Background

The fornix is the predominant outflow tract of the hippocampus, a brain region known to be affected early in the course of Alzheimer’s disease (AD). The aims of the present study were to: 1) examine the cross-sectional relationship between fornix DTI measurements (fractional anisotropy (FA), and mean (MD), axial (DA) and radial (DR) diffusivities), hippocampal volume, and memory performance, and 2) compare fornix DTI measures to hippocampal volumes as predictors of progression and transition from amnestic mild cognitive impairment (MCI) to AD dementia.

Methods

23 MCI participants with baseline hippocampal volumetry and diffusion tensor imaging received detailed evaluations at baseline, 3, 6, 12 months, and 2.5 years. Six participants converted to AD over the follow-up. Fornix and posterior cingulum DTI measurements and hippocampal volumes were ascertained using manual measures. Random effects models assessed each of the neuroimaging measures as predictors of decline on the MMSE, CDR-Sum of boxes and Memory z-scores; ROC analyses examined the predictive value for conversion to AD.

Results

There was a significant correlation between fornix FA and hippocampal volumes. However, only the fornix measurements (FA, MD, DR, DA) were cross-sectionally correlated with memory z-scores. Both fornix FA and hippocampal volumes were predictive of memory decline. Individually, fornix FA and MD and hippocampal volumes were very good predictors of progression with likelihood ratios>83, and better than 90% accuracy.

Conclusion

Fornix FA both cross-sectionally correlated with and longitudinally predicted memory decline and progression to AD. Manually-drawn fornix ROI shows comparable promise to hippocampal volume as a predictive biomarker of progression and warrants replication in a larger study.

Neuropsychiatric symptoms (NPS) occur frequently in mild cognitive impairment (MCI) and Alzheimer’s dementia (AD). We examined the relationship between NPS and white matter integrity in these conditions. Twenty two individuals with MCI and 23 with mild AD underwent clinical assessments including the Neuropsychiatric Inventory Questionnaire and 3.0 Tesla magnetic resonance scans. Fractional anisotropy (FA) was measured in the following manually-drawn regions of interest (ROI): fornix, cingulum bundle, splenium, and cerebral peduncles (control region). The probability of having NPS by tertile of ROI FA was assessed using logistic regression. Because associations were similar within MCI and AD groups, the two groups were combined. Compared to those in the highest tertile, participants within the lowest anterior cingulum (AC) FA tertile were more likely to exhibit irritability, agitation, dysphoria, apathy, and nighttime behavioral disturbances (p<0.05). After adjusting for MMSE, participants in the lowest vs. highest tertile of AC FA were more likely to report irritability (OR: 7.21, p=0.041). Using DTI, low AC FA was associated with increased odds of irritability in mild AD and MCI participants. Further imaging studies are necessary to elucidate the role of the AC in the pathophysiology of NPS in AD and MCI.

Objective

To determine whether cerebrospinal fluid (CSF) biomarkers for Alzheimer disease fluctuate significantly over time in a cohort of older, mildly symptomatic individuals.

Design

Biomarker validation in a clinical cohort.

Setting

University hospital inpatient unit.

Participants

Ten patients admitted for CSF drainage for diagnostic purposes.

Main Outcome Measures

The CSF levels of Aβ1–40, Aβ1–42, tau, and phosphorylated tau on threonine 181 (p-tau181) were measured every 6 hours for 24 or 36 hours.

Results

The mean coefficient of variation values for each biomarker assessed in our 10 patients were 5.5% (95% CI, 3.8%–10.0%) for Aβ1–42, 12.2% (9.0%–24.2%) for Aβ1–40, 8.2% (5.7%–15.1%) for total tau, and 11.9% (8.5%–23.0%) for p-tau181. These values are only slightly higher than the variability in the assay. In addition, no significant circadian fluctuation in any Alzheimer disease biomarker was observed given the limitations of our sampling frequency.

Conclusion

In a cohort of elderly patients, little fluctuation in the levels of important Alzheimer disease biomarkers in lumbar CSF is seen as a function of time.

