images. SIENA and BSI results correlated very well with gold standard data (Pearson coefficient of 0.962 and 0.969 respectively), achieving small mean absolute differences with respect to the gold standard (percentage change from baseline volume): BSI of 0.23%+/-0.26%; SIENA of 0.22%+/-0.28%. Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD-based technique outperformed the fluid one in all evaluated structures (mean absolute differences from the gold standard in percentage change from baseline volume): whole brain, FFD=0.31%, fluid=0.58%; lateral ventricles, FFD=0.79%; fluid=1.45%; left hippocampus, FFD=0.82%; fluid=1.42%; right hippocampus, FFD=0.95%; fluid=1.62%. The largest errors for both local techniques occurred in the sulcal CSF (FFD=2.27%; fluid=3.55%) regions. For large structures such as the whole brain, these mean absolute differences, relative to the applied atrophy, represented similar percentages for the BSI, SIENA and FFD techniques (controls/patients): BSI, 51.99%/16.36%; SIENA, 62.34%/21.59%; FFD, 41.02%/24.95%. For small structures such as the hippocampi, these percentages were larger, especially for controls where errors were approximately equal to the small applied changes (controls/patients): FFD, 92.82%/43.61%. However, these apparently large relative errors have not prevented the global or hippocampal measures from finding significant group separation in our study. The evaluation framework presented here will help in quantifying whether the accuracy of future methodological developments is sufficient for analysing change in smaller or less atrophied local brain regions. Results obtained in our experiments with realistic simulated data confirm previously published estimates of accuracy for both evaluated global techniques. Regarding Jacobian Integration methods, the FFD-based one demonstrated promising results and potential for being used in clinical studies alongside (or in place of) the more common global methods. The generated gold standard data has also allowed us to identify some stages and sets of parameters in the evaluated techniques--the brain extraction step in the global techniques and the number of multi-resolution levels and the stopping criteria in the registration-based methods--that are critical for their accuracy.

A meta-analysis of hippocampal atrophy rates in Alzheimer's disease

Hippocampal atrophy rates are useful in both diagnosing and tracking Alzheimer's disease (AD). However, cohorts and methods used to determine such rates are heterogeneous, leading to differences in reported annualised rates. We performed a meta-analysis of hippocampal atrophy rates in AD patients and matched controls from studies reported in the peer-reviewed literature. Studies reporting longitudinal volume change in hippocampi in AD subjects together with controls were systematically identified and appraised. All authors were contacted either to confirm the results or to provide missing data. Meta-analysis and meta-regression were then performed on this data. Nine studies were included from seven centres, with data from a total of 595 AD and 212 matched controls. Mean (95% CIs) annualised hippocampal atrophy rates were found to be 4.66% (95% CI 3.92, 5.40) for AD subjects and 1.41% (0.52, 2.30) for controls. The difference between AD and control subject in this rate was 3.33% (1.73, 4.94).

Hippocampal atrophy and disconnection in incipient and mild Alzheimer's disease

Quantitative imaging techniques allow the in vivo investigation of age and disease related changes in the brain and their relation to cognitive function. In this chapter we review imaging evidence indicating that the entorhinal cortex and hippocampus show atrophy very early in Alzheimer's disease (AD) and in individuals who are at risk of developing AD compared to age appropriate controls. Furthermore, the extent and rate of atrophy of the entorhinal cortex, a brain region pathologically involved very early in the disease process, can predict who among the elderly will develop AD. Techniques that assess the integrity of white matter further demonstrate that alterations in the parahippocampal white matter in the region that includes the perforant path could partially disconnect the dentate gyrus and other hippocampal subfields from incoming sensory information. Such partial disconnection and degradation in transmission of sensory information in people at risk of AD and in patients with very mild AD could contribute to the memory dysfunction associated with the early stages of the disease.

Spatiotemporal normalization for longitudinal analysis of gray matter atrophy in frontotemporal dementia

We present a unified method, based on symmetric diffeomorphisms, for studying longitudinal neurodegeneration. Our method first uses symmetric diffeomorphic normalization to find a spatiotemporal parameterization of an individual's image time series. The second step involves mapping a representative image or set of images from the time series into an optimal template space. The template mapping is then combined with the intrasubject spatiotemporal map to enable pairwise statistical tests to be performed on a population of normalized time series images. Here, we apply this longitudinal analysis protocol to study the gray matter atrophy patterns induced by frontotemporal dementia (FTD). We sample our normalized spatiotemporal maps at baseline (time zero) and time one year to generate an annualized atrophy map (AAM) that estimates the annual effect of FTD. This spatiotemporal normalization enables us to locate neuroanatomical regions that consistently undergo significant annual gray matter atrophy across the population. We found the majority of annual atrophy to occur in the frontal and temporal lobes in our population of 20 subjects. We also found significant effects in the hippocampus, insula and cingulate gyrus. Our novel results, significant at p < 0.05 after false discovery rate correction, are represented in local template space but also assigned Talairach coordinates and Brodmann and Anatomical Automatic Labeling (AAL) labels. This paper shows the statistical power of symmetric diffeomorphic normalization for performing deformation-based studies of longitudinal atrophy.

