BIOMEDICAL INFORMATICS RESEARCH NETWORK: FUNCTIONAL IMAGING RESEARCH IN SCHIZOPHRENIA TESTBED S.G. Potkin 1 ; J.A. Turner 1 *; G.G. Brown 2 ; G.H. Glover 5 ; S. Heckers 4 ; D.B. Keator 1 ; J.S. Grethe 3 ; FIRST BIRN 6 1. Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA 2. Psychiatry, 3. BIRN-Coordinating Center, University of California, San Diego, La Jolla, CA, USA 4. Psychiatry, Mass. General Hospital, Charlestown, MA, USA 5. Lucas Center, Stanford University, Stanford, CA, USA 6. Introduction Methods: QA Calibration Methods: Human Calibration Results Effect of subject x day x site Non-human phantom scans are used to (1) perform a one time system check to test a scanner’s geometric accuracy using a specialized cylindrical geometry phantom and (2) perform ongoing quality assurance scans using a spherical agar phantom to verify inter-image scanner stability and drift. The phantoms, protocols, and measures were developed at Stanford; the phantoms were built at UCSD; the measures were made useable across different file formats by UCI. The data obtained from scanning the spherical agar phantom are analyzed to measure the Signal to Noise ratio, the drift and fluctuation over time, and spatial correlations within the images. The imaging data are uploaded to the SRB and shared with all the consortium sites. Analysis occurs on a site by site basis. All sites have access to all the human phantom data and can download and analyze it as they wish. The current goals are to assess the variability within the imaging data and develop methods to counteract it. The preliminary analyses being presented involve per-scan, global measures of 1)Percentage of voxels activated by the task (p <.0001) (P) 2)The amount of head movement in mm (MC) 3)The average percent signal change in all the active voxels (M). These global measures were calculated at MGH on the following sites’ data: UCI (1.5T), UCSD (1.5T), MGH (3T), Minnesota (3T), New Mexico (1.5T), Iowa (1.5T), Duke (1.5T), Duke (4T). Example results from the breathholding task for one subject, collapsed across the two runs. This is a vascular response which activates grey matter throughout the brain. Behavioral data (above, collected at MGH) indicated the subject successfully complied with the breathing instructions. Example EPI images from the same subject at four different sites show the variation in image intensities and distortions. Preliminary analyses Effect of scanner strength Effect of paradigm x site Ongoing calibration development ANOVA design: 2 (breathhold and sensorimotor) x 2 (first two runs of each paradigm) x 2 (day) x 8 (sites) using the 3 dependent measures (P, M, MC). The following significant effects were found: Site x paradigm interaction on P (see figure below) Run x paradigm interaction on MC (not shown) Run effect on MC: The second run showed consistently less head motion than the first run, and there was more of an effect for the breathholding task than the sensorimotor task (not shown); Site effect on P, M, MC (see figure below). The analysis was completed at UCI. ABOUT THE FUNCTIONAL IMAGING RESEARCH IN SCHIZOPHRENIA TESTBED – FIRST BIRN The FIRST BIRN is developing and validating functional magnetic resonance imaging (fMRI) methods to combine data from different sites using a common protocol, for a large-scale multi-center study of schizophrenia. The proposal is crystallized around a high- speed broadband network supporting a federated database, specifically developed for the pooling and sharing of data across sites, to facilitate large-scale hypothesis testing and intelligent data mining to address complex scientific problems. Each center will also conduct its own unique studies on the same patients being studied by the FIRST BIRN consortium, to provide added value. Sites participating in the FIRST BIRN are shown in the image to the left. The advances of the FIRST BIRN federated database will specifically facilitate this combining of site-specific data with the consortium data. This “value added” sharing will enhance the FIRST BIRN’s scientific discovery process. GOALS OF THE FIRST BIRN The FIRST BIRN has two major goals: Technological: development of a distributed network infrastructure that will support the creation of a federated database consisting of large-sample fMRI datasets contributed by the 10 centers. Clinical: Study brain function in schizophrenia with fMRI. We propose to use the technology developed herein to study changes in brain function in the development, progression, and treatment of schizophrenia as assessed by fMRI. We will investigate two domains that have been demonstrated to be dysfunctional in schizophrenia: early auditory sensory processing, and working memory/executive functioning. Collaborative studies will focus initially upon first onset, chronic, and late-onset patients. FIRST BIRN will perform: a. Standardization and calibration of equipment and imaging activation paradigms across sites using mechanical and human phantoms b. Collection of imaging data using the consortium fMRI protocol on populations of persons with schizophrenia at different sites c. Combining of unique imaging data collected with diverse activation methods into the federated database. We present here the initial progress toward the standardization and calibration of equipment and activation paradigms made by the FIRST BIRN over the past year. Left: One of the subjects doing the sensorimotor task in a 1.5T scanner; Right: the same subject and task in a 3T scanner. The stronger field strength shows the expected increase in sensitivity to the BOLD response in the auditory, motor, and visual areas. (Data from Duke and MGH; images from MGH.) The differences between sites in the overall amount of brain which shows an activation to the task, with the same 5 subjects doing the task in each scanner. 