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Reeder SB, Yokoo T, França M, Hernando D, Alberich-Bayarri Á, Alústiza JM, Gandon Y, Henninger B, Hillenbrand C, Jhaveri K, Karçaaltıncaba M, Kühn JP, Mojtahed A, Serai SD, Ward R, Wood JC, Yamamura J, Martí-Bonmatí L. Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR. Radiology 2023; 307:e221856. [PMID: 36809220 PMCID: PMC10068892 DOI: 10.1148/radiol.221856] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 10/20/2022] [Accepted: 11/16/2022] [Indexed: 02/23/2023]
Abstract
Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.
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Affiliation(s)
- Scott B. Reeder
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Takeshi Yokoo
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Manuela França
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Diego Hernando
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Ángel Alberich-Bayarri
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - José María Alústiza
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Yves Gandon
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Benjamin Henninger
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Claudia Hillenbrand
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Kartik Jhaveri
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Musturay Karçaaltıncaba
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Jens-Peter Kühn
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Amirkasra Mojtahed
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Suraj D. Serai
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Richard Ward
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - John C. Wood
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Jin Yamamura
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Luis Martí-Bonmatí
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
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Hernando D, Zhao R, Yuan Q, Aliyari Ghasabeh M, Ruschke S, Miao X, Karampinos DC, Mao L, Harris DT, Mattison RJ, Jeng MR, Pedrosa I, Kamel IR, Vasanawala S, Yokoo T, Reeder SB. Multicenter Reproducibility of Liver Iron Quantification with 1.5-T and 3.0-T MRI. Radiology 2023; 306:e213256. [PMID: 36194113 PMCID: PMC9885339 DOI: 10.1148/radiol.213256] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 07/22/2022] [Accepted: 08/08/2022] [Indexed: 01/26/2023]
Abstract
Background MRI is a standard of care tool to measure liver iron concentration (LIC). Compared with regulatory-approved R2 MRI, R2* MRI has superior speed and is available in most MRI scanners; however, the cross-vendor reproducibility of R2*-based LIC estimation remains unknown. Purpose To evaluate the reproducibility of LIC via single-breath-hold R2* MRI at both 1.5 T and 3.0 T with use of a multicenter, multivendor study. Materials and Methods Four academic medical centers using MRI scanners from three different vendors (three 1.5-T scanners, one 2.89-T scanner, and two 3.0-T scanners) participated in this prospective cross-sectional study. Participants with known or suspected liver iron overload were recruited to undergo multiecho gradient-echo MRI for R2* mapping at 1.5 T and 3.0 T (2.89 T or 3.0 T) on the same day. R2* maps were reconstructed from the multiecho images and analyzed at a single center. Reference LIC measurements were obtained with a commercial R2 MRI method performed using standardized 1.5-T spin-echo imaging. R2*-versus-LIC calibrations were generated across centers and field strengths using linear regression and compared using F tests. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic performance of R2* MRI in the detection of clinically relevant LIC thresholds. Results A total of 207 participants (mean age, 38 years ± 20 [SD]; 117 male participants) were evaluated between March 2015 and September 2019. A linear relationship was confirmed between R2* and LIC. All calibrations within the same field strength were highly reproducible, showing no evidence of statistically significant center-specific differences (P > .43 across all comparisons). Calibrations for 1.5 T and 3.0 T were generated, as follows: for 1.5 T, LIC (in milligrams per gram [dry weight]) = -0.16 + 2.603 × 10-2 R2* (in seconds-1); for 2.89 T, LIC (in milligrams per gram) = -0.03 + 1.400 × 10-2 R2* (in seconds-1); for 3.0 T, LIC (in milligrams per gram) = -0.03 + 1.349 × 10-2 R2* (in seconds-1). Liver R2* had high diagnostic performance in the detection of clinically relevant LIC thresholds (area under the ROC curve, >0.98). Conclusion R2* MRI enabled accurate and reproducible quantification of liver iron overload over clinically relevant ranges of liver iron concentration (LIC). The data generated in this study provide the necessary calibrations for broad clinical dissemination of R2*-based LIC quantification. ClinicalTrials.gov registration no.: NCT02025543 © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Diego Hernando
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ruiyang Zhao
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Qing Yuan
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Mounes Aliyari Ghasabeh
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Stefan Ruschke
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Xinran Miao
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Dimitrios C. Karampinos
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Lu Mao
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - David T. Harris
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ryan J. Mattison
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Michael R. Jeng
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ivan Pedrosa
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Ihab R. Kamel
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Shreyas Vasanawala
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Takeshi Yokoo
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
| | - Scott B. Reeder
- From the Departments of Radiology (D.H., R.Z., D.T.H., S.B.R.),
Medical Physics (D.H., R.Z., S.B.R.), Statistics (X.M.), Biostatistics and
Medical Informatics (L.M.), Medicine (R.J.M.), Biomedical Engineering (S.B.R.),
Medicine (S.B.R.), and Emergency Medicine, University of
Wisconsin–Madison, 1111 Highland Ave, WIMR2, Room 2472, Madison, WI 53705
(S.B.R.); Department of Radiology (Q.Y., I.P., T.Y.) and Advanced Imaging
Research Center (I.P., T.Y.), University of Texas Southwestern Medical Center,
Dallas, Tex; Department of Radiology, The Johns Hopkins University, Baltimore,
Md (M.A.G., I.R.K.); Department of Diagnostic and Interventional Radiology,
School of Medicine, Klinikum rechts der Isar, Technical University of Munich,
Munich, Germany (S.R., D.C.K.); and Departments of Pediatrics (M.R.J.) and
Radiology (S.V.), Stanford University, Palo Alto, Calif
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3
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Shah FT, Porter JB, Sadasivam N, Kaya B, Moon JC, Velangi M, Ako E, Pancham S. Guidelines for the monitoring and management of iron overload in patients with haemoglobinopathies and rare anaemias. Br J Haematol 2022; 196:336-350. [PMID: 34617272 DOI: 10.1111/bjh.17839] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 08/10/2021] [Accepted: 09/02/2021] [Indexed: 01/19/2023]
Affiliation(s)
- Farrukh T Shah
- Department of Haematology, Whittington Health, London, UK
| | - John B Porter
- Department of Haematology, University College Hospitals, London, UK
| | - Nandini Sadasivam
- Department of Haematology, Manchester Royal Infirmary, Manchester, UK
| | - Banu Kaya
- Department of Paediatric Haematology and Oncology, Barts Health NHS Trust, London, UK
| | - James C Moon
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, UK
- Institutes for Cardiovascular Science, University College London, London, UK
| | - Mark Velangi
- Department of Haematology, Birmingham Children's Hospital, Birmingham, UK
| | - Emmanuel Ako
- Department of Cardiology, Chelsea and Westminster Hospital, London, UK
| | - Shivan Pancham
- Department of Haematology, Sandwell and West Birmingham NHS Trust, West Bromwich, UK
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4
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Doyle EK, Thornton S, Ghugre NR, Coates TD, Nayak KS, Wood JC. Effects of B 1 + Heterogeneity on Spin Echo-Based Liver Iron Estimates. J Magn Reson Imaging 2021; 55:1419-1425. [PMID: 34555245 PMCID: PMC8940739 DOI: 10.1002/jmri.27928] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 09/07/2021] [Accepted: 09/10/2021] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Liver iron concentration (LIC) measured by MRI has become the clinical reference standard for managing iron overload in chronically transfused patients. Transverse relaxivity (R2 or R2 * ) measurements are converted to LIC units using empirically derived calibration curves. HYPOTHESIS That flip angle (FA) error due to B1 + spatial heterogeneity causes significant LIC quantitation error. B1 + scale (b1 , [FAactual /FAspecified ]) variation is a major problem at 3 T which could reduce the accuracy of transverse relaxivity measurements. STUDY TYPE Prospective. POPULATION Forty-seven subjects with chronic transfusional iron overload undergoing clinically indicated LIC assessment. FIELD STRENGTH/SEQUENCE 5 T/3 T dual-repetition time B1 + mapping sequence ASSESSMENT: We quantified the average/standard deviation b1 in the right and left lobes of the liver from B1 + maps acquired at 1.5 T and 3 T. The impact of b1 variation on spin echo LIC estimates was determined using a Monte Carlo model. STATISTICAL TESTS Mean, median, and standard deviation in whole liver and right and left lobes; two-sided t-test between whole-liver b1 means. RESULTS Average b1 within the liver was 99.3% ± 12.3% at 1.5 T versus 69.6% ± 14.6% at 3 T and was independent of iron burden (P < 0.05). Monte Carlo simulations demonstrated that b1 systematically increased R2 estimates at lower LIC (<~25 mg/g at 1.5 T, <~15 mg/g at 3 T) but flattened or even inverted the R2 -LIC relationship at higher LIC (≥~25 mg/g to 1.5 T, ≥~15 mg/g to 3 T); changes in the R2 -LIC relationship were symmetric with respect to over and under excitation and were similar at 1.5 T and 3 T (for the same R2 value). The R2 * -LIC relationship was independent of b1 . CONCLUSION Spin echo R2 measurement of LIC at 3 T is error-prone without correction for b1 errors. The impact of b1 error on current 1.5 T spin echo-based techniques for LIC quantification is large enough to introduce measurable intersubject variability but the in vivo effect size needs a dedicated validation study. LEVEL OF EVIDENCE 1. TECHNICAL EFFICACY STAGE 2.
