Young Investigator Award
Oral Session - Young Investigator Awards
Other
Monday, 17 May 2021 14:00 - 15:00
  • Estimation of fractional myocardial blood volume and water exchange using ferumoxytol-enhanced MRI
    Caroline Colbert1, Michael A. Thomas2, Ran Yan3, Aleksandra Radjenovic4, J. Paul Finn1,5, Peng Hu1,3,5, and Kim-Lien Nguyen1,2,5
    1Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 2Division of Cardiology, UCLA David Geffen School of Medicine, Los Angeles, CA, United States, 3Department of Radiology, UCLA David Geffen School of Medicine, Los Angeles, CA, United States, 4Institute of Cardiovascular & Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom, 5Diagnostic Cardiovascular Imaging Laboratory, Department of Radiological Sciences, UCLA David Geffen School of Medicine, Los Angeles, CA, United States
    Healthy normal swine showed a mean mid-ventricular fMBV of 7.2 ± 1.4%. This study demonstrates the feasibility of fMBV estimation using multi-dose FE‑MRI with a two-compartment water exchange model.
    Figure 2. Pixelwise fMBV and water exchange maps in a swine model of regional myocardial hypoperfusion (a, b) and a normal swine subject (d, e). In the swine subject with artificially induced coronary stenosis (top panel), differences in fMBV (a) and water exchange (b) can be observed in the hypoperfused anterior, septal, and inferior segments. Angiographic image (c) acquired following deployment of a 3D printed coronary implant in the mid LAD shows severe coronary narrowing.
    Figure 1. Ferumoxytol multi-dose T1 mapping study protocol. Following anesthesia and localizers, we acquired mid-ventricular short axis T1 maps at eight cumulative ferumoxytol doses (0.0 – 4.0 mg/kg). Following each ferumoxytol infusion, we observed a five-minute delay to achieve contrast steady state. MOLLI, Modified Look-Locker Inversion.
  • Brain oxygen extraction is differentially altered by Alzheimer’s and vascular diseases
    Dengrong Jiang1,2, Zixuan Lin1,2, Peiying Liu1, Sandeepa Sur1, Cuimei Xu1, Kaisha Hazel1, George Pottanat1, Jacqueline Darrow3, Jay J. Pillai1,4, Sevil Yasar5, Paul Rosenberg6, Abhay Moghekar3, Marilyn Albert3, and Hanzhang Lu1,2,7
    1The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 3Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 4Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 5Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 6Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 7F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States
    Cerebral oxygen extraction fraction (OEF) is differentially affected by Alzheimer’s (decrease OEF) and vascular (increase OEF) pathology. Therefore, OEF can be useful in differential diagnosis of Alzheimer’s disease and vascular cognitive impairment.
    Table 1. Characteristics of the participants.
    Figure 1. TRUST OEF data of representative normal (top row), MCI (second row) and demented (bottom row) subjects. Subtraction between control (first column) and labeled (second row) images yields strong venous blood signal in the superior sagittal sinus (yellow arrows) in the difference images (third column). The scatter plots on the far right show venous signal as a function of effective TE (eTE). Fitted venous blood T2 and the corresponding OEF values (before correction) are also shown.
  • Three-Dimensional Surface-Based Analysis of Cartilage MRI Data in Knee Osteoarthritis: Validation and Initial Clinical Application
    James W. MacKay1,2, Joshua Kaggie1, Graham M. Treece3, Stephen M. McDonnell4, Wasim Khan4, Alexandra R. Roberts5,6, Rob L. Janiczek5, Martin J. Graves1, Tom D. Turmezei2,7, Andrew W. McCaskie4, and Fiona J. Gilbert1
    1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Norwich Medical School, University of East Anglia, Norwich, United Kingdom, 3Department of Engineering, University of Cambridge, Cambridge, United Kingdom, 4Department of Surgery, University of Cambridge, Cambridge, United Kingdom, 5Clinical Imaging, GlaxoSmithKline, London, United Kingdom, 6Antaros Medical, Uppsala, Sweden, 7Department of Radiology, Norfolk & Norwich University Hospital, Norwich, United Kingdom
    We propose a novel approach to analysis of cartilage MRI data in knee osteoarthritis which improves responsiveness and reduces analysis burden vs standard methods. This could improve our ability to detect treatment effects in shorter, smaller studies.

    Figure 2:

    Fig 2A: Outline of initial steps in 3D-CaSM pipeline, from image acquisition to thickness measurement. Femur used for demonstration purposes – 3D-CaSM is also performed for tibial cartilage surfaces.

    Fig 2B: Outline of cartilage composition measurement process. In this example, a T1rho map is used. Note focal area of increased T1rho values on the medial femoral condyle (black arrowhead) corresponding to an area of partial thickness cartilage loss on the 3D SPGR images (white arrowhead).

