Space Utilization: The Functional MRI Facility (FMRIF) currently occupies approximately 4800 sq. ft of space, divided between the scanner bays, control rooms and electronics/machine rooms for 3TA, 3TB, 3TC, 3TD, and 7T MRI scanners located within the NMR center and office space on the second floor above the NMR center in the FMRIF/SFIM suite (approximately 1400 sq ft total, including shared conference space). Staff: The FMRIF staff (currently 14 full time employees) consist of: the facility director, three staff scientists to keep the scanners running, six MRI technologists, an information technology specialist, a programmer, and a program assistant. The functional MRI facility supports the research of over 30 Principal Investigators translating to over 300 researchers overall. Over 70 research protocols are active and making use of FMRIF scanners. Each scanner has scheduled operating hours of 105 hours per week. Since the year 2000 until Sep 2013, a total of 884 publications have made use of the core facility. The total is divided among 586 for NIMH, 223 from NINDS, and 75 from the other institutes). These papers have been cited 60,033 times for a combined h-index of 124. This year, we have continued to increase the overall utility of the fMRI core facility. As we adjust our personnel to accommodate some budget cuts, we continue to increase efficiency and availability of cutting edge fMRI and MRI scanning capability. In particular the quality and depth of our specific collaborations with users has increased. IT accomplishments (mostly from Roark Maccado, Joe Naegele, Souheil Inati, and Sean Marrett): We created a new storage backup storage system for FMRIF and new hardware cluster with virtual-machine architecture which has improved reliability and increased on-line storage capabilities from 40TB to more than 200TB of data storage. We deployed a project management system (Redmine/Chilliproject) used in conjunction with github for project task tracking as well as collaborative science and software development efforts. Redesign of scanner utilization tracking system to use the new imaging archive database Software for automatic generation of periodic spreadsheet reports of scanner utilization in the FMRIF Lastly, we created a new project management system that has greatly improved the ability for FMRIF to collaborate scientifically and to make software efforts more efficient. 7T accomplishments: We continued development/adoption and evaluation of cutting edge pulse sequences for NIH collaborators as we improved resolution for EPI BOLD data acquisition protocols from approximately 1.6-1.8 mm3 to 1.2-1.3mm3 by using sinusoidal EPI readout pulse sequences. We continue to evaluate TSNR tradeoffs with multi-slice excitation pulse at 3T and 7T using development pulse sequences developed at The University of Minnesota. We have implemented a new eye tracking system for 7T using off-the shelf integrated illuminator and camera. In general, we have also improved physiological monitoring system on the Siemens 3T and 7T scanners. Specific Staff Scientist Accomplishments: Souheil Inati: Dr. Inati has continued to be essential for the development of Siemens pulse sequences as well as tools for performing rapid automated image reconstruction, analysis, and storage off-line. He developed a new algorithm for optimal combination of images from multiple receiver coils. This algorithm is being considered for incorporation into the image reconstruction pipelines of several vendors. This is a collaboration with Peter Kellman and Michael Hansen of NHLBI. He has collaborated with Daniel Reich and members of his group in NINDS on a project involving dynamic contrast enhanced imaging of white matter lesions and on high resolution anatomical images of cortical lesions in Multiple Sclerosis. He has continued work on development and validation of denoising methods based on multi-echo EPI. He began a large scale study using multi-echo fmri of task and resting state fmri comparing Autism Spectrum Disorder patients to typically developing normal controls in collaboration with Alex Martin, Steve Gotts, Ziad Saad and Bob Cox of NIMH. Vinai Roopchansingh: Over the last year, Dr. Roopchansinghs primary development efforts have focused on helping Souheil Inati and Joseph Naegele develop the General Electric MRI scanner raw data interface to the ISMRMRD raw data format. We have developed translation layers for two versions of the GE platform (versions 15M4, and DV22_O2 - the two versions of General Electric scanner software operated and supported by the FMRIF) to the ISMRMRD format. He has also developed components for the Gadgetron reconstruction framework to allow production of DICOM images from custom MRI scanner pulse sequences. This allowed data from custom scanner sequences to be integrated into the same workflow as data from vendor-provided sequences. Currently, a custom B0 mapping sequence on both versions of the GE scanner platform can utilize these developments to produce images. In collaboration with Joelle Sarlls, he is now in the final stages of showing the utility of the in-session QA and re-scan for Diffusion Tensor Imaging data acquisition. Data has been collected in matched normal/clinical populations, and data analysis is underway that will show how the ability to immediately re-collect corrupted data improves statistics and inferences that can be drawn from DTI data.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Scientific Cores Intramural Research (ZIC)
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U.S. National Institute of Mental Health
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