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Affiliation(s)
- Eamon K Doyle
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.,Division of Cardiology and Radiology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Samuel Thornton
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA
| | - Nilesh R Ghugre
- Schulich Heart Research Program, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Thomas D Coates
- Division of Hematology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA
| | - John C Wood
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.,Division of Cardiology and Radiology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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5
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Doyle EK, Thornton S, Toy KA, Powell AJ, Wood JC. Improving CPMG liver iron estimates with a T 1 -corrected proton density estimator. Magn Reson Med 2021; 86:3348-3359. [PMID: 34324729 DOI: 10.1002/mrm.28943] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 07/06/2021] [Accepted: 07/07/2021] [Indexed: 01/19/2023]
Abstract
PURPOSE CPMG spin echo acquisitions are attractive for diagnosing and monitoring liver iron concentration in iron overload disorders due to their time efficiency and potential to reveal unique information about tissue iron distribution. Clinical adoption remains low due to the insensitivity of CPMG-based R 2 estimates to liver iron concentration (LIC) when common fitting techniques are applied. In this work, we demonstrate that the inclusion of a proton density estimator (PDE) derived from the CPMG acquisition increase the sensitivity of CPMG R 2 estimates to LIC in both simulated and in-vivo human data. THEORY AND METHODS CPMG R 2 acquisitions from 50 clinically indicated MRI studies in patients with iron overload were analyzed with and without PDE constraints. Liver regions of interest were fit to monoexpontial and nonexponential signal decay equations. LIC by R 2 ∗ served as the reference standard. The observed calibration between CPMG R 2 values and LIC were compared to results predicted from a previously validated Monte Carlo model. RESULTS The sensitivity of CPMG-derived R 2 triples when a proton density constraint is applied. When compared with R 2 ∗ -LIC estimates, both monoexponential and nonexponential models were unbiased but demonstrated broad 95% confidence intervals particularly for LIC values below 12 mg/g. Absolute error did not increase with LIC. CONCLUSION A proton density constraint can increase the sensitivity of CPMG-based models to iron. CPMG acquisitions are time-efficient and could potentially improve the dynamic range of single spin echo techniques as well as providing insight into tissue iron distribution.
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Affiliation(s)
- Eamon K Doyle
- Cardiology, Children's Hospital of Los Angeles, Los Angeles, CA, USA.,Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Samuel Thornton
- Electrical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Kristin A Toy
- Cardiology, Children's Hospital of Los Angeles, Los Angeles, CA, USA
| | | | - John C Wood
- Cardiology, Children's Hospital of Los Angeles, Los Angeles, CA, USA.,Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
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6
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MRI-based R2* mapping in patients with suspected or known iron overload. Abdom Radiol (NY) 2021; 46:2505-2515. [PMID: 33388804 DOI: 10.1007/s00261-020-02912-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/09/2020] [Accepted: 12/11/2020] [Indexed: 01/19/2023]
Abstract
PURPOSE R2* relaxometry is a quantitative method for assessment of iron overload. The purpose is to analyze the cross-sectional relationships between R2* in organs across patients with primary and secondary iron overload. Secondary analyses were conducted to analyze R2* according to treatment regimen. METHODS This is a retrospective, cross-sectional, institutional review board-approved study of eighty-one adult patients with known or suspected iron overload. R2* was measured by segmenting the liver, spleen, bone marrow, pancreas, renal cortex, renal medulla, and myocardium using breath-hold multi-echo gradient-recalled echo imaging at 1.5 T. Phlebotomy, transfusion, and chelation therapy were documented. Analyses included correlation, Kruskal-Wallis, and post hoc Dunn tests. p < 0.01 was considered significant. RESULTS Correlations between liver R2* and that of the spleen, bone marrow, pancreas, and heart were respectively 0.49, 0.33, 0.27, and 0.34. R2* differed between patients with primary and secondary overload in the liver (p < 0.001), spleen (p < 0.001), bone marrow (p < 0.01), renal cortex (p < 0.001), and renal medulla (p < 0.001). Liver, spleen, and bone marrow R2* were higher in thalassemia than in hereditary hemochromatosis (all p < 0.01). Renal cortex R2* was higher in sickle cell disease than in hereditary hemochromatosis (p < 0.001) and in thalassemia (p < 0.001). Overall, there was a trend toward lower liver R2* in patients assigned to phlebotomy and higher liver R2* in patients assigned to transfusion and chelation therapy. CONCLUSION R2* relaxometry revealed differences in degree or distribution of iron overload between organs, underlying etiologies, and treatment.
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7
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Garcia-Casal MN, Pasricha SR, Martinez RX, Lopez-Perez L, Peña-Rosas JP. Serum or plasma ferritin concentration as an index of iron deficiency and overload. Cochrane Database Syst Rev 2021; 5:CD011817. [PMID: 34028001 PMCID: PMC8142307 DOI: 10.1002/14651858.cd011817.pub2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND Reference standard indices of iron deficiency and iron overload are generally invasive, expensive, and can be unpleasant or occasionally risky. Ferritin is an iron storage protein and its concentration in the plasma or serum reflects iron stores; low ferritin indicates iron deficiency, while elevated ferritin reflects risk of iron overload. However, ferritin is also an acute-phase protein and its levels are elevated in inflammation and infection. The use of ferritin as a diagnostic test of iron deficiency and overload is a common clinical practice. OBJECTIVES To determine the diagnostic accuracy of ferritin concentrations (serum or plasma) for detecting iron deficiency and risk of iron overload in primary and secondary iron-loading syndromes. SEARCH METHODS We searched the following databases (10 June 2020): DARE (Cochrane Library) Issue 2 of 4 2015, HTA (Cochrane Library) Issue 4 of 4 2016, CENTRAL (Cochrane Library) Issue 6 of 12 2020, MEDLINE (OVID) 1946 to 9 June 2020, Embase (OVID) 1947 to week 23 2020, CINAHL (Ebsco) 1982 to June 2020, Web of Science (ISI) SCI, SSCI, CPCI-exp & CPCI-SSH to June 2020, POPLINE 16/8/18, Open Grey (10/6/20), TRoPHI (10/6/20), Bibliomap (10/6/20), IBECS (10/6/20), SCIELO (10/6/20), Global Index Medicus (10/6/20) AIM, IMSEAR, WPRIM, IMEMR, LILACS (10/6/20), PAHO (10/6/20), WHOLIS 10/6/20, IndMED (16/8/18) and Native Health Research Database (10/6/20). We also searched two trials registers and contacted relevant organisations for unpublished studies. SELECTION CRITERIA We included all study designs seeking to evaluate serum or plasma ferritin concentrations measured by any current or previously available quantitative assay as an index of iron status in individuals of any age, sex, clinical and physiological status from any country. DATA COLLECTION AND ANALYSIS We followed standard Cochrane methods. We designed the data extraction form to record results for ferritin concentration as the index test, and bone marrow iron content for iron deficiency and liver iron content for iron overload as the reference standards. Two other authors further extracted and validated the number of true positive, true negative, false positive, false negative cases, and extracted or derived the sensitivity, specificity, positive and negative predictive values for each threshold presented for iron deficiency and iron overload in included studies. We assessed risk of bias and applicability using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. We used GRADE assessment to enable the quality of evidence and hence strength of evidence for our conclusions. MAIN RESULTS Our search was conducted initially in 2014 and updated in 2017, 2018 and 2020 (10 June). We identified 21,217 records and screened 14,244 records after duplicates were removed. We assessed 316 records in full text. We excluded 190 studies (193 records) with reasons and included 108 studies (111 records) in the qualitative and quantitative analysis. There were 11 studies (12 records) that we screened from the last search update and appeared eligible for a future analysis. We decided to enter these as awaiting classification. We stratified the analysis first by participant clinical status: apparently healthy and non-healthy populations. We then stratified by age and pregnancy status as: infants and children, adolescents, pregnant women, and adults. Iron deficiency We included 72 studies (75 records) involving 6059 participants. Apparently healthy populations Five studies screened for iron deficiency in people without apparent illness. In the general adult population, three studies reported sensitivities of 63% to 100% at the optimum cutoff for ferritin, with corresponding specificities of 92% to 98%, but the ferritin cutoffs varied between studies. One study in healthy children reported a sensitivity of 74% and a specificity of 77%. One study in pregnant women reported a sensitivity of 88% and a specificity of 100%. Overall confidence in these estimates was very low because of potential bias, indirectness, and sparse and heterogenous evidence. No studies screened for iron overload in apparently healthy people. People presenting for medical care There were 63 studies among adults presenting for medical care (5042 participants). For a sample of 1000 subjects with a 35% prevalence of iron deficiency (of the included studies in this category) and supposing a 85% specificity, there would be 315 iron-deficient subjects correctly classified as having iron deficiency and 35 iron-deficient subjects incorrectly classified as not having iron deficiency, leading to a 90% sensitivity. Thresholds proposed by the authors of the included studies ranged between 12 to 200 µg/L. The estimated diagnostic odds ratio was 50. Among non-healthy adults using a fixed threshold of 30 μg/L (nine studies, 512 participants, low-certainty evidence), the pooled estimate for sensitivity was 79% with a 95% confidence interval of (58%, 91%) and specificity of 98%, with a 95% confidence interval of (91%, 100%). The estimated diagnostic odds ratio was 140, a relatively highly informative test. Iron overload We included 36 studies (36 records) involving 1927 participants. All studies concerned non-healthy populations. There were no studies targeting either infants, children, or pregnant women. Among all populations (one threshold for males and females; 36 studies, 1927 participants, very low-certainty evidence): for a sample of 1000 subjects with a 42% prevalence of iron overload (of the included studies in this category) and supposing a 65% specificity, there would be 332 iron-overloaded subjects correctly classified as having iron overload and 85 iron-overloaded subjects incorrectly classified as not having iron overload, leading to a 80% sensitivity. The estimated diagnostic odds ratio was 8. AUTHORS' CONCLUSIONS At a threshold of 30 micrograms/L, there is low-certainty evidence that blood ferritin concentration is reasonably sensitive and a very specific test for iron deficiency in people presenting for medical care. There is very low certainty that high concentrations of ferritin provide a sensitive test for iron overload in people where this condition is suspected. There is insufficient evidence to know whether ferritin concentration performs similarly when screening asymptomatic people for iron deficiency or overload.
