Dominic Holland

One year brain atrophy evident in healthy aging

An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures, and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60–91 years of age) were followed with repeated MRI, and were compared with 122 patients with mild to moderate Alzheimers disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest. Cortical reductions in the healthy elderly were extensive after only 1 year, especially evident in temporal and prefrontal cortices, where annual decline was ∼0.5%. All subcortical and ventricular regions except caudate nucleus and the fourth ventricle changed significantly over 1 year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.

Alzheimer Disease: Quantitative Structural Neuroimaging for Detection and Prediction of Clinical and Structural Changes in Mild Cognitive Impairment

PURPOSE To use structural magnetic resonance (MR) images to identify a pattern of regional atrophy characteristic of mild Alzheimer disease (AD) and to investigate whether presence of this pattern prospectively can aid prediction of 1-year clinical decline and increased structural loss in mild cognitive impairment (MCI). MATERIALS AND METHODS The study was conducted with institutional review board approval and compliance with HIPAA regulations. Written informed consent was obtained from each participant. High-throughput volumetric segmentation and cortical surface reconstruction methods were applied to MR images from 84 subjects with mild AD, 175 with MCI, and 139 healthy control (HC) subjects. Stepwise linear discriminant analysis was used to identify regions that best can aid discrimination of HC subjects from subjects with AD. A classifier trained on data from HC subjects and those with AD was applied to data from subjects with MCI to determine whether presence of phenotypic AD atrophy at baseline was predictive of clinical decline and structural loss. RESULTS Atrophy in mesial and lateral temporal, isthmus cingulate, and orbitofrontal areas aided discrimination of HC subjects from subjects with AD, with fully cross-validated sensitivity of 83% and specificity of 93%. Subjects with MCI who had phenotypic AD atrophy showed significantly greater 1-year clinical decline and structural loss than those who did not and were more likely to have progression to probable AD (annual progression rate of 29% for subjects with MCI who had AD atrophy vs 8% for those who did not). CONCLUSION Semiautomated, individually specific quantitative MR imaging methods can be used to identify a pattern of regional atrophy in MCI that is predictive of clinical decline. Such information may aid in prediction of patient prognosis and increase the efficiency of clinical trials.

What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimers disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.

Regional rates of neocortical atrophy from normal aging to early Alzheimer disease

Objective: To evaluate the spatial pattern and regional rates of neocortical atrophy from normal aging to early Alzheimer disease (AD). Methods: Longitudinal MRI data were analyzed using high-throughput image analysis procedures for 472 individuals diagnosed as normal, mild cognitive impairment (MCI), or AD. Participants were divided into 4 groups based on Clinical Dementia Rating Sum of Boxes score (CDR-SB). Annual atrophy rates were derived by calculating percent cortical volume loss between baseline and 12-month scans. Repeated-measures analyses of covariance were used to evaluate group differences in atrophy rates across regions as a function of impairment. Planned comparisons were used to evaluate the change in atrophy rates across levels of disease severity. Results: In patients with MCI–CDR-SB 0.5–1, annual atrophy rates were greatest in medial temporal, middle and inferior lateral temporal, inferior parietal, and posterior cingulate. With increased impairment (MCI–CDR-SB 1.5–2.5), atrophy spread to parietal, frontal, and lateral occipital cortex, followed by anterior cingulate cortex. Analysis of regional trajectories revealed increasing rates of atrophy across all neocortical regions with clinical impairment. However, increases in atrophy rates were greater in early disease within medial temporal cortex, whereas increases in atrophy rates were greater at later stages in prefrontal, parietal, posterior temporal, parietal, and cingulate cortex. Conclusions: Atrophy is not uniform across regions, nor does it follow a linear trajectory. Knowledge of the spatial pattern and rate of decline across the spectrum from normal aging to Alzheimer disease can provide valuable information for detecting early disease and monitoring treatment effects at different stages of disease progression.

CSF Biomarkers in Prediction of Cerebral and Clinical Change in Mild Cognitive Impairment and Alzheimer's Disease

Brain atrophy and altered CSF levels of amyloid β (Aβ42) and the microtubule-associated protein tau are potent biomarkers of Alzheimers disease (AD)-related pathology. However, the relationship between CSF biomarkers and brain morphometry is poorly understood. Thus, we addressed the following questions. (1) Can CSF biomarker levels explain the morphometric differences between normal controls (NC) and patients with mild cognitive impairment (MCI) or AD? (2) How are CSF biomarkers related to atrophy across the brain? (3) How closely are CSF biomarkers and morphometry related to clinical change [clinical dementia rating sum of boxes (CDR-sb)]? Three hundred seventy participants (105 NC, 175 MCI, 90 AD) from the Alzheimers Disease Neuroimaging Initiative were studied, of whom 309 were followed for 1 year and 176 for 2 years. Analyses were performed across the entire cortical surface, as well as for 30 cortical and subcortical regions of interest. Results showed that CSF biomarker levels could not account for group differences in brain morphometry at baseline but that CSF biomarker levels showed moderate relationships to longitudinal atrophy rates in numerous brain areas, not restricted to medial temporal structures. Baseline morphometry was at least as predictive of atrophy as were CSF biomarkers. Even MCI patients with levels of Aβ42 comparable with controls and of p-tau lower than controls showed more atrophy than the controls. Morphometry predicted change in CDR-sb better than did CSF biomarkers. These results indicate that morphometric changes in MCI and AD are not secondary to CSF biomarker changes and that the two types of biomarkers yield complementary information.

