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Muslu Y, Tamada D, Roberts NT, Cashen TA, Mandava S, Kecskemeti SR, Hernando D, Reeder SB. Free-breathing, fat-corrected T 1 mapping of the liver with stack-of-stars MRI, and joint estimation of T 1, PDFF, R 2 * , and B 1 + . Magn Reson Med 2024; 92:1913-1932. [PMID: 38923009 DOI: 10.1002/mrm.30182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 05/03/2024] [Accepted: 05/16/2024] [Indexed: 06/28/2024]
Abstract
PURPOSE Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat andB 1 + $$ {B}_1^{+} $$ inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition. THEORY AND METHODS Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T. RESULTS The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps. CONCLUSION The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, andB 1 + $$ {B}_1^{+} $$ in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.
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Affiliation(s)
- Yavuz Muslu
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Daiki Tamada
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | | | | | | | - Diego Hernando
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
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2
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Dean DC, Tisdall MD, Wisnowski JL, Feczko E, Gagoski B, Alexander AL, Edden RAE, Gao W, Hendrickson TJ, Howell BR, Huang H, Humphreys KL, Riggins T, Sylvester CM, Weldon KB, Yacoub E, Ahtam B, Beck N, Banerjee S, Boroday S, Caprihan A, Caron B, Carpenter S, Chang Y, Chung AW, Cieslak M, Clarke WT, Dale A, Das S, Davies-Jenkins CW, Dufford AJ, Evans AC, Fesselier L, Ganji SK, Gilbert G, Graham AM, Gudmundson AT, Macgregor-Hannah M, Harms MP, Hilbert T, Hui SCN, Irfanoglu MO, Kecskemeti S, Kober T, Kuperman JM, Lamichhane B, Landman BA, Lecour-Bourcher X, Lee EG, Li X, MacIntyre L, Madjar C, Manhard MK, Mayer AR, Mehta K, Moore LA, Murali-Manohar S, Navarro C, Nebel MB, Newman SD, Newton AT, Noeske R, Norton ES, Oeltzschner G, Ongaro-Carcy R, Ou X, Ouyang M, Parrish TB, Pekar JJ, Pengo T, Pierpaoli C, Poldrack RA, Rajagopalan V, Rettmann DW, Rioux P, Rosenberg JT, Salo T, Satterthwaite TD, Scott LS, Shin E, Simegn G, Simmons WK, Song Y, Tikalsky BJ, Tkach J, van Zijl PCM, Vannest J, Versluis M, Zhao Y, Zöllner HJ, Fair DA, Smyser CD, Elison JT. Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol. Dev Cogn Neurosci 2024; 70:101452. [PMID: 39341120 PMCID: PMC11466640 DOI: 10.1016/j.dcn.2024.101452] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 08/29/2024] [Accepted: 09/13/2024] [Indexed: 09/30/2024] Open
Abstract
The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the study's core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.
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Affiliation(s)
- Douglas C Dean
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA; Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA; Waisman Center, University of Wisconsin-Madison, Madison, WI, USA.
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jessica L Wisnowski
- Department of Pediatrics, Children's Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA, USA; Department of Radiology, Children's Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Andrew L Alexander
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA; Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Wei Gao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA; Bioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN, USA
| | - Brittany R Howell
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA; Department of Human Development and Family Science, Virginia Tech, Blacksburg, VA, USA
| | - Hao Huang
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kathryn L Humphreys
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - Tracy Riggins
- Department of Psychology, University of Maryland, College Park, MD, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA; Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA; Taylor Family Institute for Innovative Psychiatric Research, Washington University in St. Louis, St. Louis, MO, USA
| | - Kimberly B Weldon
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Banu Ahtam
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Natacha Beck
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | | | - Sergiy Boroday
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | | | - Bryan Caron
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Samuel Carpenter
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | | | - Ai Wern Chung
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Anders Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Samir Das
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Christopher W Davies-Jenkins
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Alexander J Dufford
- Department of Psychiatry and Center for Mental Health Innovation, Oregon Health & Science University, Portland, OR, USA
| | - Alan C Evans
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Laetitia Fesselier
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Sandeep K Ganji
- MR Clinical Science, Philips Healthcare, Best, the Netherlands
| | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare, Mississauga, Ontario, Canada
| | - Alice M Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Aaron T Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Maren Macgregor-Hannah
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Michael P Harms
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland,; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland,; LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Steve C N Hui
- Developing Brain Institute, Children's National Hospital, Washington, DC, USA; Department of Radiology, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA; Department of Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - M Okan Irfanoglu
- Quantitative Medical Imaging Laboratory, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
| | | | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland,; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland,; LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Joshua M Kuperman
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Bidhan Lamichhane
- Center for Health Sciences, Oklahoma State University, Tulsa, OK, USA
| | - Bennett A Landman
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Xavier Lecour-Bourcher
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Erik G Lee
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA; Bioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN, USA
| | - Xu Li
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Leigh MacIntyre
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; Lasso Informatics, Canada
| | - Cecile Madjar
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Mary Kate Manhard
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | | | - Kahini Mehta
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lucille A Moore
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Saipavitra Murali-Manohar
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Cristian Navarro
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Sharlene D Newman
- Alabama Life Research Institute, University of Alabama, Tuscaloosa, AL, USA; Department of Psychology, University of Alabama, Tuscaloosa, AL, USA
| | - Allen T Newton
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Monroe Carell Jr. Children's Hospital at Vandebrilt, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Elizabeth S Norton
- Department of Communication Sciences and Disorders, School of Communication, Northwestern University, Evanston, IL, USA; Department of Medical Social Sciences, Feinberg School of Medicine, Chicago, IL, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Regis Ongaro-Carcy
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Xiawei Ou
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Arkansas Children's Research Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Minhui Ouyang
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Todd B Parrish
- Department of Radiology, Feinberg School of Medicine, Chicago, IL, USA; Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - James J Pekar
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Thomas Pengo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Carlo Pierpaoli
- Quantitative Medical Imaging Laboratory, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
| | | | - Vidya Rajagopalan
- Department of Pediatrics, Children's Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA, USA; Department of Radiology, Children's Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | | | - Pierre Rioux
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute-Hospital, Montréal, Québec, Canada; McConnell Brain Imaging Centre, McGill University, Montréal, Québec, Canada
| | - Jens T Rosenberg
- Advanced Magnetic Resonance Imaging and Spectroscopy Facility, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Taylor Salo
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lisa S Scott
- Department of Psychology, University of Florida, Gainesville, FL, USA
| | - Eunkyung Shin
- Department of Psychology, Pennsylvania State University, University Park, PA, USA
| | - Gizeaddis Simegn
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - W Kyle Simmons
- Department of Pharmacology and Physiology, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA; OSU Biomedical Imaging Center, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Barry J Tikalsky
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Jean Tkach
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jennifer Vannest
- Department of Communication Sciences and Disorders, University of Cincinnati, Cincinnati, OH, USA; Communication Sciences Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Yansong Zhao
- MR Clinical Science, Philips Healthcare, Cleveland, OH, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Institute of Child Development, University of Minnesota, Minneapolis, MN, USA.
| | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA; Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA; Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA.
| | - Jed T Elison
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Institute of Child Development, University of Minnesota, Minneapolis, MN, USA.
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Zimmermann M, Abbas Z, Sommer Y, Lewin A, Ramkiran S, Felder J, Worthoff WA, Oros-Peusquens AM, Yun SD, Shah NJ. QRAGE-Simultaneous multiparametric quantitative MRI of water content, T 1, T 2*, and magnetic susceptibility at ultrahigh field strength. Magn Reson Med 2024. [PMID: 39219160 DOI: 10.1002/mrm.30272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 07/26/2024] [Accepted: 08/10/2024] [Indexed: 09/04/2024]
Abstract
PURPOSE To introduce quantitative rapid gradient-echo (QRAGE), a novel approach for the simultaneous mapping of multiple quantitative MRI parameters, including water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength. METHODS QRAGE leverages a newly developed multi-echo MPnRAGE sequence, facilitating the acquisition of 171 distinct contrast images across a range of inversion and TE points. To maintain a short acquisition time, we introduce MIRAGE2, a novel model-based reconstruction method that exploits prior knowledge of temporal signal evolution, represented as damped complex exponentials. MIRAGE2 minimizes local Block-Hankel and Casorati matrices. Parameter maps are derived from the reconstructed contrast images through postprocessing steps. We validate QRAGE through extensive simulations, phantom studies, and in vivo experiments, demonstrating its capability for high-precision imaging. RESULTS In vivo brain measurements show the promising performance of QRAGE, with test-retest SDs and deviations from reference methods of < 0.8% for water content, < 17 ms for T1, and < 0.7 ms for T2*. QRAGE achieves whole-brain coverage at a 1-mm isotropic resolution in just 7 min and 15 s, comparable to the acquisition time of an MP2RAGE scan. In addition, QRAGE generates a contrast image akin to the UNI image produced by MP2RAGE. CONCLUSION QRAGE is a new, successful approach for simultaneously mapping multiple MR parameters at ultrahigh field.
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Affiliation(s)
- Markus Zimmermann
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
| | - Zaheer Abbas
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
| | - Yannic Sommer
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
| | - Alexander Lewin
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-11, Jülich, Germany
| | - Shukti Ramkiran
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Jörg Felder
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | - Wieland A Worthoff
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
| | | | - Seong Dae Yun
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
| | - N Jon Shah
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-4, Jülich, Germany
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine-11, Jülich, Germany
- JARA-BRAIN-Translational Medicine, Aachen, Germany
- Department of Neurology, RWTH Aachen University, Aachen, Germany
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Rivera-Rivera LA, Vikner T, Eisenmenger L, Johnson SC, Johnson KM. Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities. NMR IN BIOMEDICINE 2024; 37:e5082. [PMID: 38124351 PMCID: PMC11162953 DOI: 10.1002/nbm.5082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/03/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023]
Abstract
Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow.
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Affiliation(s)
- Leonardo A Rivera-Rivera
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Tomas Vikner
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Radiation Sciences, Radiation Physics and Biomedical Engineering, Umeå University, Umeå, Sweden
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Yablonski M, Zhou Z, Cao X, Schauman S, Liao C, Setsompop K, Yeatman JD. Fast and reliable quantitative measures of white matter development with magnetic resonance fingerprinting. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.26.600735. [PMID: 38979185 PMCID: PMC11230456 DOI: 10.1101/2024.06.26.600735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Developmental cognitive neuroscience aims to shed light on evolving relationships between brain structure and cognitive development. To this end, quantitative methods that reliably measure individual differences in brain tissue properties are fundamental. Standard qualitative MRI sequences are influenced by scan parameters and hardware-related biases, and also lack physical units, making the analysis of individual differences problematic. In contrast, quantitative MRI can measure physical properties of the tissue but with the cost of long scan durations and sensitivity to motion. This poses a critical limitation for studying young children. Here, we examine the reliability and validity of an efficient quantitative multiparameter mapping method - Magnetic Resonance Fingerprinting (MRF) - in children scanned longitudinally. We focus on T1 values in white matter, since quantitative T1 values are known to primarily reflect myelin content, a key factor in brain development. Forty-nine children aged 8-13y (mean 10.3y ±1.4) completed two scanning sessions 2-4 months apart. In each session, two 2-minute 3D-MRF scans at 1mm isotropic resolution were collected to evaluate the effect of scan duration on image quality and scan-rescan reliability. A separate calibration scan was used to measure B0 inhomogeneity and correct for bias. We examined the impact of scan time and B0 inhomogeneity correction on scan-rescan reliability of values in white matter, by comparing single 2-min and combined two 2-min scans, with and without B0-correction. Whole-brain voxel-based reliability analysis showed that combining two 2-min MRF scans improved reliability (pearson's r=0.87) compared with a single 2-min scan (r=0.84), while B0-correction had no effect on reliability in white matter (r=0.86 and 0.83 4-min vs 2-min). Using diffusion tractography, we delineated MRF-derived T1 profiles along major white matter fiber tracts and found similar or higher reliability for T1 from MRF compared to diffusion parameters (based on a 10-minute dMRI scan). Lastly, we found that T1 values in multiple white matter tracts were significantly correlated with age. In sum, MRF-derived T1 values were highly reliable in a longitudinal sample of children and replicated known age effects. Reliability in white matter was improved by longer scan duration but was not affected by B0-correction, making it a quick and straightforward scan to collect. We propose that MRF provides a promising avenue for acquiring quantitative brain metrics in children and patient populations where scan time and motion are of particular concern.
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Zong F, Wang L, Liu H, Xue B, Bai R, Liu Y. A genetic optimisation and iterative reconstruction framework for sparse multi-dimensional diffusion-relaxation correlation MRI. Comput Biol Med 2024; 175:108508. [PMID: 38678941 DOI: 10.1016/j.compbiomed.2024.108508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 04/11/2024] [Accepted: 04/21/2024] [Indexed: 05/01/2024]
Abstract
Multi-dimensional diffusion-relaxation correlation (DRC) magnetic resonance imaging (MRI) techniques have recently been developed to investigate tissue microstructures. Sub-voxel tissue heterogeneity is resolved from the local correlation distributions of relaxation time and molecular diffusivity. However, the implementation of these techniques considerably increases the total acquisition time, and simply reducing the scan time may be at the expense of detailed structural resolution. To overcome these limitations, an optimised framework was proposed for acquiring microstructural maps of the human brain on a clinically feasible timescale. First, the acquisition parameters of the multi-dimensional DRC MRI method were sparsely optimised using a genetic algorithm with a fitness function according to the spectral resolution of the correlation map, hardware requirements, and total scan time. Next, the acquired DRC MRI data were processed using a proposed numerical algorithm based on the dynamic inverse Laplace transform (ILT). Prior knowledge from one-dimensional data was then utilised in the iterative procedure to improve the spectral resolution. Finally, the proposed framework was validated using Monte Carlo simulations and experimental data acquired from healthy participants on an MRI scanner. The results demonstrated that the suggested approach is feasible for offering high-resolution DRC maps that correspond to distinct microstructures with a limited amount of optimised acquisition data from two-dimensional DRC sampling space. By significantly reducing scan time while retaining structural resolution, this approach may enable multi-dimensional DRC MRI to be more widely used for quantitative evaluation in biological and medical settings.