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Affiliation(s)
| | - Sant-Rayn Pasricha
- Division: Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
| | | | | | - Juan Pablo Peña-Rosas
- Department of Nutrition and Food Safety, World Health Organization, Geneva, Switzerland
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8
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Planeta K, Kubala-Kukus A, Drozdz A, Matusiak K, Setkowicz Z, Chwiej J. The assessment of the usability of selected instrumental techniques for the elemental analysis of biomedical samples. Sci Rep 2021; 11:3704. [PMID: 33580127 PMCID: PMC7881205 DOI: 10.1038/s41598-021-82179-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 01/18/2021] [Indexed: 02/06/2023] Open
Abstract
The fundamental role of major, minor and trace elements in different physiological and pathological processes occurring in living organism makes that elemental analysis of biomedical samples becomes more and more popular issue. The most often used tools for analysis of the elemental composition of biological samples include Flame and Graphite Furnace Atomic Absorption Spectroscopy (F-AAS and GF-AAS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Each of these techniques has many advantages and limitations that should be considered in the first stage of planning the measurement procedure. Their reliability can be checked in the validation process and the precision, trueness and detection limits of elements belong to the most frequently determined validation parameters. The main purpose of this paper was the discussion of selected instrumental techniques (F-AAS, GF-AAS, ICP-OES and ICP-MS) in term of the achieved validation parameters and the usefulness in the analysis of biological samples. The focus in the detailed literature studies was also put on the methods of preparation of the biomedical samples. What is more based on the own data the usefulness of the total reflection X-ray fluorescence spectroscopy for the elemental analysis of animal tissues was examined. The detection limits of elements, precision and trueness for the technique were determined and compared with the literature data concerning other of the discussed techniques of elemental analysis. Reassuming, the following paper is to serve as a guide and comprehensive source of information concerning the validation parameters achievable in different instrumental techniques used for the elemental analysis of biomedical samples.
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Affiliation(s)
- Karolina Planeta
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland
| | - Aldona Kubala-Kukus
- Institute of Physics, Jan Kochanowski University, Kielce, Poland
- Holly Cross Cancer Centre, Kielce, Poland
| | - Agnieszka Drozdz
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland
| | - Katarzyna Matusiak
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland
| | - Zuzanna Setkowicz
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | - Joanna Chwiej
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland.
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9
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Headley AM, Grice JV, Pickens DR. Reproducibility of liver iron concentration estimates in MRI through R2* measurement determined by least-squares curve fitting. J Appl Clin Med Phys 2020; 21:295-303. [PMID: 33207043 PMCID: PMC7769411 DOI: 10.1002/acm2.13096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/28/2020] [Accepted: 10/21/2020] [Indexed: 12/13/2022] Open
Abstract
Measuring transverse relaxation rate (R2* = 1/T2*) via MRI allows for noninvasive evaluation of multiple clinical parameters, including liver iron concentration (LIC) and fat fraction. Both fat and iron contribute to diffuse liver disease when stored in excess in the liver. This liver damage leads to fibrosis and cirrhosis with an increased risk of developing hepatocellular carcinoma. Liver iron concentration is linearly related to R2* measurements using MRI. A phantom was constructed to assess R2* quantification variability on 1.5 and 3 T MRI systems. Quantification was executed using least-squares curve fitting techniques. The phantom was created using readily available, low-cost materials. It contains four vials with R2* values that cover a clinically relevant range (100 to 420 Hz at 1.5 T). Iron content was achieved using ferric chloride solutions contained in glass vials, each affixed in a three-dimensional (3D)-printed polylactide (PLA) structure, surrounded by distilled water, all housed in a sealed acrylic cylinder. Multiple phantom stands were also 3D-printed using PLA for precise orientation of the phantom with respect to the direction of the static magnetic field. Acquisitions at different phantom angles, across multiple MRI systems, and with different pulse sequence parameters were evaluated. The variability between any two R2* measurements, taken in the same vial under these various acquisition conditions, on a 1.5 T MRI system, was <7% for each of the four vials. For 3 T MRI systems, variability was less than 14% in all cases. Variability was <6% for both 1.5 and 3 T acquisitions when unchanged pulse sequence parameters were used. The phantom can be used to mimic a range of clinically relevant levels of R2* relaxation rates, as measured using MRI. These measurements were found to be reproducible relative to the gold-standard method, liver biopsy, across several different image acquisition conditions.
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Affiliation(s)
- Andrew M. Headley
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTNUSA
| | - Jared V. Grice
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTNUSA
| | - David R. Pickens
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTNUSA
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10
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Abstract
Iron overload is a common clinical problem resulting from hereditary hemochromatosis or secondary hemosiderosis (mainly associated with transfusion therapy), being also associated with chronic liver diseases and metabolic disorders. Excess of iron accumulates in organs like the liver, pancreas and heart. Without treatment, patients with iron overload disorders will develop liver cirrhosis, diabetes and cardiomyopathy. Iron quantification is therefore crucial not only for diagnosis of iron overload but also to monitor iron-reducing therapies. Liver iron concentration is considered the surrogate marker of total body iron stores. Because liver biopsy is invasive and prone to high variability and sampling bias, MR imaging has emerged as a non-invasive method and gained wide acceptance, now being considered the standard of care for assessing iron overload. Nevertheless, there are different MR techniques for iron quantification and there is still no consensus about the best technique or postprocessing tool for hepatic iron quantification, with the choice of imaging technique depending mainly on the local expertise as well on the available equipment and software. Because different methods should not be used interchangeably, it is important to choose one method and use the same one when following up patients over time.
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Affiliation(s)
- Manuela França
- Radiology Department - Centro Hospitalar Universitário do Porto, Largo Prof Abel Salazar, 4099-001, Porto, Portugal.
- Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, I3S, Instituto de Investigação e Inovação em Saúde, Porto, Portugal.
| | - João Gomes Carvalho
- Radiology Department - Centro Hospitalar Universitário do Porto, Largo Prof Abel Salazar, 4099-001, Porto, Portugal
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11
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Grant ES, Clucas DB, McColl G, Hall LT, Simpson DA. Re-examining ferritin-bound iron: current and developing clinical tools. Clin Chem Lab Med 2020; 59:459-471. [PMID: 33090965 DOI: 10.1515/cclm-2020-1095] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 10/01/2020] [Indexed: 12/11/2022]
Abstract
Iron is a highly important metal ion cofactor within the human body, necessary for haemoglobin synthesis, and required by a wide range of enzymes for essential metabolic processes. Iron deficiency and overload both pose significant health concerns and are relatively common world-wide health hazards. Effective measurement of total iron stores is a primary tool for both identifying abnormal iron levels and tracking changes in clinical settings. Population based data is also essential for tracking nutritional trends. This review article provides an overview of the strengths and limitations associated with current techniques for diagnosing iron status, which sets a basis to discuss the potential of a new serum marker - ferritin-bound iron - and the improvement it could offer to iron assessment.
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Affiliation(s)
- Erin S Grant
- School of Physics, University of Melbourne, Parkville, VIC, Australia
| | - Danielle B Clucas
- Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia.,Diagnostic Haematology, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Gawain McColl
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health and the University of Melbourne, Parkville, VIC, Australia
| | - Liam T Hall
- School of Physics, University of Melbourne, Parkville, VIC, Australia
| | - David A Simpson
- School of Physics, University of Melbourne, Parkville, VIC, Australia
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Real-World Experience Measurement of Liver Iron Concentration by R2 vs. R2 Star MRI in Hemoglobinopathies. Diagnostics (Basel) 2020; 10:diagnostics10100768. [PMID: 33003498 PMCID: PMC7601611 DOI: 10.3390/diagnostics10100768] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 09/16/2020] [Accepted: 09/23/2020] [Indexed: 01/19/2023] Open
Abstract
Background: Non-invasive determination of liver iron concentration (LIC) is a valuable tool that guides iron chelation therapy in transfusion-dependent patients. Multiple methods have been utilized to measure LIC by MRI. The purpose of this study was to compare free breathing R2* (1/T2*) to whole-liver Ferriscan R2 method for estimation of LIC in a pediatric and young adult population who predominantly have hemoglobinopathies. Methods: Clinical liver and cardiac MRI scans from April 2016 to May 2018 on a Phillips 1.5 T scanner were reviewed. Free breathing T2 and T2* weighted images were acquired on each patient. For T2, multi-slice spin echo sequences were obtained. For T2*, a single mid-liver slice fast gradient echo was performed starting at 0.6 ms with 1.2 ms increments with signal averaging. R2 measurements were performed by Ferriscan analysis. R2* measurements were performed by quantitative T2* map analysis. Results: 107 patients underwent liver scans with the following diagnoses: 76 sickle cell anemia, 20 Thalassemia, 9 malignancies and 2 Blackfan Diamond anemia. Mean age was 12.5 ± 4.5 years. Average scan time for R2 sequences was 10 min, while R2* sequence time was 20 s. R2* estimation of LIC correlated closely with R2 with a correlation coefficient of 0.94. Agreement was strongest for LIC < 15 mg Fe/g dry weight. Overall bias from Bland–Altman plot was 0.66 with a standard deviation of 2.8 and 95% limits of agreement −4.8 to 6.1. Conclusion: LIC estimation by R2* correlates well with R2-Ferriscan in the pediatric age group. Due to the very short scan time of R2*, it allows imaging without sedation or anesthesia. Cardiac involvement was uncommon in this cohort.
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Henninger B, Plaikner M, Zoller H, Viveiros A, Kannengiesser S, Jaschke W, Kremser C. Performance of different Dixon-based methods for MR liver iron assessment in comparison to a biopsy-validated R2* relaxometry method. Eur Radiol 2020; 31:2252-2262. [PMID: 32965571 PMCID: PMC7979591 DOI: 10.1007/s00330-020-07291-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 07/14/2020] [Accepted: 09/14/2020] [Indexed: 01/19/2023]
Abstract
Objectives To prospectively evaluate a 3D-multiecho-Dixon sequence with inline calculation of proton density fat fraction (PDFF) and R2* (qDixon), and an improved version of it (qDixon-WIP), for the MR-quantification of hepatic iron in a clinical setting. Methods Patients with increased serum ferritin underwent 1.5-T MRI of the liver for the evaluation of hepatic iron overload. The imaging protocol for R2* quantification included as follows: (1) a validated, 2D multigradient-echo sequence (initial TE 0.99 ms, R2*-ME-GRE), (2) a 3D-multiecho-Dixon sequence with inline calculation of PDFF and R2* (initial TE 2.38 ms, R2*-qDixon), and optionally (3) a prototype (works-in-progress, WIP) version of the latter (initial TE 1.04 ms, R2*-qDixon-WIP) with improved water/fat separation and noise-corrected parameter fitting. For all sequences, three manually co-registered regions of interest (ROIs) were placed in the liver. R2* values were compared and linear regression analysis and Bland-Altman plots calculated. Results Forty-six out of 415 patients showed fat-water (F/W) swap with qDixon and were excluded. A total of 369 patients (mean age 52 years) were included; in 203/369, the optional qDixon-WIP was acquired, which showed no F/W swaps. A strong correlation was found between R2*-ME-GRE and R2*-qDixon (r2 = 0.92, p < 0.001) with Bland-Altman revealing a mean difference of − 3.82 1/s (SD = 21.26 1/s). Correlation between R2*-GRE-ME and R2*-qDixon-WIP was r2 = 0.95 (p < 0.001) with Bland-Altman showing a mean difference of − 0.125 1/s (SD = 30.667 1/s). Conclusions The 3D-multiecho-Dixon sequence is a reliable tool to quantify hepatic iron. Results are comparable with established relaxometry methods. Improvements to the original implementation eliminate occasional F/W swaps and limitations regarding maximum R2* values. Key Points • The 3D-multiecho-Dixon sequence for 1.5 T is a reliable tool to quantify hepatic iron. • Results of the 3D-multiecho-Dixon sequence are comparable with established relaxometry methods. • An improved version of the 3D-multiecho-Dixon sequence eliminates minor drawbacks.