This study explores the longitudinal relationship between patient characteristics and use of four drug classes (antihypertensives, antidepressants, antipsychotics, and hormones) that showed significant changes in use rates over time in patients with Alzheimer’s disease (AD). Patient/caregiver-reported prescription medication usage was categorized by drug class for 201 patients from the Predictors Study. Patient characteristics included use of cholinesterase inhibitors and/or memantine, function, cognition, living situation, baseline age, and gender. Assessment interval, year of study entry, and site were controlled for. Before adjusting for covariates, use increased for antihypertensives (47.8% to 62.2%), antipsychotics (3.5% to 27.0%), and antidepressants (32.3% to 40.5%); use of hormones decreased (19.4% to 5.4%). After controlling for patient characteristics, effects of time on the use of antidepressants were no longer significant. Antihypertensive use was associated with poorer functioning, concurrent use of memantine, and older age. Antipsychotic use was associated with poorer functioning and poorer cognition. Antidepressant use was associated with younger age, poorer functioning, and concurrent use of cholinesterase inhibitors and memantine. Hormone use was associated with being female and younger age. Findings suggest accurate modeling of the AD treatment paradigm for certain subgroups of patients should include antihypertensives and antipsychotics in addition to cholinesterase inhibitors and memantine.

The National Institute on Aging and the Alzheimer’s Association charged a workgroup with the task of developing criteria for the symptomatic predementia phase of Alzheimer’s disease (AD), referred to in this article as mild cognitive impairment due to AD. The workgroup developed the following two sets of criteria: (1) core clinical criteria that could be used by healthcare providers without access to advanced imaging techniques or cerebrospinal fluid analysis, and (2) research criteria that could be used in clinical research settings, including clinical trials. The second set of criteria incorporate the use of biomarkers based on imaging and cerebrospinal fluid measures. The final set of criteria for mild cognitive impairment due to AD has four levels of certainty, depending on the presence and nature of the biomarker findings. Considerable work is needed to validate the criteria that use biomarkers and to standardize biomarker analysis for use in community settings.

DTI is one of the most effective MR tools for the investigation of the brain anatomy. In addition to the gray matter, histopathological studies indicate that white matter is also a good target for both the early diagnosis of AD and for monitoring disease progression, which motivates us to use DTI to study AD patients in vivo. There are already a large amount of studies reporting significant differences between AD patients and controls, as well as to predict progression of disease in symptomatic non-demented individuals. Application of these findings in clinical practice remains to be demonstrated.

Background

The Clinical Dementia Rating (CDR) and CDR-Sum-of-Boxes (CDR-SB) can be utilized to grade mild but clinically important cognitive symptoms. However, sensitive clinical interview formats are lengthy.

Objective

To develop a brief instrument for obtaining CDR scores, and to assess its reliability and cross-sectional validity.

Methods

Using legacy data from expanded interviews conducted among 347 community-dwelling, older adults in a longitudinal study, we identified 60 questions about cognitive functioning in daily life–out of a possible 131– using clinical judgment, inter-item correlations, and principal components analysis. Items were selected in one cohort (n=147), and a computer algorithm for generating CDR scores was developed in this same cohort and re-run in a replication cohort (n=200) to evaluate how well the 60 items retained information from the original 131. Then, short interviews based on the 60 items were administered to 50 consecutively-recruited elders, with no or mild cognitive symptoms, at an Alzheimer Disease Research Center. CDR scores based on short interviews were compared with those from independent long interviews.

Results

In the replication cohort, agreement between short and long CDR interviews ranged from κ =0.65–0.79, with κ =0.76 for Memory; κ =0.77 for global CDR; ICC (intra-class correlation coefficient) for CDR-SB=0.89. In the cross-sectional validation, short interview scores were slightly lower than those from long interviews, but good agreement was observed: κ ≥ 0.70 for global CDR and Memory; ICC for CDR-SB=0.73.

Conclusions

The SIST-M is a brief, reliable and sensitive instrument for obtaining CDR scores in persons with symptoms along the spectrum of mild cognitive change.

This study examined in detail patterns of cholinesterase inhibitors (ChEIs) and memantine use and explored the relationship between patient characteristics and such use. Patients with probable Alzheimer disease AD (n = 201) were recruited from the Predictors Study in 3 academic AD centers and followed from early disease stages for up to 6 years. Random effects logistic regressions were used to examine effects of patient characteristics on ChEIs/memantine use over time. Independent variables included measures of function, cognition, comorbidities, the presence of extrapyramidal signs, psychotic symptoms, age, sex, and patient’s living situation at each interval. Control variables included assessment interval, year of study entry, and site. During a 6-year study period, rate of ChEIs use decreased (80.6% to 73.0%) whereas memantine use increased (2.0% to 45.9%). Random effects logistic regression analyses showed that ChEI use was associated with better function, no psychotic symptoms, and younger age. Memantine use was associated with better function, poorer cognition, living at home, later assessment interval, and later year of study entry. Results suggest that high rate of ChEI use and increasing memantine use over time are consistent with current practice guidelines of initiation of ChEIs in mild-to-moderate AD patients and initiation of memantine in moderate-to-severe patients.