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Affiliation(s)
- Fangrong Zong
- School of Artificial Intelligence, Beijing University of Post and Telecommunication, Beijing, 100876, China.
| | - Lixian Wang
- Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Huabing Liu
- Beijing Limecho Technology Co., Ltd., Beijing, 102200, China
| | - Bing Xue
- School of Engineering and Computer Science, Victoria University of Wellington, Victoria, 6140, New Zealand
| | - Ruiliang Bai
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310020, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310030, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Post and Telecommunication, Beijing, 100876, China.
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Jun Y, Arefeen Y, Cho J, Fujita S, Wang X, Ellen Grant P, Gagoski B, Jaimes C, Gee MS, Bilgic B. Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS. Magn Reson Med 2024; 91:2459-2482. [PMID: 38282270 PMCID: PMC11005062 DOI: 10.1002/mrm.30018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 12/15/2023] [Accepted: 01/06/2024] [Indexed: 01/30/2024]
Abstract
PURPOSE To develop and evaluate methods for (1) reconstructing 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) time-series images using a low-rank subspace method, which enables accurate and rapid T1 and T2 mapping, and (2) improving the fidelity of subspace QALAS by combining scan-specific deep-learning-based reconstruction and subspace modeling. THEORY AND METHODS A low-rank subspace method for 3D-QALAS (i.e., subspace QALAS) and zero-shot deep-learning subspace method (i.e., Zero-DeepSub) were proposed for rapid and high fidelity T1 and T2 mapping and time-resolved imaging using 3D-QALAS. Using an ISMRM/NIST system phantom, the accuracy and reproducibility of the T1 and T2 maps estimated using the proposed methods were evaluated by comparing them with reference techniques. The reconstruction performance of the proposed subspace QALAS using Zero-DeepSub was evaluated in vivo and compared with conventional QALAS at high reduction factors of up to nine-fold. RESULTS Phantom experiments showed that subspace QALAS had good linearity with respect to the reference methods while reducing biases and improving precision compared to conventional QALAS, especially for T2 maps. Moreover, in vivo results demonstrated that subspace QALAS had better g-factor maps and could reduce voxel blurring, noise, and artifacts compared to conventional QALAS and showed robust performance at up to nine-fold acceleration with Zero-DeepSub, which enabled whole-brain T1, T2, and PD mapping at 1 mm isotropic resolution within 2 min of scan time. CONCLUSION The proposed subspace QALAS along with Zero-DeepSub enabled high fidelity and rapid whole-brain multiparametric quantification and time-resolved imaging.
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Affiliation(s)
- Yohan Jun
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Yamin Arefeen
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas, Austin, TX, United States
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Shohei Fujita
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Xiaoqing Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - P. Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Camilo Jaimes
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
| | - Michael S. Gee
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States
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Surgent O, Guerrero-Gonzalez J, Dean DC, Adluru N, Kirk GR, Kecskemeti SR, Alexander AL, Li JJ, Travers BG. Microstructural neural correlates of maximal grip strength in autistic children: the role of the cortico-cerebellar network and attention-deficit/hyperactivity disorder features. Front Integr Neurosci 2024; 18:1359099. [PMID: 38808069 PMCID: PMC11130426 DOI: 10.3389/fnint.2024.1359099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 04/24/2024] [Indexed: 05/30/2024] Open
Abstract
Introduction Maximal grip strength, a measure of how much force a person's hand can generate when squeezing an object, may be an effective method for understanding potential neurobiological differences during motor tasks. Grip strength in autistic individuals may be of particular interest due to its unique developmental trajectory. While autism-specific differences in grip-brain relationships have been found in adult populations, it is possible that such differences in grip-brain relationships may be present at earlier ages when grip strength is behaviorally similar in autistic and non-autistic groups. Further, such neural differences may lead to the later emergence of diagnostic-group grip differences in adolescence. The present study sought to examine this possibility, while also examining if grip strength could elucidate the neuro-motor sources of phenotypic heterogeneity commonly observed within autism. Methods Using high resolution, multi-shell diffusion, and quantitative R1 relaxometry imaging, this study examined how variations in key sensorimotor-related white matter pathways of the proprioception input, lateral grasping, cortico-cerebellar, and corticospinal networks were associated with individual variations in grip strength in 68 autistic children and 70 non-autistic (neurotypical) children (6-11 years-old). Results In both groups, results indicated that stronger grip strength was associated with higher proprioceptive input, lateral grasping, and corticospinal (but not cortico-cerebellar modification) fractional anisotropy and R1, indirect measures concordant with stronger microstructural coherence and increased myelination. Diagnostic group differences in these grip-brain relationships were not observed, but the autistic group exhibited more variability particularly in the cortico-cerebellar modification indices. An examination into the variability within the autistic group revealed that attention-deficit/hyperactivity disorder (ADHD) features moderated the relationships between grip strength and both fractional anisotropy and R1 relaxometry in the premotor-primary motor tract of the lateral grasping network and the cortico-cerebellar network tracts. Specifically, in autistic children with elevated ADHD features (60% of the autistic group) stronger grip strength was related to higher fractional anisotropy and R1 of the cerebellar modification network (stronger microstructural coherence and more myelin), whereas the opposite relationship was observed in autistic children with reduced ADHD features. Discussion Together, this work suggests that while the foundational elements of grip strength are similar across school-aged autistic and non-autistic children, neural mechanisms of grip strength within autistic children may additionally depend on the presence of ADHD features. Specifically, stronger, more coherent connections of the cerebellar modification network, which is thought to play a role in refining and optimizing motor commands, may lead to stronger grip in children with more ADHD features, weaker grip in children with fewer ADHD features, and no difference in grip in non-autistic children. While future research is needed to understand if these findings extend to other motor tasks beyond grip strength, these results have implications for understanding the biological basis of neuromotor control in autistic children and emphasize the importance of assessing co-occurring conditions when evaluating brain-behavior relationships in autism.
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Affiliation(s)
- Olivia Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
| | - Jose Guerrero-Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Gregory R. Kirk
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | | | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - James J. Li
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Psychology Department, University of Wisconsin-Madison, Madison, WI, United States
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Occupational Therapy Program in the Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States
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9
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Travers BG, Surgent O, Guerrero-Gonzalez J, Dean DC, Adluru N, Kecskemeti SR, Kirk GR, Alexander AL, Zhu J, Skaletski EC, Naik S, Duran M. Role of autonomic, nociceptive, and limbic brainstem nuclei in core autism features. Autism Res 2024; 17:266-279. [PMID: 38278763 PMCID: PMC10922575 DOI: 10.1002/aur.3096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024]
Abstract
Although multiple theories have speculated about the brainstem reticular formation's involvement in autistic behaviors, the in vivo imaging of brainstem nuclei needed to test these theories has proven technologically challenging. Using methods to improve brainstem imaging in children, this study set out to elucidate the role of the autonomic, nociceptive, and limbic brainstem nuclei in the autism features of 145 children (74 autistic children, 6.0-10.9 years). Participants completed an assessment of core autism features and diffusion- and T1-weighted imaging optimized to improve brainstem images. After data reduction via principal component analysis, correlational analyses examined associations among autism features and the microstructural properties of brainstem clusters. Independent replication was performed in 43 adolescents (24 autistic, 13.0-17.9 years). We found specific nuclei, most robustly the parvicellular reticular formation-alpha (PCRtA) and to a lesser degree the lateral parabrachial nucleus (LPB) and ventral tegmental parabrachial pigmented complex (VTA-PBP), to be associated with autism features. The PCRtA and some of the LPB associations were independently found in the replication sample, but the VTA-PBP associations were not. Consistent with theoretical perspectives, the findings suggest that individual differences in pontine reticular formation nuclei contribute to the prominence of autistic features. Specifically, the PCRtA, a nucleus involved in mastication, digestion, and cardio-respiration in animal models, was associated with social communication in children, while the LPB, a pain-network nucleus, was associated with repetitive behaviors. These findings highlight the contributions of key autonomic brainstem nuclei to the expression of core autism features.
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Affiliation(s)
- Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Kinesiology, Occupational Therapy Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Olivia Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Jose Guerrero-Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Gregory R. Kirk
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Jun Zhu
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
| | - Emily C. Skaletski
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Kinesiology, Occupational Therapy Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Sonali Naik
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Monica Duran
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
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10
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Cho J, Gagoski B, Kim TH, Wang F, Manhard MK, Dean D, Kecskemeti S, Caprihan A, Lo WC, Splitthoff DN, Liu W, Polak D, Cauley S, Setsompop K, Grant PE, Bilgic B. Time-efficient, high-resolution 3T whole-brain relaxometry using 3D-QALAS with wave-CAIPI readouts. Magn Reson Med 2024; 91:630-639. [PMID: 37705496 DOI: 10.1002/mrm.29865] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/16/2023] [Accepted: 08/25/2023] [Indexed: 09/15/2023]
Abstract
PURPOSE Volumetric, high-resolution, quantitative mapping of brain-tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time-efficient wave-controlled aliasing in parallel imaging (wave-CAIPI) readouts with the 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS), enabling full-brain quantitative T1 , T2 , and proton density (PD) maps at 1.15-mm3 isotropic voxels in 3 min. METHODS Wave-CAIPI readouts were embedded in the standard 3D-QALAS encoding scheme, enabling full-brain quantitative parameter maps (T1 , T2 , and PD) at acceleration factors of R = 3 × 2 with minimum SNR loss due to g-factor penalties. The quantitative parameter maps were estimated using a dictionary-based mapping algorithm incorporating inversion efficiency and B1 -field inhomogeneity effects. The parameter maps using the accelerated protocol were quantitatively compared with those obtained from the conventional 3D-QALAS sequence using GRAPPA acceleration of R = 2 in the ISMRM/NIST phantom, and in 10 healthy volunteers. RESULTS When tested in both the ISMRM/NIST phantom and 10 healthy volunteers, the quantitative maps using the accelerated protocol showed excellent agreement against those obtained from conventional 3D-QALAS at RGRAPPA = 2. CONCLUSION Three-dimensional QALAS enhanced with wave-CAIPI readouts enables time-efficient, full-brain quantitative T1 , T2 , and PD mapping at 1.15 mm3 in 3 min at R = 3 × 2 acceleration. The quantitative maps obtained from the accelerated wave-CAIPI 3D-QALAS protocol showed very similar values to those from the standard 3D-QALAS (R = 2) protocol, alluding to the robustness and reliability of the proposed method.
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Affiliation(s)
- Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Tae Hyung Kim
- Department of Computer Engineering, Hongik University, Seoul, South Korea
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mary Kate Manhard
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Douglas Dean
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Steven Kecskemeti
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Wei-Ching Lo
- Siemens Medical Solutions USA, Inc., Charlestown, Massachusetts, USA
| | | | - Wei Liu
- Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Stephen Cauley
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Patricia Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard/MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
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11
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Aggarwal N, Oler JA, Tromp DPM, Roseboom PH, Riedel MK, Elam VR, Brotman MA, Kalin NH. A preliminary study of the effects of an antimuscarinic agent on anxious behaviors and white matter microarchitecture in nonhuman primates. Neuropsychopharmacology 2024; 49:405-413. [PMID: 37516801 PMCID: PMC10724160 DOI: 10.1038/s41386-023-01686-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 07/31/2023]
Abstract
Myelination subserves efficient neuronal communication, and alterations in white matter (WM) microstructure have been implicated in numerous psychiatric disorders, including pathological anxiety. Recent work in rodents suggests that muscarinic antagonists may enhance myelination with behavioral benefits; however, the neural and behavioral effects of muscarinic antagonists have yet to be explored in non-human primates (NHP). Here, as a potentially translatable therapeutic strategy for human pathological anxiety, we present data from a first-in-primate study exploring the effects of the muscarinic receptor antagonist solifenacin on anxious behaviors and WM microstructure. 12 preadolescent rhesus macaques (6 vehicle control, 6 experimental; 8F, 4M) were included in a pre-test/post-test between-group study design. The experimental group received solifenacin succinate for ~60 days. Subjects underwent pre- and post-assessments of: 1) anxious temperament (AT)-related behaviors in the potentially threatening no-eye-contact (NEC) paradigm (30-min); and 2) WM and regional brain metabolism imaging metrics, including diffusion tensor imaging (DTI), quantitative relaxometry (QR), and FDG-PET. In relation to anxiety-related behaviors expressed during the NEC, significant Group (vehicle control vs. solifenacin) by Session (pre vs. post) interactions were found for freezing, cooing, and locomotion. Compared to vehicle controls, solifenacin-treated subjects exhibited effects consistent with reduced anxiety, specifically decreased freezing duration, increased locomotion duration, and increased cooing frequency. Furthermore, the Group-by-Session-by-Sex interaction indicated that these effects occurred predominantly in the males. Exploratory whole-brain voxelwise analyses of post-minus-pre differences in DTI, QR, and FDG-PET metrics revealed some solifenacin-related changes in WM microstructure and brain metabolism. These findings in NHPs support the further investigation of the utility of antimuscarinic agents in targeting WM microstructure as a means to treat pathological anxiety.
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Affiliation(s)
- Nakul Aggarwal
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA.
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Do P M Tromp
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Patrick H Roseboom
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Marissa K Riedel
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Victoria R Elam
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
| | - Melissa A Brotman
- Neuroscience and Novel Therapeutics Unit, National Institute of Mental Health, Bethesda, MD, 20892, USA
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA
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12
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Jun Y, Cho J, Wang X, Gee M, Grant PE, Bilgic B, Gagoski B. SSL-QALAS: Self-Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D-QALAS. Magn Reson Med 2023; 90:2019-2032. [PMID: 37415389 PMCID: PMC10527557 DOI: 10.1002/mrm.29786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/27/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023]
Abstract
PURPOSE To develop and evaluate a method for rapid estimation of multiparametric T1 , T2 , proton density, and inversion efficiency maps from 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) measurements using self-supervised learning (SSL) without the need for an external dictionary. METHODS An SSL-based QALAS mapping method (SSL-QALAS) was developed for rapid and dictionary-free estimation of multiparametric maps from 3D-QALAS measurements. The accuracy of the reconstructed quantitative maps using dictionary matching and SSL-QALAS was evaluated by comparing the estimated T1 and T2 values with those obtained from the reference methods on an International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom. The SSL-QALAS and the dictionary-matching methods were also compared in vivo, and generalizability was evaluated by comparing the scan-specific, pre-trained, and transfer learning models. RESULTS Phantom experiments showed that both the dictionary-matching and SSL-QALAS methods produced T1 and T2 estimates that had a strong linear agreement with the reference values in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom. Further, SSL-QALAS showed similar performance with dictionary matching in reconstructing the T1 , T2 , proton density, and inversion efficiency maps on in vivo data. Rapid reconstruction of multiparametric maps was enabled by inferring the data using a pre-trained SSL-QALAS model within 10 s. Fast scan-specific tuning was also demonstrated by fine-tuning the pre-trained model with the target subject's data within 15 min. CONCLUSION The proposed SSL-QALAS method enabled rapid reconstruction of multiparametric maps from 3D-QALAS measurements without an external dictionary or labeled ground-truth training data.
