Faculty Bibliography

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 T(1)-weighted image, a T(2) 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 T(1)-based morphometry or diffusion anisotropy analysis. CONCLUSION/CONCLUSIONS:The multi-modal approach has the potential to increase the value of MRI in predicting conversion from aMCI to AD.

Tractography based on diffusion tensor imaging (DTI) is widely used to quantitatively analyze the status of the white matter anatomy in a tract-specific manner in many types of diseases. This approach, however, involves subjective judgment in the tract-editing process to extract only the tracts of interest. This process, usually performed by manual delineation of regions of interest, is also time-consuming, and certain tracts, especially the short cortico-cortical association fibers, are difficult to reconstruct. In this paper, we propose an automated approach for reconstruction of a large number of white matter tracts. In this approach, existing anatomical knowledge about tract trajectories (called the Template ROI Set or TRS) were stored in our DTI-based brain atlas with 130 three-dimensional anatomical segmentations, which were warped non-linearly to individual DTI data. We examined the degree of matching with manual results for selected fibers. We established 30 TRSs to reconstruct 30 prominent and previously well-described fibers. In addition, TRSs were developed to delineate 29 short association fibers that were found in all normal subjects examined in this paper (N=20). Probabilistic maps of the 59 tract trajectories were created from the normal subjects and were incorporated into our image analysis tool for automated tract-specific quantification.

Quantification of normal brain maturation is a crucial step in understanding developmental abnormalities in brain anatomy and function. The aim of this study was to develop atlas-based tools for time-dependent quantitative image analysis, and to characterize the anatomical changes that occur from 2years of age to adulthood. We used large deformation diffeomorphic metric mapping to register diffusion tensor images of normal participants into the common coordinates and used a pre-segmented atlas to segment the entire brain into 176 structures. Both voxel- and atlas-based analyses reported a structure that showed distinctive changes in terms of its volume and diffusivity measures. In the white matter, fractional anisotropy (FA) linearly increased with age in logarithmic scale, while diffusivity indices, such as apparent diffusion coefficient (ADC), and axial and radial diffusivity, decreased at a different rate in several regions. The average, variability, and the time course of each measured parameter are incorporated into the atlas, which can be used for automated detection of developmental abnormalities. As a demonstration of future application studies, the brainstem anatomy of cerebral palsy patients was evaluated and the altered anatomy was delineated.

Myeloma bone disease is caused by uncoupling of osteoclastic bone resorption and osteoblastic bone formation. Bidirectional signaling between the cell-surface ligand ephrinB2 and its receptor, EphB4, is involved in the coupling of osteoblastogenesis and osteoclastogenesis and in angiogenesis. EphrinB2 and EphB4 expression in mesenchymal stem cells (MSCs) from myeloma patients and in bone cells in myelomatous bones was lower than in healthy counterparts. Wnt3a induced up-regulation of EphB4 in patient MSCs. Myeloma cells reduced expression of these genes in MSCs, whereas in vivo myeloma cell-conditioned media reduced EphB4 expression in bone. In osteoclast precursors, EphB4-Fc induced ephrinB2 phosphorylation with subsequent inhibition of NFATc1 and differentiation. In MSCs, EphB4-Fc did not induce ephrinB2 phosphorylation, whereas ephrinB2-Fc induced EphB4 phosphorylation and osteogenic differentiation. EphB4-Fc treatment of myelomatous SCID-hu mice inhibited myeloma growth, osteoclastosis, and angiogenesis and stimulated osteoblastogenesis and bone formation, whereas ephrinB2-Fc stimulated angiogenesis, osteoblastogenesis, and bone formation but had no effect on osteoclastogenesis and myeloma growth. These chimeric proteins had similar effects on normal bone. Myeloma cells expressed low to undetectable ephrinB2 and EphB4 and did not respond to the chimeric proteins. The ephrinB2/EphB4 axis is dysregulated in MM, and its activation by EphB4-Fc inhibits myeloma growth and bone disease.

In the human brain, different regions of the cortex communicate via white matter tracts. Investigation of this connectivity is essential for understanding brain function. It has been shown that trajectories of white matter fiber bundles can be estimated based on orientational information that is obtained from diffusion tensor imaging (DTI). By extrapolating this information, cortical regions associated with a specific white matter tract can be estimated. In this study, we created population-averaged cortical maps of brain connectivity for 4 major association fiber tracts, the corticospinal tract (CST), and commissural fibers. It is shown that these 4 association fibers interconnect all 4 lobes of the hemispheres. Cortical regions that were assigned based on association with the CST and the superior longitudinal fasciculus (SLF) agreed with locations of their known (CST: motor) or putative (SLF: language) functions. The proposed approach can potentially be used for quantitative assessment of the effect of white matter abnormalities on associated cortical regions.

