David E. Rex

The LONI Pipeline Processing Environment

The analysis of raw data in neuroimaging has become a computationally entrenched process with many intricate steps run on increasingly larger datasets. Many software packages exist that provide either complete analyses or specific steps in an analysis. These packages often possess diverse input and output requirements, utilize different file formats, run in particular environments, and have limited abilities with certain types of data. The combination of these packages to achieve more sensitive and accurate results has become a common tactic in brain mapping studies but requires much work to ensure valid interoperation between programs. The handling, organization, and storage of intermediate data can prove difficult as well. The LONI Pipeline Processing Environment is a simple, efficient, and distributed computing solution to these problems enabling software inclusion from different laboratories in different environments. It is used here to derive a T1-weighted MRI atlas of the human brain from 452 normal young adult subjects with fully automated processing. The LONI Pipeline Processing Environments parallel processing efficiency using an integrated client/server dataflow model was 80.9% when running the atlas generation pipeline from a PC client (Acer TravelMate 340T) on 48 dedicated server processors (Silicon Graphics Inc. Origin 3000). The environment was 97.5% efficient when the same analysis was run on eight dedicated processors.

Gender differences in cortical complexity

Cortical complexity, a measure that quantifies the spatial frequency of gyrification and fissuration of the brain surface, has not been thoroughly characterized with respect to gender differences in the human brain. Using a new three-dimensional (3D) analytic technique with magnetic resonance imaging, we found greater gyrification in women than men in frontal and parietal regions. Increased complexity implies more cortical surface area, which may offset gender differences in brain volume and account for behavioral gender differences.

Gender effects on cortical thickness and the influence of scaling

Using magnetic resonance imaging and well‐validated computational cortical pattern matching methods in a large and well‐matched sample of healthy subjects (n = 60), we analyzed the regional specificity of gender‐related cortical thickness differences across the lateral and medial cortices at submillimeter resolution. To establish the influences of brain size correction on gender effects, comparisons were performed with and without applying affine transformations to scale each image volume to a template. We revealed significantly greater cortical thickness in women compared to men, after correcting for individual differences in brain size, while no significant regional thickness increases were observed in males. The pattern and direction of the results were similar without brain size correction, although effects were less pronounced and a small cortical region in the lateral temporal lobes showed greater thickness in males. Our gender‐specific findings support a dimorphic organization in male and female brains that appears to involve the architecture of the cortical mantle and that manifests as increased thickness in female brains. This sexual dimorphism favoring women, even without correcting for brain size, may have functional significance and possibly account for gender‐specific abilities and/or behavioral differences between sexes. Hum Brain Mapp, 2005.

Quantitative Evaluation of Automated Skull-Stripping Methods Applied to Contemporary and Legacy Images: Effects of Diagnosis, Bias Correction, and Slice Location

Performance of automated methods to isolate brain from nonbrain tissues in magnetic resonance (MR) structural images may be influenced by MR signal inhomogeneities, type of MR image set, regional anatomy, and age and diagnosis of subjects studied. The present study compared the performance of four methods: Brain Extraction Tool (BET; Smith [ 2002 ]: Hum Brain Mapp 17:143–155); 3dIntracranial (Ward [ 1999 ] Milwaukee: Biophysics Research Institute, Medical College of Wisconsin; in AFNI); a Hybrid Watershed algorithm (HWA, Segonne et al. [ 2004 ] Neuroimage 22:1060–1075; in FreeSurfer); and Brain Surface Extractor (BSE, Sandor and Leahy [ 1997 ] IEEE Trans Med Imag 16:41–54; Shattuck et al. [ 2001 ] Neuroimage 13:856–876) to manually stripped images. The methods were applied to uncorrected and bias‐corrected datasets; Legacy and Contemporary T1‐weighted image sets; and four diagnostic groups (depressed, Alzheimers, young and elderly control). To provide a criterion for outcome assessment, two experts manually stripped six sagittal sections for each dataset in locations where brain and nonbrain tissue are difficult to distinguish. Methods were compared on Jaccard similarity coefficients, Hausdorff distances, and an Expectation‐Maximization algorithm. Methods tended to perform better on contemporary datasets; bias correction did not significantly improve method performance. Mesial sections were most difficult for all methods. Although AD image sets were most difficult to strip, HWA and BSE were more robust across diagnostic groups compared with 3dIntracranial and BET. With respect to specificity, BSE tended to perform best across all groups, whereas HWA was more sensitive than other methods. The results of this study may direct users towards a method appropriate to their T1‐weighted datasets and improve the efficiency of processing for large, multisite neuroimaging studies. Hum. Brain Mapping, 2005.