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Affiliation(s)
- Yohan Jun
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Xiaoqing Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Michael Gee
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
| | - P. Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
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13
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Chen Y, Holmes JH, Corum C, Magnotta V, Jacob M. DEEP FACTOR MODEL: A NOVEL APPROACH FOR MOTION COMPENSATED MULTI-DIMENSIONAL MRI. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2023; 2023:10.1109/isbi53787.2023.10230725. [PMID: 38738186 PMCID: PMC11087023 DOI: 10.1109/isbi53787.2023.10230725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Abstract
Recent quantitative parameter mapping methods including MR fingerprinting (MRF) collect a time series of images that capture the evolution of magnetization. The focus of this work is to introduce a novel approach termed as Deep Factor Model(DFM), which offers an efficient representation of the multi-contrast image time series. The higher efficiency of the representation enables the acquisition of the images in a highly undersampled fashion, which translates to reduced scan time in 3D high-resolution multi-contrast applications. The approach integrates motion estimation and compensation, making the approach robust to subject motion during the scan.
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14
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Iyer SS, Schauman SS, Sandino CM, Yurt M, Cao X, Liao C, Ruengchaijatuporn N, Chatnuntawech I, Tong E, Setsompop K. Deep Learning Initialized Compressed Sensing (Deli-CS) in Volumetric Spatio-Temporal Subspace Reconstruction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.28.534431. [PMID: 37034586 PMCID: PMC10081201 DOI: 10.1101/2023.03.28.534431] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Introduction Spatio-temporal MRI methods enable whole-brain multi-parametric mapping at ultra-fast acquisition times through efficient k-space encoding, but can have very long reconstruction times, which limit their integration into clinical practice. Deep learning (DL) is a promising approach to accelerate reconstruction, but can be computationally intensive to train and deploy due to the large dimensionality of spatio-temporal MRI. DL methods also need large training data sets and can produce results that don't match the acquired data if data consistency is not enforced. The aim of this project is to reduce reconstruction time using DL whilst simultaneously limiting the risk of deep learning induced hallucinations, all with modest hardware requirements. Methods Deep Learning Initialized Compressed Sensing (Deli-CS) is proposed to reduce the reconstruction time of iterative reconstructions by "kick-starting" the iterative reconstruction with a DL generated starting point. The proposed framework is applied to volumetric multi-axis spiral projection MRF that achieves whole-brain T1 and T2 mapping at 1-mm isotropic resolution for a 2-minute acquisition. First, the traditional reconstruction is optimized from over two hours to less than 40 minutes while using more than 90% less RAM and only 4.7 GB GPU memory, by using a memory-efficient GPU implementation. The Deli-CS framework is then implemented and evaluated against the above reconstruction. Results Deli-CS achieves comparable reconstruction quality with 50% fewer iterations bringing the full reconstruction time to 20 minutes. Conclusion Deli-CS reduces the reconstruction time of subspace reconstruction of volumetric spatio-temporal acquisitions by providing a warm start to the iterative reconstruction algorithm.
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Affiliation(s)
- Siddharth S. Iyer
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, MA, USA
- Department of Radiology, Stanford University, CA, USA
| | | | | | - Mahmut Yurt
- Department of Electrical Engineering, Stanford University, CA, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, CA, USA
| | - Congyu Liao
- Department of Radiology, Stanford University, CA, USA
| | - Natthanan Ruengchaijatuporn
- Center of Excellence in Computational Molecular Biology, Chulalongkorn University, Bangkok, Thailand
- Center for Artificial Intelligence in Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Itthi Chatnuntawech
- National Nanotechnology Center, National Science and Technology Development Agency, Pathum Thani, Thailand
| | | | - Kawin Setsompop
- Department of Radiology, Stanford University, CA, USA
- Department of Electrical Engineering, Stanford University, CA, USA
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15
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Solomon E, Lotan E, Zan E, Sodickson DK, Block KT, Chandarana H. MP-RAVE: IR-Prepared T 1 -Weighted Radial Stack-of-Stars 3D GRE imaging with retrospective motion correction. Magn Reson Med 2023; 90:202-210. [PMID: 36763847 DOI: 10.1002/mrm.29614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/17/2022] [Accepted: 01/24/2023] [Indexed: 02/12/2023]
Abstract
PURPOSE To describe an inversion-recovery T1 -weighted radial stack-of-stars 3D gradient echo (GRE) sequence with comparable image quality to conventional MP-RAGE and to demonstrate how the radial acquisition scheme can be utilized for additional retrospective motion correction to improve robustness to head motion. METHODS The proposed sequence, named MP-RAVE, has been derived from a previously described radial stack-of-stars 3D GRE sequence (RAVE) and includes a 180° inversion recovery pulse that is generated once for every stack of radial views. The sequence is combined with retrospective 3D motion correction to improve robustness. The effectiveness has been evaluated in phantoms and healthy volunteers and compared to conventional MP-RAGE acquisition. RESULTS MP-RAGE and MP-RAVE anatomical images were rated "good" to "excellent" in overall image quality, with artifact level between "mild" and "no artifacts", and with no statistically significant difference between methods. During head motion, MP-RAVE showed higher inherent robustness with artifacts confined to local brain regions. In combination with motion correction, MP-RAVE provided noticeably improved image quality during different head motion and showed statistically significant improvement in image sharpness. CONCLUSION MP-RAVE provides comparable image quality and contrast to conventional MP-RAGE with improved robustness to head motion. In combination with retrospective 3D motion correction, MP-RAVE can be a useful alternative to MP-RAGE, especially in non-cooperative or pediatric patients.
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Affiliation(s)
- Eddy Solomon
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, University Grossman School of Medicine, New York, New York, USA
| | - Eyal Lotan
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, University Grossman School of Medicine, New York, New York, USA
| | - Elcin Zan
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, University Grossman School of Medicine, New York, New York, USA
| | - Daniel K Sodickson
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, University Grossman School of Medicine, New York, New York, USA
| | - Kai Tobias Block
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, University Grossman School of Medicine, New York, New York, USA
| | - Hersh Chandarana
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, University Grossman School of Medicine, New York, New York, USA
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16
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Ma YJ, Moazamian D, Cornfeld DM, Condron P, Holdsworth SJ, Bydder M, Du J, Bydder GM. Improving the understanding and performance of clinical MRI using tissue property filters and the central contrast theorem, MASDIR pulse sequences and synergistic contrast MRI. Quant Imaging Med Surg 2022; 12:4658-4690. [PMID: 36060593 PMCID: PMC9403590 DOI: 10.21037/qims-22-394] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 05/31/2022] [Indexed: 01/05/2023]
Abstract
This paper updates and extends three previous papers on tissue property filters (TP-filters), Multiplied, Added, Divided and/or Subtracted Inversion Recovery (MASTIR) pulse sequences and synergistic contrast MRI (scMRI). It does this by firstly adding the central contrast theorem (CCT) to TP-filters, secondly including division with MASTIR sequences to make them Multiplied, Added, Subtracted and/or Divided IR (MASDIR) sequences, and thirdly incorporating division into the image processing needed for scMR to increase synergistic T1 contrast. These updated concepts are then used to explain and improve contrast at tissue boundaries, as well as to develop imaging regimes to detect and monitor small changes to the brain over time and quantify T1. The CCT is in two parts: the first part states that contrast produced by each TP is the product of the change in TP multiplied by the TP sequence weighting which is the first partial derivative of the TP-filter. The second part states that the overall fractional contrast is the algebraic sum of the fractional contrasts produced by each of the TPs. Subtraction of two IR sequences alone about doubles contrast relative to a conventional single IR sequence. Division of this subtraction can amplify contrast 5-15 times compared with conventional IR sequences. Dividing sequences can be problematic in areas where the signal is zero but this is avoided by dividing the difference in signal of two magnitude reconstructed IR sequences by the sum of their signals. The basis for the production of high contrast, high spatial resolution boundaries at white-gray matter junctions, between cerebral cortex and cerebrospinal fluid (CSF) and at other sites with subtracted IR (SIR) and divided subtracted IR (dSIR) sequences is explained and examples are shown. A key concept is the tissue fraction f, which is the proportion of a tissue in a mixture of two tissues within a voxel. Contrast at boundaries is a function of the partial derivative of the TP-filter, the partial derivative of the relevant TP with respect to f, and the partial derivative of f with respect to distance, x. Location of tissue boundaries is important for segmentation and is helpful in determining if inversion times have been chosen correctly. In small change regimes, the high sensitivity to small changes in T1 provided by dSIR images, together with the high definition boundaries, afford mechanisms for detecting small changes due to contrast agents, disease, perfusion and other causes. 3D isotropic rigid body registration provides a technique for following these changes over time in serial studies. Images showing high lesion contrast, high definition tissue and fluid boundaries, and the detection of small changes are included. T1 maps can be created by linearly scaling dSIR images.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Dina Moazamian
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Daniel M. Cornfeld
- Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand;,Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Paul Condron
- Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand;,Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Samantha J. Holdsworth
- Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand;,Department of Anatomy and Medical Imaging and Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Mark Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jiang Du
- Department of Radiology, University of California San Diego, San Diego, CA, USA;,Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA;,Department of Bioengineering, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA;,Mātai Medical Research Institute, Tairāwhiti-Gisborne, New Zealand
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17
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Grupe DW, Barnes AL, Gresham L, Kirvin-Quamme A, Nord E, Alexander AL, Abercrombie HC, Schaefer SM, Davidson RJ. Perceived stress associations with hippocampal-dependent behavior and hippocampal subfield volume. Neurobiol Stress 2022; 19:100469. [PMID: 35859546 PMCID: PMC9289864 DOI: 10.1016/j.ynstr.2022.100469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/13/2022] [Accepted: 07/05/2022] [Indexed: 12/04/2022] Open
Abstract
Background Individual differences in stress appraisals influence trajectories of risk and resilience following exposure to chronic and acute stressors. Smaller hippocampal volume may contribute to elevated stress appraisals via deficient pattern separation, a process depending on dentate gyrus (DG)/CA3 hippocampal subfields. Here, we investigated links between perceived stress, DG/CA3 volume, and behavioral pattern separation to test hypothesized mechanisms underlying stress-related psychopathology. Methods We collected the Perceived Stress Scale (PSS) and ratings of subjective stress reactivity during the Trier Social Stress Test (TSST) from 71 adult community participants. We obtained high-resolution T2 MRI scans and used Automatic Segmentation of Hippocampal Subfields to estimate DG/CA3 volume in 56 of these participants. Participants completed the mnemonic similarity task, which provides a behavioral index of pattern separation. Analyses investigated associations between perceived stress, DG/CA3 volume, and behavioral pattern separation, controlling for age, gender, hemisphere, and intracranial volume. Results Greater PSS scores and TSST subjective stress reactivity were each independently related to poorer behavioral pattern separation, together accounting for 15% of variance in behavioral performance in a simultaneous regression. Contrary to hypotheses, DG/CA3 volume was not associated with either stress measure, although exploratory analyses suggested a link between hippocampal volume asymmetry and PSS scores. Conclusions We observed novel associations between laboratory and questionnaire measures of perceived stress and a behavioral assay of pattern separation. Additional work is needed to clarify the involvement of the hippocampus in this stress-behavior relationship and determine the relevance of behavioral pattern separation for stress-related disorders.
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Affiliation(s)
- Daniel W Grupe
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA.,University of Wisconsin-Madison Waisman Laboratory for Brain Imaging and Behavior, 1500 Highland Ave, Madison, WI, 53705, USA
| | - Alexandra L Barnes
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA
| | - Lauren Gresham
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA
| | - Andrew Kirvin-Quamme
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA
| | - Elizabeth Nord
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA
| | - Andrew L Alexander
- University of Wisconsin-Madison Waisman Laboratory for Brain Imaging and Behavior, 1500 Highland Ave, Madison, WI, 53705, USA.,University of Wisconsin-Madison Department of Medical Physics, 1111 Highland Ave, Madison, WI, 53705, USA.,University of Wisconsin-Madison Department of Psychiatry, 6001 Research Park Blvd, Madison, WI, 53719, USA
| | - Heather C Abercrombie
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA.,University of Wisconsin-Madison Waisman Laboratory for Brain Imaging and Behavior, 1500 Highland Ave, Madison, WI, 53705, USA
| | - Stacey M Schaefer
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA.,University of Wisconsin-Madison Waisman Laboratory for Brain Imaging and Behavior, 1500 Highland Ave, Madison, WI, 53705, USA
| | - Richard J Davidson
- University of Wisconsin-Madison Center for Healthy Minds, 625 W Washington Ave, Madison, WI, 53703, USA.,University of Wisconsin-Madison Waisman Laboratory for Brain Imaging and Behavior, 1500 Highland Ave, Madison, WI, 53705, USA.,University of Wisconsin-Madison Department of Psychiatry, 6001 Research Park Blvd, Madison, WI, 53719, USA.,University of Wisconsin-Madison Department of Psychology, 1202 W Johnson St, Madison, WI, 53706, USA
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18
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Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images. NEUROIMAGE: REPORTS 2022; 2. [PMID: 36032692 PMCID: PMC9409374 DOI: 10.1016/j.ynirp.2022.100086] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background and purpose: Large MRI studies often pool data gathered from widely varying imaging sequences. Pooled data creates a potential source of variation in structural analyses which may cause misinterpretation of findings. The purpose of this study is to determine if data acquired using different scan sequences, head coils and scanners offers consistent structural measurements. Materials and methods: Participants (163 right-handed males: 82 typically developing controls, 81 participants with autism spectrum disorder) were scanned on the same day using an MPRAGE sequence with a 12-channel headcoil on a Siemens 3T Trio scanner and an MP2RAGE sequence with a 64-channel headcoil on a Siemens 3T Prisma scanner. Segmentation was performed using FreeSurfer to identify regions exhibiting variation between sequences on measures of volume, surface area, and cortical thickness. Intraclass correlation coefficient (ICC) and mean percent difference (MPD) were used as test-retest reproducibility measures. Results: ICC for total brain segmented volume yielded a 0.99 intraclass correlation, demonstrating high overall volumetric reproducibility. Comparison of individual regions of interest resulted in greater variation. Volumetric variability, although low overall, was greatest in the entorhinal cortex (ICC = 0.71), frontal (ICC = 0.60) and temporal (ICC = 0.60) poles. Surface area variability was greatest in the insula (ICC = 0.65), temporal (ICC = 0.64) and frontal (ICC = 0.68) poles. Cortical thickness was most variable in the frontal (ICC = 0.41) and temporal (ICC = 0.35) poles. Conclusion: Data collected on different scanners and head coils using MPRAGE and MP2RAGE are generally consistent for surface area and volume estimates. However, regional variability may constrain accuracy in some regions and cortical thickness measurements exhibit higher generalized variability.