Objectives

To examine the effect of specific “CSF profiles” on the rate of cognitive decline, disease progression, and risk of conversion to Alzheimer's disease (AD) dementia in patients with amnestic mild cognitive impairment (MCI).

Design

Total tau (t-tau), tau phosphorylated at threonine 181 (p-tau181), and β-amyloid 1-42 peptide (Aβ42) were immunoassayed in CSF samples obtained from MCI patients enrolled in the Alzheimer's Disease Neuroimaging Initiative. Patients were then stratified by “CSF profiles”: (1) normal t-tau and Aβ42 levels (i.e., normal–t-tauAβ42), (2) normal t-tau but abnormal Aβ42 (i.e., abnormal–Aβ42), (3) abnormal t-tau but normal Aβ42 (i.e., abnormal–t-tau), and (4) abnormal t-tau and Aβ42 (i.e., abnormal–t-tauAβ42).

Setting

Fifty-eight sites in the US and Canada.

Participants

One hundred ninety-five MCI patients.

Main Outcome Measures

A composite cognitive measure, the CDR-Sum of Boxes, and conversion to AD.

Results

MCI patients with a CSF profile of abnormal–Aβ42 or abnormal–t-tauAβ42 experienced a faster rate of decline on the composite cognitive measure and the CDR-Sum of Boxes compared to those with normal–t-tauAβ42. They also had a greater risk of converting to AD relative to the normal–t-tauAβ42 group. In contrast, those with a CSF profile of abnormal–t-tau did not differ from the normal–t-tauAβ42 group on any outcome. These findings were generally replicated when the sample was reclassified by patterns of p-tau181 and Aβ42 abnormalities.

Conclusions

β-amyloid abnormalities, but not tau alterations, are associated with cognitive deterioration, disease progression, and increased risk of conversion to AD dementia in patients with MCI. Patients with abnormal levels of Aβ42 may be prime targets for drug treatment and clinical trials in MCI.

The ability to form associations between previously unrelated items of information, such as names and faces, is an essential aspect of episodic memory function. The neural substrate that determines success vs. failure in learning these associations remains to be elucidated. Using event-related functional MRI during the encoding of novel face-name associations, we found that successfully remembered face-name pairs showed significantly greater activation in the anterior hippocampal formation bilaterally and left inferior prefrontal cortex, compared to pairs that were forgotten. Functional connectivity analyses revealed significant correlated activity between the right and left hippocampus and neocortical regions during successful, but not attempted, encoding. These findings suggest that anterior regions of the hippocampal formation, in particular, are crucial for successful associative encoding and that the degree of coordination between hippocampal and neocortical activity may predict the likelihood of subsequent memory.

Most estimates of the cost of informal caregiving in patients with Alzheimer’s disease (AD) remain cross-sectional. Longitudinal estimates of informal caregiving hours and costs are less frequent and are from assessments covering only short periods of time. The objectives of this study were to estimate long-term trajectories of the use and cost of informal caregiving for patients with AD and the effects of patient characteristics on the use and cost of informal caregiving. The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers in the United States (n = 170). Generalized linear mixed models were used to estimate the effects of patient characteristics on use and cost of informal caregiving. Patients’ clinical characteristics included cognitive status (Mini-Mental State Examination), functional capacity (Blessed Dementia Rating Scale (BDRS)), comorbidities, psychotic symptoms, behavioral problems, depressive symptoms, and extrapyramidal signs. Results show that rates of informal care use and caregiving hours (and costs) increased substantially over time but were related differently to patients’ characteristics. Use of informal care was significantly associated with worse cognition, worse function, and higher comorbidities. Conditional on receiving informal care, informal caregiving hours (and costs) were mainly associated with worse function. Each additional point on the BDRS increased informal caregiving costs 5.4%. Average annual informal cost was estimated at $25,381 per patient, increasing from $20,589 at baseline to $43,030 in Year 4.