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Affiliation(s)
- Benjamin Henninger
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Michaela Plaikner
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
| | - Heinz Zoller
- Department of Internal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - André Viveiros
- Department of Internal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Werner Jaschke
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Christian Kremser
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
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Xi H, Lu MC, Yang QX, Zhang QM. Room Temperature Magnetoelectric Sensor Arrays For Application of Detecting Iron Profiles in Organs. SENSORS AND ACTUATORS. A, PHYSICAL 2020; 311:112064. [PMID: 32661455 PMCID: PMC7357878 DOI: 10.1016/j.sna.2020.112064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Noninvasive measurement of liver iron concentration (LIC) is clinically important. Yet, at the present time, it can only be achieved with SQUID technology. However, SQUID based BLS suffers high costs and cumbersome cryogenic requirements that prevent SQUID BLS from being adopted by clinical applications. Recently, we demonstrated that a single channel ME sensor with piezo-single crystals could detect LIC from only 3cc of mouse liver tissue without any magnetic field shielding. The results demonstrated not only the sensitivity of ME sensor system for LIC but also the feasibility for mapping LIC profiles spatially. This investigation further developed ME sensor arrays, exploiting the compact size and room temperature operation. A Dual-Channel 1-D ME sensor array along the vertical, Z-direction, was developed and shown to be sensitive to the skin-liver distance change which can be utilized to calibrate and eliminate the inter-subject variability of the LIC measurement due to skin-liver distance. With phantom having spatially dependent iron concentrations, the 1-D ME sensor array was capable of mapping the one-dimensional profile of the iron concentration in the horizontal X- and Y-directions. The results of the prototype sensor devices show the feasibility of an array ME-sensors for imaging iron profile.
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Affiliation(s)
- Hao Xi
- Department of Electrical Engineering and Materials Research Institute, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Meng-Chien Lu
- Department of Electrical Engineering and Materials Research Institute, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Qing X. Yang
- Departments of Radiology and Neurosurgery Penn State College of Medicine, Hershey, PA 17033, USA
| | - Q. M. Zhang
- Department of Electrical Engineering and Materials Research Institute, The Pennsylvania State University, University Park, PA, 16802, USA
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Complex confounder-corrected R2* mapping for liver iron quantification with MRI. Eur Radiol 2020; 31:264-275. [PMID: 32785766 DOI: 10.1007/s00330-020-07123-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 06/05/2020] [Accepted: 07/30/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES MRI-based R2* mapping may enable reliable and rapid quantification of liver iron concentration (LIC). However, the performance and reproducibility of R2* across acquisition protocols remain unknown. Therefore, the objective of this work was to evaluate the performance and reproducibility of complex confounder-corrected R2* across acquisition protocols, at both 1.5 T and 3.0 T. METHODS In this prospective study, 40 patients with suspected iron overload and 10 healthy controls were recruited with IRB approval and informed written consent and imaged at both 1.5 T and 3.0 T. For each subject, acquisitions included four different R2* mapping protocols at each field strength, and an FDA-approved R2-based method performed at 1.5 T as a reference for LIC. R2* maps were reconstructed from the complex data acquisitions including correction for noise effects and fat signal. For each subject, field strength, and R2* acquisition, R2* measurements were performed in each of the nine liver Couinaud segments and the spleen. R2* measurements were compared across protocols and field strength (1.5 T and 3.0 T), and R2* was calibrated to LIC for each acquisition and field strength. RESULTS R2* demonstrated high reproducibility across acquisition protocols (p > 0.05 for 96/108 pairwise comparisons across 2 field strengths and 9 liver segments, ICC > 0.91 for each field strength/segment combination) and high predictive ability (AUC > 0.95 for four clinically relevant LIC thresholds). Calibration of R2* to LIC was LIC = - 0.04 + 2.62 × 10-2 R2* at 1.5 T and LIC = 0.00 + 1.41 × 10-2 R2* at 3.0 T. CONCLUSIONS Complex confounder-corrected R2* mapping enables LIC quantification with high reproducibility across acquisition protocols, at both 1.5 T and 3.0 T. KEY POINTS • Confounder-corrected R2* of the liver provides reproducible R2* across acquisition protocols, including different spatial resolutions, echo times, and slice orientations, at both 1.5 T and 3.0 T. • For all acquisition protocols, high correlation with R2-based liver iron concentration (LIC) quantification was observed. • The calibration between confounder-corrected R2* and LIC, at both 1.5 T and 3.0 T, is determined in this study.
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Chan WY, Hartono S, Thng CH, Koh DM. New Advances in Magnetic Resonance Techniques in Abdomen and Pelvis. Magn Reson Imaging Clin N Am 2020; 28:433-445. [PMID: 32624160 DOI: 10.1016/j.mric.2020.04.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
This article explores new acquisition methods in magnetic resonance (MR) imaging to provide high spatial and temporal resolution imaging for a wide spectrum of clinical applications in the abdomen and pelvis. We present an overview of some of these advanced MR techniques, such as non-cartesian image acquisition, fast sampling and compressed sensing, diffusion quantification and quantitative MR that can improve data sampling, enhance image quality, yield quantitative measurements, and/or optimize diagnostic performance in the body.
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Affiliation(s)
- Wan Ying Chan
- Division of Oncologic Imaging, National Cancer Centre, 11 Hospital Crescent, Singapore 169610, Singapore
| | - Septian Hartono
- Department of Neurology, National Neuroscience Institute, Singapore, 11 Jln Tan Tock Seng, Singapore 308433, Singapore
| | - Choon Hua Thng
- Division of Oncologic Imaging, National Cancer Centre, 11 Hospital Crescent, Singapore 169610, Singapore
| | - Dow-Mu Koh
- Department of Radiology, Royal Marsden Hospital, Downs Road, Sutton SM2 5PT, UK.
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Kontoghiorghes GJ, Kontoghiorghe CN. Iron and Chelation in Biochemistry and Medicine: New Approaches to Controlling Iron Metabolism and Treating Related Diseases. Cells 2020; 9:E1456. [PMID: 32545424 PMCID: PMC7349684 DOI: 10.3390/cells9061456] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/04/2020] [Accepted: 06/05/2020] [Indexed: 02/07/2023] Open
Abstract
Iron is essential for all living organisms. Many iron-containing proteins and metabolic pathways play a key role in almost all cellular and physiological functions. The diversity of the activity and function of iron and its associated pathologies is based on bond formation with adjacent ligands and the overall structure of the iron complex in proteins or with other biomolecules. The control of the metabolic pathways of iron absorption, utilization, recycling and excretion by iron-containing proteins ensures normal biologic and physiological activity. Abnormalities in iron-containing proteins, iron metabolic pathways and also other associated processes can lead to an array of diseases. These include iron deficiency, which affects more than a quarter of the world's population; hemoglobinopathies, which are the most common of the genetic disorders and idiopathic hemochromatosis. Iron is the most common catalyst of free radical production and oxidative stress which are implicated in tissue damage in most pathologic conditions, cancer initiation and progression, neurodegeneration and many other diseases. The interaction of iron and iron-containing proteins with dietary and xenobiotic molecules, including drugs, may affect iron metabolic and disease processes. Deferiprone, deferoxamine, deferasirox and other chelating drugs can offer therapeutic solutions for most diseases associated with iron metabolism including iron overload and deficiency, neurodegeneration and cancer, the detoxification of xenobiotic metals and most diseases associated with free radical pathology.
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Affiliation(s)
- George J. Kontoghiorghes
- Postgraduate Research Institute of Science, Technology, Environment and Medicine, CY-3021 Limassol, Cyprus;
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Nazarova EE, Tereshchenko GV, Kupriyanov DA, Smetanina NS, Novichkova GA. Free-breathing T2* mapping for MR myocardial iron assessment at 3 T. Eur Radiol Exp 2020; 4:25. [PMID: 32303909 PMCID: PMC7165216 DOI: 10.1186/s41747-020-00156-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 03/19/2020] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Timely diagnosis of cardiac iron overload is important for children with transfusion-dependent anaemias and requires modern measure methods. Nowadays, myocardial iron quantification is performed by magnetic resonance (MR) breath-hold techniques, sensitive to respiratory motion and unfeasible in patients who are unable to hold their breath. Free-breathing T2* mapping sequences would allow to scan children who cannot hold their breath for a specified duration. Our aim was to test a free-breathing T2* mapping sequence, based on motion correction by multiple signal accumulation technique. METHODS We used an electrocardiographically gated T2* mapping sequence based on multiple gradient echo at 3-T in 37 paediatric patients with haematologic disorders aged from 2 to 16. We compared T2* values of myocardium and signal-to-noise ratio of this new sequence with standard breath-holding T2* mapping sequence. T2* values were measured in the interventricular septum for both methods in studies with adequate image quality. RESULTS All children were scanned without complications. Five patients were excluded from analysis because of the presence of respiratory artefacts on the T2* images with breath-holding technique due to patient's inability to hold their breath. Breath-holding T2* was 19.5 ± 7.7 ms (mean ± standard deviation), free-breathing T2* was 19.4 ± 7.6 ms, with positive correlation (r = 0.99, R2 = 0.98; p < 0.001). The free-breathing sequence had a higher signal-to-noise ratio (median 212.8, interquartile range 148.5-566.5) than the breath-holding sequence (112.6, 71.1-334.1) (p = 0.03). CONCLUSION A free-breathing sequence provided accurate measurement of myocardial T2* values in children.
