Prediction of cognitive decline based on hemispheric cortical surface maps of FDDNP PET.

OBJECTIVES: A cross-sectional study to establish whether a subject's cognitive state can be predicted based on regional values obtained from brain cortical maps of FDDNP Distribution Volume Ratio (DVR), which shows the pattern of beta amyloid and neurofibrillary binding, along with those of early summed FDDNP PET images (reflecting the pattern of perfusion) was performed. METHODS: Dynamic FDDNP PET studies were performed in a group of 23 subjects (8 control (NL), 8 Mild Cognitive Impairment (MCI) and 7 Alzheimer's Disease (AD) subjects). FDDNP DVR images were mapped to the MR derived hemispheric cortical surface map warped into a common space. A set of Regions of Interest (ROI) values of FDDNP DVR and early summed FDDNP PET (0-6 min post tracer injection), were thus calculated for each subject which along with the MMSE score were used to construct a linear mathematical model relating ROI values to MMSE. After the MMSE prediction models were developed, the models' predictive ability was tested in a non-overlapping set of 8 additional individuals, whose cognitive status was unknown to the investigators who constructed the predictive models. RESULTS: Among all possible subsets of ROIs, we found that the standard deviation of the predicted MMSE was 1.8 by using only DVR values from medial and lateral temporal and prefrontal regions plus the early summed FDDNP value in the posterior cingulate gyrus. The root mean square prediction error for the eight new subjects was 1.6. CONCLUSION: FDDNP scans reflect progressive neuropathology accumulation and can potentially be used to predict the cognitive state of an individual.

Plaque and tangle imaging and cognition in normal aging and Alzheimer's disease.

Amyloid plaques and tau neurofibrillary tangles, the pathological hallmarks of Alzheimer's disease (AD), begin accumulating in the healthy human brain decades before clinical dementia symptoms can be detected. There is great interest in how this pathology spreads in the living brain and its association with cognitive deterioration. Using MRI-derived cortical surface models and four-dimensional animation techniques, we related cognitive ability to positron emission tomography (PET) signal from 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile ([(18)F]FDDNP), a molecular imaging probe for plaques and tangles. We examined this relationship at each cortical surface point in 23 older adults (10 cognitively intact, 6 with amnestic mild cognitive impairment, 7 with AD). [(18)F]FDDNP-PET signal was highly correlated with cognitive performance, even in cognitively intact subjects. Animations of [(18)F]FDDNP signal growth with decreased cognition across all subjects (http://www.loni.ucla.edu/ approximately thompson/FDDNP/video.html) mirrored the classic Braak and Braak trajectory in lateral temporal, parietal, and frontal cortices. Regions in which cognitive performance was significantly correlated with [(18)F]FDDNP signal include those that deteriorate earliest in AD, suggesting the potential utility of [(18)F]FDDNP for early diagnosis.

Altered hippocampal morphology in unmedicated patients with major depressive illness.

Despite converging evidence that major depressive illness is associated with both memory impairment and hippocampal pathology, findings vary widely across studies and it is not known whether these changes are regionally specific. In the present study we acquired brain MRIs (magnetic resonance images) from 31 unmedicated patients with MDD (major depressive disorder; mean age 39.2+/-11.9 years; 77% female) and 31 demographically comparable controls. Three-dimensional parametric mesh models were created to examine localized alterations of hippocampal morphology. Although global volumes did not differ between groups, statistical mapping results revealed that in MDD patients, more severe depressive symptoms were associated with greater left hippocampal atrophy, particularly in CA1 (cornu ammonis 1) subfields and the subiculum. However, previous treatment with atypical antipsychotics was associated with a trend towards larger left hippocampal volume. Our findings suggest effects of illness severity on hippocampal size, as well as a possible effect of past history of atypical antipsychotic treatment, which may reflect prolonged neuroprotective effects. This possibility awaits confirmation in longitudinal studies.

Genetics of brain fiber architecture and intellectual performance.

