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Dickie BR, Ahmed Z, Arvidsson J, Bell LC, Buckley DL, Debus C, Fedorov A, Floca R, Gutmann I, van der Heijden RA, van Houdt PJ, Sourbron S, Thrippleton MJ, Quarles C, Kompan IN. A community-endorsed open-source lexicon for contrast agent-based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI). Magn Reson Med 2024; 91:1761-1773. [PMID: 37831600 DOI: 10.1002/mrm.29840] [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: 05/17/2023] [Revised: 07/25/2023] [Accepted: 08/04/2023] [Indexed: 10/15/2023]
Abstract
This manuscript describes the ISMRM OSIPI (Open Science Initiative for Perfusion Imaging) lexicon for dynamic contrast-enhanced and dynamic susceptibility-contrast MRI. The lexicon was developed by Taskforce 4.2 of OSIPI to provide standardized definitions of commonly used quantities, models, and analysis processes with the aim of reducing reporting variability. The taskforce was established in February 2020 and consists of medical physicists, engineers, clinicians, data and computer scientists, and DICOM (Digital Imaging and Communications in Medicine) standard experts. Members of the taskforce collaborated via a slack channel and quarterly virtual meetings. Members participated by defining lexicon items and reporting formats that were reviewed by at least two other members of the taskforce. Version 1.0.0 of the lexicon was subject to open review from the wider perfusion imaging community between January and March 2022, and endorsed by the Perfusion Study Group of the ISMRM in the summer of 2022. The initial scope of the lexicon was set by the taskforce and defined such that it contained a basic set of quantities, processes, and models to enable users to report an end-to-end analysis pipeline including kinetic model fitting. We also provide guidance on how to easily incorporate lexicon items and definitions into free-text descriptions (e.g., in manuscripts and other documentation) and introduce an XML-based pipeline encoding format to encode analyses using lexicon definitions in standardized and extensible machine-readable code. The lexicon is designed to be open-source and extendable, enabling ongoing expansion of its content. We hope that widespread adoption of lexicon terminology and reporting formats described herein will increase reproducibility within the field.
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Affiliation(s)
- Ben R Dickie
- Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Center, Manchester Academic Health Science Center, The University of Manchester, Manchester, UK
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Jonathan Arvidsson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Laura C Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | | | - Andrey Fedorov
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ralf Floca
- National Center for Radiation Research in Oncology, Heidelberg Institute for Radiation Oncology, Heidelberg, Germany
| | - Ingomar Gutmann
- Faculty of Physics, Physics of Functional Materials, University of Vienna, Vienna, Austria
| | - Rianne A van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Steven Sourbron
- Department of Infection, Immunity, and Cardiovascular Diseases, University of Sheffield, Sheffield, UK
| | - Michael J Thrippleton
- Edinburgh Imaging and Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Chad Quarles
- Department of Cancer Systems Imaging, UT MD Anderson Cancer Center, Houston, Texas, USA
| | - Ina N Kompan
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
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Kjærgaard U, Bøgh N, Hansen ESS, Tougaard RS, Bertelsen LB, Schulte RF, Laustsen C. Assessment of focal renal ischemia–reperfusion injury in a porcine model using hyperpolarized [
1‐
13
C
]pyruvate
MRI. Magn Reson Med 2023; 90:655-663. [DOI: 10.1002/mrm.29649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 03/09/2023] [Accepted: 03/09/2023] [Indexed: 03/29/2023]
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Echeverria‐Chasco R, Martin‐Moreno PL, Garcia‐Fernandez N, Vidorreta M, Aramendia‐Vidaurreta V, Cano D, Villanueva A, Bastarrika G, Fernández‐Seara MA. Multiparametric renal magnetic resonance imaging: A reproducibility study in renal allografts with stable function. NMR IN BIOMEDICINE 2023; 36:e4832. [PMID: 36115029 PMCID: PMC10078573 DOI: 10.1002/nbm.4832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 06/15/2023]
Abstract