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Affiliation(s)
- E E Nazarova
- Radiology department, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Samory Mashela st., 1, Moscow, Russia, 117997.
| | - G V Tereshchenko
- Radiology department, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Samory Mashela st., 1, Moscow, Russia, 117997
| | - D A Kupriyanov
- Radiology department, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Samory Mashela st., 1, Moscow, Russia, 117997
- Philips Healthcare, Moscow, Russia
| | - N S Smetanina
- Radiology department, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Samory Mashela st., 1, Moscow, Russia, 117997
- 3Pirogov Russian National Research Medical University, Moscow, Russia
| | - G A Novichkova
- Radiology department, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Samory Mashela st., 1, Moscow, Russia, 117997
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Bafna V, Bhat S, Raj V, Badiger S, Annapandian VM, Nataraj KS, Damodar S. Quantification of Liver Iron Overload: Correlation of MRI and Liver Tissue Biopsy in Pediatric Thalassemia Major Patients Undergoing Bone Marrow Transplant. Indian J Hematol Blood Transfus 2020; 36:667-673. [PMID: 33100708 DOI: 10.1007/s12288-020-01256-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Accepted: 01/14/2020] [Indexed: 12/31/2022] Open
Abstract
Determination of the magnitude of body iron stores helps to identify individuals at risk of iron-induced organ damage in Thalassemia patients. The most direct clinical method of measuring liver iron concentration (LIC) is through chemical analysis of needle biopsy specimens. Here we present a noninvasive method for the measurement of LIC in vivo using magnetic resonance imaging (MRI). Twenty-three pediatric Thalassemia major patients undergoing bone marrow transplantation at our centre were studied. All 23 patients had MRI T2* and R2* decay time for evaluation of LIC on a 1.5 Tesla MRI system followed by liver tissue biopsy for the assessment of iron concentration using an atomic absorption spectrometry. Simultaneously, serum ferritin levels were measured by enzymatic assay. We have correlated biopsy LIC with liver T2* and serum ferritin values with liver R2*. Of the 23 patients 11 were males, the mean age was 8.3 ± 3.7 years. The study results showed a significant correlation between biopsy LIC and liver T2* MRI (r = 0.768; p < 0.001). Also, there was a significant correlation between serum ferritin levels and liver R2* MRI (r = 0.5647; p < 0.01). Two patients had high variance in serum ferritin levels (2100 and 4100 mg/g) while their LIC was around 24 mg/g, whereas the difference was not seen in T2* MRI. Hence, the liver T2* MRI is a better modality for assessing LIC. Serum ferritin is less reliable than quantitative MRI. The liver T2* MRI is a safe, reliable, feasible and cost-effective method compared to liver tissue biopsy for LIC assessment.
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Affiliation(s)
- Varun Bafna
- Department of Hematology and Bone Marrow Transplant Unit, Mazumdar Shaw Medical Center, Narayana Health City, Bangalore, Karnataka India
| | - Sunil Bhat
- Department of Hematology and Bone Marrow Transplant Unit, Mazumdar Shaw Medical Center, Narayana Health City, Bangalore, Karnataka India
| | - Vimal Raj
- Department of Radiology, Narayana Health City, Bangalore, Karnataka India
| | - Shobha Badiger
- Department of Hematology and Bone Marrow Transplant Unit, Mazumdar Shaw Medical Center, Narayana Health City, Bangalore, Karnataka India
| | | | - K S Nataraj
- Department of Hematology and Bone Marrow Transplant Unit, Mazumdar Shaw Medical Center, Narayana Health City, Bangalore, Karnataka India
| | - Sharat Damodar
- Department of Hematology and Bone Marrow Transplant Unit, Mazumdar Shaw Medical Center, Narayana Health City, Bangalore, Karnataka India
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Histological Scores Validate the Accuracy of Hepatic Iron Load Measured by Signal Intensity Ratio and R2* Relaxometry MRI in Dialysis Patients. J Clin Med 2019; 9:jcm9010017. [PMID: 31861625 PMCID: PMC7019535 DOI: 10.3390/jcm9010017] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 12/14/2019] [Accepted: 12/17/2019] [Indexed: 01/02/2023] Open
Abstract
Almost all haemodialysis patients are treated with parenteral iron to compensate for blood loss and to allow the full therapeutic effect of erythropoiesis-stimulating agents. Iron overload is an increasingly recognised clinical situation diagnosed by quantitative magnetic resonance imaging (MRI). MRI methods have not been fully validated in dialysis patients. We compared Deugnier’s and Turlin’s histological scoring of iron overload and Scheuer’s classification (with Perls’ stain) with three quantitative MRI methods for measuring liver iron concentration (LIC)—signal intensity ratio (SIR), R2* relaxometry, and R2* multi-peak spectral modelling (Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL-IQ®)) relaxometry—in 16 haemodialysis patients in whom a liver biopsy was formally indicated for medical follow-up. LIC MRI with these three different methods was highly correlated with Deugnier’s and Turlin’s histological scoring (SIR: r = 0.8329, p = 0.0002; R2* relaxometry: r = −0.9099, p < 0.0001; R2* relaxometry (IDEAL-IQ®): r = −0.872, p = 0.0018). Scheuer’s classification was also significantly correlated with these three MRI techniques. The positive likelihood ratio for the diagnosis of abnormal LIC by Deugnier’s histological scoring was > 62 for the three MRI methods. This study supports the accuracy of quantitative MRI methods for the non-invasive diagnosis and follow-up of iron overload in haemodialysis patients.
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Barrera CA, Khrichenko D, Serai SD, Hartung HD, Biko DM, Otero HJ. Biexponential R2* relaxometry for estimation of liver iron concentration in children: A better fit for high liver iron states. J Magn Reson Imaging 2019; 50:1191-1198. [PMID: 30950562 DOI: 10.1002/jmri.26735] [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: 01/28/2019] [Revised: 03/15/2019] [Accepted: 03/18/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND R2* relaxometry's capacity to calculate liver iron concentration (LIC) is limited in patients with severe overload. Hemosiderin increases in these patients, which exhibits a non-monoexponential decay that renders a failed R2* analysis. PURPOSE/HYPOTHESIS To evaluate a biexponential R2* relaxometry model in children with different ranges of iron overload. STUDY TYPE Retrospective. POPULATION In all, 181 children with different conditions associated with iron overload. FIELD STRENGTH/SEQUENCE 1.5T, T2 *-weighted gradient echo sequence. ASSESSMENT Bi- and monoexponential R2* relaxometry were measured in the liver using two regions of interest (ROIs) using a nonproprietary software: one encompassing the whole liver parenchyma (ROI-1) and the other only the periphery (ROI-2). These were drawn by a single trained observer. The residuals for each fitting model were estimated. A ratio between the residuals of the mono- and biexponential models was calculated to identify the best fitting model. Patients with 1) residual ratio ≥1.5 and 2) R2*fast ≥R2*slow were considered as having a predominant biexponential behavior. STATISTICAL TESTS Nonparametric tests, Bland-Altman plots, linear correlation, intraclass correlation coefficient. Patients were divided according to their LIC into stable (n = 23), mild (n = 58), moderate (n = 61), and severe (n = 39). RESULTS The biexponential model was more suitable for patients with severe iron overload when compared with the other three LIC categories (P < 0.001) for both ROIs. For ROI-1, 37 subjects met criteria for a predominant biexponential behavior. The slow component (5.7%) had a lower fraction than the fast component (94.2%). For ROI-2, 22 subjects met criteria for a predominant biexponential behavior. The slow component (4.7%) had a lower fraction than the fast component (95.2%). The intraobserver variability between both ROIs was excellent. DATA CONCLUSION The biexponential R2* relaxometry model is more suitable in children with severe iron overload. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1191-1198.
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Affiliation(s)
- Christian A Barrera
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Dmitry Khrichenko
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Suraj D Serai
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Helge D Hartung
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - David M Biko
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Hansel J Otero
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
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Werner S, Krauss B, Haberland U, Bongers M, Starke U, Bakchoul T, Enkel S, Nikolaou K, Horger M. Dual-energy CT for liver iron quantification in patients with haematological disorders. Eur Radiol 2018; 29:2868-2877. [DOI: 10.1007/s00330-018-5785-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 08/28/2018] [Accepted: 09/20/2018] [Indexed: 12/22/2022]
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Plaikner M, Kremser C, Zoller H, Jaschke W, Henninger B. Monitoring Iron Overload: Relationship between R2* Relaxometry of the Liver and Serum Ferritin under Different Therapies. J Clin Imaging Sci 2018; 8:40. [PMID: 30283722 PMCID: PMC6157097 DOI: 10.4103/jcis.jcis_30_18] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 07/09/2018] [Indexed: 12/19/2022] Open
Abstract
Objective: The objective of this study was to evaluate the relationship between hepatic magnetic resonance imaging (MRI) with R2* relaxometry and serum ferritin in therapy monitoring of patients with iron overload. Further, a possible influence of the chosen therapy (phlebotomy or chelation) was assessed. Materials and Methods: We retrospectively evaluated 42 patients with baseline and follow-up R2* relaxometry and determination of serum ferritin before and during therapeutic phlebotomy or iron chelation therapy or watchful waiting, respectively. Linear regression analysis was used to analyze the correlation between changes of R2* and serum ferritin. Regression lines for different groups were compared with analysis of covariance. Results: We found a moderate positive statistical correlation (r = 0.509) between serum ferritin and R2*, a moderate positive correlation between absolute R2* changes and serum ferritin changes (r = 0.497), and a strong correlation for percentage changes (r = 0.712). The correlation analysis between relative changes of R2* and serum ferritin for the different therapies resulted in a strong correlation between phlebotomy and chelation (r = 0.855/0.727) and a moderate for no applied therapy (r = 0.536). In 22/92 paired examinations, a discordance of R2* and ferritin was found, particularly involving patients under chelation. Conclusions: Despite the good correlation between serum ferritin and R2* relaxometry in monitoring iron overload, treatment response may be misinterpreted when only serum ferritin is considered. Although ferritin is an acceptable and far cheaper tool for monitoring, MRI should be performed for confirmation, especially in case of unexpected ferritin changes, particularly under chelation therapy.