1.5T scanners are shown on the left; 3 and 4T scanners on the right. Even within the 1.5T scanners, there are consistent site to site differences in fMRI sensitivity, which need to be accounted for before data can be combined. Example QA results from two different 1.5T scanners at two different sites. Three different measures can independently indicate the functionality of the scanner, detecting drift and increases in noise, as well as malfunction prior to component failure. The collaborative efforts in sharing this data have forced some consistency across the sites, since the evidence regarding each scanner is available to all. Scanner manufacturers are using these data to improve imaging performance. Left: Normalized areas used to compare results across subjects and sites. Right: The average F value in the hand area on day 1 and day 2, at UCI and UCSD, for two different subjects shows a consistent subject x day interaction. A similar pattern was seen in the motor and auditory areas. (Analysis completed at UCSD.) Subject 104 Subject 105 The percent of voxels in the entire brain which showed significant activation (p <.0001) showed a significant interaction between site and the paradigm: While fewer voxels overall were active for the sensorimotor than the breatholding task, the 1.5T scanners were more similar for the sensorimotor task than for the breathholding task. Assess the variability Determine which global measures reflect critical variance components ROI measures: The final calibration might be region-specific Calculate reliability maps (e.g., ICCs) Model-based analysis (e.g., GLM) Bayesian estimates of effects Correlation between the various tasks: Can the results from one task be used to remove variance in the results from another task? Determine correlations between results and QA measures from a given scanner Cognitive tasks were also performed by the human phantoms (results to be presented): Apply the possible calibration/correction methods to results from the cognitive tasks as a test. The development of calibration method is a multi-site effort that is currently ongoing, working with this unique dataset. The second phase of the calibration effort will collect a larger dataset on site-specific subjects, which will be used to test the developed calibration methods. Integration of different methods and measures Example Query of Federated Database PET & fMRI Are chronic, but not first-onset patients, associated with superior temporal gyrus dysfunction? Integrated View Receptor Density ERP Web PubMed, Expasy Wrapper Structure Wrapper Clinical Wrapper Mediator The kind of data the FIRST BIRN will be combining across the country: a) Cortical activations to a thought or perception, from an individual; b) Measures of group differences in activations on a partially-inflated cortical model; c) The macro-circuitry of the brain involved in schizophrenic syndromes; d) The micro-circuitry of the cortical layers; e) Areas with differences in cortical thickness over the brain, between patients and controls; f) Data from other species or studies regarding cell types, locations, receptor densities, etc. a) b) e) f) c) d) Data Integration A user’s query to the federated database requires integrating the different kinds of data shown above. The software architecture of such integration systems consists of a two-part middleware, called the wrapper and the mediator, that are between the information sources and the user. The wrapper converts the data from the respective information source to a form that the mediator can accept and manipulate. The mediator converts a user’s query into smaller sub-queries that are sent to each source, and to integrate the results returned from each source. The integration of the returned data is directly dependent on the ontological/semantic information available. The FIRST BIRN group is actively working to define the ontology describing patient populations needed to share imaging data. 3 or 4T 1.5T Example sensorimotor results from one subject on day 1 (upper) and day 2 (lower) from a single site (UCI), shown overlaid on the subject’s mean image. The primary visual, sensorimotor, and auditory areas are successfully activated, though not identically from day to day. This research was supported by the Functional Imaging Research in Schizophrenia Testbed (FIRST) Biomedical Informatics Research Network (BIRN, which is funded by the National Center for Research Resources at the National Institutes of Health (NIH). Five male right handed subjects traveled to all ten scanning sites over the course of August and July 2003, and were scanned on two separate days doing the same tasks repeatedly. They served as human phantoms, being the same brain doing the same task. The primary tasks used were multiple repetitions or runs of the following: 1)Resting: The subject laid with eyes open, 4.5 minutes; two runs per session. 2)Breathholding: The subject alternated between breathing normally and holding his breath every 15 s, for 4.5 minutes; two runs per session. 3)Sensorimotor task: The subject tapped his fingers and heard tones in time with a 3Hz flashing checkerboard (left), alternating with rest periods every 15 s, for 4.5 minutes; four runs per session. This collection of multiple runs, visits, tasks, and scanners across a consistent set of subjects is a unique fMRI dataset that allows us to assess the relative variability introduced by each of these factors. University of California, Irvine