Medical Biophysics

Nilesh Ghugre PhD, University of Southern California
Assistant Professor
Photo of Dr. Nilesh Ghugre
Contact Info
T: (416) 480-6100 x85053
F: (416) 480-5003
Sunnybrook Health Sciences Centre
2075 Bayview Avenue, M7 510
Toronto, ON, M4N 3M5
Research Interests
Biomedical Imaging, Cardiovascular Sciences, Image-Guided Therapy and Device Development, Stem Cells and Regenerative Medicine

Additional Contact Info

Senior Administrative Assistant (Research): Tasneem Dalal
Phone: (416) 480-4975
Fax: (416) 480-5003
Email Tasneem Dalal

At A Glance

  • Development and validation of quantitative cardiac Magnetic Resonance Imaging (MRI) techniques
  • Establishing Image-guidance technologies for cardiac regenerative medicine
  • Development of cardiac blood oxygen level dependent (BOLD) imaging
  • Detection of microvascular dysfunction in heart disease
  • Development of novel preclinical models of heart disease

Short Bio

Dr. Nilesh Ghugre is a Scientist in the Schulich Heart Program at Sunnybrook Research Institute with a focus on imaging in cardiovascular disease. His interest is to develop novel experimental models, coupled with new imaging biomarkers to understand the underlying pathophysiology of disease.

Acute myocardial infarction (or a heart attack) occurs when blood supply to the heart muscle is interrupted. This can destroy heart cells and severely compromise pumping action, resulting in progression toward heart failure. Dr. Ghugre’s research focus is to utilize advanced cardiac MRI biomarkers to characterize the post-infarct “remodeling” process and determine efficacy of novel therapeutic interventions to prevent heart failure. To this end, he is involved in exploring novel experimental models that represent clinical manifestation of heart disease.

His lab is developing MRI tools to probe cardiac pathophysiology parameters including viability, edema and inflammation, hemorrhage, perfusion, strain and microvascular integrity and function. Quantitative T1, T2 and T2-star MRI relaxation mechanisms form the basis for this in vivo tissue characterization, allowing for intra- and inter-subject comparisons. Another focus has been the in vivo assessment of microvascular dysfunction, including abnormal blood flow and perfusion reserve in patients with diabetes or severe infarction. This assessment is done using cardiac blood oxygenation level dependent (BOLD) imaging and arterial spin-label imaging.

His lab is also advancing image-guidance technologies for cardiac regenerative medicine. Given that the human heart lacks regenerative capacity, stem cell-based therapies are a revolutionary means to repopulate lost cells in scar tissue and regain lost contractile function. The lab aims to develop MRI-based technologies that will facilitate minimally invasive and accurate cell delivery to the infarct scar, and image cell fate, tissue response and outcomes, all within the same framework.


Research Synopsis

MRI Relaxometry in Iron-Overloaded Tissues: In 2005, we probed the mechanisms of tissue-iron interaction using MRI relaxation - R1 (1/T1), R2 (1/T2) and multi-echo R2 in fresh human liver biopsy specimens taken from patients with transfusion-dependent anemia. Our study demonstrated that to standardize in vivo calibration (inter-site and -sequence variability), it is important to understand the complex interaction of stored iron particles and water protons within the tissue of interest. Later in 2006, we were the first to demonstrate inequivocally that cardiac R2 and R2* are predominantly determined by cardiac iron concentration in humans. Since tissue biopsy is not a feasible option for the heart in the clinic, this data further supported the clinical use of cardiac MRI in iron-overload syndromes.

MRI-Iron Calibration by Monte-Carlo Modeling: In 2011, we were the first to develop a ‘human-derived’ Monte-Carlo framework for probing the underlying biophysics in hepatic iron overload; this demonstrated that knowledge of iron susceptibility/distribution and proton mobility are sufficient to characterize MRI relaxation. The iron size and structure was incorporated into a virtual liver model to interrogate R2 and R2* under various iron morphologies and concentrations. In 2015, we demonstrated the use of this model to predict R2- and R2*-iron relationship at higher field strengths in patients. The important application of such tissue-specific models is in the iron calibration of inaccessible organs like heart, where tissue biopsy is not an option. Establishing these models will avoid recalibration in patients for MRI sequence, field strength, iron-chelation therapy and organ.