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Affiliation(s)
- Michaela Plaikner
- Department of Radiology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Christian Kremser
- Department of Radiology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Heinz Zoller
- Department of Internal Medicine, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Werner Jaschke
- Department of Radiology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Benjamin Henninger
- Department of Radiology, Medical University of Innsbruck, 6020 Innsbruck, Austria
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Golfeyz S, Lewis S, Weisberg IS. Hemochromatosis: pathophysiology, evaluation, and management of hepatic iron overload with a focus on MRI. Expert Rev Gastroenterol Hepatol 2018; 12:767-778. [PMID: 29966105 DOI: 10.1080/17474124.2018.1496016] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Hereditary hemochromatosis (HH) is an autosomal recessive disorder that occurs in approximately 1 in 200-250 individuals. Mutations in the HFE gene lead to excess iron absorption. Excess iron in the form of non-transferrin-bound iron (NTBI) causes injury and is readily uptaken by cardiomyocytes, pancreatic islet cells, and hepatocytes. Symptoms greatly vary among patients and include fatigue, abdominal pain, arthralgias, impotence, decreased libido, diabetes, and heart failure. Untreated hemochromatosis can lead to chronic liver disease, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Many invasive and noninvasive diagnostic tests are available to aid in diagnosis and treatment. MRI has emerged as the reference standard imaging modality for the detection and quantification of hepatic iron deposition, as ultrasound (US) is unable to detect iron overload and computed tomography (CT) findings are nonspecific and influenced by multiple confounding variables. If caught and treated early, HH disease progression can significantly be altered. Area covered: The data on Hemochromatosis, iron overload, and MRI were gathered by searching PubMed. Expert commentary: MRI is a great tool for diagnosis and management of iron overload. It is safe, effective, and a standard protocol should be included in diagnostic algorithms of future treatment guidelines.
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Affiliation(s)
- Shmuel Golfeyz
- a Department of Internal Medicine , Mount Sinai Beth Israel , New York , NY , USA
| | - Sara Lewis
- b Department of Radiology , Icahn School of Medicine at Mount Sinai , New York , NY , USA.,c Translational and Molecular Imaging Institute , Icahn School of Medicine at Mount Sinai , New York , NY , USA
| | - Ilan S Weisberg
- d Department of Digestive Diseases and Hepatology , Mount Sinai Beth Israel , New York , NY , USA
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25
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Garcia-Casal MN, Pasricha SR, Martinez RX, Lopez-Perez L, Peña-Rosas JP. Are Current Serum and Plasma Ferritin Cut-offs for Iron Deficiency and Overload Accurate and Reflecting Iron Status? A Systematic Review. Arch Med Res 2018; 49:405-417. [DOI: 10.1016/j.arcmed.2018.12.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 12/06/2018] [Indexed: 12/11/2022]
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26
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Kobayashi H, Yoshimura N, Uemura S, Katagiri T, Tanaka T, Ushiki T, Fuse K, Shibasaki Y, Narita M, Sone H, Masuko M. Heterogeneity of intrahepatic iron deposition in transfusion-dependent iron overload patients with hematological malignancies. Leuk Res 2018; 70:41-44. [DOI: 10.1016/j.leukres.2018.05.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Revised: 05/12/2018] [Accepted: 05/15/2018] [Indexed: 01/05/2023]
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27
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Pirasteh A, Yuan Q, Hernando D, Reeder SB, Pedrosa I, Yokoo T. Inter-method reproducibility of biexponential R 2 MR relaxometry for estimation of liver iron concentration. Magn Reson Med 2018; 80:2691-2701. [PMID: 29770484 DOI: 10.1002/mrm.27348] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 04/03/2018] [Accepted: 04/16/2018] [Indexed: 12/17/2022]
Abstract
PURPOSE To assess the reproducibility of biexponential R2 -relaxometry MRI for estimation of liver iron concentration (LIC) between proprietary and nonproprietary analysis methods. METHODS This single-center retrospective study, approved by investigational review board and compliant with the Health Insurance Portability and Accountability Act, included 40 liver MRI exams in 38 subjects with suspected or known iron overload. From spin-echo images of the liver, acquired at 5 different echo times (TE = 6-18 ms), biexponential R2 maps were calculated using 1 proprietary (FerriScan, Resonance Health Ltd., Claremont WA, Australia) and 3 nonproprietary (simulated annealing, nonlinear least squares, dictionary search) analysis methods. Each subject's average liver R2 value was converted to LIC using a previously validated calibration curve. Inter-method reproducibility for liver R2 and LIC were assessed for linearity using linear regression analysis and absolute agreement using intraclass correlation and Bland-Altman analysis. For point estimates, 95% confidence intervals were calculated; P values < 0.05 were considered statistically significant. RESULTS Linearity between the proprietary and nonproprietary methods was excellent across the observed range for R2 (20-312 s-1 ) and LIC (0.4-52.2 mg/g), with all coefficients of determination (R2 ) ≥ 0.95. No statistically significant bias was found (slope estimates ∼ 1; intercept estimates ∼ 0; P values > 0.05). Agreement between the 4 methods was excellent for both liver R2 and LIC (intraclass correlations ≥ 0.97). Bland-Altman 95% limits of agreement in % difference between the proprietary and nonproprietary methods were ≤ 9% and ≤ 16% for R2 and LIC, respectively. CONCLUSION Biexponential R2 -relaxometry MRI for LIC estimation is reproducible between proprietary and nonproprietary analysis methods.
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Affiliation(s)
- Ali Pirasteh
- Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Qing Yuan
- Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Diego Hernando
- Radiology, Medical Physics, University of Wisconsin, Madison, Wisconsin
| | - Scott B Reeder
- Radiology, Medical Physics, Biomedical Engineering, Medicine, Emergency Medicine, University of Wisconsin, Madison, Wisconsin
| | - Ivan Pedrosa
- Radiology, University of Texas Southwestern Medical Center, Dallas, Texas.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Takeshi Yokoo
- Radiology, University of Texas Southwestern Medical Center, Dallas, Texas.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
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28
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Xi H, Lu MC, Luo HS, Yang QX, Zhang QM. A Novel Magnetoelectric Biomagnetic Susceptometer on Iron Level Detection with Mice Tissue in Vitro. MEDICAL DEVICES & SENSORS 2018; 1:e10004. [PMID: 30643870 PMCID: PMC6329597 DOI: 10.1002/mds3.10004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 06/15/2018] [Indexed: 12/20/2022]
Abstract
Iron plays a vital role in human body. Liver Iron Concentration (LIC) is directly correlated to total body iron and can be an important indicator to a variety of pathologies. Non-invasive methods to quantitatively assess tissue iron with low cost and high sensitivity have drawn vast interests and investments. Among various methods, the magnetoelectric (ME) sensor based biomagnetic liver susceptometer (BLS) is of great promise because it operates at room temperature but with the same principle as that of the well-developed SQUID (Superconducting Quantum Interference Device). Here, we report a magnetoelectric (ME) sensor based BLS system exploiting the recently developed PIN-PMN-PT piezoelectric single crystal. The newly developed ME BLS, which employs the horizontal scanning mechanism with a water bath interface to automatically eliminate the diamagnetic background of the tissues and irregular shape of torso, exhibits an overall sensitivity advancement (300X) to the sensor system previously reported. A linear correlation (R2 = 0.97) found between the system measurements and the biopsy data demonstrates the validity of the system. The ability to detect signals from only 3cc of mouse liver tissue samples suggests a high spatial resolution which could be used for finer scanning and enable magnetic distribution image and profiling.
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Affiliation(s)
- Hao Xi
- Department of Electrical Engineering and Materials Research Institute, the Pennsylvania State University, University Park, PA, 16802, USA
| | - Meng-Chien Lu
- Department of Electrical Engineering and Materials Research Institute, the Pennsylvania State University, University Park, PA, 16802, USA
| | - Hao-Su Luo
- Laboratory of Functional Inorganic Materials, Shanghai Institute of Ceramics, Chinese Academy of Science, Shanghai, China
| | - Q. X. Yang
- Departments of Radiology and Neurosurgery, Penn State College of Medicine, Hershey, PA 17033, USA
| | - Q. M. Zhang
- Department of Electrical Engineering and Materials Research Institute, the Pennsylvania State University, University Park, PA, 16802, USA
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29
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Ryan JD, Armitage AE, Cobbold JF, Banerjee R, Borsani O, Dongiovanni P, Neubauer S, Morovat R, Wang LM, Pasricha SR, Fargion S, Collier J, Barnes E, Drakesmith H, Valenti L, Pavlides M. Hepatic iron is the major determinant of serum ferritin in NAFLD patients. Liver Int 2018; 38:164-173. [PMID: 28679028 DOI: 10.1111/liv.13513] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2017] [Accepted: 06/28/2017] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND AIMS Elevated serum ferritin is common in NAFLD, and is associated with more advanced disease and increased mortality. Hyperferritinaemia in NAFLD is often attributed to inflammation, while in other conditions ferritin closely reflects body iron stores. The aim of this study was to clarify the underlying cause of hyperferritinaemia in NAFLD. METHODS Ferritin levels were examined with markers of iron status, inflammation and liver injury across the clinical spectrum of NAFLD using blood, tissue and magnetic resonance (MR) imaging. A separate larger group of NAFLD patients with hepatic iron staining and quantification were used for validation. RESULTS Serum ferritin correlated closely with the iron regulatory hormone hepcidin, and liver iron levels determined by MR. Furthermore, ferritin levels reflected lower serum adiponectin, a marker of insulin resistance, and liver fat, but not cytokine or CRP levels. Ferritin levels differed according to fibrosis stage, increasing from early to moderate disease, and declining in cirrhosis. A similar pattern was found in the validation cohort of NAFLD patients, where ferritin levels were highest in those with macrophage iron deposition. Multivariate analysis revealed liver iron and hepcidin levels as the major determinants of serum ferritin. CONCLUSIONS While hyperferritinaemia is associated with markers of liver injury and insulin resistance, serum hepcidin and hepatic iron are the strongest predictors of ferritin levels. These findings highlight the role of disordered iron homeostasis in the pathogenesis of NAFLD, suggesting that therapies aimed at correcting iron metabolism may be beneficial.