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19
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Moody JF, Aggarwal N, Dean DC, Tromp DPM, Kecskemeti SR, Oler JA, Kalin NH, Alexander AL. Longitudinal assessment of early-life white matter development with quantitative relaxometry in nonhuman primates. Neuroimage 2022; 251:118989. [PMID: 35151851 PMCID: PMC8940652 DOI: 10.1016/j.neuroimage.2022.118989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 01/13/2022] [Accepted: 02/09/2022] [Indexed: 12/01/2022] Open
Abstract
Alterations in white matter (WM) development are associated with many neuropsychiatric and neurodevelopmental disorders. Most MRI studies examining WM development employ diffusion tensor imaging (DTI), which relies on estimating diffusion patterns of water molecules as a reflection of WM microstructure. Quantitative relaxometry, an alternative method for characterizing WM microstructural changes, is based on molecular interactions associated with the magnetic relaxation of protons. In a longitudinal study of 34 infant non-human primates (NHP) (Macaca mulatta) across the first year of life, we implement a novel, high-resolution, T1-weighted MPnRAGE sequence to examine WM trajectories of the longitudinal relaxation rate (qR1) in relation to DTI metrics and gestational age at scan. To the best of our knowledge, this is the first study to assess developmental WM trajectories in NHPs using quantitative relaxometry and the first to directly compare DTI and relaxometry metrics during infancy. We demonstrate that qR1 exhibits robust logarithmic growth, unfolding in a posterior-anterior and medial-lateral fashion, similar to DTI metrics. On a within-subject level, DTI metrics and qR1 are highly correlated, but are largely unrelated on a between-subject level. Unlike DTI metrics, gestational age at birth (time in utero) is a strong predictor of early postnatal qR1 levels. Whereas individual differences in DTI metrics are maintained across the first year of life, this is not the case for qR1. These results point to the similarities and differences in using quantitative relaxometry and DTI in developmental studies, providing a basis for future studies to characterize the unique processes that these measures reflect at the cellular and molecular level.
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Affiliation(s)
- Jason F Moody
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States.
| | - Nakul Aggarwal
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Douglas C Dean
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Department of Pediatrics, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Do P M Tromp
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Steve R Kecskemeti
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Andrew L Alexander
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
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20
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Saiote C, Sutter E, Xenopoulos-Oddsson A, Rao R, Georgieff M, Rudser K, Peyton C, Dean D, McAdams RM, Gillick B. Study Protocol: Multimodal Longitudinal Assessment of Infant Brain Organization and Recovery in Perinatal Brain Injury. Pediatr Phys Ther 2022; 34:268-276. [PMID: 35385465 PMCID: PMC9200232 DOI: 10.1097/pep.0000000000000886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE Perinatal brain injury is a primary cause of cerebral palsy, a condition resulting in lifelong motor impairment. Infancy is an important period of motor system development, including development of the corticospinal tract (CST), the primary pathway for cortical movement control. The interaction between perinatal stroke recovery, CST organization, and resultant motor outcome in infants is not well understood. METHODS Here, we present a protocol for multimodal longitudinal assessment of brain development and motor function following perinatal brain injury using transcranial magnetic stimulation and magnetic resonance imaging to noninvasively measure CST functional and structural integrity across multiple time points in infants 3 to 24 months of age. We will further assess the association between cortical excitability, integrity, and motor function. DISCUSSION This protocol will identify bioindicators of motor outcome and neuroplasticity and subsequently inform early detection, diagnosis, and intervention strategies for infants with perinatal stroke, brain bleeds, and related diagnoses.
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Affiliation(s)
- Catarina Saiote
- Waisman Center (Drs Saiote, Sutter, Dean, and Gillick), Department of Pediatrics (Drs Dean, McAdams, and Gillick), and Department of Medical Physics (Dr Dean), University of Wisconsin-Madison, Madison, Wisconsin; Department of Rehabilitation Medicine (Dr Sutter and Ms Xenopoulos-Oddsson), Department of Pediatrics (Drs Rao and Georgieff), and Division of Biostatistics (Dr Rudser), University of Minnesota, Minneapolis, Minnesota; Department of Physical Therapy and Human Movement Sciences, Department of Pediatrics (Dr Peyton), Northwestern University, Chicago, Illinois
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21
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Guerrero-Gonzalez J, Surgent O, Adluru N, Kirk GR, Dean III DC, Kecskemeti SR, Alexander AL, Travers BG. Improving Imaging of the Brainstem and Cerebellum in Autistic Children: Transformation-Based High-Resolution Diffusion MRI (TiDi-Fused) in the Human Brainstem. Front Integr Neurosci 2022; 16:804743. [PMID: 35310466 PMCID: PMC8928227 DOI: 10.3389/fnint.2022.804743] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/31/2022] [Indexed: 11/24/2022] Open
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) of the brainstem is technically challenging, especially in young autistic children as nearby tissue-air interfaces and motion (voluntary and physiological) can lead to artifacts. This limits the availability of high-resolution images, which are desirable for improving the ability to study brainstem structures. Furthermore, inherently low signal-to-noise ratios, geometric distortions, and sensitivity to motion not related to molecular diffusion have resulted in limited techniques for high-resolution data acquisition compared to other modalities such as T1-weighted imaging. Here, we implement a method for achieving increased apparent spatial resolution in pediatric dMRI that hinges on accurate geometric distortion correction and on high fidelity within subject image registration between dMRI and magnetization prepared rapid acquisition gradient echo (MPnRAGE) images. We call this post-processing pipeline T1 weighted-diffusion fused, or "TiDi-Fused". Data used in this work consists of dMRI data (2.4 mm resolution, corrected using FSL's Topup) and T1-weighted (T1w) MPnRAGE anatomical data (1 mm resolution) acquired from 128 autistic and non-autistic children (ages 6-10 years old). Accurate correction of geometric distortion permitted for a further increase in apparent resolution of the dMRI scan via boundary-based registration to the MPnRAGE T1w. Estimation of fiber orientation distributions and further analyses were carried out in the T1w space. Data processed with the TiDi-Fused method were qualitatively and quantitatively compared to data processed with conventional dMRI processing methods. Results show the advantages of the TiDi-Fused pipeline including sharper brainstem gray-white matter tissue contrast, improved inter-subject spatial alignment for group analyses of dMRI based measures, accurate spatial alignment with histology-based imaging of the brainstem, reduced variability in brainstem-cerebellar white matter tracts, and more robust biologically plausible relationships between age and brainstem-cerebellar white matter tracts. Overall, this work identifies a promising pipeline for achieving high-resolution imaging of brainstem structures in pediatric and clinical populations who may not be able to endure long scan times. This pipeline may serve as a gateway for feasibly elucidating brainstem contributions to autism and other conditions.
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Affiliation(s)
- Jose Guerrero-Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Olivia Surgent
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Gregory R. Kirk
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean III
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
| | | | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Occupational Therapy Program in the Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States
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22
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Kecskemeti S, Freeman A, Travers BG, Alexander AL. FreeSurfer based cortical mapping and T1-relaxometry with MPnRAGE: Test-retest reliability with and without retrospective motion correction. Neuroimage 2021; 242:118447. [PMID: 34358661 PMCID: PMC8525331 DOI: 10.1016/j.neuroimage.2021.118447] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 07/25/2021] [Accepted: 08/02/2021] [Indexed: 12/22/2022] Open
Abstract
A test-retest study of FreeSurfer derived cortical thickness, cortical surface area, and cortical volume, as well as quantitative R1 relaxometry assessed on the midpoint of the cortex, was performed on a cohort of pediatric subjects (6-12 years old) scanned without sedation using SNARE-MPnRAGE (self navigated retrospective motion corrected magnetization prepared with n rapid gradient echoes) imaging. Reliability was assessed with coefficients of variation (CoVs) and intraclass correlation coefficients (ICCs) and statistical tests were used to determine differences with and without SNARE motion correction. Comparison of the test-retest measures of SNARE-MPnRAGE with prospectively motion corrected PROMO MPRAGE were also performed. When SNARE motion correction was used all parameters had statistically significant improvements and demonstrated high reliability. Reliability varied depending on parameter, region, and measurement type (vertex or region of interest). For mean thickness/surface area/volume/mean R1 across the regions of FreeSurfer's DK Atlas, the mean CoVs (% x100) were (1.2/1.6/1.9/0.9) and the mean ICCs were (0.88/0.96/0.94/0.83). When assessed on a per-vertex basis, the CoVs and ICCs for thickness/R1 had mean values of (2.9/1.9) and (0.82/0.68) across the regions of the DK Atlas. Retrospectively motion corrected MPnRAGE had significantly lower CoVs and higher ICCs for the morphological measures than PROMO MPRAGE. Motion correction effectively removed motion related biases in nearly all regions for R1 and morphometric measures.
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Affiliation(s)
- Steven Kecskemeti
- Waisman Center, University of Wisconsin, Madison, United States; Radiology, University of Wisconsin, Madison, United States.
| | - Abigail Freeman
- Waisman Center, University of Wisconsin, Madison, United States; Psychiatry, University of Wisconsin, Madison, United States
| | | | - Andrew L Alexander
- Waisman Center, University of Wisconsin, Madison, United States; Medical Physics, University of Wisconsin, Madison, United States; Psychiatry, University of Wisconsin, Madison, United States
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Zhou R, Weller DS, Yang Y, Wang J, Jeelani H, Mugler JP, Salerno M. Dual-excitation flip-angle simultaneous cine and T 1 mapping using spiral acquisition with respiratory and cardiac self-gating. Magn Reson Med 2021; 86:82-96. [PMID: 33590591 PMCID: PMC8849625 DOI: 10.1002/mrm.28675] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/18/2020] [Accepted: 12/19/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE To develop a free-breathing cardiac self-gated technique that provides cine images and B1+ slice profile-corrected T1 maps from a single acquisition. METHODS Without breath-holding or electrocardiogram gating, data were acquired continuously on a 3T scanner using a golden-angle gradient-echo spiral pulse sequence, with an inversion RF pulse applied every 4 seconds. Flip angles of 3° and 15° were used for readouts after the first four and second four inversions. Self-gating cardiac triggers were extracted from heart image navigators, and respiratory motion was corrected by rigid registration on each heartbeat. Cine images were reconstructed from the steady-state portion of 15° readouts using a low-rank plus sparse reconstruction. The T1 maps were fit using a projection onto convex sets approach from images reconstructed using slice profile-corrected dictionary learning. This strategy was evaluated in a phantom and 14 human subjects. RESULTS The self-gated signal demonstrated close agreement with the acquired electrocardiogram signal. The image quality for the proposed cine images and standard clinical balanced SSFP images were 4.31 (±0.50) and 4.65 (±0.30), respectively. The slice profile-corrected T1 values were similar to those of the inversion-recovery spin-echo technique in phantom, and had a higher global T1 value than that of MOLLI in human subjects. CONCLUSIONS Cine and T1 mapping using spiral acquisition with respiratory and cardiac self-gating successfully acquired T1 maps and cine images in a single acquisition without the need for electrocardiogram gating or breath-holding. This dual-excitation flip-angle approach provides a novel approach for measuring T1 while accounting for B1+ and slice profile effect on the apparent T1∗ .
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Affiliation(s)
- Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Daniel S. Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, United States
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Junyu Wang
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Haris Jeelani
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - John P. Mugler
- Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Michael Salerno
- Cardiology, Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
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de Sitter A, Burggraaff J, Bartel F, Palotai M, Liu Y, Simoes J, Ruggieri S, Schregel K, Ropele S, Rocca MA, Gasperini C, Gallo A, Schoonheim MM, Amann M, Yiannakas M, Pareto D, Wattjes MP, Sastre-Garriga J, Kappos L, Filippi M, Enzinger C, Frederiksen J, Uitdehaag B, Guttmann CRG, Barkhof F, Vrenken H. Development and evaluation of a manual segmentation protocol for deep grey matter in multiple sclerosis: Towards accelerated semi-automated references. NEUROIMAGE-CLINICAL 2021; 30:102659. [PMID: 33882422 PMCID: PMC8082260 DOI: 10.1016/j.nicl.2021.102659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 03/19/2021] [Accepted: 03/31/2021] [Indexed: 10/25/2022]
Abstract
BACKGROUND Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. OBJECTIVES This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). METHODS A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. RESULTS All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. CONCLUSIONS The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.