The study is the first to analyze genetic and environmental factors that affect brain fiber architecture and its genetic linkage with cognitive function. We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4 Tesla), in 92 identical and fraternal twins. White matter integrity, quantified using fractional anisotropy (FA), was used to fit structural equation models (SEM) at each point in the brain, generating three-dimensional maps of heritability. We visualized the anatomical profile of correlations between white matter integrity and full-scale, verbal, and performance intelligence quotients (FIQ, VIQ, and PIQ). White matter integrity (FA) was under strong genetic control and was highly heritable in bilateral frontal (a(2)=0.55, p=0.04, left; a(2)=0.74, p=0.006, right), bilateral parietal (a(2)=0.85, p<0.001, left; a(2)=0.84, p<0.001, right), and left occipital (a(2)=0.76, p=0.003) lobes, and was correlated with FIQ and PIQ in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, callosal isthmus, and the corona radiata (p=0.04 for FIQ and p=0.01 for PIQ, corrected for multiple comparisons). In a cross-trait mapping approach, common genetic factors mediated the correlation between IQ and white matter integrity, suggesting a common physiological mechanism for both, and common genetic determination. These genetic brain maps reveal heritable aspects of white matter integrity and should expedite the discovery of single-nucleotide polymorphisms affecting fiber connectivity and cognition.

Time-lapse mapping of cortical changes in schizophrenia with different treatments.

Using time-lapse maps, we visualized the dynamics of schizophrenia progression, revealing spreading cortical changes that depend on the type of antipsychotic treatment. Dynamic, 4-dimensional models of disease progression were created from 4 repeated high-resolution brain magnetic resonance imaging scans of 36 first-episode schizophrenia patients (30 men/6 women; mean age: 24.2 +/- 5.1 SD years) randomized to haloperidol (HAL) (n = 15) or olanzapine (OLZ) treatment (n = 21), imaged at baseline, 3, 6, and 12 months (144 scans). Based on surface-based cortical models and point-by-point measures of gray matter volume, we generated time-lapse maps for each treatment. Disease trajectories differed for atypical versus typical neuroleptic drugs. A rapidly advancing parietal-to-frontal deficit trajectory, in HAL-treated patients, mirrored normal cortical maturation but greatly intensified. The disease trajectory advanced even after symptom normalization, involving the frontal cortex within 12 months with typical drug treatment. Areas with fastest tissue loss shifted anteriorly in the first year of psychosis. This trajectory was not seen with OLZ. Whether this association reflects either reduced neurotoxicity or neuroprotection cannot be addressed with neuroimaging; changes may relate to glial rather than neural components. These maps revise current models of schizophrenia progression; due to power limitations, the findings require confirmation in a sample large enough to model group x time interactions.

Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study.

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Three-dimensional brain growth abnormalities in childhood-onset schizophrenia visualized by using tensor-based morphometry.

Earlier studies revealed progressive cortical gray matter (GM) loss in childhood-onset schizophrenia (COS) across both lateral and medial surfaces of the developing brain. Here, we use tensor-based morphometry to visualize white matter (WM) growth abnormalities in COS throughout the brain. Using high-dimensional elastic image registration, we compared 3D maps of local WM growth rates in COS patients and healthy children over a 5-year period, based on analyzing longitudinal brain MRIs from 12 COS patients and 12 healthy controls matched for age, gender, and scan interval. COS patients showed up to 2.2% slower growth rates per year than healthy controls in WM (P = 0.02, all P values corrected). The greatest differences were in the right hemisphere (P = 0.006). This asymmetry was attributable to a right slower than left hemisphere growth rate mapped in COS patients (P = 0.037) but not in healthy controls. WM growth rates reached 2.6% per year in healthy controls (P = 0.0002). COS patients showed only a 1.3% per year trend for growth in the left hemisphere (P = 0.066). In COS, WM growth rates were associated with improvement in the Children's Global Assessment Scale (R = 0.64, P = 0.029). Growth rates were reduced throughout the brain in COS, but this process appeared to progress in a front-to-back (frontal-parietal) fashion, and this effect was not attributable to lower IQ. Growth rates were correlated with functional prognosis and were visualized as detailed 3D maps. Finally, these findings also confirm that the progressive GM deficits seen in schizophrenia are not the result of WM overgrowth.

Mapping cerebellar degeneration in HIV/AIDS.