Arterial spin labeling (ASL) MRI is becoming a popular method for measuring perfusion due to its ability of generating perfusion maps non-invasively. This allows for frequent repeat scanning, which is especially useful for follow-up studies. However, limited information is available regarding the reliability and reproducibility of ASL perfusion measurements. Here, the reliability and reproducibility of pulsed ASL (PASL) was investigated in an elderly population to determine the variation in perfusion among cognitively normal individuals in different brain structures. Intra-class correlation coefficients (ICC) and within-subject variation coefficients (wsCV) were used to estimate reliability and reproducibility over a period of one year. Twelve cognitively normal subjects (75.5±5.3 years old, six male and six female) were scanned four times (at 0, 3, 6 and 12 months). No significant difference in cerebral blood flow (CBF) was found over this period. CBF values ranged from 46–53 ml/100g/min in the medial frontal gyrus (MFG) and from 40–44 ml/100g/min over all gray matter regions in the superior part of the brain. Data obtained from the first two scans were processed by two readers and showed high reliability (ICC>0.97) and reproducibility (wsCV <6%). However, over the total period of one year, reliability reduced to a moderate level (ICC = 0.63–0.74) with wsCVs of gray matter, left MFG, right MFG of13.5%, 12.3% , and 15.4%, respectively. In conclusion, measurement of CBF with pulsed ASL provided good agreement between inter-raters. A moderate level of reliability was obtained over a one-year period, which was attributed to variance in slice positioning and coregistration. As such pulsed ASL has the potential to be used for CBF comparison in longitudinal studies.

There is widespread evidence that memory deteriorates with aging, however the exact mechanisms that underlie these changes are not well understood. Given the growing size of the aging population, there is an imperative to study age-related neurocognitive changes in order to better parse healthy from pathological aging. Using a behavioral paradigm that taxes pattern separation (the ability to differentiate novel yet similar information from previously learned information and thus avoid interference), we investigated age-related neural changes in the human hippocampus using high-resolution (1.5 mm isotropic) BOLD fMRI. Recent evidence from animal studies suggests that hyperactivity in the CA3 region of the hippocampus may underlie behavioral deficits in pattern separation in aged rats. Here, we report evidence that is consistent with findings from the animal studies. We found a behavioral impairment in pattern separation in a sample of healthy older adults compared to young controls. We also found a related increase in CA3/dentate gyrus activity levels during an fMRI contrast that stresses pattern separation abilities. In a detailed analysis of behavior, we also found that the pattern of impairment was consistent with the predictions of the animal model, where larger changes in the input (greater dissimilarity) were required in order for elderly adults to successfully encode new information as distinct from previously learned information. These findings are also consistent with recent fMRI and behavioral reports in healthy aging, and further suggest that a specific functional deficit in the CA3/dentate network contributes to memory difficulties with aging.

Background

A blood-based biomarker of Alzheimer disease (AD) would be superior to CSF and neuroimaging measures in terms of cost, invasiveness and feasibility for repeated measures. We previously reported blood ceramides varied in relation to timing of memory impairment in a population-based study. The present objective was to examine whether plasma ceramides varied by AD severity in a well-characterized clinic sample and were associated with cognitive decline and hippocampal volume loss over one year.

Methods

Participants included 25 normal controls (NC), 17 amnestic Mild Cognitive Impairment (MCI), and 21 early probable AD. A thorough neuropsychological battery and neuroimaging with hippocampal volume determination were conducted at baseline and one year later. Plasma ceramides were assayed at baseline using HPLC-coupled electrospray ionization tandem mass spectrometry.

Results

While all saturated ceramides were lower in MCI compared to AD at baseline, Ceramides C22:0 and C24:0 were significantly lower in the MCI group compared to both NC and AD groups (p<0.01). Ceramide levels did not differ (p>0.05) in AD versus NC. There were no cross-sectional associations between ceramides C22:0 and C24:0 and either cognitive performance or hippocampal volume among any group. However, among the MCI group, higher baseline ceramide C22:0 and C24:0 levels were predictive of cognitive decline and hippocampal volume loss one year later.

Conclusion

Results suggest that very long-chain plasma ceramides C22:0 and C24:0 are altered in MCI and predict memory loss and right hippocampal volume loss among subjects with MCI. These plasma ceramides may be early indicators of AD progression.

