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). The FMRIF staff (currently 14 full-time positions) consists of: the facility director, three staff scientists to keep the scanners running, six MRI technologists, an information technology specialist, a programmer, a technical laboratory manager, and an administrative laboratory manger. 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 its inception in 2000 until July 2015, a total of 999 peer-reviewed publications from intramural investigators have used data acquired in the FMRIF core facility. The total is distributed among 672 papers from NIMH, 234 papers from NINDS, and 93 from the other institutes. These papers have been cited a total of 81,899 times for a combined h-index of 141. In other words, 141 papers using the FMRIF have been cited at least 141 times. A full listing of all of these publications is available at this link: https://fmrif.nimh.nih.gov/public/FMRIF_all_Aug2015.xlsx/at_download/file Projects: Multi-echo EPI: An ongoing collaboration with Dr. Bandettini's SFIM has been in the development and implementation of a multi-echo EPI acquisition and analysis pipeline in order to minimize non- blood oxygen level dependent (BOLD) and therefore, artifactual, signal changes. The basic concept is that fractional BOLD signal changes increase linearly with echo time. With multi-echo acquisition, the TE-dependence of the signal can be assessed at each TR. The basic procedure is to first perform Independent Component Analysis (ICA) on a time series of a composite concatenated image made up of the three echoes obtained with each TR, and to then determine the echo time dependence of each ICA component. Those ICA components that do not show linear TE dependence are removed. Centralized image reconstruction: Dr. Roopchansingh, Dr. Inati, and Joe Naegele as well as Dr. Michael Hansen (NHLBI) worked to develop and extend the Gadgetron framework. Briefly, the Gadgetron is a stand-alone recon engine that can receive raw data from a growing number of different datasets across scanner and vendor, and then pass it back to the scanner (or elsewhere) in the appropriate format. One of the key outcomes of this project has been to provide converters for most major vendors' custom MRI raw data formats into a new standard ISMRMRD format, which allows reconstruction algorithms to be more easily shared and used. Joe Naegele developed components for the Gadgetron reconstruction framework to allow production of DICOM images from custom MRI scanner pulse sequences. This system is currently in use on the GE scanner platforms, specifically for Dr. Roopchansingh's custom B0 mapping sequence. Joe Naegele also developed a dynamic Python interface to the Gadgetron to allow writing reconstruction chains using Python tools. Joe Naegele played a critical role in developing solutions for continuous building, testing, and deployment of the Gadgetron, ISMRMRD and other related software projects. Motion Correction: In collaboration with GE, Dr. Roopchansingh has been working with scientists in the NMRF to evaluate the efficacy and applicability of a GE product PROMO that performs prospective motion correction. This has been implemented primarily to improve the quality of 3D anatomical data acquired from patients and subjects prone to motion. One of the initial projects compared the efficacy of PROMO in improving the consistency of metrics output by FreeSurfer. Dr. Roopchansingh also modified the sequence provided by GE to allow researchers to collect motion-compensated multi-echo MP-RAGE data. More recently, he worked with Dr. Basser's Section to provide motion-compensated MP2-RAGE capability using PROMO. The FMRIF Siemens Skyra (3TD) scanner has a KinetiCor Prospective Motion Correction (PMC) accessory. The KinetiCor system is a commercially available device that employs in-bore camera tracking with an external computer to identify subject motion modeled as a rigid body. The motion tracking data is then fed back to the MRI system and used to prospectively track the imaging scan volume with subject motion. The KinetiCor device is based around the Metria Innovation Moir Phase Tracking system that employs a single 12mm x 12mm marker with a Moir fringe pattern that changes with all 6 translational and rotational aspects of a rigid body transformation. The ability of the device to obtain the full rigid body motion from a single camera and marker together with favorable reports in early scientific publications generated optimism that the device would offer a straightforward solution to problems with patient motion during long imaging scans (3D anatomical and fMRI). Although the KinetiCor device works well during tests with phantoms, preliminary results employing the device with direct skin attachment to the nasion or nasal bone have been mixed with the Siemens 20-channel coil and poor with the 32-channel. As a result of our experiences and in collaboration with other groups (Maastricht, UCL, and others), we have concluded that directly mounting the marker on the skin is unreliable due to problems of skin movement relative to the brain, possible bumping of the marker against the coil elements and the likelihood of optical occlusion by the camera. Therefore, we have decided to implement a tooth-clip solution similar to that being used for motion logging at UCL. The in console-room manufacture of a patient-specific tooth-clip adds approximately 30 minutes additional time to an exam. While the FMRIF recognizes that an orally attached device will not be suitable for all patients, it will almost certainly help some research groups, and appears to be the most reliable way to use the KinetiCor device at present. Additionally, we have been in communication with KinetiCor to obtain the latest software for the camera system and MRI scanner, including the latest version of the XPace libraries for the scanner that offers the ability to simultaneously track up to 3 markers. It is hoped that this redundancy may provide some robustness to problems with optical occlusion of the markers due to the coil elements. Finally, we are programming and compiling KinetiCor aware pulse sequences locally which should allow PMC to be enabled with specialized pulse sequences in addition to the standard variants supplied with the KinetiCor device. Project sharing: Joe Naegele has deployed a project management system (Redmine) for project task tracking and collaborative science efforts. Joe maintains the FMRIF Github organization, used for collaborating on both open source and private software projects. He also created a project management system using Python for sharing data on POSIX file systems, which has greatly improved the ability of the FMRIF to collaborate scientifically and has made software development and testing efforts more efficient. Virtual Desktops: In 2014 our technologists needed a workstation solution that would allow them an uninterrupted desktop session while moving between scanner rooms within the MRI facility. Roark Maccado implemented a Virtual Desktop Infrastructure solution to replace our technologists' and administrators' MACs/Windows desktops.
|Thomas, Adam G; Marrett, Sean; Saad, Ziad S et al. (2009) Functional but not structural changes associated with learning: an exploration of longitudinal voxel-based morphometry (VBM). Neuroimage 48:117-25|