Progressive brain atrophy in HIV/AIDS is associated with impaired psychomotor performance, perhaps partly reflecting cerebellar degeneration; yet little is known about how HIV/AIDS affects the cerebellum. We visualized the three-dimensional profile of atrophy in 19 HIV-positive patients (age: 42.9+/-8.3 years) versus 15 healthy controls (age: 38.5+/-12.0 years). We localized consistent patterns of subregional atrophy with an image analysis method that automatically deforms each patient's scan, in three dimensions, to match a reference image. Atrophy was greatest in the posterior cerebellar vermis (14.9% deficit) and correlated with depression severity (P=0.009, corrected), but not with dementia, alcohol/substance abuse, CD4+T-cell counts, or viral load. Profound cerebellar deficits in HIV/AIDS (P=0.007, corrected) were associated with depression, suggesting a surrogate disease marker for antiretroviral trials.

3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometry.

Tensor-based morphometry (TBM) creates three-dimensional maps of disease-related differences in brain structure, based on nonlinearly registering brain MRI scans to a common image template. Using two different TBM designs (averaging individual differences versus aligning group average templates), we compared the anatomical distribution of brain atrophy in 40 patients with Alzheimer's disease (AD), 40 healthy elderly controls, and 40 individuals with amnestic mild cognitive impairment (aMCI), a condition conferring increased risk for AD. We created an unbiased geometrical average image template for each of the three groups, which were matched for sex and age (mean age: 76.1 years+/-7.7 SD). We warped each individual brain image (N=120) to the control group average template to create Jacobian maps, which show the local expansion or compression factor at each point in the image, reflecting individual volumetric differences. Statistical maps of group differences revealed widespread medial temporal and limbic atrophy in AD, with a lesser, more restricted distribution in MCI. Atrophy and CSF space expansion both correlated strongly with Mini-Mental State Exam (MMSE) scores and Clinical Dementia Rating (CDR). Using cumulative p-value plots, we investigated how detection sensitivity was influenced by the sample size, the choice of search region (whole brain, temporal lobe, hippocampus), the initial linear registration method (9- versus 12-parameter), and the type of TBM design. In the future, TBM may help to (1) identify factors that resist or accelerate the disease process, and (2) measure disease burden in treatment trials.

Three-dimensional mapping of hippocampal anatomy in adolescents with bipolar disorder.

OBJECTIVE: Early-onset bipolar disorder is thought to be a particularly severe variant of the illness. Continuity with the adult form of illness remains unresolved, but preliminary evidence suggests similar biological underpinnings. Recently, we observed localized hippocampal decreases in unmedicated adults with bipolar disorder that were not detectable with conventional volumetric measures. Using the same three-dimensional mapping methods, we sought to investigate whether a similar pattern exists in adolescents with bipolar disorder. METHOD: High-resolution brain magnetic resonance images were acquired from 16 adolescents meeting DSM-IV criteria for bipolar disorder (mean age 15.5 +/- 3.4 years, 50% female) and 20 demographically matched, typically developing control subjects. Three-dimensional parametric mesh models of the hippocampus were created from manual tracings of the hippocampal formation. RESULTS: Controlling for total brain volume, total hippocampal volume was significantly smaller in adolescent patients with bipolar disorder relative to controls (by 9.2%). Statistical mapping results, confirmed by permutation testing, revealed significant localized deformations in the head and tail of the left hippocampus in adolescents with bipolar disorder, relative to normal controls. In addition, there was a significant positive correlation between hippocampal size and age in patients with bipolar disorder, whereas healthy controls showed an inverse relation. DISCUSSION: Localized hippocampal deficits in adolescent patients with bipolar disorder suggest a possible neural correlate for memory deficits observed in this illness. Moreover, age-related increases in hippocampal size in patients with bipolar disorder, not observed in healthy controls, may reflect abnormal developmental mechanisms in bipolar disorder. This possibility must be confirmed by longitudinal studies.

Three-dimensional mapping of hippocampal anatomy in unmedicated and lithium-treated patients with bipolar disorder.