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.

Monocyte chemoattractant protein 1 (CCL2) is a recently identified prominent regulator of prostate cancer growth and metastasis. The purpose of this study was to investigate the mechanistic role of CCL2 in prostate cancer growth in bone. The present study found that CCL2 was up-regulated in osteoblasts (3-fold by PC-3 and 2-fold by VCaP conditioned medium) and endothelial cells (2-fold by PC-3 and VCaP conditioned medium). Parathyroid hormone-related protein (PTHrP) treatment of osteoblastic cells up-regulated CCL2 and was blocked by a PTHrP antagonist, suggesting that prostate cancer-derived PTHrP plays an important role in elevation of osteoblast-derived CCL2. CCL2 indirectly increased blood vessel formation in endothelial cells through vascular endothelial growth factor-A, which was up-regulated 2-fold with administration of CCL2 in prostate cancer cells. In vivo, anti-CCL2 treatment suppressed tumor growth in bone. The decreased tumor burden was associated with decreased bone resorption (serum TRAP5b levels were decreased by 50-60% in anti-CCL2-treated animals from VCaP or PC-3 cell osseous lesions) and microvessel density was decreased by 70% in anti-CCL2-treated animals with bone lesions from VCaP cells. These data suggest that a destructive cascade is driven by tumor cell-derived, PTHrP-mediated induction of CCL2, which facilitates tumor growth via enhanced osteoclastic and endothelial cell activity in bone marrow. Taken together, CCL2 mediates the interaction between tumor-derived factors and host-derived chemokines acting in cooperation to promote skeletal metastasis.

Although DTI can provide detailed information about white matter anatomy, it is not yet straightforward enough to quantify the anatomical information it visualizes. In this study, we developed and tested a new tool to perform brain normalization and voxel-based analysis of DTI data. For the normalization part, manually placed landmarks ensured that the visualized white matter tracts were well-registered among the populations. A standard landmark set in ICBM-152 space and an interface to remap them to subject data were integrated in the procedure. After landmark placement, highly elastic non-linear Large Deformation Diffeomorphic Metric Mapping (LDDMM) was driven by the landmarks to normalize the brainstem anatomy of normal subjects. The approach was then applied to delineate brainstem tract abnormalities in patients with left chronic middle cerebral artery (MCA) stroke. The voxel-based comparison between control and patient groups identified abnormalities in the ipsilesional corticospinal tract and contralesional cerebellar peduncles. We believe that this tool is useful for regional brain normalization of patients with severe anatomical alterations, such as stroke, brain tumor, and lobectomy, for whom standard automated normalization tools may not work properly.

Expression of parathyroid hormone-related protein (PTHrP) correlates with prostate cancer skeletal progression; however, the impact of prostate cancer-derived PTHrP on the microenvironment and osteoblastic lesions in skeletal metastasis has not been completely elucidated. In this study, PTHrP overexpressing prostate cancer clones were stably established by transfection of full length rat PTHrP cDNA. Expression and secretion of PTHrP were verified by western blotting and IRMA assay. PTHrP overexpressing prostate cancer cells had higher growth rates in vitro, and generated larger tumors when inoculated subcutaneously into athymic mice. The impact of tumor-derived PTHrP on bone was investigated using a vossicle co-implant model. Histology revealed increased bone mass adjacent to PTHrP overexpressing tumor foci, with increased osteoblastogenesis, osteoclastogenesis and angiogenesis. In vitro analysis demonstrated pro-osteoclastic and pro-osteoblastic effects of PTHrP. PTHrP enhanced proliferation of bone marrow stromal cells and early osteoblast differentiation. PTHrP exerted a pro-angiogenic effect indirectly, as it increased angiogenesis but only in the presence of bone marrow stromal cells. These data suggest PTHrP plays a role in tumorigenesis in prostate cancer, and that PTHrP is a key mediator for communication and interactions between prostate cancer and the bone microenvironment. Prostate cancer-derived PTHrP is actively involved in osteoblastic skeletal progression.

Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.