Background: Alterations of the gray and white matter have been identified in Alzheimer’s disease (AD) by structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). However, whether the combination of these modalities could increase the diagnostic performance is unknown. Methods: Participants included 19 AD patients, 22 amnestic mild cognitive impairment (aMCI) patients, and 22 cognitively normal elderly (NC). The aMCI group was further divided into an “aMCI-converter” group (converted to AD dementia within 3 years), and an “aMCI-stable” group who did not convert in this time period. A T1-weighted image, a T2 map, and a DTI of each participant were normalized, and voxel-based comparisons between AD and NC groups were performed. Regions-of-interest, which defined the areas with significant differences between AD and NC, were created for each modality and named “disease-specific spatial filters” (DSF). Linear discriminant analysis was used to optimize the combination of multiple MRI measurements extracted by DSF to effectively differentiate AD from NC. The resultant DSF and the discriminant function were applied to the aMCI group to investigate the power to differentiate the aMCI-converters from the aMCI-stable patients. Results: The multi-modal approach with AD-specific filters led to a predictive model with an area under the receiver operating characteristic curve (AUC) of 0.93, in differentiating aMCI-converters from aMCI-stable patients. This AUC was better than that of a single-contrast-based approach, such as T1-based morphometry or diffusion anisotropy analysis. Conclusion: The multi-modal approach has the potential to increase the value of MRI in predicting conversion from aMCI to AD.

Functional magnetic resonance imaging (fMRI) studies have observed hyperactivity in the hippocampal region in individuals with Mild Cognitive Impairment (MCI). However, the actual source of such hyperactivity is not well understood. Studies of aged rats observed similar hyperactive signals in the CA3 region of the hippocampus that correlated with spatial memory deficits and, in particular, with their ability to represent novel environments as being distinct from familiar ones (pattern separation). In this study, we tested the hypothesis that patients with amnestic MCI (aMCI) have deficits in pattern separation, along with hyperactive fMRI BOLD activity in the CA3 region of the hippocampus. We used high-resolution fMRI during a continuous recognition task designed to emphasize pattern separation. We conducted hippocampal subfield-level region of interest analyses to test for dysfunctional activity in aMCI patients. We found that patients showed impaired performance on trials that taxed their pattern separation abilities. We also observed hyperactive BOLD signals in the CA3/dentate and hypoactive signals in the entorhinal cortex during the separation condition. In a high-resolution morphometric analysis of hippocampal subfields, aMCI patients also had smaller CA3/dentate and CA1 volumes (no difference in the subiculum). The CA3/dentate region bilaterally also exhibited the largest shape deformations in aMCI patients, suggesting that this locus is affected early in the course of the disease. These findings suggest that structural and functional changes in the CA3/dentate region of the hippocampus contribute to the deficits in episodic memory that are observed in patients with aMCI. The functional hyperactivity may be evidence for a dysfunctional encoding mechanism, consistent with the predictions of computational models of hippocampal learning.

Background

Delusions and hallucinations are common in Alzheimer disease (AD) and there are conflicting reports regarding their ability to predict cognitive decline, functional decline, and institutionalization. According to all previous literature, they are not associated with mortality.

Objective

To examine whether the presence of delusions or hallucinations has predictive value for important outcomes in AD.

Design, Setting, and Participants

A total of 456 patients with AD at early stages (mean Folstein Mini-Mental State Examination [MMSE] score of 21 of 30 at entry) were recruited and followed up semiannually for up to 14 years (mean, 4.5 years) in 5 university-based AD centers in the United States and Europe. Using the Columbia University Scale for Psychopathology in AD (administered every 6 months, for a total of 3266 visit-assessments, average of 7.2 per patient), the presence of delusions and hallucinations was extracted and examined as time-dependent predictors in Cox models. The models controlled for cohort effect, recruitment center, informant status, sex, age, education, a comorbidity index, baseline cognitive and baseline functional performance, behavioral symptoms, and use of neuroleptics and cholinesterase inhibitors.

Main Outcome Measures

Cognitive (Columbia MMSE score of ≤20/57 [approximate Folstein MMSE score of ≤10/30]), functional (Blessed Dementia Rating Scale [parts I and II] score of ≥10), institutionalization equivalent index, and death.

