Events

Dec 13, 2017
12:00 PM
Building 149 Rm 2204

 

Abstract:

Motion is widely recognised as a major problem in MR neuroimaging, with consequences including impaired clinical diagnosis, wasted time and money for repeat scanning, and biased research results. Motion during 3D-encoded scans, such as T1-weighted MPRAGE and T2-weighted SPACE, creates complicated artifacts due inconsistencies in the acquired k-space data. These artifacts are difficult to correct post-hoc, and some estimate of the head motion is usually necessary. One way to estimate motion is with fast volume navigator (vNav) images inserted every ~3 s, and using the tracking information to adapt the sequence in real-time to maintain a consistent view of the head has been shown to substantially reduce artifacts. Motion can also be estimated with camera and marker systems, and this allows sequence-independent, high-frequency real-time correction, however, the requirement to attach a marker to patients or subjects (e.g. on the forehead or with a bite-bar) can be prohibitive, and can also result in less accurate estimates of head motion.

In this talk I will present our latest work on markerless real-time motion correction for MPRAGE and T2-SPACE. We used the “Tracoline” optical camera system (TracInnovations, Copenhagen, Denmark), which reconstructs 3D “point clouds” of the subject’s face and registers them to a reference point cloud to estimate head movement. This is appealing because: i) it can provide high-frequency motion estimates (every ~30 ms), ii) it is expected to have low impact on the MRI workflow. Our results suggest that the ability to update the FOV rapidly can have benefits over slower updates (e.g. vNav correction every ~3 s). We also show that the morphometry measures from the corrected images acquired during substantial motion are consistent with those derived from artifact-free images acquired without intentional motion.

 

About the Speaker:

My background is in MRI physics and pulse sequence development for application to diffusion imaging, and more recently, real-time motion correction. During my PhD research with Peter Jezzard and Karla Miller at the FMRIB Centre, University of Oxford, we worked on the readout-segmented EPI (or RESOLVE) sequence for high-resolution diffusion imaging with reduced EPI distortion and blurring artifacts. In collaboration with David Porter (Siemens), we demonstrated partial Fourier and simultaneous multi-slice (SMS) accelerations, which reduce the otherwise prohibitive scan times to clinically feasible durations and enable multi-direction diffusion studies. We also worked on a cardiac synchronised multi-slab implementation, which like SMS, improves the SNR efficiency by reducing the repetition time (TR).

In 2013 I started post-doctoral research on real-time motion correction with Peter Jezzard at the FMRIB Centre. In collaboration with Andre van der Kouwe and Dylan Tisdall we deployed the volume navigator (vNav) technique in some specialised research sequences, including vessel-encoded dynamic ASL angiography. In work on vessel wall imaging in the neck, we developed a navigator approach to identify motion-corrupted data, which were then estimated with parallel imaging. Since 2016 I have been working at the MGH Martinos Center with Andre van der Kouwe and Bruce Fischl, primarily on motion correction with markerless tracking and vNavs.

Jan 31, 2018
12:00 PM
149 13th Street (Building 149), Room 2204

 

Abstract:

Partners institutions have a robust clinical informatics infrastructure supporting the research enterprise.  Over the past several years new tools have been developed to facilitate regulated access to medical image data collected during the conduct of routine clinical care.  The visionary leadership and research efforts in the Departments of Radiology at Partners institutions together with a high volume of patients yields a large volume of medical images in the institutional archives acquired with parameters comparable to the best quality research scans.  This talk will review the tools available to all Partners faculty and staff to identify, access and work with data extracted from the electronic healthcare records including the medical images. The newest of the suite of tools is the Partners Clinical Image Bank, which is a user friendly portal that enables interactive analysis and exploration of valuable image repositories.  An exemplar project that uses ADC values from brain MR images to identify neonatal hypoxic ischemic encephalopathy lesions will be used to illustrate the clinical potential of these tools. The Clinical Image Bank is in a period of expansion and the characteristics of new image registries that would be of greatest value will be discussed.

 

About the Speaker:

Randy L. Gollub is Professor of Psychiatry and Associate Director of Translational Research in the Neuroimaging Research Program at Massachusetts General Hospital. She is a recognized leader in the development and application of advanced neuroimaging technologies to understand the pathophysiology of neuropsychiatric disorders including neonatal hypoxic ischemic encephalopathy, chronic pain and schizophrenia. She is currently working on translating these advances into clinical radiology practice to improve patient care through the use of large-scale imaging informatics approaches.