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Affiliation(s)
- Alexandra de Sitter
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands
| | - Jessica Burggraaff
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands.
| | - Fabian Bartel
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands
| | - Miklos Palotai
- Center for Neurological Imaging, Department of radiology, Brigham and Women's Hospital, Harvard Medical School Boston, MA, USA
| | - Yaou Liu
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands
| | - Jorge Simoes
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands
| | - Serena Ruggieri
- Department of Human Neurosciences, "Sapienza" University of Rome, Rome, IT, Italy; Department of Neurosciences, San Camillo Forlanini Hospital, Rome, IT, Italy
| | - Katharina Schregel
- Center for Neurological Imaging, Department of radiology, Brigham and Women's Hospital, Harvard Medical School Boston, MA, USA; Institute of Neuroradiology, University Medical Center Goettingen, Goettingen, DE, Germany
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, AT, Austria
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, United States; Neurology Unit, San Raffaele Scientific Institute, UniSR, Milan, IT, Italy
| | - Claudio Gasperini
- Department of Neurosciences, San Camillo Forlanini Hospital, Rome, IT, Italy
| | - Antonio Gallo
- Division of Neurology and 3T MRI Research Center, Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, IT, Italy
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, NL, Netherlands
| | - Michael Amann
- Medical Image Analysis Center (MIAC), United States; Neurologic Clinic and Policlinic and Neuroradiology, Department of Biomedical Engineering, University Hospital Basel, Basel, CH, Switzerland
| | - Marios Yiannakas
- Department of Neuroinflammation, Institute of Neurology, UCL, London, UK
| | - Deborah Pareto
- Section of Neuroradiology and MRI Unit, Department of Radiology, University Hospital Valld'Hebron, Autonomous University of Barcelona, Barcelona, ES, Spain
| | - Mike P Wattjes
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands; Deptartment of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, DE, Germany
| | - Jaume Sastre-Garriga
- Department of Neurology, University Hospital iValld'Hebron, Autonomous University of Barcelona, Barcelona, ES, Spain
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic and Neuroradiology, Department of Biomedical Engineering, University Hospital Basel, Basel, CH, Switzerland
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, United States; Neurology Unit, San Raffaele Scientific Institute, UniSR, Milan, IT, Italy; Neurophysiology Unit, San Raffaele Scientific Institute, Italy; Vita-Salute San Raffaele University, Milan, IT, Italy
| | - Christian Enzinger
- Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, AT, Austria
| | - Jette Frederiksen
- Department of Neurology, Glostrup University Hospital, Copenhagen, DK, Denmark
| | - Bernard Uitdehaag
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands
| | - Charles R G Guttmann
- Center for Neurological Imaging, Department of radiology, Brigham and Women's Hospital, Harvard Medical School Boston, MA, USA
| | - Frederik Barkhof
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands; Institutes of Neurology & Healthcare Engineering, UCL, London, UK
| | - Hugo Vrenken
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, NL, Netherlands
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Schmaranzer F, Afacan O, Lerch TD, Kim YJ, Siebenrock KA, Ith M, Cullmann JL, Kober T, Klarhoefer M, Tannast M, Bixby SD, Novais EN, Jung B. Magnetization-prepared 2 Rapid Gradient-Echo MRI for B 1 Insensitive 3D T1 Mapping of Hip Cartilage: An Experimental and Clinical Validation. Radiology 2021; 299:150-158. [PMID: 33620288 DOI: 10.1148/radiol.2021200085] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background Often used for T1 mapping of hip cartilage, three-dimensional (3D) dual-flip-angle (DFA) techniques are highly sensitive to flip angle variations related to B1 inhomogeneities. The authors hypothesized that 3D magnetization-prepared 2 rapid gradient-echo (MP2RAGE) MRI would help provide more accurate T1 mapping of hip cartilage at 3.0 T than would 3D DFA techniques. Purpose To compare 3D MP2RAGE MRI with 3D DFA techniques using two-dimensional (2D) inversion recovery T1 mapping as a standard of reference for hip cartilage T1 mapping in phantoms, healthy volunteers, and participants with hip pain. Materials and Methods T1 mapping at 3.0 T was performed in phantoms and in healthy volunteers using 3D MP2RAGE MRI and 3D DFA techniques with B1 field mapping for flip angle correction. Participants with hip pain prospectively (July 2019-January 2020) underwent indirect MR arthrography (with intravenous administration of 0.2 mmol/kg of gadoterate meglumine), including 3D MP2RAGE MRI. A 2D inversion recovery-based sequence served as a T1 reference in phantoms and in participants with hip pain. In healthy volunteers, cartilage T1 was compared between 3D MP2RAGE MRI and 3D DFA techniques. Paired t tests and Bland-Altman analysis were performed. Results Eleven phantoms, 10 healthy volunteers (median age, 27 years; range, 26-30 years; five men), and 20 participants with hip pain (mean age, 34 years ± 10 [standard deviation]; 17 women) were evaluated. In phantoms, T1 bias from 2D inversion recovery was lower for 3D MP2RAGE MRI than for 3D DFA techniques (mean, 3 msec ± 11 vs 253 msec ± 85; P < .001), and, unlike 3D DFA techniques, the deviation found with MP2RAGE MRI did not correlate with increasing B1 deviation. In healthy volunteers, regional cartilage T1 difference (109 msec ± 163; P = .008) was observed only for the 3D DFA technique. In participants with hip pain, the mean T1 bias of 3D MP2RAGE MRI from 2D inversion recovery was -23 msec ± 31 (P < .001). Conclusion Compared with three-dimensional (3D) dual-flip-angle techniques, 3D magnetization-prepared 2 rapid gradient-echo MRI enabled more accurate T1 mapping of hip cartilage, was less affected by B1 inhomogeneities, and showed high accuracy against a T1 reference in participants with hip pain. © RSNA, 2021.
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Affiliation(s)
- Florian Schmaranzer
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Onur Afacan
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Till D Lerch
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Young-Jo Kim
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Klaus A Siebenrock
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Michael Ith
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Jennifer L Cullmann
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Tobias Kober
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Markus Klarhoefer
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Moritz Tannast
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Sarah D Bixby
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Eduardo N Novais
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Bernd Jung
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
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Aggarwal N, Moody JF, Dean DC, Tromp DPM, Kecskemeti SR, Oler JA, Alexander AL, Kalin NH. Spatiotemporal dynamics of nonhuman primate white matter development during the first year of life. Neuroimage 2021; 231:117825. [PMID: 33549752 DOI: 10.1016/j.neuroimage.2021.117825] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/22/2021] [Accepted: 01/27/2021] [Indexed: 11/15/2022] Open
Abstract
White matter (WM) development early in life is a critical component of brain development that facilitates the coordinated function of neuronal pathways. Additionally, alterations in WM have been implicated in various neurodevelopmental disorders, including psychiatric disorders. Because of the need to understand WM development in the weeks immediately following birth, we characterized changes in WM microstructure throughout the postnatal macaque brain during the first year of life. This is a period in primates during which genetic, developmental, and environmental factors may have long-lasting impacts on WM microstructure. Studies in nonhuman primates (NHPs) are particularly valuable as a model for understanding human brain development because of their evolutionary relatedness to humans. Here, 34 rhesus monkeys (23 females, 11 males) were imaged longitudinally at 3, 7, 13, 25, and 53 weeks of age with T1-weighted (MPnRAGE) and diffusion tensor imaging (DTI). With linear mixed-effects (LME) modeling, we demonstrated robust logarithmic growth in FA, MD, and RD trajectories extracted from 18 WM tracts across the brain. Estimated rate of change curves for FA, MD, and RD exhibited an initial 10-week period of exceedingly rapid WM development, followed by a precipitous decline in growth rates. K-means clustering of raw DTI trajectories and rank ordering of LME model parameters revealed distinct posterior-to-anterior and medial-to-lateral gradients in WM maturation. Finally, we found that individual differences in WM microstructure assessed at 3 weeks of age were significantly related to those at 1 year of age. This study provides a quantitative characterization of very early WM growth in NHPs and lays the foundation for future work focused on the impact of alterations in early WM developmental trajectories in relation to human psychopathology.
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Affiliation(s)
- Nakul Aggarwal
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States.
| | - Jason F Moody
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States
| | - Douglas C Dean
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Department of Pediatrics, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Do P M Tromp
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Steve R Kecskemeti
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
| | - Andy L Alexander
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States; Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States; Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705, United States
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Boulevard, Madison, WI 53719, United States
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Kecskemeti S, Alexander AL. Three-dimensional motion-corrected T 1 relaxometry with MPnRAGE. Magn Reson Med 2020; 84:2400-2411. [PMID: 32301173 PMCID: PMC7396302 DOI: 10.1002/mrm.28283] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 03/23/2020] [Accepted: 03/23/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE To test the performance of the MPnRAGE motion-correction algorithm on quantitative relaxometry estimates. METHODS Twelve children (9.4 ± 2.6 years, min = 6.5 years, max = 13.8 years) were imaged 3 times in a session without sedation. Stabilization padding was not used for the second and third scans. Quantitative T1 values were estimated in each voxel on images reconstructed with and without motion correction. Mean T1 values were assessed in various regions determined from automated segmentation algorithms. Statistical tests were performed on mean values and the coefficient of variation across the measurements. Accuracy of T1 estimates were determined by scanning the High Precision Devices (Boulder, CO) MRI system phantom with the same protocol. RESULTS The T1 values obtained with MPnRAGE agreed within 4% of the reference values of the High Precision Devices phantom. The best fit line was T1 (MPnRAGE) = 1.02 T1 (reference)-0.9 ms, R2 = 0.9999. For in vivo studies, motion correction reduced the coefficients of variation of mean T1 values in whole-brain tissue regions determined by FSL FAST by 74% ± 7%, and subcortical regions determined by FIRST and FreeSurfer by 32% ± 21% and 33% ± 26%, respectively. Across all participants, the mean coefficients of variation ranged from 0.8% to 2.0% for subcortical regions and 0.6% ± 0.5% for cortical regions when motion correction was applied. CONCLUSION The MPnRAGE technique demonstrated highly accurate values in phantom measurements. When combined with retrospective motion correction, MPnRAGE demonstrated highly reproducible T1 values, even in participants who moved during the acquisition.
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Affiliation(s)
- Steven Kecskemeti
- Waisman Center, University of Wisconsin – Madison
- Radiology, University of Wisconsin – Madison
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin – Madison
- Medical Physics, University of Wisconsin – Madison
- Psychiatry, University of Wisconsin - Madison
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Ma YJ, Shao H, Fan S, Lu X, Du J, Young IR, Bydder GM. New options for increasing the sensitivity, specificity and scope of synergistic contrast magnetic resonance imaging (scMRI) using Multiplied, Added, Subtracted and/or FiTted (MASTIR) pulse sequences. Quant Imaging Med Surg 2020; 10:2030-2065. [PMID: 33014733 PMCID: PMC7495319 DOI: 10.21037/qims-20-795] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 07/23/2020] [Indexed: 11/06/2022]
Abstract
This paper reviews magnetic resonance (MR) pulse sequences in which the same or different tissue properties (TPs) such as T1 and T2 are used to contribute synergistically to lesion contrast. It also shows how synergistic contrast can be created with Multiplied, Added, Subtracted and/or fiTted Inversion Recovery (MASTIR) sequences, and be used to improve the sensitivity, specificity and scope of clinical magnetic resonance imaging (MRI) protocols. Synergistic contrast can be created from: (i) the same TP, e.g., T1 used twice or more in a pulse sequence; (ii) different TPs such as ρm, T1, T2, and D* used once or more within a sequence, and (iii) additional suppression or reduction of signals from tissues and/or fluids such as fat, long T2 tissues and cerebrospinal fluid (CSF). The short inversion time (TI) inversion recovery (IR) (STIR) and double IR (DIR) sequences usually show synergistic positive contrast for lesions which have increases in both T1 and T2. The diffusion weighted pulsed gradient spin echo (PGSE) sequence shows synergistic contrast for lesions which have an increase in T2 and a decrease in D*; the sequence is both positively weighted for T2 and negatively weighted for D*. In the brain, when an IR sequence nulling white matter has subtracted from it an IR sequence nulling gray matter to form the subtracted IR (SIR) sequence, increases in the single TP T1 between the two nulling points of the original two sequences generate high synergistic positive contrast. In addition, the subtraction to produce the SIR sequence reduces fat and CSF signals. To provide high sensitivity to changes in TPs in disease the SIR sequence can be used (i) alone to provide synergistic T1 contrast as above; (ii) with T2-weighting to provide synergistic T1 and T2 contrast, and (iii) with T2- and D*-weighting to provide synergistic T1, T2, and D* contrast. The SIR sequence can also be used in reversed form (longer TI form minus shorter TI form) to produce very high positive synergistic T1 contrast for reductions in T1, and so increase the positive contrast enhancement produced by clinical gadolinium-based contrast agents (GBCAs) when they reduce T1. The specificity of MRI examinations can be improved by using the reversed SIR sequence with a long echo time (TE) gradient echo as well as echo subtraction to show synergistic high contrast from T1 and T2* shortening produced by organic iron. Other added and subtracted forms of the MASTIR sequence can be used synergistically to selectively show myelin, myelin water and fluids including blood and CSF. Protocols using MASTIR sequences to provide synergistic contrast in MRI of the brain, prostate and articular cartilage are included as illustrative examples, and the features of synergistic contrast MRI (scMRI) are compared to those of multiparametric MRI (mpMRI) and functional MRI (fMRI).
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California, San Diego, CA, USA
| | - Hongda Shao
- Department of Radiology, University of California, San Diego, CA, USA
| | - Shujuan Fan
- Department of Radiology, University of California, San Diego, CA, USA
| | - Xing Lu
- Department of Radiology, University of California, San Diego, CA, USA
| | - Jiang Du
- Department of Radiology, University of California, San Diego, CA, USA
| | - Ian R. Young
- Formerly Department of Electrical Engineering, Imperial College, London, UK
| | - Graeme M. Bydder
- Department of Radiology, University of California, San Diego, CA, USA
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Liu X, Gómez PA, Solana AB, Wiesinger F, Menzel MI, Menze BH. Silent 3D MR sequence for quantitative and multicontrast T1 and proton density imaging. Phys Med Biol 2020; 65:185010. [PMID: 32663809 DOI: 10.1088/1361-6560/aba5e8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining the signal evolution to a temporal subspace which was learned from the signal model. Parameter maps were obtained by fitting the data to the signal model, and bias-field correction was conducted on T1w images. Accuracy and repeatability of the method was accessed in repeated experiments with phantom and volunteers. For the phantom study, T1 values obtained by the proposed method were highly consistent with values from the gold standard method, R2 = 0.9976. Coefficients of variation (CVs) ranged from 0.09% to 0.83%. For the volunteer study, T1 values from gray and white matter regions were consistent with literature values, and peaks of gray and white matter can be clearly delineated on whole-brain T1 histograms. CVs ranged from 0.01% to 2.30%. The acoustic noise measured at the scanner isocenter was 2.6 dBA higher compared to the in-bore background. Rapid and with low acoustic noise, the proposed method is shown to produce accurate T1 and PD maps with high repeatability by reconstructing sparsely sampled T1w images at different TIs using temporal subspace. Our approach can greatly enhance patient comfort during examination and therefore increase the acceptance of the procedure.