Results

During the full course of follow-up, 38% of patients reached the cognitive, 41% the functional, 54% the institutionalization, and 49% the mortality end point. Delusions were noted for 34% of patients at baseline and 70% at any evaluation. Their presence was associated with increased risk for cognitive (risk ratio [RR], 1.50; 95% confidence interval [CI], 1.07-2.08) and functional decline (RR, 1.41; 95% CI, 1.02-1.94). Hallucinations were present in 7% of patients at initial visit and in 33% at any visit. Their presence was associated with increased risk for cognitive decline (RR, 1.62; 95% CI, 1.06-2.47), functional decline (RR, 2.25; 95% CI, 1.54-2.27), institutionalization (RR, 1.60; 95% CI, 1.13-2.28), and death (RR, 1.49; 95% CI, 1.03-2.14).

Conclusions

Delusions and hallucinations are very common in AD and predict cognitive and functional decline. Presence of hallucinations is also associated with institutionalization and mortality.

The posteromedial cortices and other regions of the “default network” are particularly vulnerable to the pathology of Alzheimer disease (AD). In this study, we performed fMRI to investigate whether the presence of apolipoprotein E (APOE) ε4 allele and degree of memory impairment were associated with dysfunction of these brain regions. Seventy-five elderly subjects ranging from cognitively normal to mild AD, divided into ε4 carriers and non-carriers, underwent fMRI during a memory encoding task. Across all subjects, posteromedial and ventral anterior cingulate cortices (key components of the default network) as well as right middle and inferior prefrontal regions demonstrated reduced task-induced deactivation in the ε4 carriers relative to non-carriers. Even among cognitively normal subjects, ε4 carriers demonstrated reduced posteromedial deactivation compared to non-carriers, in the same regions which demonstrated failure of deactivation in AD patients. Greater failure of posteromedial deactivation was related to worse memory performance (delayed recall) across all subjects and within the range of cognitively normal subjects. In summary, the posteromedial cortical fMRI response pattern is modulated both by the presence of APOE ε4 and episodic memory capability. Altered fMRI activity of the posteromedial areas of the brain default network may be an early indicator of risk for AD.

The relationship between engagement in pleasant activities as rated by the patient and as rated by the caregiver from the patient's perspective was examined using structural equation modeling in a sample of patients (N = 277) diagnosed with mild to moderate Alzheimer's disease. The two activity participation ratings were only moderately related to one another. Furthermore, depression was the only significant predictor of the patient-rated activity participation, whereas severity of depression, degree of personality change, level of dependence, and cognition were all significant predictors of caregiver-rated activity participation. These findings suggest that caregivers consider a wider range of variables when evaluating the patient's engagement in activities than does the patient. Predictors of patient-rated activity participation did not differ as a function of age or cognition.

Impairment in executive cognition (EC) is now recognized as relatively common among older persons with mild cognitive impairment (MCI), and may be predictive of the development of dementia. However, both MCI and executive functioning are broad and heterogeneous constructs. The present study sought to determine whether impairments in specific domains of EC are associated with specific subtypes of MCI. 124 MCI patients were divided into four subgroups (amnestic versus nonamnestic, and single- versus multiple-domain) based on their performance of widely-used neuropsychological screening tests. These patients and 68 normal elderly were administered 18 clinical and experimental tests of executive function. Principal components analysis suggested two highly reliable EC components, planning/problem-solving and working memory, and a less reliable third component, judgment. Planning/problem-solving and working memory, but not judgment, were impaired among the MCI patients. This was true even among those with Apure amnestic@ MCI, the least impaired group overall. Multiple-domain MCI patients had more severe impairments in planning/problem-solving and working memory than single-domain patients, leading to the supposition that they, not pure amnestic MCIs, are at highest risk of imminent dementia.

Diffusion tensor imaging (DTI) can reveal detailed white matter anatomy and has the potential to detect abnormalities in specific white matter structures. Such detection and quantification are, however, not straightforward. The voxel-based analysis after image normalization is one of the most widely used methods for quantitative image analyses. To apply this approach to DTI, it is important to examine if structures in the white matter are well registered among subjects, which would be highly dependent on employed algorithms for normalization. In this paper, we evaluate the accuracy of normalization of DTI data using a highly elastic transformation algorithm, called large deformation diffeomorphic metric mapping. After simulation-based validation of the algorithm, DTI data from normal subjects were used to measure the registration accuracy. To examine the impact of morphological abnormalities on the accuracy, the algorithm was also tested using data from Alzheimer’s disease (AD) patients with severe brain atrophy. The accuracy level was measured by using manual landmark-based white matter matching and surface-based brain and ventricle matching as gold standard. To improve the accuracy level, cascading and multi-contrast approaches were developed. The accuracy level for the white matter was 1.88 ± 0.55 and 2.19 ± 0.84 mm for the measured locations in the controls and patients, respectively.

