Some of the ongoing research projects are listed below.

Accelerated Imaging

Data acquisition in magnetic resonance imaging (MRI) is inherently slow. An MRI exam may take more than an hour to complete. Therefore, performing imaging in clinically feasible acquisition times requires high acceleration, especially for volumetric and free-breathing real-time imaging. Typically, the acquisition process is accelerated by prospective undersampling of the k-space. Recovering diagnostic images from highly undersampled data requires utilizing image priors, which are included as regularizing terms in an optimization problem. We have developed compressed sensing (CS) inspired accelerated imaging techniques [1, 2] that are now clinically used at our institute. Our ongoing efforts are focused on developing and implementing highly accelerated deep learning (DL)-based methods that can preserve fine details that may be lost in sparsity-based CS methods [3]. Target applications include cardiac imaging and neuroimaging in both adult and pediatric populations.

  1. C. Chen, Y. Liu, P. Schniter, N. Jin, J. Craft, O. Simonetti, and R. Ahmad, “Sparsity adaptive reconstruction for highly accelerated cardiac MRI,” Magnetic Resonance in Medicine, vol. 81, no. 6, pp. 3875–3887, 2019
  2. A. Rich, M. Gregg, N. Jin, Y. Liu, L. Potter, O. Simonetti, and R. Ahmad, “Cartesian sampling with variable density and adjustable temporal resolution (CAVA),” Magnetic Resonance in Medicine, vol. 83, no. 6, pp. 2015–2025, 2020.
  3. R. Ahmad, C. A. Bouman, G. T. Buzzard, S. Chan, S. Liu, E. T. Reehorst, and P. Schniter, “Plug-and-play methods for Magnetic Resonance Imaging: Using denoisers for image recovery,” IEEE Signal Processing Magazine, vol. 37, no. 1, pp. 105–116, 2020.

4D Flow Imaging

MRI-based 4D flow imaging has emerged as a comprehensive alternative for measuring hemodynamics. Extending the principles of phase-contrast MRI (PC-MRI), 4D flow imaging provides a full volumetric and temporally resolved mapping of the three-dimensional velocity vector, offering an advantage over PC-MRI with regard to anatomical coverage and hemodynamic visualization. Post-processing enables retrospective interrogation of arbitrary slice planes, long after the patient is removed from the magnet. Advanced hemodynamic parameters can also be calculated which may carry additional prognostic value. Despite its advantages, the clinical adoption of 4D flow imaging has been hampered by prohibitively long acquisition times. We recently proposed a highly accelerated data acquisition and processing framework that enables whole-heart 4D flow imaging from a five-minute scan [1, 2]. The 4D flow image on the left displays the speed of the blood in the heart and great vessels.

  1. A. Rich, L. C. Potter, N. Jin, Y. Liu, O. P. Simonetti, and R. Ahmad, “A Bayesian approach for 4D flow imaging of aortic valve in a single breath-hold,” Magnetic Resonance in Medicine, vol. 81, no. 2, pp. 811–824, 2019
  2. A. Pruitt, A. Rich, Y. Liu, N. Jin, L. Potter, M. Tong, S. Rajpal, O. Simonetti, and R. Ahmad, “Fully self-gated whole-heart 4D flow imaging from a 5-minute scan,” Magnetic Resonance in Medicine, vol. 85, no. 3, pp. 1222–1236, 2021.

Motion Encoding and Compensation

Unaccounted physiological motion, e.g., respiratory motion, can corrupt cardiovascular MRI (CMR). Breath-holding and ECG triggering are strategies commonly used to suppress respiratory motion and to synchronize the acquisition with the cardiac rhythm, respectively. Many patients, however, cannot breath-hold, and placement of ECG leads can be time-consuming. To encode both cardiac and respiratory motions, we are developing methods based on the Pilot Tone (PT) technology [1, 2]. PT is a transmitter that emits electromagnetic waves close to the Larmor frequency. The transmitted signal is modulated by the physiological motions and is picked up by the receive coils. With PT, the physiological motions are seamlessly encoded into the raw MRI data and can be separated from the image content using signal processing techniques.

  1. A. Pruitt, Y. Liu, N. Jin, P. Speier, O.P. Simonetti, R. Ahmad. “Evaluating Pilot Tone and self-gating for retrospective cardiac binning in highly accelerated, whole heart 4D flow imaging,” 2021 ISMRM & SMRT Annual Meeting, 2021, Virtual
  2. C. Chen, Y. Liu, O.P. Simonetti, M. Tong, N. Jin, P. Speier, R. Ahmad, “Extraction of cardiac and respiratory motion from Pilot Tone—a patient study,” SCMR 24th Annual Scientific Sessions, 2021, Virtual

Exercise Stress Imaging

Exercise stress CMR is an emerging area of research. By exposing cardiac function impairment that may not be evident at rest, stress CMR may yield biomarkers for early diagnosis of cardiovascular conditions, including pulmonary hypertension, heart failure, valvular disease, and ischemic heart disease. At OSU, we have access to exercise equipment that allows the subjects to be imaged while they exercise inside the MRI magnet. However, imaging during exercise stress is more challenging due to higher heart rate and exaggerated respiratory motion. We are developing new protocols to facilitate exercise stress CMR [1, 2]. An image series acquired during exercise is shown on the left.

  1. A. Pruitt, Y. Liu, N. Jin, R. LaFountain, C. Crabtree, O.P. Simonetti, R. Ahmad, R. “Exercise 4D flow: towards feasibility of rapid, free-running whole-heart 4D flow during moderate exercise at 1.5T,” SCMR 23rd Annual Scientific Sessions, 2020, Orlando, Florida, USA
  2. C. Chen, Y. Liu, J. Craft, M. Tong, O.P. Simonetti, R. Ahmad, “High resolution exercise stress real-time cine imaging,” SCMR 22nd Annual Scientific Sessions, 2019, Bellevue, WA, USA