Quantitative MRI following Acute Myocardial Infarction (AMI): In 2011, we demonstrated that multi-parametric MRI exploiting T2 and T2* relaxation properties can assess the state of myocardial tissue (edema, hemorrhage, microvascular reactivity) in vivo in a preclinical model of AMI. We have also demonstrated the value of T2 relaxation for vasodilatory function using the BOLD effect. In 2013, we demonstrated that such characterization can also distinguish the intrinsic remodeling mechanisms based on severity of injury. In 2017, we were the first to mechanistically demonstrate that hemorrhage is an active contributor to inflammation and myocardial and microvascular damage post-AMI, beyond the initial ischemic insult. Thus, quantitative MRI techniques allow regional, longitudinal, and cross-subject comparisons, and hence are powerful tools for evaluating treatment strategies, potentially improving clinical outcomes.

Clinical Studies: In 2012, we demonstrated the utility of quantitative MRI techniques in evaluating disease progression post-PCI in patients presenting with STEMI. One study demonstrated that quantitative T2 and T2* mapping can visualize edema and hemorrhage, respectively in human AMI and that remote zone remodeling in the hemorrhagic group may be indicative of more adverse remodeling. In another study we showed that thrombus aspiration during PCI was associated with reduced myocardial edema, hemorrhage and microvascular obstruction. This study was recognized as a ‘highly accessed article relative to age’ in JCMR with more than 1000 reads within the first month of publication. Since 2012, we have several publications demonstrating the utility of MRI mapping techniques to evaluate risk factors associated with diabetes including inflammation and microvascular disease.

Publications and Awards

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Recent Publications

  • Ghugre NR, Pop M, Thomas R, Newbigging S, Qi X, Barry J, Strauss BH, Wright GA. Hemorrhage promotes inflammation and myocardial damage following acute myocardial infarction: Insights from a novel preclinical model and cardiovascular magnetic resonance. J. Cardiovasc. Magn. Reson. 2017 July 4;19:50
  • Roifman I, Ghugre NR, Zia MI, Farkouh ME, Zavodni A, Wright GA, Connelly KA. Diabetes is an independent predictor of right ventricular dysfunction post ST-elevation myocardial infarction. Cardiovasc Diabetol. 2016 Feb 18;15(1):34.
  • Ghugre NR, Doyle EK, Storey P, Wood JC. Relaxivity-iron calibration in hepatic iron overload: Predictions of a Monte Carlo model, Magn Reson Med. 2015 Sep;74(3):879-83
  • Ghugre NR, Pop M, Barry J, Connelly KA, Wright GA. Quantitative magnetic resonance imaging can distinguish remodeling mechanisms after acute myocardial infarction based on the severity of ischemic insult. Magn Reson Med. 2013 Oct;70(4):1095–1105.
  • Zia MI, Ghugre NR, Connelly KA, Strauss BH, Dick AJ, Wright GA. Characterizing myocardial edema and hemorrhage using quantitative T2 and T2* mapping at multiple time intervals post ST elevation myocardial infarction. Circ Cardiovasc Imaging. 2012 Sep 1;5(5):566–72.
  • Ghugre NR, Ramanan V, Pop M, Yang Y, Barry J, Qiang B, Connelly K, Dick AJ, Wright GA. Myocardial BOLD imaging at 3T using quantitative T2: Application in a myocardial infarct model. Magn Reson Med. 2011 Dec;66(6):1739–47.
  • Ghugre NR, Ramanan V, Pop M, Yang Y, Barry J, Qiang B, Connelly K, Dick AJ, Wright GA. Quantitative tracking of edema, hemorrhage and microvascular obstruction in sub-acute myocardial infarction in a porcine model by MRI. Magn Reson Med. 2011 Oct;66(4):1129–41.