Mapping cortical gray matter in the young adult brain: Effects of gender

Using magnetic resonance imaging and well-validated computational cortical pattern matching methods in a large and well-matched sample of healthy subjects, we analyzed the effects of gender on regional gray matter (GM) concentration across the cortex. To clarify discrepancies in previous reports, we also examined sexual dimorphisms for whole-brain tissue volumes with and without controlling for brain size differences. In addition, we generated spatially detailed maps of average GM distributions and variability across the entire cortex given that these descriptors are not well characterized in the normative literature. After brain size correction, we detected numerous cortical regions showing significantly increased GM concentration in females compared to males, but no regionally increased GM concentration in males. Permutation testing confirmed the statistical significance of these findings. Locally increased concentration of cortical GM in females corroborates findings of larger global GM volumes in females after correcting for individual brain sizes. Larger global volumes of GM, white matter and CSF, however, are observed in males when individual brain volumes are not taken into account. Our results show that gender is a major contributor to regional and global GM differences between individuals, although the nature of these effects depend on whether brain size is taken into account.

A meta-algorithm for brain extraction in MRI

Accurate identification of brain tissue and cerebrospinal fluid (CSF) in a whole-head MRI is a critical first step in many neuroimaging studies. Automating this procedure can eliminate intra- and interrater variance and greatly increase throughput for a labor-intensive step. Many available procedures perform differently across anatomy and under different acquisition protocols. We developed the Brain Extraction Meta-Algorithm (BEMA) to address these concerns. It executes many extraction algorithms and a registration procedure in parallel to combine the results in an intelligent fashion and obtain improved results over any of the individual algorithms. Using an atlas space, BEMA performs a voxelwise analysis of training data to determine the optimal Boolean combination of extraction algorithms to produce the most accurate result for a given voxel. This allows the provided extractors to be used differentially across anatomy, increasing both the accuracy and robustness of the procedure. We tested BEMA using modified forms of BrainSuites Brain Surface Extractor (BSE), FSLs Brain Extraction Tool (BET), AFNIs 3dIntracranial, and FreeSurfers MRI Watershed as well as FSLs FLIRT for the registration procedure. Training was performed on T1-weighted scans of 136 subjects from five separate data sets with different acquisition parameters on separate scanners. Testing was performed on 135 separate subjects from the same data sets. BEMA outperformed the individual algorithms, as well as interrater results from a subset of the scans, when compared for the mean Dice coefficient, a rating of the similarity of output masks to the manually defined gold standards.

Comparing gray matter loss profiles between dementia with Lewy bodies and Alzheimer's disease using cortical pattern matching: diagnosis and gender effects.

We used magnetic resonance imaging (MRI) and cortical pattern matching to map differences in cortical gray matter deficits between Alzheimers disease (AD) and dementia with Lewy bodies (DLB), and explored the possible influence of gender on these patterns. Twenty-nine patients with AD (age 77.9 +/- 5.5), 16 patients with DLB (76.4 +/- 6.7), and 38 controls (75.3 +/- 6.8) were included. Dementia groups were matched for illness severity. Detailed spatial analyses of gray matter were conducted across the entire cerebral cortex by measuring local proportions of gray matter at thousands of homologous cortical surface locations in each subject and between diagnostic groups. To visualize regional changes, statistical differences were mapped at each cortical surface location in 3D. Main effects of diagnosis demonstrated prominent gray matter differences in orbitofrontal and temporal cortices, where AD exhibited the greatest deficits relative to DLB. Main effects of sex showed less gray matter in men within all group comparisons. Exploratory findings for sex by diagnosis interactions suggest greater gray matter loss in the anterior cingulate for men with AD, relative to controls, AD females, and individuals with DLB. Relative preservation of orbitofrontal cortices in addition to temporal structures may contribute to distinguishing DLB from AD. Further investigation of the influence of gender might provide a more comprehensive understanding of the pathophysiological differences underlying the two forms of dementia.