Brain development and aging: Overlapping and unique patterns of change

Early-life development is characterized by dramatic changes, impacting lifespan function more than changes in any other period. Developmental origins of neurocognitive late-life functions are acknowledged, but detailed longitudinal magnetic resonance imaging studies of brain maturation and direct comparisons with aging are lacking. To these aims, a novel method was used to measure longitudinal volume changes in development (n=85, 8-22 years) and aging (n=142, 60-91 years). Developmental reductions exceeded 1% annually in much of the cortex, more than double to that seen in aging, with a posterior-to-anterior gradient. Cortical reductions were greater than the subcortical during development, while the opposite held in aging. The pattern of lateral cortical changes was similar across development and aging, but the pronounced medial temporal reduction in aging was not precast in development. Converging patterns of change in adolescents and elderly, particularly in the medial prefrontal areas, suggest that late developed cortices are especially vulnerable to atrophy in aging. A key question in future research will be to disentangle the neurobiological underpinnings for the differences and the similarities between brain changes in development and aging.

Brain Changes in Older Adults at Very Low Risk for Alzheimer's Disease

Alzheimers disease (AD) has a slow onset, so it is challenging to distinguish brain changes in healthy elderly persons from incipient AD. One-year brain changes with a distinct frontotemporal pattern have been shown in older adults. However, it is not clear to what extent these changes may have been affected by undetected, early AD. To address this, we estimated 1-year atrophy by magnetic resonance imaging (MRI) in 132 healthy elderly persons who had remained free of diagnosed mild cognitive impairment or AD for at least 3 years. We found significant volumetric reductions throughout the brain. The sample was further divided into low-risk groups based on clinical, biomarker, genetic, or cognitive criteria. Although sample sizes varied, significant reductions were observed in all groups, with rates and topographical distribution of atrophy comparable to that of the full sample. Volume reductions were especially pronounced in the default mode network, closely matching the previously described frontotemporal pattern of changes in healthy aging. Atrophy in the hippocampus predicted change in memory, with no additional default mode network contributions. In conclusion, reductions in regional brain volumes can be detected over the course of 1 year even in older adults who are unlikely to be in a presymptomatic stage of AD.

Automated white-matter tractography using a probabilistic diffusion tensor atlas: Application to temporal lobe epilepsy

Diffusion‐weighted magnetic resonance imaging allows researchers and clinicians to identify individual white matter fiber tracts and map their trajectories. The reliability and interpretability of fiber‐tracking procedures is improved when a priori anatomical information is used as a guide. We have developed an automated method for labeling white matter fiber tracts in individual subjects based on a probabilistic atlas of fiber tract locations and orientations. The probabilistic fiber atlas contains 23 fiber tracts and was constructed by manually identifying fiber tracts in 21 healthy controls and 21 patients with temporal lobe epilepsy (TLE). The manual tract identification method required ∼40 h of manual editing by a trained image analyst using multiple regions of interest to select or exclude streamline fibers. Identification of fiber tracts with the atlas does not require human intervention, but nonetheless benefits from the a priori anatomical information that was used to manually identify the tracts included in the atlas. We applied this method to compare fractional anisotropy—thought to be a measure of white matter integrity—in individual fiber tracts between control subjects and patients with TLE. We found that the atlas‐based and manual fiber selection methods produced a similar pattern of results. However, the between‐group effect sizes using the atlas‐derived fibers were generally as large or larger than those obtained with manually selected fiber tracks. Hum Brain Mapp, 2009.

Amyloid-β–Associated Clinical Decline Occurs Only in the Presence of Elevated P-tau

OBJECTIVE To elucidate the relationship between the 2 hallmark proteins of Alzheimer disease (AD), amyloid-(Aβ) and tau, and clinical decline over time among cognitively normal older individuals. DESIGN A longitudinal cohort of clinically and cognitively normal older individuals assessed with baseline lumbar puncture and longitudinal clinical assessments. SETTING Research centers across the United States and Canada. PATIENTS We examined 107 participants with a Clinical Dementia Rating (CDR) of 0 at baseline examination. MAIN OUTCOME MEASURES Using linear mixed effects models, we investigated the relationship between cerebrospinal fluid (CSF) phospho-tau 181 (p-tau(181p)),CSF Aβ(1-42), and clinical decline as assessed using longitudinal change in global CDR, CDR-Sum of Boxes, and the Alzheimer Disease Assessment Scale-cognitive subscale. RESULTS We found a significant relationship between decreased CSF Aβ(1-42) and longitudinal change in global CDR,CDR-Sum of Boxes, and Alzheimer Disease Assessment Scale-cognitive subscale in individuals with elevated CSFp-tau(181p). In the absence of CSF p-tau(181p), the effect of CSF Aβ(1-42) on longitudinal clinical decline was not significantly different from 0. CONCLUSIONS In cognitively normal older individuals,A-associated clinical decline during a mean of 3 years may occur only in the presence of ongoing downstream neurodegeneration.

Nonlinear registration of longitudinal images and measurement of change in regions of interest

We describe here a method, Quarc, for accurately quantifying structural changes in organs, based on serial MRI scans. The procedure can be used to measure deformations globally or in regions of interest (ROIs), including large-scale changes in the whole organ, and subtle changes in small-scale structures. We validate the method with model studies, and provide an illustrative analysis using the brain. We apply the method to the large, publicly available ADNI database of serial brain scans, and calculate Cohens d effect sizes for several ROIs. Using publicly available derived-data, we directly compare effect sizes from Quarc with those from four existing methods that quantify cerebral structural change. Quarc produced a slightly improved, though not significantly different, whole brain effect size compared with the standard KN-BSI method, but in all other cases it produced significantly larger effect sizes.