Declarative memory impairments are common in patients with bipolar illness, suggesting underlying hippocampal pathology. However, hippocampal volume deficits are rarely observed in bipolar disorder. Here we used surface-based anatomic mapping to examine hippocampal anatomy in bipolar patients treated with lithium relative to matched control subjects and unmedicated patients with bipolar disorder. High-resolution brain magnetic resonance images were acquired from 33 patients with bipolar disorder (21 treated with lithium and 12 unmedicated), and 62 demographically matched healthy control subjects. Three-dimensional parametric mesh models were created from manual tracings of the hippocampal formation. Total hippocampal volume was significantly larger in lithium-treated bipolar patients compared with healthy controls (by 10.3%; p=0.001) and unmedicated bipolar patients (by 13.9%; p=0.003). Statistical mapping results, confirmed by permutation testing, revealed localized deficits in the right hippocampus, in regions corresponding primarily to cornu ammonis 1 subfields, in unmedicated bipolar patients, as compared to both normal controls (p=0.01), and in lithium-treated bipolar patients (p=0.03). These findings demonstrate the sensitivity of these anatomic mapping methods for detecting subtle alterations in hippocampal structure in bipolar disorder. The observed reduction in subregions of the hippocampus in unmedicated bipolar patients suggests a possible neural correlate for memory deficits frequently reported in this illness. Moreover, increased hippocampal volume in lithium-treated bipolar patients may reflect postulated neurotrophic effects of this agent, a possibility warranting further study in longitudinal investigations.

Statistical properties of Jacobian maps and the realization of unbiased large-deformation nonlinear image registration.

Maps of local tissue compression or expansion are often computed by comparing magnetic resonance imaging (MRI) scans using nonlinear image registration. The resulting changes are commonly analyzed using tensor-based morphometry to make inferences about anatomical differences, often based on the Jacobian map, which estimates local tissue gain or loss. Here, we provide rigorous mathematical analyses of the Jacobian maps, and use themto motivate a new numerical method to construct unbiased nonlinear image registration. First, we argue that logarithmic transformation is crucial for analyzing Jacobian values representing morphometric differences. We then examine the statistical distributions of log-Jacobian maps by defining the Kullback-Leibler (KL) distance on material density functions arising in continuum-mechanical models. With this framework, unbiased image registration can be constructed by quantifying the symmetric KL-distance between the identity map and the resulting deformation. Implementation details, addressing the proposed unbiased registration as well as the minimization of symmetric image matching functionals, are then discussed and shown to be applicable to other registration methods, such as inverse consistent registration. In the results section, we test the proposed framework, as well as present an illustrative application mapping detailed 3-D brain changes in sequential magnetic resonance imaging scans of a patient diagnosed with semantic dementia. Using permutation tests, we show that the symmetrization of image registration statistically reduces skewness in the log-Jacobian map.

Information-theoretic analysis of brain white matter fiber orientation distribution functions.

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

Longitudinal stability of MRI for mapping brain change using tensor-based morphometry.

Measures of brain change can be computed from sequential MRI scans, providing valuable information on disease progression, e.g., for patient monitoring and drug trials. Tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of tissue growth or atrophy, but its sensitivity depends on the contrast and geometric stability of the images. As part of the Alzheimer's Disease Neuroimaging Initiative (ADNI), 17 normal elderly subjects were scanned twice (at a 2-week interval) with several 3D 1.5 T MRI pulse sequences: high and low flip angle SPGR/FLASH (from which Synthetic T1 images were generated), MP-RAGE, IR-SPGR (N = 10) and MEDIC (N = 7) scans. For each subject and scan type, a 3D deformation map aligned baseline and follow-up scans, computed with a nonlinear, inverse-consistent elastic registration algorithm. Voxelwise statistics, in ICBM stereotaxic space, visualized the profile of mean absolute change and its cross-subject variance; these maps were then compared using permutation testing. Image stability depended on: (1) the pulse sequence; (2) the transmit/receive coil type (birdcage versus phased array); (3) spatial distortion corrections (using MEDIC sequence information); (4) B1-field intensity inhomogeneity correction (using N3). SPGR/FLASH images acquired using a birdcage coil had least overall deviation. N3 correction reduced coil type and pulse sequence differences and improved scan reproducibility, except for Synthetic T1 images (which were intrinsically corrected for B1-inhomogeneity). No strong evidence favored B0 correction. Although SPGR/FLASH images showed least deviation here, pulse sequence selection for the ADNI project was based on multiple additional image analyses, to be reported elsewhere.