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Affiliation(s)
- John D Ryan
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Andrew E Armitage
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Jeremy F Cobbold
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | | | - Oscar Borsani
- Internal Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Paola Dongiovanni
- Internal Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Stefan Neubauer
- Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, UK
| | - Reza Morovat
- Department of Biochemistry, John Radcliffe Hospital, Oxford, UK
| | - Lai Mun Wang
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Sant-Rayn Pasricha
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Silvia Fargion
- Internal Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Jane Collier
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Eleanor Barnes
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Hal Drakesmith
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Luca Valenti
- Internal Medicine and Metabolic Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Michael Pavlides
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK.,Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, UK
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30
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Mueller J, Raisi H, Rausch V, Peccerella T, Simons D, Ziener CH, Schlemmer HP, Seitz HK, Waldburger N, Longerich T, Straub BK, Mueller S. Sensitive and non-invasive assessment of hepatocellular iron using a novel room-temperature susceptometer. J Hepatol 2017; 67:535-542. [PMID: 28483679 DOI: 10.1016/j.jhep.2017.04.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 04/11/2017] [Accepted: 04/26/2017] [Indexed: 12/17/2022]
Abstract
BACKGROUND & AIMS Liver iron accumulates in various chronic liver diseases where it is an independent factor for survival and carcinogenesis. We tested a novel room-temperature susceptometer (RTS) to non-invasively assess liver iron concentration (LIC). METHODS Two hundred and sixty-four patients with or without signs of iron overload or liver disease were prospectively enrolled. Thirty-five patients underwent liver biopsy with semiquantitative iron determination (Prussian Blue staining), atomic absorption spectroscopy (AAS, n=33), or magnetic resonance imaging (MRI, n=15). RESULTS In vitro studies demonstrated a highly linear (r2=0.998) association between RTS-signal and iron concentration, with a detection limit of 0.3mM. Using an optimized algorithm, accounting for the skin-to-liver capsule distance, valid measurements could be obtained in 84% of cases. LIC-RTS showed a significant correlation with LIC-AAS (r=0.74, p<0.001), LIC-MRI (r=0.64, p<0.001) and hepatocellular iron (r=0.58, p<0.01), but not with macrophage iron (r=0.32, p=0.30). Normal LIC-RTS was 1.4mg/g dry weight. Besides hereditary and transfusional iron overload, LIC-RTS was also significantly elevated in patients with alcoholic liver disease. The areas under the receiver operating characteristic curve (AUROC) for grade 1, 2 and 3 hepatocellular iron overload were 0.72, 0.89 and 0.97, respectively, with cut-off values of 2.0, 4.0 and 5.0mg/g dry weight. Notably, the positive and negative predictive values, sensitivity, specificity and accuracy of severe hepatic iron overload (HIO) (grade ≥2) detection, were equal to AAS and superior to all serum iron markers. Depletion of hepatic iron could be efficiently monitored upon phlebotomy. CONCLUSIONS RTS allows for the rapid and non-invasive measurement of LIC. In comparison to MRI, it could be a cost-effective bedside method for LIC screening. Lay summary: Novel room-temperature susceptometer (RTS) allows for the rapid, sensitive, and non-invasive measurement of liver iron concentration. In comparison to MRI, it could be a cost-effective bedside method for liver iron concentration screening.
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Affiliation(s)
- Johannes Mueller
- Dept. of Medicine, Salem Medical Center and Center for Alcohol Research and Liver Disease, University of Heidelberg, Germany
| | - Hanna Raisi
- Dept. of Medicine, Salem Medical Center and Center for Alcohol Research and Liver Disease, University of Heidelberg, Germany
| | - Vanessa Rausch
- Dept. of Medicine, Salem Medical Center and Center for Alcohol Research and Liver Disease, University of Heidelberg, Germany
| | - Teresa Peccerella
- Dept. of Medicine, Salem Medical Center and Center for Alcohol Research and Liver Disease, University of Heidelberg, Germany
| | - David Simons
- Dept. of Radiology, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
| | | | | | - Helmut Karl Seitz
- Dept. of Medicine, Salem Medical Center and Center for Alcohol Research and Liver Disease, University of Heidelberg, Germany
| | | | | | | | - Sebastian Mueller
- Dept. of Medicine, Salem Medical Center and Center for Alcohol Research and Liver Disease, University of Heidelberg, Germany.
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31
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Tan CH, Venkatesh SK. Magnetic Resonance Elastography and Other Magnetic Resonance Imaging Techniques in Chronic Liver Disease: Current Status and Future Directions. Gut Liver 2017; 10:672-86. [PMID: 27563019 PMCID: PMC5003189 DOI: 10.5009/gnl15492] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Revised: 11/29/2015] [Accepted: 12/15/2015] [Indexed: 12/13/2022] Open
Abstract
Recent advances in the noninvasive imaging of chronic liver disease have led to improvements in diagnosis, particularly with magnetic resonance imaging (MRI). A comprehensive evaluation of the liver may be performed with the quantification of the degree of hepatic steatosis, liver iron concentration, and liver fibrosis. In addition, MRI of the liver may be used to identify complications of cirrhosis, including portal hypertension, ascites, and the development of hepatocellular carcinoma. In this review article, we discuss the state of the art techniques in liver MRI, namely, magnetic resonance elastography, hepatobiliary phase MRI, and liver fat and iron quantification MRI. The use of these advanced techniques in the management of chronic liver diseases, including non-alcoholic fatty liver disease, will be elaborated.
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Affiliation(s)
- Cher Heng Tan
- Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore
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32
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Doyle EK, Toy K, Valdez B, Chia JM, Coates T, Wood JC. Ultra-short echo time images quantify high liver iron. Magn Reson Med 2017. [PMID: 28643355 DOI: 10.1002/mrm.26791] [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] [Indexed: 01/25/2023]
Abstract
PURPOSE 1.5T gradient echo-based R2∗ estimates are standard-of-care for assessing liver iron concentration (LIC). Despite growing popularity of 3T, echo time (TE) limitations prevent 3T liver iron quantitation in the upper half of the clinical range (LIC ⪆20 mg/g). In this work, a 3D radial pulse sequence was assessed to double the dynamic range of 3T LIC estimates. THEORY AND METHODS The minimum TE limits the dynamic range of pulse sequences to estimate R2∗. 23 chronically-transfused human volunteers were imaged with 1.5T Cartesian gradient echo (1.5T-GRE), 3T Cartesian gradient echo (3T-GRE), and 3T ultrashort TE radial (3T-UTE) pulse sequences; minimum TEs were 0.96, 0.76, and 0.19 ms, respectively. R2∗ was estimated with an exponential signal model, normalized to 1.5T equivalents, and converted to LIC. Bland-Altman analysis compared 3T-based estimates to 1.5T-GRE. RESULTS LIC by 3T-GRE was unbiased versus 1.5T-GRE for LIC ≤ 25 mg/g (sd = 9.6%); 3T-GRE failed to quantify LIC > 25 mg/g. At high iron loads, 3T-UTE was unbiased (sd = 14.5%) compared to 1.5T-GRE. Further, 3T-UTE estimated LIC up to 50 mg/g, exceeding 1.5T-GRE limits. CONCLUSION 3T-UTE imaging can reliably estimate high liver iron burdens. In conjunction with 3T-GRE, 3T-UTE allows clinical LIC estimation across a wide range of liver iron loads. Magn Reson Med 79:1579-1585, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Eamon K Doyle
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.,Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - Kristin Toy
- College of Medicine, University of Toledo, Toledo, Ohio, USA
| | - Bertin Valdez
- Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, California, USA
| | | | - Thomas Coates
- Division of Hematology, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - John C Wood
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.,Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, California, USA
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33
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Ou G, Ko HH, Tiwari P, Sandhu N, Galorport C, Lee T, Ezzat H. Utility of Transient Elastography in Estimating Hepatic Iron Concentration in Comparison to Magnetic Resonance Imaging in Patients Who are Transfusion-Dependent: A Canadian Center Experience. Hemoglobin 2017; 41:21-25. [PMID: 28532285 DOI: 10.1080/03630269.2017.1307763] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Transfusion-dependent hereditary anemias such as β-thalassemia (β-thal), predispose patients to iron overload and its numerous clinical sequelae. Accurate assessment of overall iron status and prompt initiation of chelation therapy to prevent irreversible end-organ damage can be achieved using magnetic resonance imaging (MRI) to measure liver iron concentration (LIC) as a surrogate marker of total body iron; however, its access may be associated with long wait times and delay in treatment. We report an observational cohort study at a single tertiary care center assessing the theoretical role of transient elastography (TE), which measures liver stiffness, in estimating LIC compared to other established diagnostic measures. While regression analyses confirm a moderate correlation between LIC per R2 MRI and serum ferritin level (pooled estimate of correlation = 0.55), there was no significant correlation between TE reading and LIC based on R2 MRI (pooled estimate of correlation = -0.06), and only a weak correlation was observed with serum ferritin level (pooled estimate of correlation = 0.45). These results suggest TE may not be sensitive enough to detect subtle changes in the hepatic parenchymal stiffness associated with liver iron deposition.