Spatial/temporal correlation of BOLD and optical intrinsic signals in humans

Comparing the BOLD signal with electrophysiological maps and other perfusion‐dependent signals, such as the optical intrinsic signal (OIS), within subjects should provide insight into the etiology of the BOLD signal. Tongue activations were compared in five human subjects using BOLD fMRI, 610‐nm OIS, and the electrocortical stimulation map (ESM). Robust fMRI activations centered on the lateral inferior aspect of the central sulcus and extended into pre‐ and post‐central gyri, adjacent to ESM tongue loci. OIS and fMRI maps colocalized, although optical responses were spatially larger (P < .001 across multiple thresholds) and contained more gyral components. The timecourses of the fMRI and OIS signals were similar, appearing within 2.5 s and peaking 6–8 s after task onset. Although many processes contribute to increased 610‐nm reflectance, optical spectroscopy and fluorescent dye imaging suggest that a significant part of this signal is due to a concomitant decrease in deoxyhemoglobin and increase in oxyhemoglobin concentrations. The spatial/temporal correlation of BOLD and the positive 610‐nm response within subjects suggests that the two signals may share similar etiologies. The OIS/fMRI inconsistencies may be due to cell swelling and light‐scattering contributions to OIS and fMRI sensitivity. This study also demonstrates that fMRI maps do not precisely colocalize with ESM, rather they emphasize changes in adjacent venous/sulcal structures. Magn Reson Med 47:766–776, 2002.

Characterization of optical intrinsic signals and blood volume during cortical spreading depression.

Cortical spreading depression (CSD) was imaged in vivo in a rodent model with optical intrinsic signals (OIS). This is the first study to identify a triphasic OIS response and to characterize the rate and timing of the response. The initial OIS phase had a highly uniform wavefront, which spread at a rate characteristic of CSD, 3.5 mm/min. Later phases were more diffuse and inhomogeneous. Blood volume changes, measured with intravascular fluorescent dye, correlated in time and location with the later phases of OIS reponse. This suggests that the inhomogeneity of the late OIS response may be due to complex residual hemodynamic contributions, as opposed to underlying cortical circuitry.

Lobar distribution of lesion volumes in late-life depression : The Biomedical Informatics Research Network (BIRN)

White matter hyperintense lesions on T2-weighted images are associated with late-life depression. Little work has been carried out examining differences in lesion location between elderly individuals with and without depression. In contrast to previous studies examining total brain white matter lesion volume, this study examined lobar differences in white matter lesion volumes derived from brain magnetic resonance imaging. This study examined 49 subjects with a DSM-IV diagnosis of major depression and 50 comparison subjects without depression. All participants were age 60 years or older. White matter lesion volumes were measured in each hemisphere using a semiautomated segmentation process and localized to lobar regions using a lobar atlas created for this sample using the imaging tools provided by the Biomedical Informatics Research Network (BIRN). The lobar lesion volumes were compared against depression status. After controlling for age and hypertension, subjects with depression exhibited significantly greater total white matter lesion volume in both hemispheres and in both frontal lobes than did control subjects. Although a similar trend was observed in the parietal lobes, the difference did not reach a level of statistical significance. Models of the temporal and occipital lobes were not statistically significant. Older individuals with depression have greater white matter disease than healthy controls, predominantly in the frontal lobes. These changes are thought to disrupt neural circuits involved in mood regulation, thus increasing the risk of developing depression.