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Affiliation(s)
- Xin Liu
- Technical University Munich, Garching, Germany. GE Global Research Europe, Munich, Germany
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Ma YJ, Fan S, Shao H, Du J, Szeverenyi NM, Young IR, Bydder GM. Use of Multiplied, Added, Subtracted and/or FiTted Inversion Recovery (MASTIR) pulse sequences. Quant Imaging Med Surg 2020; 10:1334-1369. [PMID: 32550142 DOI: 10.21037/qims-20-568] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The group of Multiplied, Added, Subtracted and/or fiTted Inversion Recovery (MASTIR) pulse sequences in which usually two or more inversion recovery (IR) images of different types are combined is described, and uses for this type of sequence are outlined. IR sequences of different types can be multiplied, added, subtracted, and/or fitted together to produce variants of the MASTIR sequence. The sequences provide a range of options for increasing image contrast, demonstrating specific tissues and fluids of interest, and suppressing unwanted signals. A formalism using the concept of pulse sequences as tissue property filters is used to explain the signal, contrast and weighting of the pulse sequences with both univariate and multivariate filter models. Subtraction of one magnitude reconstructed IR image from another with a shorter TI can produce very high T1 dependent positive contrast from small increases in T1. The reverse subtracted IR sequence can provide high positive contrast enhancement with gadolinium chelates and iron deposition which decrease T1. Additional contrast to that arising from increases in T1 can be produced by supplementing this with contrast arising from concurrent increases in ρm and T2, as well as increases or decreases in diffusion using subtraction IR with echo subtraction and/or diffusion subtraction. Phase images may show 180º differences as a result of rotating into the transverse plane both positive and negative longitudinal magnetization. Phase images with contrast arising in this way, or other ways, can be multiplied by magnitude IR images to increase the contrast of the latter. Magnetization Transfer (MT) and susceptibility can be used with IR sequences to improve contrast. Selective images of white and brown adipose tissue lipid and water components can be produced using different TIs and in and out-of-phase TEs. Selective images of ultrashort and short T2 tissue components can be produced by nulling long T2 tissue components with an inversion pulse and subtraction of images with longer TEs from images with ultrashort TEs. The Double Echo Sliding IR (DESIRE) sequence provides images with a wide range of TIs from which it is possible to choose values of TI to achieve particular types of tissue and/or fluid contrast (e.g., for subtraction with different TIs, as described above, and for long T2 tissue signal nulling with UTE sequences). Unwanted tissue and fluid signals can be suppressed by addition and subtraction of phase-sensitive (ps) and magnitude reconstructed images. The sequence also offers options for synergistic use of the changes in blood and tissue ρm, T1, T2/T2*, D* and perfusion that can be seen with fMRI of the brain. In-vivo and ex-vivo illustrative examples of normal brain, cartilage, multiple sclerosis, Alzheimer's disease, and peripheral nerve imaged with different forms of the MASTIR sequence are included.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | - Shujuan Fan
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | - Hongda Shao
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | - Jiang Du
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
| | | | - Ian R Young
- Formerly Department of Electrical Engineering, Imperial College, London, UK
| | - Graeme M Bydder
- Department of Radiology, University of California, San Diego, San Diego, CA, USA
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Kecskemeti SR, Alexander AL. Test-retest of automated segmentation with different motion correction strategies: A comparison of prospective versus retrospective methods. Neuroimage 2020; 209:116494. [PMID: 31899289 PMCID: PMC7056555 DOI: 10.1016/j.neuroimage.2019.116494] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 12/22/2019] [Accepted: 12/23/2019] [Indexed: 01/10/2023] Open
Abstract
Test-retest of automated image segmentation algorithms (FSL FAST, FSL FIRST, and FREESURFER) are computed on magnetic resonance images from 12 unsedated children aged 9.4±2.6 years ([min,max] = [6.5 years, 13.8 years]) using different approaches to motion correction (prospective versus retrospective). The prospective technique, PROMO MPRAGE, dynamically estimates motion using specially acquired navigator images and adjusts the remaining acquisition accordingly, whereas the retrospective technique, MPnRAGE, uses a self-navigation property to retrospectively estimate and account for motion during image reconstruction. To increase the likelihood and range of motions, participants heads were not stabilized with padding during repeated scans. When motion was negligible both techniques had similar performance. When motion was not negligible, the automated image segmentation and anatomical labeling software tools showed the most consistent performance with the retrospectively corrected MPnRAGE technique (≥80% volume overlaps for 15 of 16 regions for FIRST and FREESURFER, with greater than 90% volume overlaps for 12 regions with FIRST and 11 regions with FREESURFER). Prospectively corrected MPRAGE with linear view-ordering also demonstrated lower performance than MPnRAGE without retrospective motion correction.
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Naji N, Sun H, Wilman AH. On the value of QSM from MPRAGE for segmenting and quantifying iron‐rich deep gray matter. Magn Reson Med 2020; 84:1486-1500. [DOI: 10.1002/mrm.28226] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/20/2020] [Accepted: 02/03/2020] [Indexed: 01/10/2023]
Affiliation(s)
- Nashwan Naji
- Department of Biomedical Engineering University of Alberta Edmonton Alberta Canada
| | - Hongfu Sun
- School of Information Technology and Electrical Engineering University of Queensland Brisbane Queensland Australia
| | - Alan H. Wilman
- Department of Biomedical Engineering University of Alberta Edmonton Alberta Canada
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Ma YJ, Searleman AC, Jang H, Wong J, Chang EY, Corey-Bloom J, Bydder GM, Du J. Whole-Brain Myelin Imaging Using 3D Double-Echo Sliding Inversion Recovery Ultrashort Echo Time (DESIRE UTE) MRI. Radiology 2020; 294:362-374. [PMID: 31746689 PMCID: PMC6996715 DOI: 10.1148/radiol.2019190911] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 08/21/2019] [Accepted: 08/30/2019] [Indexed: 11/11/2022]
Abstract
Background Signal contamination from long T2 water is a major challenge in direct imaging of myelin with MRI. Nulling of the unwanted long T2 signals can be achieved with an inversion recovery (IR) preparation pulse to null long T2 white matter within the brain. The remaining ultrashort T2 signal from myelin can be detected with an ultrashort echo time (UTE) sequence. Purpose To develop patient-specific whole-brain myelin imaging with a three-dimensional double-echo sliding inversion recovery (DESIRE) UTE sequence. Materials and Methods The DESIRE UTE sequence generates a series of IR images with different inversion times during a single scan. The optimal inversion time for nulling long T2 signal is determined by finding minimal signal on the second echo. Myelin images are generated by subtracting the second echo image from the first UTE image. To validate this method, a prospective study was performed in phantoms, cadaveric brain specimens, healthy volunteers, and patients with multiple sclerosis (MS). A total of 20 healthy volunteers (mean age, 40 years ± 13 [standard deviation], 10 women) and 20 patients with MS (mean age, 58 years ± 8; 15 women) who underwent MRI between November 2017 and February 2019 were prospectively included. Analysis of variance was performed to evaluate the signal difference between MS lesions and normal-appearing white matter in patients with MS. Results High signal intensity and corresponding T2* and T1 of the extracted myelin vesicles provided evidence for direct imaging of ultrashort-T2 myelin protons using the UTE sequence. Gadobenate dimeglumine phantoms with a wide range of T1 values were selectively suppressed with DESIRE UTE. In the ex vivo brain study of MS lesions, signal loss was observed in MS lesions and was conformed with histologic analysis. In the human study, there was a significant reduction in normalized signal intensity in MS lesions compared with that in normal-appearing white matter (0.19 ± 0.10 vs 0.76 ± 0.11, respectively; P < .001). Conclusion The double-echo sliding inversion recovery ultrashort echo time sequence can generate whole-brain myelin images specifically with a clinical 3-T scanner. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Port in this issue.
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Affiliation(s)
- Ya-Jun Ma
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Adam C. Searleman
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Hyungseok Jang
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Jonathan Wong
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Eric Y. Chang
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Jody Corey-Bloom
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Graeme M. Bydder
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
| | - Jiang Du
- From the Departments of Radiology (Y.J.M., A.C.S., H.J., J.W.,
E.Y.C., G.M.B., J.D.) and Neurosciences (J.C.), University of California San
Diego, 9452 Medical Center Dr, La Jolla, CA 92037; and Radiology Service, VA San
Diego Healthcare System, San Diego, Calif (J.W., E.Y.C.)
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Patsenko EG, Adluru N, Birn RM, Stodola DE, Kral TRA, Farajian R, Flook L, Burghy CA, Steinkuehler C, Davidson RJ. Mindfulness video game improves connectivity of the fronto-parietal attentional network in adolescents: A multi-modal imaging study. Sci Rep 2019; 9:18667. [PMID: 31822684 PMCID: PMC6904443 DOI: 10.1038/s41598-019-53393-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 10/23/2019] [Indexed: 12/23/2022] Open
Abstract
Mindfulness training has been shown to improve attention and change the underlying brain substrates in adults. Most mindfulness training programs involve a myriad of techniques, and it is difficult to attribute changes to any particular aspect of the program. Here, we created a video game, Tenacity, which models a specific mindfulness technique – focused attention on one’s breathing – and assessed its potential to train an attentional network in adolescents. A combined analysis of resting state functional connectivity (rs-FC) and diffusion tensor imaging (DTI) yielded convergent results – change in communication within the left fronto-parietal network after two weeks of playing Tenacity compared to a control game. Rs-FC analysis showed greater connectivity between left dorsolateral prefrontal cortex (dlPFC) and left inferior parietal cortex (IPC) in the Tenacity group. Importantly, changes in left dlPFC – IPC rs-FC and changes in structural connectivity of the white matter tract that connects these regions –left superior longitudinal fasiculus (SLF) – were associated with changes in performance on an attention task. Finally, changes in left dlPFC – IPC rs-FC correlated with the change in left SLF structural connectivity as measured by fractional anisotropy (FA) in the Tenacity group only.
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Affiliation(s)
- Elena G Patsenko
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA.
| | - Nagesh Adluru
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA
| | - Rasmus M Birn
- Department of Psychiatry, University of Wisconsin - Madison, 6001 Research Park Blvd., Madison, WI, 53719, USA
| | - Diane E Stodola
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA
| | - Tammi R A Kral
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA.,Department of Psychology, University of Wisconsin - Madison, 1202 West Johnson Street, Madison, WI, 53706, USA
| | - Reza Farajian
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA
| | - Lisa Flook
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA
| | - Cory A Burghy
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA
| | - Constance Steinkuehler
- Department of Informatics, University of California, Irvine, 5019 Donald Bren Hall, Irvine, CA, 92697-3440, USA
| | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin - Madison, 625W. Washington Avenue, Madison, WI, 53703, USA.,Department of Psychology, University of Wisconsin - Madison, 1202 West Johnson Street, Madison, WI, 53706, USA
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Rasoanandrianina H, Massire A, Taso M, Guye M, Ranjeva JP, Kober T, Callot V. Regional T 1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence. NMR IN BIOMEDICINE 2019; 32:e4142. [PMID: 31393649 DOI: 10.1002/nbm.4142] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 05/20/2019] [Accepted: 06/18/2019] [Indexed: 06/10/2023]
Abstract
The recently-proposed MP2RAGE sequence was purposely optimized for cervical spinal cord imaging at 3T. Sequence parameters were chosen to optimize gray/white matter T1 contrast with sub-millimetric resolution and scan-time < 10 min while preserving reliable T1 determination with minimal B1+ variation effects within a range of values compatible with pathologies and surrounding structures. Results showed good agreements with IR-based measurements, high MP2RAGE-based T1 reproducibility and preliminary evidences of age- and tract-related T1 variations in the healthy spinal cord.
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Affiliation(s)
- Henitsoa Rasoanandrianina
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Aix-Marseille University, IFSTTAR, LBA UMR_T24, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Aurélien Massire
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Manuel Taso
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center & Harvard Medical School, Boston, Massachusetts, USA
| | - Maxime Guye
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Virginie Callot
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
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Jang H, Ma Y, Searleman AC, Carl M, Corey-Bloom J, Chang EY, Du J. Inversion recovery UTE based volumetric myelin imaging in human brain using interleaved hybrid encoding. Magn Reson Med 2019; 83:950-961. [PMID: 31532032 DOI: 10.1002/mrm.27986] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 07/12/2019] [Accepted: 08/15/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Direct myelin imaging can improve the characterization of myelin-related diseases such as multiple sclerosis. In this study, we explore a novel method to directly image myelin using inversion recovery-prepared hybrid encoding (IR-HE) UTE MRI. METHODS The IR-HE sequence uses an adiabatic inversion pulse to suppress the long T2 white matter signal, followed by 3D dual-echo HE utilizing both single point imaging and radial frequency encoding, for which the subtraction image between 2 echoes reveals the myelin signal with high contrast. To reduce scan time, it is common to obtain multiple spokes per IR. Here, we invented a novel method to improve the HE, adapted for the multi-spoke IR imaging-termed interleaved HE-for which single point imaging encoding is interleaved between radial frequency encodings near nulling point to allow more efficient IR-signal suppression. To evaluate the proposed approach, a computer simulation, myelin phantom experiment, an ex vivo experiment with a cadaveric multiple sclerosis brain, and an in vivo experiment with 8 healthy volunteers and 13 multiple sclerosis patients were performed. RESULTS The computer simulation showed that IR-interleaved HE allows for improved contrast of myelin signal with reduced imaging artifacts. The myelin phantom experiment showed IR-interleaved HE allows direct imaging of myelin lipid with excellent suppression of water signal. In the ex vivo and in vivo experiments, the proposed method demonstrated highly specific imaging of myelin in white matter of the brain. CONCLUSION IR-interleaved HE allows for time-efficient, high-contrast direct myelin imaging and can detect demyelinated lesions in multiple sclerosis patients.