Parallel transport in diffeomorphisms distinguishes the time-dependent pattern of hippocampal surface deformation due to healthy aging and the dementia of the Alzheimer's type

Hippocampal surface structure was assessed at twice 2 years apart in 26 nondemented subjects (CDR 0), in 18 subjects with early dementia of Alzheimer type (DAT, CDR 0.5), and in 9 subjects who converted from the nondemented (CDR 0) to the demented (CDR 0.5) state using magnetic resonance (MR) imaging. We used parallel transport in diffeomorphisms under the large deformation diffeomorphic metric mapping framework to translate within-subject deformation of the hippocampal surface as represented in the MR images between the two time points in a global template coordinate system. We then performed hypothesis testing on the longitudinal variation of hippocampal shape in the global template. Both subjects with early DAT and converters showed greater rates of hippocampal deformation across time than nondemented controls within every subfield of the hippocampus. In a random field analysis, inward surface deformation across time occurred in a non-uniform manner across the hippocampal surface in subjects with early DAT relative to the nondemented controls. Also, compared to the controls, the lateral aspect of the left hippocampal tail showed inward surface deformation in the converters. Using surface deformation patterns as features in a linear discriminant analysis, we were able to respectively distinguish converters and patients with early DAT from healthy nondemented controls at classification rates of 0.77 and 0.87, which were obtained in the same training set using the leave-one-out cross validation approach.

Automated measurement of hippocampal atrophy using fluid-registered serial MRI in AD and controls

OBJECTIVE

To assess hippocampal atrophy rates calculated from fluid registration methods.

METHODS

Hippocampi were segmented on baseline and registered-repeat scans of 32 probable Alzheimer disease (AD) subjects and 55 controls. Fluid-based atrophy rates were calculated.

RESULTS

In AD patients, the mean (SD) atrophy rates for manual, fluidly propagated, and Jacobian methods were 5.09 (3.59), 5.34 (3.43), and 3.55 (2.70) (percentage per year). In controls, atrophy rates were 1.31 (2.00), 0.89 (0.75), and 0.56 (1.12) (percentage per year). In AD, fluid propagation and manual rates were similar in means (P = 0.55) and variances (P = 0.71). Jacobian rates were smaller in mean (P = 0.002) and variance (P = 0.026) than in manual rates. In controls, fluid-propagated rates were similar in mean to manual rates (P = 0.12), but less variable (P < 0.0001). Jacobian rates were smaller in mean (P = 0.014) and less variable (P < 0.0001) than in manual rates. Both fluid methods were superior to manual measures in separating AD from controls (P < 0.0001).

CONCLUSIONS

Fluid-based methods may be useful in large serial hippocampal studies.

Structural neuroimaging in the diagnosis of dementia

This article reviews recent use of structural imaging in the diagnosis of dementia and presents evidence-based recommendations approved at the meeting of the Third Canadian Consensus Conference on the Diagnosis and Treatment of Dementia held in Montreal in March, 2006. Although the consensus group concurs that it is possible to specify circumstances in which structural imaging has a role to rule out pathology, it also has a role in ruling in concomitant cerebrovascular disease for patient management.

3D maps from multiple MRI illustrate changing atrophy patterns as subjects progress from mild cognitive impairment to Alzheimer's disease