The purpose of this paper is to establish single-participant white matter atlases based on diffusion tensor imaging. As one of the applications of the atlas, automated brain segmentation was performed and the accuracy was measured using Large Deformation Diffeomorphic Metric Mapping (LDDMM). High-quality diffusion tensor imaging (DTI) data from a single-participant were B0-distortion-corrected and transformed to the ICBM-152 atlas or to Talairach coordinates. The deep white matter structures, which have been previously well documented and clearly identified by DTI, were manually segmented. The superficial white matter areas beneath the cortex were defined, based on a population-averaged white matter probability map. The white matter was parcellated into 176 regions based on the anatomical labeling in the ICBM-DTI-81 atlas. The automated parcellation was achieved by warping this parcellation map to normal controls and to Alzheimer’s disease patients with severe anatomical atrophy. The parcellation accuracy was measured by a kappa analysis between the automated and manual parcellation at 11 anatomical regions. The kappa values were 0.70 for both normal controls and patients while the inter-rater reproducibility was 0.81 (controls) and 0.82 (patients), suggesting “almost perfect” agreement. A power analysis suggested that the proposed method is suitable for detecting FA and size abnormalities of the white matter in clinical studies.

Automated MRI-derived measurements of in-vivo human brain volumes provide novel insights into normal and abnormal neuroanatomy, but little is known about measurement reliability. Here we assess the impact of image acquisition variables (scan session, MRI sequence, scanner upgrade, vendor and field strengths), Freesurfer segmentation preprocessing variables (image averaging, B1 field inhomogeneity correction) and segmentation analysis variables (probabilistic atlas) on resultant image segmentation volumes from older (n=15, mean age 69.5) and younger (both n=5, mean ages 34 and 36.5) healthy subjects. The variability between hippocampal, thalamic, caudate, putamen, lateral ventricular and total intracranial volume measures across sessions on the same scanner on different days is less than 4.3% for the older group and less than 2.3% for the younger group. Within-scanner measurements are remarkably reliable across scan sessions, being minimally affected by averaging of multiple acquisitions, B1 correction, acquisition sequence (MPRAGE vs. multi-echo-FLASH), major scanner upgrades (Sonata-Avanto, Trio-TrioTIM), and segmentation atlas (MPRAGE or multi-echo-FLASH). Volume measurements across platforms (Siemens Sonata vs. GE Signa) and field strengths (1.5T vs. 3T) result in a volume difference bias but with a comparable variance as that measured within-scanner, implying that multi-site studies may not necessarily require a much larger sample to detect a specific effect. These results suggest that volumes derived from automated segmentation of T1-weighted structural images are reliable measures within the same scanner platform, even after upgrades; however, combining data across platform and across field-strength introduces a bias that should be considered in the design of multi-site studies, such as clinical drug trials. The results derived from the young groups (scanner upgrade effects and B1 inhomogeneity correction effects) should be considered as preliminary and in need for further validation with a larger dataset.

Background

White matter disruption has been suggested as one of anatomical features associated with Alzheimer's disease (AD). Diffusion tensor imaging (DTI), which has been widely used in AD studies, obtains new insights into the white matter structure.

Methods

We introduced surface-based geometric models of the deep white matter tracts extracted from DTI, allowing the characterization of their shape variations relative to an atlas as well as fractional anisotropy (FA) variations on the atlas surface through large deformation diffeomorphic metric mapping (LDDMM). We applied it to assess local shapes and FA variations of twenty-three deep white matter tracts in 13 patients with AD and 19 healthy control subjects.

Results

Our results showed regionally-specific shape abnormalities and FA reduction in the cingulum tract and the sagittal stratum tract in AD, suggesting that disruption in the white matter tracts near the temporal lobe may represent the secondary consequence of the medial temporal lobe pathology in AD. Moreover, the regionally-specific patterns of FA and shape of the white matter tracts were shown to be of sufficient sensitivity to robustly differentiate patients with AD from healthy comparison controls when compared with the mean FA and volumes within the regions of the white matter tracts. Finally, greater FA or deformation abnormalities of the white matter tracts were associated with lower MMSE scores.

Conclusion

The regionally-specific shape and FA patterns could be potential imaging markers for differentiating AD from normal aging.