    Figure 5: Implementation of 3D-CaSM in a clinical study of knee joint distraction using statistical parametric mapping to detect effects at group level. Surface data represent mean change from baseline mapped to the canonical surface and masked for statistical significance. Significant increases in cartilage thickness are seen over the weight-bearing medial femoral condyle at up to 5 years follow-up, with a delayed compensatory response in the lateral compartment at 7 years & 10 years follow-up.
  • Simultaneous Multiple Resonance Frequency Imaging (SMURF): Fat‑water imaging using multi‑band principles
    Beata Bachrata1,2, Bernhard Strasser1,3, Wolfgang Bogner1, Albrecht Ingo Schmid4, Radim Korinek5, Martin Krššák1,2,6, Siegfried Trattnig1,2, and Simon Daniel Robinson1,7,8
    1High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria, 2Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria, 3Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, 4High Field MR Centre, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria, 5Institute of Scientific Instruments of the CAS, Brno, Czech Republic, 6Department of Internal Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria, 7Centre of Advanced Imaging, University of Queensland, St. Lucia, Australia, 8Department of Neurology, Medical University of Graz, Graz, Austria
    The proposed Simultaneous Multiple Resonance Frequency imaging (SMURF) approach achieved similar or better fat-water separation than state-of-the-art techniques in the knee, breasts and abdomen and allowed the elimination of chemical shift effects in fat-water images.
    Figure 3: Excitation selectivity and unaliasing quality of SMURF imaging demonstrated for one exemplary volunteer for each body region under consideration. The acquired aliased images show the overlapping water and fat images, which are CAIPIRINHA‐shifted along the phase‐encoding (PE) direction. Separate SMURF water and fat images, reconstructed from the aliased images, illustrate the achieved separation quality. (The separated images were rescaled for improved visibility.)
    Figure 1: Fat‐water separation, chemical shift corrections, and recombination in Simultaneous Multiple Resonance Frequency (SMURF) imaging. Overlapping water and CAIPIRINHA‐shifted fat images are unaliased using slice‐GRAPPA (Step 1). The fat image is shifted to reverse chemical shift displacement – see the positions relative to the red reference line – and, for GRE acquisitions, corrected for chemical shift‐related phase evolution (Step 2). The fat and water images are then recombined (Step 3), generating a fat‐water image free of chemical shift artefacts.
  • MRI of [2-13C]Lactate without J-coupling artifacts
    Keshav Datta1 and Daniel Spielman1
    1Department of Radiology, Stanford University, Stanford, CA, United States
    Two methods based on quadrature detection are presented to resolve J-coupling modulated artifacts during imaging of spin-1/2 nuclei. A primary application is imaging of [2-13C]Lactate in hyperpolarized [2-13C]Pyruvate experiments.
    Figure 1 (A) Schematic of an RF pulse followed by gradient waveform for EPI readout (FOV=128mm, 32x32 matrix, TE=28.4ms, readout=28.8ms) highlights the evolution of J-modulation during imaging. (B) k-space weighting due to J-modulation is significant in the slower phase encode direction (ky). (C) Spatial frequencies nulled due to J-coupling evolution during readout (Acq1), compensated by acquiring a quadrature component by delaying the acquisition time by 1/2J (Acq2). (D) Complex combination of these two quadrature components restores the original image, (E).
    Figure 2 Narrowband excitation for resolving J-coupling induced doublet in [2-13C]Lac. Evolution of J-coupling during a short RF pulse (500μs, 2kHz bandwidth) is negligible and hence results in a doublet during signal collection (top row). A long narrow bandwidth pulse (13.33ms, 75Hz), J/2 Hz off-resonance (70Hz), on the other hand, generates in-phase and anti-phase coherences that combine to result in a singlet during signal acquisition.
  • Five-Dimensional Quantitative Low-Dose Multitasking Dynamic Contrast- Enhanced MRI (LD-MT-DCE): Preliminary Study on Breast Cancer
    Nan Wang1,2, Yibin Xie1, Zhaoyang Fan1,2, Sen Ma1,2, Rola Saouaf3, Yu Guo1,4, Stephen L. Shiao5,6, Anthony G. Christodoulou1,2, and Debiao Li1,2
    1Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA, United States, 2Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, 3Department of Imaging, Cedars Sinai Medical Center, Los Angeles, CA, United States, 4Department of Radiology, Tianjin First Central Hospital, Tianjin, China, 5Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 6Biomedical Sciences, Division of Immunology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
    The low-dose Multitasking DCE was proposed for DCE quantification with whole-breast coverage and high spatiotemporal resolution at 20% dose. The technique showed excellent image quality and repeatability, and matched diagnosis from clinical standard.
    Figure 2: Representative maps of kinetic parameters showing normal breast tissue from a 52-year-old healthy volunteer (A), a benign tumor (marked by a yellow solid boundary) from a 49-year-old patient (B), and a malignant tumor (marked by a red dashed boundary) from a 65-year-old patient (C). The gray-scale images display peak-enhanced LD-MT-DCE images and the standard-dose images at the same slice. The overlaid colormaps represents Fp, vp, Ktrans, and ve, respectively.
    Figure 4: Mean and standard deviation measurements of Fp, vp, Ktrans, and ve for control group, and benign and malignant tumors in patient group. The P value of each pair by one-way ANOVA with Tukey test are marked on top of the bar graphs. Fp, vp, and Ktrans were significantly different between control and malignant tumor, and between benign and malignant tumors; Fp, and vp were significantly different between control and benign tumors. * indicates statistically significant difference.