Mild cognitive impairment (MCI), particularly the amnestic subtype (aMCI), is considered as a transitional stage between normal aging and a diagnosis of clinically probable Alzheimer's disease (AD). The aMCI construct is particularly useful as it provides an opportunity to assess a clinical stage which in most subjects represents prodromal AD. The aim of this study was to assess the progression of cerebral atrophy over multiple serial MRI during the period from aMCI to progression to AD. Thirty-three subjects were selected that fulfilled clinical criteria for aMCI and had three serial MRI scans: the first scan approximately 3 years before the diagnosis of AD, the second scan approximately 1 year before, and the third scan at the time of the diagnosis of AD. A group of 33 healthy controls were age and gender-matched to the study cohort. Voxel-based morphometry (VBM) was used to assess patterns of grey matter atrophy in the aMCI subjects at each time-point compared to the control group. Customized templates and prior probability maps were used to avoid normalization and segmentation bias. The pattern of grey matter loss in the aMCI subject scans that were 3 years before the diagnosis of AD was focused primarily on the medial temporal lobes, including the amygdala, anterior hippocampus and entorhinal cortex, with some additional involvement of the fusiform gyrus, compared to controls. The extent and magnitude of the cerebral atrophy further progressed by the time the subjects were 1 year before the diagnosis of AD. At this point atrophy in the temporal lobes spread to include the middle temporal gyrus, and extended into more posterior regions of the temporal lobe to include the entire extent of the hippocampus. The parietal lobe also started to become involved. By the time the subjects had progressed to a clinical diagnosis of AD the pattern of grey matter atrophy had become still more widespread with more severe involvement of the medial temporal lobes and the temporoparietal association cortices and, for the first time, substantial involvement of the frontal lobes. This pattern of progression fits well with the Braak and Braak neurofibrillary pathological staging scheme in AD. It suggests that the earliest changes occur in the anterior medial temporal lobe and fusiform gyrus, and that these changes occur at least 3 years before progression to the diagnosis of AD. These results also suggest that 3D patterns of grey matter atrophy may help to predict the time to the first diagnosis of AD in subjects with aMCI.

Structural magnetic resonance imaging-derived biomarkers for Alzheimer’s disease

The development and validation of biomarkers for prediction, diagnosis and tracking of progression of Alzheimer’s disease are both increasingly important. As potential pharmaceutical agents are developed for Alzheimer’s disease, their efficacy needs to be assessed. When medications become available, those subjects who may derive most benefit from such treatments need to be selected and their response to treatment monitored. As such, there has been much research into biomarkers in recent years, with many showing promise in all areas of biomarker utility. This review focuses on the potential of structural imaging as a biomarker in Alzheimer’s disease.

Cerebral ventricular changes associated with transitions between normal cognitive function, mild cognitive impairment, and dementia

Expansion of the cerebral ventricles may occur at an accelerated rate in subjects with dementia, but the time course of expansion during transitions between normal cognitive function, mild cognitive impairment (MCI), and dementia is not well understood. Furthermore, the effects of cardiovascular risk factors on rate of ventricular expansion are unclear. We used a fully automated segmentation technique to measure change rate in lateral ventricle-to-brain ratio (VBR) on 145 longitudinal pairs of magnetic resonance images of subjects in the Cardiovascular Health Study Cognition Study from the Pittsburgh Center. A multivariate model analyzed VBR change rate, accounting for dementia statuses at both imaging times (normal, MCI, or dementia), age, sex, education, race, magnetic resonance-defined infarcts, Center for Epidemiology Studies Depression Scale, baseline ventricular volume, and cardiovascular risk factors. VBR change was faster in subjects who were demented or transitioned from MCI to dementia, compared with subjects normal at both images and subjects who transitioned from normal to MCI or dementia. Patients with diabetes had faster VBR change. Ventricular expansion may accelerate late in the progression from normal cognitive function to dementia, and may be modulated by diabetes.

Knowledge-based localization of hippocampus in human brain MRI

We present a novel and efficient method for localization of human brain structures such as hippocampus. Landmark localization is important for segmentation and registration. This method follows a statistical roadmap, consisting of anatomical landmarks, to reach the desired structures. Using a set of desired and undesired landmarks, identified on a training set, we estimate Gaussian models and determine optimal search areas for desired landmarks. The statistical models form a set of rules to evaluate the extracted landmarks during the search procedure. When applied on 900 MR images of 10 epileptic patients, this method demonstrated an overall success rate of 83%.

Improved reliability of hippocampal atrophy rate measurement in mild cognitive impairment using fluid registration

MRI-derived rates of hippocampal atrophy may serve as surrogate markers of disease progression in mild cognitive impairment (MCI). Manual delineation is the gold standard in hippocampal volumetry; however, this technique is time-consuming and subject to errors. We aimed to compare regional non-linear (fluid) registration measurement of hippocampal atrophy rates against manual delineation in MCI. Hippocampi of 18 subjects were manually outlined twice on MRI scan-pairs (interval+/-SD: 2.01+/-0.11 years), and volumes were subtracted to calculate change over time. Following global affine and local rigid registration, regional fluid registration was performed from which atrophy rates were derived from the Jacobian determinants over the hippocampal region. Atrophy rates as derived by fluid registration were computed using both forward (repeat onto baseline) and backward (baseline onto repeat) registration. Reliability for both methods and agreement between methods was assessed. Mean+/-SD hippocampal atrophy rates (%/year) derived by manual delineation were: left: 2.13+/-1.62; right: 2.36+/-1.78 and for regional fluid registration: forward: left: 2.39+/-1.68; right: 2.49+/-1.52 and backward: left: 2.21+/-1.51; right: 2.42+/-1.49. Mean hippocampal atrophy rates did not differ between both methods. Reliability for manual hippocampal volume measurements (cross-sectional) was high (intraclass correlation coefficient (ICC): baseline and follow-up, left and right, >0.99). However, the resulting ICC for manual measurements of hippocampal volume change (longitudinal) was considerably lower (left: 0.798; right: 0.850) compared with regional fluid registration (forward: left: 0.985; right: 0.988 and backward: left: 0.975; right: 0.989). We conclude that regional fluid registration is more reliable than manual delineation in assessing hippocampal atrophy rates, without sacrificing sensitivity to change. This method may be useful to quantify hippocampal volume change, given the reduction in operator time and improved precision.