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Affiliation(s)
- Hyungseok Jang
- Department of Radiology, University of California San Diego, San Diego, California
| | - Yajun Ma
- Department of Radiology, University of California San Diego, San Diego, California
| | - Adam C Searleman
- Department of Radiology, University of California San Diego, San Diego, California
| | | | - Jody Corey-Bloom
- Department of Neurosciences, University of California, San Diego, California
| | - Eric Y Chang
- Department of Radiology, University of California San Diego, San Diego, California.,Radiology Service, VA San Diego Healthcare System, San Diego, California
| | - Jiang Du
- Department of Radiology, University of California San Diego, San Diego, California
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Radial MP2RAGE sequence for rapid 3D T 1 mapping of mouse abdomen: application to hepatic metastases. Eur Radiol 2019; 29:5844-5851. [PMID: 30888483 DOI: 10.1007/s00330-019-06081-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 01/22/2019] [Accepted: 02/07/2019] [Indexed: 10/27/2022]
Abstract
OBJECTIVES The T1 longitudinal recovery time is regarded as a biomarker of cancer treatment efficiency. In this scope, the Magnetization Prepared 2 RApid Gradient Echo (MP2RAGE) sequence relevantly complies with fast 3D T1 mapping. Nevertheless, with its Cartesian encoding scheme, it is very sensitive to respiratory motion. Consequently, a radial encoding scheme was implemented for the detection and T1 measurement of hepatic metastases in mice at 7T. METHODS A 3D radial encoding scheme was developed using a golden angle distribution for the k-space trajectories. As in that case, each projection contributes to the image contrast, the signal equations had to be modified. Phantoms containing increasing gadoteridol concentrations were used to determine the accuracy of the sequence in vitro. Healthy mice were repetitively scanned to assess the reproducibility of the T1 values. The growth of hepatic metastases was monitored. Undersampling robustness was also evaluated. RESULTS The accuracy of the T1 values obtained with the radial MP2RAGE sequence was > 90% compared to the Inversion-Recovery sequence. The motion robustness of this new sequence also enabled repeatable T1 measurements on abdominal organs. Hepatic metastases of less than 1-mm diameter were easily detected and T1 heterogeneities within the metastasis and between the metastases within the same animal were measured. With a twofold acceleration factor using undersampling, high-quality 3D T1 abdominal maps were achieved in 9 min. CONCLUSIONS The radial MP2RAGE sequence could be used for fast 3D T1 mapping, to detect and characterize metastases in regions subjected to respiratory motion. KEY POINTS • The Cartesian encoding of the MP2RAGE sequence was modified to a radial encoding. The modified sequence enabled accurate T 1 measurements on phantoms and on abdominal organs of mice. • Hepatic metastases were easily detected due to high contrast. Heterogeneity in T 1 was measured within the metastases and between each metastasis within the same animal. • As implementation of this sequence does not require specific hardware, we expect that it could be readily available for clinical practice in humans.
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Caan MWA, Bazin PL, Marques JP, de Hollander G, Dumoulin SO, van der Zwaag W. MP2RAGEME: T 1 , T 2 * , and QSM mapping in one sequence at 7 tesla. Hum Brain Mapp 2018; 40:1786-1798. [PMID: 30549128 PMCID: PMC6590660 DOI: 10.1002/hbm.24490] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 11/21/2018] [Accepted: 11/28/2018] [Indexed: 12/19/2022] Open
Abstract
Quantitative magnetic resonance imaging generates images of meaningful physical or chemical variables measured in physical units that allow quantitative comparisons between tissue regions and among subjects scanned at the same or different sites. Here, we show that we can acquire quantitative T1, T2*, and quantitative susceptibility mapping (QSM) information in a single acquisition, using a multi‐echo (ME) extension of the second gradient‐echo image of the MP2RAGE sequence. This combination is called MP2RAGE ME, or MP2RAGEME. The simultaneous acquisition results in large time savings, perfectly coregistered data, and minimal image quality differences compared to separately acquired data. Following a correction for residual transmit B1+‐sensitivity, quantitative T1, T2*, and QSM values were in excellent agreement with those obtained from separately acquired, also B1+‐corrected, MP2RAGE data and ME gradient echo data. The quantitative values from reference regions of interests were also in very good correspondence with literature values. From the MP2RAGEME data, we further derived a multiparametric cortical parcellation, as well as a combined arterial and venous map. In sum, our MP2RAGEME sequence has the benefit in large time savings, perfectly coregistered data and minor image quality differences.
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Affiliation(s)
- Matthan W A Caan
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.,Amsterdam UMC, University of Amsterdam, Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.,Social Brain Laboratory, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Gilles de Hollander
- Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.,Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands.,Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
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A G Teixeira RP, Malik SJ, Hajnal JV. Fast quantitative MRI using controlled saturation magnetization transfer. Magn Reson Med 2018; 81:907-920. [PMID: 30257044 PMCID: PMC6492254 DOI: 10.1002/mrm.27442] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2018] [Revised: 06/04/2018] [Accepted: 06/10/2018] [Indexed: 01/31/2023]
Abstract
Purpose This study demonstrates magnetization transfer (MT) effects directly affect relaxometry measurements and develops a framework that allows single‐pool models to be valid in 2‐pool MT systems. Methods A theoretical framework is developed in which a 2‐pool MT system effectively behaves as a single‐pool if the RMS RF magnetic field (B1rms{\text{B}}_{1}^{{{\text{rms}}}}) is kept fixed across all measurements. A practical method for achieving controlled saturation magnetization transfer (CSMT) using multiband RF pulses is proposed. Numerical, Phantom, and in vivo validations were performed directly comparing steady state (SS) estimation approaches that under correct single‐pool assumptions would be expected to vary in precision but not accuracy. Results Numerical simulations predict single‐pool estimates obtained from MT model generated data are not consistent for different SS estimation methods, and a systematic underestimation of T2 is expected. Neither effect occurs under the proposed CSMT approach. Both phantom and in vivo experiments corroborate the numerical predictions. Experimental data highlights that even when using the same relaxometry method, different estimates are obtained depending on which combination of flip angles (FAs) and TRs are used if the CSMT approach is not used. Using CSMT, stable measurements of both T1 and T2 are obtained. The measured T1(T1CSMT)) depends on B1rms{\text{B}}_{1}^{{{\text{rms}}}}, which is therefore an important parameter to specify. Conclusion This work demonstrates that conventional single pool relaxometry, which is highly efficient for human studies, results in unreliable parameter estimates in biological tissues because of MT effects. The proposed CSMT framework is shown to allow single‐pool assumptions to be valid, enabling reliable and efficient quantitative imaging to be performed.
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Affiliation(s)
- Rui Pedro A G Teixeira
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Shaihan J Malik
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
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Kecskemeti S, Samsonov A, Velikina J, Field AS, Turski P, Rowley H, Lainhart JE, Alexander AL. Robust Motion Correction Strategy for Structural MRI in Unsedated Children Demonstrated with Three-dimensional Radial MPnRAGE. Radiology 2018; 289:509-516. [PMID: 30063192 DOI: 10.1148/radiol.2018180180] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To develop and evaluate a retrospective method to minimize motion artifacts in structural MRI. Materials and Methods The motion-correction strategy was developed for three-dimensional radial data collection and demonstrated with MPnRAGE, a technique that acquires high-resolution volumetric magnetization-prepared rapid gradient-echo, or MPRAGE, images with multiple tissue contrasts. Forty-four pediatric participants (32 with autism spectrum disorder [mean age ± standard deviation, 13 years ± 3] and 12 age-matched control participants [mean age, 12 years ± 3]) were imaged without sedation. Images with and images without retrospective motion correction were scored by using a Likert scale (0-4 for unusable to excellent) by two experienced neuroradiologists. The Tenengrad metric (a reference-free measure of image sharpness) and statistical analyses were performed to determine the effects of performing retrospective motion correction. Results MPnRAGE T1-weighted images with retrospective motion correction were all judged to have good or excellent quality. In some cases, retrospective motion correction improved the image quality from unusable (Likert score of 0) to good (Likert score of 3). Overall, motion correction improved mean Likert scores from 3.0 to 3.8 and reduced standard deviations from 1.1 to 0.4. Image quality was significantly improved with motion correction (Mann-Whitney U test; P < .001). Intraclass correlation coefficients for absolute agreement of Tenengrad scores with reviewers 1 and 2 were 0.92 and 0.88 (P < .0005 for both), respectively. In no cases did the retrospective motion correction induce severe image degradation. Conclusion Retrospective motion correction of MPnRAGE data were shown to be highly effective for consistently improving image quality of T1-weighted MRI in unsedated pediatric participants, while also enabling multiple tissue contrasts to be reconstructed for structural analysis. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Steven Kecskemeti
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Alexey Samsonov
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Julia Velikina
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Aaron S Field
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Patrick Turski
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Howard Rowley
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Janet E Lainhart
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
| | - Andrew L Alexander
- From the Waisman Center (S.K., J.E.L., A.L.A.) and Departments of Radiology (S.K., A.S., A.S.F., P.T., H.R.), Medical Physics (J.V., A.L.A.), and Psychiatry (J.E.L., A.L.A.), University of Wisconsin-Madison, T123 Waisman Center, 1500 Highland Ave, Madison, WI 53705
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Berkowitz BA. Oxidative stress measured in vivo without an exogenous contrast agent using QUEST MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 291:94-100. [PMID: 29705036 PMCID: PMC5963509 DOI: 10.1016/j.jmr.2018.01.013] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 01/09/2018] [Accepted: 01/24/2018] [Indexed: 05/10/2023]
Abstract
Decades of experimental studies have implicated excessive generation of reactive oxygen species (ROS) in the decline of tissue function during normal aging, and as a pathogenic factor in a vast array of fatal or debilitating morbidities. This massive body of work has important clinical implications since many antioxidants are FDA approved, readily cross blood-tissue barriers, and are effective at improving disease outcomes. Yet, the potential benefits of antioxidants have remained largely unrealized in patients because conventional methods cannot determine the dose, timing, and drug combinations to be used in clinical trials to localize and decrease oxidative stress. To address this major problem and improve translational success, new methods are urgently needed that non-invasively measure the same ROS biomarker both in animal models and patients with high spatial resolution. Here, we summarize a transformative solution based on a novel method: QUEnch-assiSTed MRI (QUEST MRI). The QUEST MRI index is a significant antioxidant-induced improvement in pathophysiology, or a reduction in 1/T1 (i.e., R1). The latter form of QUEST MRI provides a unique measure of uncontrolled production of endogenous, paramagnetic reactive oxygen species (ROS). QUEST MRI results to-date have been validated by gold standard oxidative stress assays. QUEST MRI has high translational potential because it does not use an exogenous contrast agent and requires only standard MRI equipment. Summarizing, QUEST MRI is a powerful non-invasive approach with unprecedented potential for (i) bridging antioxidant treatment in animal models and patients, (ii) identifying tissue subregions exhibiting oxidative stress, and (iii) coupling oxidative stress localization with behavioral dysfunction, disease pathology, and genetic vulnerabilities to serve as a marker of susceptibility.
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Affiliation(s)
- Bruce A Berkowitz
- Department of Anatomy and Cell Biology, Wayne State University School of Medicine, Detroit, MI 48201, United States; Department of Ophthalmology, Wayne State University School of Medicine, Detroit, MI 48201, United States.
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Qi H, Sun J, Qiao H, Zhao X, Guo R, Balu N, Yuan C, Chen H. Simultaneous T 1 and T 2 mapping of the carotid plaque (SIMPLE) with T 2 and inversion recovery prepared 3D radial imaging. Magn Reson Med 2018; 80:2598-2608. [PMID: 29802629 DOI: 10.1002/mrm.27361] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 04/21/2018] [Accepted: 04/23/2018] [Indexed: 12/30/2022]
Abstract
PURPOSE To propose a technique that can produce different T1 and T2 contrasts in a single scan for simultaneous T1 and T2 mapping of the carotid plaque (SIMPLE). METHODS An interleaved 3D golden angle radial trajectory was used in conjunction with T2 preparation with variable duration (TEprep ) and inversion recovery pulses. Sliding window reconstruction was adopted to reconstruct images at different inversion delay time and TEprep for joint T1 and T2 fitting. In the fitting procedure, a rapid B1 correction method was presented. The accuracy of SIMPLE was investigated in phantom experiments. In vivo scans were performed on 5 healthy volunteers with 2 scans each, and on 5 patients with carotid atherosclerosis. RESULTS The phantom T1 and T2 estimations of SIMPLE agreed well with the standard methods with the percentage difference smaller than 7.1%. In vivo T1 and T2 for normal carotid vessel wall were 1213 ± 48.3 ms and 51.1 ± 1.7 ms, with good interscan repeatability. Alternations of T1 and T2 in plaque regions were in agreement with the conventional multicontrast imaging findings. CONCLUSION The proposed SIMPLE allows simultaneous T1 and T2 mapping of the carotid artery in less than 10 minutes, serving as a quantitative tool with good accuracy and reproducibility for plaque characterization.
