James R. MacFall

Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data

Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.

Hippocampal volume in geriatric depression

BACKGROUND There is a growing literature on the importance of hippocampal volume in geriatric depression. METHODS We examined hippocampal volume in a group of elderly depressed patients and a group of elderly control subjects (N = 66 geriatric depressed patients and 18 elderly nondepressed control subjects) recruited through Dukes Mental Health Clinical Research Center for the Study of Depression in the Elderly. The subjects received a standardized evaluation, including a magnetic resonance imaging scan of the brain. Patients had unipolar major depression and were free of comorbid major psychiatric illness and neurologic illness. Differences were assessed using t tests and linear regression modeling. RESULTS Accounting for the effects of age, gender, and total brain volume, depressed patients tended to have smaller right hippocampal volume (p =.014) and left hippocampal volume (p =.073). Among depressed patients, age of onset was negatively but not significantly related to right hippocampal volume (p =.052) and to left hippocampal volume (p =.062). We noted that among subjects with either right or left hippocampal volume of 3 mL or less, the vast majority were patients rather than control subjects. CONCLUSIONS These results support a role for hippocampal dysfunction in depression, particularly in late-age onset depression. Longitudinal studies examining both depressive and cognitive outcomes are needed to clarify the relationships between the hippocampus, depression, and dementia.

Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time.

Diffusion tensor imaging (DTI) measures the displacement of water molecules across tissue components, thus providing information regarding the microstructure of cerebral white matter. Fractional anisotropy (FA), the degree to which diffusion is directionally dependent, is typically higher for compact, homogeneous fiber bundles such as the corpus callosum. Previous DTI studies in adults have demonstrated an age-related decline in white matter FA, but whether the relation between FA and behavioral performance varies as a function of age has not been determined. We investigated adult age differences in FA, and age-related changes in the relation between FA and response time (RT), in a visual target-detection task. The results confirmed that, independently of age, FA is higher in the corpus callosum than in other brain regions. We also observed an age-related decline in FA that did not vary significantly across the brain regions. For both age groups, a lower level of integrity of the cerebral white matter (as indexed by FA), in specific brain regions, was associated with slower responses in the visual task. An age-related change in this relation was evident, however, in that the best predictor of RT for younger adults was FA in the splenium of the corpus callosum, whereas for older adults the best predictor was FA in the anterior limb of the internal capsule. This pattern is consistent with measures of the task-related cortical activation obtained from these same individuals and suggests an age-related increase in the attentional control of responses mediated by corticostriatal or corticothalamic circuits.

Parameter estimation and tissue segmentation from multispectral MR images

A statistical method is developed to classify tissue types and to segment the corresponding tissue regions from relaxation time T(1 ), T(2), and proton density P(D) weighted magnetic resonance images. The method assumes that the distribution of image intensities associated with each tissue type can be expressed as a multivariate likelihood function of three weighted signal intensity values (T(1), T(2), P(D)) at each location within that tissue regions. The method further assumes that the underlying tissue regions are piecewise contiguous and can be characterized by a Markov random field prior. In classifying the tissue types, the method models the likelihood of realizing the images as a finite multivariate-mixture function. The class parameters associated with the tissue types (i.e. the weighted intensity means, variances and correlation coefficients of the multivariate function, as well as the number of voxels within regions of the tissue types of are estimated by maximum likelihood. The estimation fits the class parameters to the image data via the expectation-maximization algorithm. The number of classes associated with the tissue types is determined by the information criterion of minimum description length. The method segments the tissue regions, given the estimated class parameters, by maximum a posteriori probability. The prior is constructed by the tissue-region membership of the first- and second-order neighborhood. The method is tested by a few sets of T(1), T(2), and P(D) weighted images of the brain acquired with a 1.5 Tesla whole body scanner. The number of classes and the associated class parameters are automatically estimated. The regions of different brain tissues are satisfactorily segmented.

Dorsolateral prefrontal cortex and anterior cingulate cortex white matter alterations in late-life depression

BACKGROUND The dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) are critical for mood regulation. Alterations in the white matter connections of these regions may impair their role in mood regulation and increase the risk of developing depression. This study used diffusion tensor imaging to examine for white matter microstructural abnormalities of these regions and of central white matter structures in late-life depression. METHODS One hundred six elderly depressed subjects and eighty-four elderly nondepressed subjects underwent clinical assessment and diffusion tensor imaging. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were measured in regions of interest placed in the white matter of the DLPFC, ACC, corpus callosum, and internal capsule. Differences between groups were assessed, controlling for age, sex, and total cerebral volume. RESULTS After controlling for covariates, depressed subjects had significantly lower FA values in white matter of the right ACC, bilateral superior frontal gyri, and left middle frontal gyrus. There were no significant differences in ADC values. CONCLUSIONS Lower FA, representing lower tissue organization, is observed in depressed elders in the DLPFC and right ACC. These findings support the hypothesis that altered connectivity between brain regions contributes to the risk of depression.