A knowledge-guided active model method of cortical structure segmentation on pediatric MR images

PURPOSE

To develop an automated method for quantification of cortical structures on pediatric MR images.

MATERIALS AND METHODS

A knowledge-guided active model (KAM) approach was proposed with a novel object function similar to the Gibbs free energy function. Triangular mesh models were transformed to images of a given subject by maximizing entropy, and then actively slithered to boundaries of structures by minimizing enthalpy. Volumetric results and image similarities of 10 different cortical structures segmented by KAM were compared with those traced manually. Furthermore, the segmentation performances of KAM and SPM2, (statistical parametric mapping, a MATLAB software package) were compared.

RESULTS

The averaged volumetric agreements between KAM- and manually-defined structures (both 0.95 for structures in healthy children and children with medulloblastoma) were higher than the volumetric agreement for SPM2 (0.90 and 0.80, respectively). The similarity measurements (kappa) between KAM- and manually-defined structures (0.95 and 0.93, respectively) were higher than those for SPM2 (both 0.86).

CONCLUSION

We have developed a novel automatic algorithm, KAM, for segmentation of cortical structures on MR images of pediatric patients. Our preliminary results indicated that when segmenting cortical structures, KAM was in better agreement with manually-delineated structures than SPM2. KAM can potentially be used to segment cortical structures for conformal radiation therapy planning and for quantitative evaluation of changes in disease or abnormality.

Prediction of Alzheimer's disease in mild cognitive impairment: a prospective study in Taiwan

The relationship between apolipoprotein E (ApoE) and clinical manifestations of mild cognitive impairment (MCI) has not been investigated in non-Caucasian populations. This prospective study was conducted in an ethnic Chinese population to evaluate the correlations of ApoE genotype, cognitive performance, medial temporal structure volumes, and clinical outcome in amnestic MCI. Twenty normal elders, 58 MCI, and 20 mild Alzheimer's disease (AD) patients received neuropsychological, MRI, and ApoE genotype assessments at baseline. Patients with MCI had intermediate cognitive performance and hippocampal volumes between those in normal and AD groups. In each diagnostic group, epsilon4 carriers (E4+) consistently had smaller hippocampal volume than non-carriers (E4-) did. Nineteen MCI subjects (32.7%) converted to AD during the 3-year study period. Compared with MCI non-converters and E4- MCI converters, E4+ MCI converters had the smallest hippocampal volume. However, epsilon4 was not a predictor for AD. Both cognitive performance and hippocampal volume were predictive for progression to AD. However, stepwise Cox regression model integrating both neuropsychological and radiological variables showed that global cognitive performance was the only significant predictor for AD. A poor global cognitive score may be more crucial than a small hippocampal volume in the prediction of AD.

Atrophy rates of the cingulate gyrus and hippocampus in AD and FTLD

This study explores the diagnostic utility of atrophy rates of the cingulate gyrus, its subdivisions and the hippocampus in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). Regions were manually outlined on MR images of a group of pathologically or genetically confirmed patients with AD (n=19), FTLD (n=8) and age-matched controls (n=11). Mean (S.D.) atrophy rates (%year(-1)) in the cingulate in controls, AD and FTLD were -0.3 (1.2), 5.9 (3.5), and 8.6 (4.1), respectively. Hippocampal atrophy rates in controls, AD and FTLD were -0.1 (0.8), 3.4 (2.2), and 5.2 (5.4), respectively. Atrophy rates were significantly higher in the cingulate and hippocampi in AD and FTLD compared with controls (p<0.01). There was evidence of a difference in trends of atrophy in the cingulate (more anterior in FTLD and more posterior in AD) between the disease groups (p=0.03). Cingulate atrophy rates discriminated perfectly between FTLD and controls. Significantly better discrimination between AD and controls was obtained by hippocampal rather than cingulate rates. In conclusion, cingulate atrophy is as significant a feature of AD and FTLD as hippocampal atrophy.