Monitoring renal allograft function after transplantation is key for the early detection of allograft impairment, which in turn can contribute to preventing the loss of the allograft. Multiparametric renal MRI (mpMRI) is a promising noninvasive technique to assess and characterize renal physiopathology; however, few studies have employed mpMRI in renal allografts with stable function (maintained function over a long time period). The purposes of the current study were to evaluate the reproducibility of mpMRI in transplant patients and to characterize normal values of the measured parameters, and to estimate the labeling efficiency of Pseudo-Continuous Arterial Spin Labeling (PCASL) in the infrarenal aorta using numerical simulations considering experimental measurements of aortic blood flow profiles. The subjects were 20 transplant patients with stable kidney function, maintained over 1 year. The MRI protocol consisted of PCASL, intravoxel incoherent motion, and T1 inversion recovery. Phase contrast was used to measure aortic blood flow. Renal blood flow (RBF), diffusion coefficient (D), pseudo-diffusion coefficient (D*), flowing fraction ( f ), and T1 maps were calculated and mean values were measured in the cortex and medulla. The labeling efficiency of PCASL was estimated from simulation of Bloch equations. Reproducibility was assessed with the within-subject coefficient of variation, intraclass correlation coefficient, and Bland-Altman analysis. Correlations were evaluated using the Pearson correlation coefficient. The significance level was p less than 0.05. Cortical reproducibility was very good for T1, D, and RBF, moderate for f , and low for D*, while medullary reproducibility was good for T1 and D. Significant correlations in the cortex between RBF and f (r = 0.66), RBF and eGFR (r = 0.64), and D* and eGFR (r = -0.57) were found. Normal values of the measured parameters employing the mpMRI protocol in kidney transplant patients with stable function were characterized and the results showed good reproducibility of the techniques.
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Affiliation(s)
- Rebeca Echeverria‐Chasco
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Paloma L. Martin‐Moreno
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
- Department of NephrologyClínica Universidad de NavarraPamplonaSpain
| | - Nuria Garcia‐Fernandez
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
- Department of NephrologyClínica Universidad de NavarraPamplonaSpain
| | | | - Verónica Aramendia‐Vidaurreta
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - David Cano
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
| | - Arantxa Villanueva
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
- Electrical Electronics and Communications Engineering Department and Smart Cities InstitutePublic University of NavarrePamplonaSpain
| | - Gorka Bastarrika
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
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Rankin AJ, Mayne K, Allwood-Spiers S, Hall Barrientos P, Roditi G, Gillis KA, Mark PB. Will advances in functional renal magnetic resonance imaging translate to the nephrology clinic? Nephrology (Carlton) 2021; 27:223-230. [PMID: 34724286 DOI: 10.1111/nep.13985] [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: 07/23/2021] [Revised: 10/01/2021] [Accepted: 10/09/2021] [Indexed: 11/28/2022]
Abstract
Characterizing structural and tissue abnormalities of the kidney is fundamental to understanding kidney disease. Functional multi-parametric renal magnetic resonance imaging (MRI) is a noninvasive imaging strategy whereby several sequences are employed within a single session to quantify renal perfusion, tissue oxygenation, fibrosis, inflammation, and oedema without using ionizing radiation. In this review, we discuss evidence surrounding its use in several clinical settings including acute kidney injury, chronic kidney disease, hypertension, polycystic kidney disease and around renal transplantation. Kidney size on MRI is already a validated measure for making therapeutic decisions in the setting of polycystic kidney disease. Functional MRI sequences, T1 mapping and apparent diffusion coefficient, can non-invasively quantify interstitial fibrosis and so may have a near-future role in the nephrology clinic to stratify the risk of progressive chronic kidney disease or transplant dysfunction. Beyond this, multi-parametric MRI may be used diagnostically, for example differentiating inflammatory versus ischaemic causes of renal dysfunction, but this remains to be proven. Changes in MRI properties of kidney parenchyma may be useful surrogate markers to use as end points in clinical trials to assess if drugs prevent renal fibrosis or alter kidney perfusion. Large, multi-centre studies of functional renal MRI are ongoing which aim to provide definitive answers as to its role in the management of patients with renal dysfunction.
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Affiliation(s)
- Alastair J Rankin
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK.,Glasgow Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK
| | - Kaitlin Mayne
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK.,Glasgow Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK
| | - Sarah Allwood-Spiers
- Department of Clinical Physics and Bioengineering, NHS Greater Glasgow & Clyde, Glasgow, UK
| | | | - Giles Roditi
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK.,Department of Radiology, NHS Greater Glasgow & Clyde, Glasgow, UK
| | - Keith A Gillis
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK.,Glasgow Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK
| | - Patrick B Mark
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK.,Glasgow Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK
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