O'Halloran Lab

O'Halloran Lab(Neuroimaging)

As Chief of the Image Acquisition Core, Dr. O'Halloran's work is focused on bringing innovative new imaging techniques to bear on problems in basic and clinical research. His primary area of focus is on diffusion weighted imaging (DWI), in particular on high-resolution DWI. At high spatial resolution, DWI allows visualization of the white matter pathways that connect functional areas of the brain. One application of this technique that Dr. O'Halloran is focused on is in the planning of deep brain stimulation surgery to treat conditions such as Parkinson's disease, dystonia, and depression. Dr. O'Halloran's other interests include image reconstruction and motion correction. Patient motion continues to be a major problem in MRI, causing failed or prolonged exams which ultimately results in increased heath care costs. Solutions to patient motion can be implemented on both the acquisition and image reconstruction side, and can potentially benefit a wide range of MR imaging techniques.

My Background

I am an assistant professor of Radiology at Mount Sinai with a background in Physics, MRI acquisition, MRI reconstruction, and image processing, with a focus on diffusion-weighted imaging methods. I did my graduate work at the University of Wisconsin in Madison in the area of improving rapid MRI image with a focus on hyperpolarized helium-3 MRI in the lung. My post-graduate training was at Stanford University and was focused on diffusion-weighted imaging of the brain, motion-correcction and reconstruction. My current research interests are in applications of imaging to the study of neuropsychiatric disease and surgical planning, particularly DBS planning.

DBS

Deep brain stimulation (DBS) can dramatically improve quality of life for patients with Parkinson’s disease (PD) when medication is not effective. While development of new medication holds promise, DBS is currently the only option to alleviate debilitating symptoms of PD in patients refractory to medication. While DBS is frequently very effective as currently practiced, there is room for improvement. Simply stated, our goal here is to make DBS more patient-friendly, work better, and work for more people.

To achieve these goals we propose to improve DBS surgical planning by targeting white matter pathways instead of the traditional grey matter targets, to use a network model to identify critical white matter connections, and to automate surgical planning. Having more accurate targeting will eliminate the need for keeping the patient awake during surgery, will improve efficacy, and will improve patient selection.

We propose to use diffusion-weighted MRI to characterize the white matter and thus the network connectivity of all the brain as a whole. In the first part of this work we will characterize the networks of patients with successful DBS surgery to form a database. In the second part we will use this database to develop an automatic planning tool that essentially determines a patient-specific target that best matches the white matter network in the database. This study, if successful, will improve patient experience, improve the accuracy of DBS targeting, increase basic knowledge about white matter networks in the DBS targets, and result in a package of software and accompanying database that can be used to automatically plan surgeries.

DBS Planning
Fig. 1 – Multimodal, patient-specific approach to DBS planning.

Cocaine Addiction

Substance addiction is a chronic, relapsing brain disease associated with repeated, prolonged exposure to a drug such as cocaine. In the US 1.1 million people are abuse or are dependent on cocaine. Cocaine addiction in the US costs an estimated 58-80 billion dollars annually. Cocaine use disorder (CUD) is associated with impairments in response inhibition and salience attribution (iRISA), implicating the prefrontal cortex (PFC) and its connections to midbrain’s ventral tegmental area (VTA), ventral striatum which includes the nucleus accumbens (NAcc), and hippocampus (HIPP), highly interconnected regions involved in motivation, salience, and memory. However, the study of white matter (WM) tracks connecting these regions has been lagging behind the study of the morphological integrity of these regions in addiction in general and CUD in particular. My work and interests in this area are (1) to study of the WM changes associated with CUD using 3T magnetic resonance imaging (MRI), (2) to look for subtle changes in WM using the more powerful 7T MRI, and (3) to link changes observed in the the WM with dimensions of disease severity such as craving, dependence, and withdrawal severity. I am doing this work in collaboration with the neuroimaging of addiction and related conditions (NARC) program, led by Rita Z. Goldstein.

DWI MRI
Fig. 2 – Diffusion-weighted MRI shows white matter changes throughout the brain in individuals with cocaine use disorder.

Bioinformatics

Another area of interest of mine is of visualizing large and complex datasets. The brain imaging center (BIC), of which I am a part, is focused on collecting standardized imaging datasets across many psychiatric diagnoses. we are working on ways to use this data to generate hypotheses and preliminary data for grants.

As part of the ENIGMA lifespan project in collaboration with Sophia Frangou from the Icahn School of Medicine at Mount Sinai Department of Psychiatry, I made an interactive, web-based user interface that allows anyone to visualize the data collected. https://enigmalifespan.shinyapps.io/enigma_lifespan_dataviewer/

ENIGMA lifespan
Fig. 4 – Screen capture from the ENIGMA lifespan data viewer showing hippocampal volume versus age for over 10,000 subjects

We are working on implementing similar interfaces to the data collected as a part of ongoing efforts by multiple investigators at ISMMS. We are working on ways to share data to promote an environment that fosters collaboration and open science.

Recent and Upcoming Publications

RL O’Halloran, E Sprooten, BH Kopell, W Goodman, and S Frangou. Multimodal Neuroimaging-informed clinical applications in neuropsychiatric and movement disorders. Submitted to Frontiers in Neuroscience 1-11-2016. Under Revision.

D Dima, RL O’Halloran, 93 others, S Frangou. Subcortical volumes across the lifespan: Normative data from 10,144 individuals aged 3-90 years. Submitted to Cerebral Cortex 2-24-2016. ID: CerCor-2016-00249. Under Review.

RL O’Halloran, A Chartrain, J Rasouli, RA Ramdhani, BH Kopell. A Case Study of Image-Guided Deep Brain Stimulation: MRI-Based White Matter Tractography Shows Differences in Responders and Non-Responders. Submitted to Journal of Neurosurgery 2-29-2016. ID:JNS16-488. Under Review.

H Dyvorne, RL O’Halloran, P Balchandani. Ultrahigh field single-refocused diffu- sion weighted imaging using a matched-phase adiabatic spin echo (MASE). Magnetic Resonance in Medicine. 2015 Jun 1. DOI 10.1002/mrm.25790

F Knoll, JG Raya, RL O’Halloran, S Baete, E Sigmund, R Bammer, DK Sodickson. A model-based reconstruction for undersampled radial spin-echo DTI with variational penalties on the diffusion tensor. NMR Biomed. 2015 Jan 16. DOI: 10.1002/nbm.3258

RL O’Halloran, M Aksoy, E Aboussouan, E Peterson, A Van, R Bammer. Real-Time Correction of Rigid-body-motion-Induced Phase Errors for Diffusion-Weighted Steady State Free Precession Imaging. Magn Reson Med 2014 online: DOI: 10.1002/mrm.25159

Recent Pending Patent (Work from Stanford University)

RL O’Halloran, A Van, R Bammer. An Apparatus for Real-Time Phase Correction for Diffusion-Weighted Magnetic Resonance Imaging Using Adaptive RF Pulses. Application US20130229177 A1. Filed 8-30-2012

ADDRESS

  • Address: Leon and Norma Hess Center for Science and Medicine 1470 Madison Avenue (between 101st and 102nd St) TMII - 1st Floor New York,
    NY 10029
  • Email: TMII@mssm.edu
  • Website: tmii.mssm.edu
  • Tel: (212) 824-8471
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