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Affiliation(s)
- Haikun Qi
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Jie Sun
- Department of Radiology, University of Washington, Seattle, Washington
| | - Huiyu Qiao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Rui Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Niranjan Balu
- Department of Radiology, University of Washington, Seattle, Washington
| | - Chun Yuan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.,Department of Radiology, University of Washington, Seattle, Washington
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
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How to choose the right MR sequence for your research question at 7 T and above? Neuroimage 2018; 168:119-140. [DOI: 10.1016/j.neuroimage.2017.04.044] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 12/29/2022] Open
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Speckter H, Bido J, Hernandez G, Rivera D, Suazo L, Valenzuela S, Fermin R, Oviedo J, Foerster B, Gonzalez C, Stoeter P. Inversion recovery sequences improve delineation of optic pathways in the proximity of suprasellar lesions. JOURNAL OF RADIOSURGERY AND SBRT 2018; 5:115-122. [PMID: 29657892 PMCID: PMC5893452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 11/27/2017] [Indexed: 06/08/2023]
Abstract
INTRODUCTION In Gamma Knife Radiosurgery (GKRS) of suprasellar lesions, the exact localization of the visual pathways is important to avoid radiation induced optic neuropathy (RION). Reliable identification of the optic nerve, chiasm and tracts can be challenging using routine magnetic resonance imaging, especially in patients with lesions compressing the optic structures or in patients who had prior operation of suprasellar tumors. This study investigates the application of inversion recovery sequences (Fast gray and white matter acquisition T1 inversion recovery, FGATIR) to improve identification of the optic pathway. METHODS Inversion recovery sequences were performed on 5 healthy volunteers, varying their inversion times between 400 and 500 ms, and between 800 and 1100 ms. Inversion times were optimized to either suppress or to preserve the signal of the optic structures, while increasing or suppressing the signal of processes within the surrounding cisterns. Inversion recovery sequences were performed before radiosurgery on 10 patients with suprasellar tumors that were compressing or displacing the optic structures. Signal intensities of gray and white matter, of CSF and tumors were measured and subtraction images were calculated. RESULTS Compared to a standard T1-weighted sequence, delineation of the visual pathways was superior on inversion recovery images, both on images with suppression of the optic structures as well on images with suppression of its surrounding tissues, and was rated best on subtraction images. CONCLUSION For radiosurgery of suprasellar tumors, inversion recovery sequences can be of valuable benefit for accurate delineation of optic pathway and radiosurgical dose planning in order to avoid radiation-induced normal tissue effects.
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Affiliation(s)
- Herwin Speckter
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - José Bido
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Giancarlo Hernandez
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Diones Rivera
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Luis Suazo
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Santiago Valenzuela
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Rafael Fermin
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Jairo Oviedo
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Bernd Foerster
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Cesar Gonzalez
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Peter Stoeter
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
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Qi H, Sun J, Qiao H, Chen S, Zhou Z, Pan X, Wang Y, Zhao X, Li R, Yuan C, Chen H. Carotid Intraplaque Hemorrhage Imaging with Quantitative Vessel Wall T1 Mapping: Technical Development and Initial Experience. Radiology 2017; 287:276-284. [PMID: 29117484 DOI: 10.1148/radiol.2017170526] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To develop a three-dimensional (3D) high-spatial-resolution time-efficient sequence for use in quantitative vessel wall T1 mapping. Materials and Methods A previously described sequence, simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) imaging, was extended by introducing 3D golden angle radial k-space sampling (GOAL-SNAP). Sliding window reconstruction was adopted to reconstruct images at different inversion delay times (different T1 contrasts) for voxelwise T1 fitting. Phantom studies were performed to test the accuracy of T1 mapping with GOAL-SNAP against a two-dimensional inversion recovery (IR) spin-echo (SE) sequence. In vivo studies were performed in six healthy volunteers (mean age, 27.8 years ± 3.0 [standard deviation]; age range, 24-32 years; five male) and five patients with atherosclerosis (mean age, 66.4 years ± 5.5; range, 60-73 years; five male) to compare T1 measurements between vessel wall sections (five per artery) with and without intraplaque hemorrhage (IPH). Statistical analyses included Pearson correlation coefficient, Bland-Altman analysis, and Wilcoxon rank-sum test with data permutation by subject. Results Phantom T1 measurements with GOAL-SNAP and IR SE sequences showed excellent correlation (R2 = 0.99), with a mean bias of -25.8 msec ± 43.6 and a mean percentage error of 4.3% ± 2.5. Minimum T1 was significantly different between sections with IPH and those without it (mean, 371 msec ± 93 vs 944 msec ± 120; P = .01). Estimated T1 of normal vessel wall and muscle were 1195 msec ± 136 and 1117 msec ± 153, respectively. Conclusion High-spatial-resolution (0.8 mm isotropic) time-efficient (5 minutes) vessel wall T1 mapping is achieved by using the GOAL-SNAP sequence. This sequence may yield more quantitative reproducible biomarkers with which to characterize IPH and monitor its progression. © RSNA, 2017.
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Affiliation(s)
- Haikun Qi
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Jie Sun
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Huiyu Qiao
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Shuo Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Zechen Zhou
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Xinlei Pan
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Yishi Wang
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Xihai Zhao
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Rui Li
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Chun Yuan
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
| | - Huijun Chen
- From the Center for Biomedical Imaging Research, Department of Biomedical Engineering, Room 109, School of Medicine, Tsinghua University, Haidian District, Beijing 100084, China (H. Qi, H. Qiao, S.C., X.P., Y.W., X.Z., R.L., C.Y., H.C.); Philips Research China, Shanghai, China (Z.Z.); and Department of Radiology, University of Washington, Seattle, Wash (J.S., C.Y.)
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Cao P, Zhu X, Tang S, Leynes A, Jakary A, Larson PEZ. Shuffled magnetization-prepared multicontrast rapid gradient-echo imaging. Magn Reson Med 2017; 79:62-70. [PMID: 29080236 DOI: 10.1002/mrm.26986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 10/04/2017] [Accepted: 10/05/2017] [Indexed: 01/12/2023]
Abstract
PURPOSE To develop a novel acquisition and reconstruction method for magnetization-prepared 3-dimensional multicontrast rapid gradient-echo imaging, using Hankel matrix completion in combination with compressed sensing and parallel imaging. METHODS A random k-space shuffling strategy was implemented in simulation and in vivo human experiments at 7 T for 3-dimensional inversion recovery, T2 /diffusion preparation, and magnetization transfer imaging. We combined compressed sensing, based on total variation and spatial-temporal low-rank regularizations, and parallel imaging with pixel-wise Hankel matrix completion, allowing the reconstruction of tens of multicontrast 3-dimensional images from 3- or 6-min scans. RESULTS The simulation result showed that the proposed method can reconstruct signal-recovery curves in each voxel and was robust for typical in vivo signal-to-noise ratio with 16-times acceleration. In vivo studies achieved 4 to 24 times accelerations for inversion recovery, T2 /diffusion preparation, and magnetization transfer imaging. Furthermore, the contrast was improved by resolving pixel-wise signal-recovery curves after magnetization preparation. CONCLUSIONS The proposed method can improve acquisition efficiencies for magnetization-prepared MRI and tens of multicontrast 3-dimensional images could be recovered from a single scan. Furthermore, it was robust against noise, applicable for recovering multi-exponential signals, and did not require any previous knowledge of model parameters. Magn Reson Med 79:62-70, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Peng Cao
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Xucheng Zhu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Shuyu Tang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Andrew Leynes
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Angela Jakary
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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Metere R, Kober T, Möller HE, Schäfer A. Simultaneous Quantitative MRI Mapping of T1, T2* and Magnetic Susceptibility with Multi-Echo MP2RAGE. PLoS One 2017; 12:e0169265. [PMID: 28081157 PMCID: PMC5230783 DOI: 10.1371/journal.pone.0169265] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 12/14/2016] [Indexed: 11/23/2022] Open
Abstract
The knowledge of relaxation times is essential for understanding the biophysical mechanisms underlying contrast in magnetic resonance imaging. Quantitative experiments, while offering major advantages in terms of reproducibility, may benefit from simultaneous acquisitions. In this work, we demonstrate the possibility of simultaneously recording relaxation-time and susceptibility maps with a prototype Multi-Echo (ME) Magnetization-Prepared 2 RApid Gradient Echoes (MP2RAGE) sequence. T1 maps can be obtained using the MP2RAGE sequence, which is relatively insensitive to inhomogeneities of the radio-frequency transmit field, B1+. As an extension, multiple gradient echoes can be acquired in each of the MP2RAGE readout blocks, which permits the calculation of T2* and susceptibility maps. We used computer simulations to explore the effects of the parameters on the precision and accuracy of the mapping. In vivo parameter maps up to 0.6 mm nominal resolution were acquired at 7 T in 19 healthy volunteers. Voxel-by-voxel correlations and the test-retest reproducibility were used to assess the reliability of the results. When using optimized paramenters, T1 maps obtained with ME-MP2RAGE and standard MP2RAGE showed excellent agreement for the whole range of values found in brain tissues. Simultaneously obtained T2* and susceptibility maps were of comparable quality as Fast Low-Angle SHot (FLASH) results. The acquisition times were more favorable for the ME-MP2RAGE (≈ 19 min) sequence as opposed to the sum of MP2RAGE (≈ 12 min) and FLASH (≈ 10 min) acquisitions. Without relevant sacrifice in accuracy, precision or flexibility, the multi-echo version may yield advantages in terms of reduced acquisition time and intrinsic co-registration, provided that an appropriate optimization of the acquisition parameters is performed.
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Affiliation(s)
- Riccardo Metere
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- * E-mail: (RM); (HEM)
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare HC CMEA SUI DI BM PI, Lausanne, Switzerland
- Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Harald E. Möller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- * E-mail: (RM); (HEM)
| | - Andreas Schäfer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Diagnostic Imaging—Magnetic Resonance—Research & Development, Siemens Healthcare GmbH, Erlangen, Germany
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Chaudhari AS, Sveinsson B, Moran CJ, McWalter EJ, Johnson EM, Zhang T, Gold GE, Hargreaves BA. Imaging and T 2 relaxometry of short-T 2 connective tissues in the knee using ultrashort echo-time double-echo steady-state (UTEDESS). Magn Reson Med 2017; 78:2136-2148. [PMID: 28074498 DOI: 10.1002/mrm.26577] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Revised: 10/26/2016] [Accepted: 11/19/2016] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop a radial, double-echo steady-state (DESS) sequence with ultra-short echo-time (UTE) capabilities for T2 measurement of short-T2 tissues along with simultaneous rapid, signal-to-noise ratio (SNR)-efficient, and high-isotropic-resolution morphological knee imaging. METHODS THe 3D radial UTE readouts were incorporated into DESS, termed UTEDESS. Multiple-echo-time UTEDESS was used for performing T2 relaxometry for short-T2 tendons, ligaments, and menisci; and for Dixon water-fat imaging. In vivo T2 estimate repeatability and SNR efficiency for UTEDESS and Cartesian DESS were compared. The impact of coil combination methods on short-T2 measurements was evaluated by means of simulations. UTEDESS T2 measurements were compared with T2 measurements from Cartesian DESS, multi-echo spin-echo (MESE), and fast spin-echo (FSE). RESULTS UTEDESS produced isotropic resolution images with high SNR efficiency in all short-T2 tissues. Simulations and experiments demonstrated that sum-of-squares coil combinations overestimated short-T2 measurements. UTEDESS measurements of meniscal T2 were comparable to DESS, MESE, and FSE measurements while the tendon and ligament measurements were less biased than those from Cartesian DESS. Average UTEDESS T2 repeatability variation was under 10% in all tissues. CONCLUSION The T2 measurements of short-T2 tissues and high-resolution morphological imaging provided by UTEDESS makes it promising for studying the whole knee, both in routine clinical examinations and longitudinal studies. Magn Reson Med 78:2136-2148, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Akshay S Chaudhari
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Bragi Sveinsson
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Catherine J Moran
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Emily J McWalter
- Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Ethan M Johnson
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Tao Zhang
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Garry E Gold
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Brian A Hargreaves
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Bioengineering, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
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Tamir JI, Uecker M, Chen W, Lai P, Alley MT, Vasanawala SS, Lustig M. T 2 shuffling: Sharp, multicontrast, volumetric fast spin-echo imaging. Magn Reson Med 2017; 77:180-195. [PMID: 26786745 PMCID: PMC4990508 DOI: 10.1002/mrm.26102] [Citation(s) in RCA: 122] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Revised: 11/21/2015] [Accepted: 12/06/2015] [Indexed: 12/22/2022]
Abstract
PURPOSE A new acquisition and reconstruction method called T2 Shuffling is presented for volumetric fast spin-echo (three-dimensional [3D] FSE) imaging. T2 Shuffling reduces blurring and recovers many images at multiple T2 contrasts from a single acquisition at clinically feasible scan times (6-7 min). THEORY AND METHODS The parallel imaging forward model is modified to account for temporal signal relaxation during the echo train. Scan efficiency is improved by acquiring data during the transient signal decay and by increasing echo train lengths without loss in signal-to-noise ratio (SNR). By (1) randomly shuffling the phase encode view ordering, (2) constraining the temporal signal evolution to a low-dimensional subspace, and (3) promoting spatio-temporal correlations through locally low rank regularization, a time series of virtual echo time images is recovered from a single scan. A convex formulation is presented that is robust to partial voluming and radiofrequency field inhomogeneity. RESULTS Retrospective undersampling and in vivo scans confirm the increase in sharpness afforded by T2 Shuffling. Multiple image contrasts are recovered and used to highlight pathology in pediatric patients. A proof-of-principle method is integrated into a clinical musculoskeletal imaging workflow. CONCLUSION The proposed T2 Shuffling method improves the diagnostic utility of 3D FSE by reducing blurring and producing multiple image contrasts from a single scan. Magn Reson Med 77:180-195, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jonathan I. Tamir
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Martin Uecker
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Weitian Chen
- Global Applied Science Laboratory, GE Healthcare, Menlo Park, California, USA
| | - Peng Lai
- Global Applied Science Laboratory, GE Healthcare, Menlo Park, California, USA
| | - Marcus T. Alley
- Department of Radiology, Stanford University, Stanford, California, USA
| | | | - Michael Lustig
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
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50
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Hagberg GE, Bause J, Ethofer T, Ehses P, Dresler T, Herbert C, Pohmann R, Shajan G, Fallgatter A, Pavlova MA, Scheffler K. Whole brain MP2RAGE-based mapping of the longitudinal relaxation time at 9.4T. Neuroimage 2017; 144:203-216. [DOI: 10.1016/j.neuroimage.2016.09.047] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 09/16/2016] [Accepted: 09/20/2016] [Indexed: 11/16/2022] Open
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