Clinical Characteristics of Magnetic Resonance Imaging-Defined Subcortical Ischemic Depression

BACKGROUND There is a substantial body of research supporting the vascular depression hypothesis of late-life depression. To update this hypothesis so it incorporates recent research, we propose that the term subcortical ischemic vascular depression may be a more accurate representation of the disease process. We sought to investigate this diagnosis as a construct by examining differences between depressed subjects with and without magnetic resonance imaging defined subcortical ischemic vascular depression. METHODS This case-control study examined 139 depressed elderly subjects. Demographic data, psychiatric, medical, and family history, depressive symptomatology, and functional impairment were compared between groups dichotomized based on neuroimaging findings. RESULTS Seventy-five (54%) of the subjects met neuroimaging criteria for subcortical ischemic vascular depression. Age was most strongly associated with increased prevalence of subcortical ischemic vascular depression. Lassitude and a history of hypertension were also positively associated with the diagnosis; a family history of mental illness and loss of libido were negatively associated with the diagnosis. CONCLUSIONS These data support that subcortical ischemic vascular depression may be a specific syndrome from other types of late-life depression. Further research is needed to further characterize this disorder, particularly in regards to cognitive function and treatment implications.

Classification of White Matter Lesions on Magnetic Resonance Imaging in Elderly Persons

White matter lesions, commonly seen on MRIs of elderly people, are related to various geriatric disorders, including cerebrovascular diseases, cardiovascular diseases, dementia, and psychiatric disorders. Currently, white matter lesions are divided into periventricular white matter lesions and deep white matter lesions. Although the meaning of these terms varies by study and this dichotomization itself is still in debate, a possible dissimilarity in pathogenic mechanisms between periventricular white matter lesions and deep white matter lesions are providing some clues for understanding pathophysiology of many geriatric syndromes associated with white matter lesions. We have reviewed the distinctions between periventricular white matter lesions and deep white matter lesions in terms of etiology, histopathology, functional correlates, and imaging methodologies. We suggest a new subclassification of white matter lesions that might have better etiological and functional relevance than the current simple dichotomization. The new categories are juxtaventricular, periventricular, deep white, and juxtacortical. This new classification scheme might contribute to reducing the heterogeneity of white matter lesion findings in future research.

In Vivo Monitoring of Tissue Pharmacokinetics of Liposome/Drug Using MRI: Illustration of Targeted Delivery

The purpose of this study was to determine if MnSO4/doxorubicin (DOX) loaded liposomes could be used for in vivo monitoring of liposome concentration distribution and drug release using MRI. In vitro results show that T1 shortening correlates with MnSO4 concentration. Using a temperature‐sensitive liposome formulation, it was found that MnSO4 release significantly shortened T1. This feature, therefore, suggests that content release can also be measured with these MnSO4‐loaded liposomes. The feasibility of monitoring this drug delivery and release‐imaging agent was shown in a murine tumor model. Upon tumor heating, nonthermally sensitive liposomes selectively but heterogeneously accumulated in the tumor region. The thermally sensitive liposomes showed a clear pattern of accumulation at the periphery of the tumor, concordant with the release temperature of this formulation (39–40°C). This liposome contrast agent has potential for use with hyperthermia by providing individualized monitoring of tissue drug concentration distribution during or after treatment. This would allow for: 1) modification of treatment variables to improve the uniformity of drug delivery, and 2) provide a means to select patients most likely to benefit from this liposomal drug treatment. Additionally, the drug‐loading method used for this liposome is applicable to a wide range of drugs, thereby broadening its applicability. The method is also applicable to other liposomal formulations with triggered release mechanisms. Magn Reson Med 51:1153–1162, 2004.

Diffusion Tensor Imaging: Background, Potential, and Utility in Psychiatric Research

Diffusion tensor imaging is a variation of magnetic resonance imaging that measures the diffusion of water in tissues. This can help measure and quantify a tissues orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. It is only beginning to be utilized in psychiatric research. This article reviews the theory behind diffusion tensor imaging, its potential to map fiber tracts in the brain, and its recent use in psychiatric research.

Cortical White Matter Microstructural Abnormalities in Bipolar Disorder

This article reports on preliminary findings describing microstructural abnormalities in the white matter of cortical areas thought to be associated with bipolar disorder. In all, 14 patients with bipolar disorder and 21 nonpsychiatrically ill control subjects underwent MR imaging including a diffusion tensor imaging (DTI) pulse sequence (six directions, b=1000 mm2/s). DTI data were analyzed on a workstation using a program that allowed calculation of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) within the following three white matter fiber tracts bilaterally: the orbital frontal cortex, and the superior and middle frontal gyri. These values were compared across patient groups. The left and right orbital frontal white matter exhibited significantly higher ADC values in bipolar subjects than control subjects on both the left (p=0.028) and right (p=0.011). Microstructural changes in the white matter of the orbital frontal areas as reflected by increased ADC values appear to be associated with bipolar disorder. Further research is needed to better understand the interaction of microstructural changes and bipolar symptoms and whether these changes are specific to bipolar disorder.