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Affiliation(s)
- George Ou
- a Department of Medicine, Division of Gastroenterology , University of British Columbia , Vancouver , Canada
| | - Hin Hin Ko
- a Department of Medicine, Division of Gastroenterology , University of British Columbia , Vancouver , Canada
| | - Pari Tiwari
- b Department of Radiology , University of British Columbia , Vancouver , Canada
| | - Navdeep Sandhu
- c Provincial Program of Hemoglobinopathy of British Columbia , Vancouver , Canada
| | - Cherry Galorport
- a Department of Medicine, Division of Gastroenterology , University of British Columbia , Vancouver , Canada
| | - Terry Lee
- d Centre for Health Evaluation and Outcome Sciences , St. Paul's Hospital, University of British Columbia , Vancouver , Canada
| | - Hatoon Ezzat
- e Department of Medicine, Division of Haematology , University of British Columbia , Vancouver , Canada
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Henninger B, Zoller H, Kannengiesser S, Zhong X, Jaschke W, Kremser C. 3D Multiecho Dixon for the Evaluation of Hepatic Iron and Fat in a Clinical Setting. J Magn Reson Imaging 2017; 46:793-800. [PMID: 28225576 DOI: 10.1002/jmri.25630] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 12/22/2016] [Indexed: 12/22/2022] Open
Abstract
PURPOSE To prospectively evaluate a new 3D-multiecho-Dixon (3D-ME-Dixon) sequence for the quantification of hepatic iron and fat in a clinical setting. MATERIALS AND METHODS In all, 120 patients underwent 1.5T magnetic resonance imaging of the liver between December 2013 and June 2015 including the following three sequences: 3D-ME-Dixon with inline calculation of R2* and proton-density fat-fraction (PDFF) maps, single-voxel-spectroscopy (SVS), 2D multigradient-echo sequence (2D-ME-GRE). SVS and 2D-ME-GRE were used as reference for PDFF and R2*, respectively. R2*- and PDFF-values from 3D-ME-Dixon were compared with those of the reference. Linear regression analysis, Bland-Altman plots, and agreement parameters were calculated. RESULTS In total, 103 patients were finally included (87 men and 16 women; mean age, 50.51 years); 17/120 were excluded due to fat/water-swaps or R2*-values exceeding the constraint of 400 1/s for 3D-ME-Dixon. A strong correlation (r = 0.992, P < 0.001) between R2* of 3D-ME-Dixon and the reference 2D-ME-GRE was found. Bland-Altman analysis revealed systematically lower values for 3D-ME-Dixon (16.499%). Using an adapted threshold of 57 1/s, 3D-ME-Dixon obtained a positive/negative percentage agreement (PPA/NPA) of 84.4%/91.4% for detecting hepatic iron overload. For hepatic fat the correlation between 3D-ME-Dixon and the reference SVS was strong (r = 0.957, P < 0.001); PPA/NPA was 88.3%/91.4%. CONCLUSION The 3D-ME-Dixon sequence is a valuable tool for the evaluation of hepatic iron and fat in a clinical setting. Fat/water-swaps remain a drawback requiring improvements to the implementation and making it necessary to have proven conventional sequences at hand in case of an eventual occurrence. LEVEL OF EVIDENCE 1. Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:793-800.
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Affiliation(s)
- Benjamin Henninger
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Heinz Zoller
- Department of Internal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Healthcare, Atlanta, Georgia, USA
| | - Werner Jaschke
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Christian Kremser
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria
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35
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İdilman İS, Akata D, Özmen MN, Karçaaltıncaba M. Different forms of iron accumulation in the liver on MRI. Diagn Interv Radiol 2017; 22:22-8. [PMID: 26712679 DOI: 10.5152/dir.2015.15094] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Magnetic resonance imaging (MRI) is a well-established imaging modality to evaluate increased iron deposition in the liver. Both standard liver imaging series with in-phase and out-of-phase T1-weighted sequences for visual detection, as well as advanced T2- and T2*-weighted measurements may be used for mapping the iron concentration. In this article, we describe different forms of liver iron accumulation (diffuse, heterogeneous, multinodular, focal, segmental, intralesional, periportal, and lobar) and hepatic iron sparing (focal, geographic and nodular). Focal iron sparing is characterized by hypointense areas on R2* map and hyperintense areas on T2* map. We also illustrate MRI findings of simultaneous hepatic iron and fat accumulation. Coexistence of iron (siderosis) and fat (steatosis) can make interpretation of in- and out-of-phase T1-weighted images difficult; calculation of proton density fat fraction and R2* maps can characterize abnormal signal changes observed on in- and out-of-phase images. Knowledge of different forms of hepatic iron overload and iron sparing and evaluation of T2* and R2* maps would allow correct diagnosis of iron-associated liver disorders.
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Affiliation(s)
- İlkay S İdilman
- Department of Radiology, Hacettepe University School of Medicine, Ankara, Turkey.
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36
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Loeffler RB, McCarville MB, Wagstaff AW, Smeltzer MP, Krafft AJ, Song R, Hankins JS, Hillenbrand CM. Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification? Pediatr Radiol 2017; 47:46-54. [PMID: 27752732 PMCID: PMC5203961 DOI: 10.1007/s00247-016-3700-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Revised: 07/21/2016] [Accepted: 08/26/2016] [Indexed: 11/25/2022]
Abstract
BACKGROUND Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. OBJECTIVE To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. MATERIALS AND METHODS This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. RESULTS Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. CONCLUSION We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations.
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Affiliation(s)
- Ralf B Loeffler
- Diagnostic Imaging, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105-3678, USA
| | - M Beth McCarville
- Diagnostic Imaging, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105-3678, USA
| | - Anne W Wagstaff
- Diagnostic Imaging, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105-3678, USA
- Rhodes College, Memphis, TN, USA
- University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Matthew P Smeltzer
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Axel J Krafft
- Diagnostic Imaging, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105-3678, USA
- Department of Radiology, University Hospital Center Freiburg, Freiburg, Germany
| | - Ruitian Song
- Diagnostic Imaging, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105-3678, USA
| | - Jane S Hankins
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Claudia M Hillenbrand
- Diagnostic Imaging, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105-3678, USA.
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Chuansumrit A, Laothamathat J, Sirachainan N, Sungkarat W, Wongwerawattanakoon P, Kumkrua P. Correlation between liver iron concentration determined by magnetic resonance imaging and serum ferritin in adolescents with thalassaemia disease. Paediatr Int Child Health 2016; 36:203-8. [PMID: 27595699 DOI: 10.1179/2046905515y.0000000037] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND MRI imaging is an alternative to serum ferritin for assessing iron overload in patients with thalassaemia disease. AIMS To correlate liver iron concentration (LIC) determined by MRI and clinical and biochemical parameters. METHODS An MRI study using cardiovascular magnetic resonance (CMR) tools to determine cardiac and liver iron was undertaken in adolescents with thalassaemia disease. RESULTS Eighty-nine patients (48 males) with thalassaemia disease were enrolled. Seventy patients had been transfusion-dependent since a mean (SD) age of 3.8 (3.0) years, and 19 patients were not transfusiondependent. Mean (SD) haematocrit was 27.3 (2.9)%. Twenty-eight patients were splenectomized. Mean (SD) serum ferritin was 1673 (1506) μg/L. All transfusion-dependent patients received iron chelation at the mean (SD) age of 8.4 (3.5) years with either monotherapy of desferrioxamine, deferiprone, deferasirox or combined therapy of desferrioxamine and deferiprone, while only 5 of 19 patients who were not transfusion-dependent received oral chelation. The 89 patients underwent an MRI scan at the mean (SD) age of 14.8 (3.2) years. No patients had myocardial iron overload, but nine had severe liver iron overload, 27 had moderate liver iron overload, and 36 had mild liver iron overload. A significant correlation between liver T2* and serum ferritin was expressed as the equation: T2* (ms) = 28.080-7.629 log ferritin (μg/L) (r(2) 0.424, P = 0.0001). Patients with serum ferritin of >1000 to >2500 μg/L risked moderate and severe liver iron loading with the odds ratio ranging from 6.8 to 13.3 (95% CI 2.5-50.8). CONCLUSION In thalassaemia, MRI is an alternative means of assessing iron stores, but when it is not available serum ferritin can be used to estimate liver T2*.
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Affiliation(s)
- Ampaiwan Chuansumrit
- a Departments of Pediatrics , Faculty of Medicine Ramathibodi Hospital, Mahidol University , Bangkok , Thailand
| | - Jiraporn Laothamathat
- b Radiology and Faculty of Medicine Ramathibodi Hospital , Mahidol University , Bangkok , Thailand.,d Advanced Diagnostic Imaging Center, Faculty of Medicine Ramathibodi Hospital , Mahidol University , Bangkok , Thailand
| | - Nongnuch Sirachainan
- a Departments of Pediatrics , Faculty of Medicine Ramathibodi Hospital, Mahidol University , Bangkok , Thailand
| | - Witaya Sungkarat
- b Radiology and Faculty of Medicine Ramathibodi Hospital , Mahidol University , Bangkok , Thailand.,d Advanced Diagnostic Imaging Center, Faculty of Medicine Ramathibodi Hospital , Mahidol University , Bangkok , Thailand
| | | | - Patrapop Kumkrua
- d Advanced Diagnostic Imaging Center, Faculty of Medicine Ramathibodi Hospital , Mahidol University , Bangkok , Thailand
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A Room Temperature Ultrasensitive Magnetoelectric Susceptometer for Quantitative Tissue Iron Detection. Sci Rep 2016; 6:29740. [PMID: 27465206 PMCID: PMC4964576 DOI: 10.1038/srep29740] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 06/22/2016] [Indexed: 11/08/2022] Open
Abstract
Iron is a trace mineral that plays a vital role in the human body. However, absorbing and accumulating excessive iron in body organs (iron overload) can damage or even destroy an organ. Even after many decades of research, progress on the development of noninvasive and low-cost tissue iron detection methods is very limited. Here we report a recent advance in a room-temperature ultrasensitive biomagnetic susceptometer for quantitative tissue iron detection. The biomagnetic susceptometer exploits recent advances in the magnetoelectric (ME) composite sensors that exhibit an ultrahigh AC magnetic sensitivity under the presence of a strong DC magnetic field. The first order gradiometer based on piezoelectric and magnetostrictive laminate (ME composite) structure shows an equivalent magnetic noise of 0.99 nT/rt Hz at 1 Hz in the presence of a DC magnetic field of 0.1 Tesla and a great common mode noise rejection ability. A prototype magnetoelectric liver susceptometry has been demonstrated with liver phantoms. The results indicate its output signals to be linearly responsive to iron concentrations from normal iron dose (0.05 mg Fe/g liver phantom) to 5 mg Fe/g liver phantom iron overload (100X overdose). The results here open up many innovative possibilities for compact-size, portable, cost-affordable, and room-temperature operated medical systems for quantitative determinations of tissue iron.
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Chin JL, Pavlides M, Moolla A, Ryan JD. Non-invasive Markers of Liver Fibrosis: Adjuncts or Alternatives to Liver Biopsy? Front Pharmacol 2016; 7:159. [PMID: 27378924 PMCID: PMC4913110 DOI: 10.3389/fphar.2016.00159] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 05/31/2016] [Indexed: 12/13/2022] Open
Abstract
Liver fibrosis reflects sustained liver injury often from multiple, simultaneous factors. Whilst the presence of mild fibrosis on biopsy can be a reassuring finding, the identification of advanced fibrosis is critical to the management of patients with chronic liver disease. This necessity has lead to a reliance on liver biopsy which itself is an imperfect test and poorly accepted by patients. The development of robust tools to non-invasively assess liver fibrosis has dramatically enhanced clinical decision making in patients with chronic liver disease, allowing a rapid and informed judgment of disease stage and prognosis. Should a liver biopsy be required, the appropriateness is clearer and the diagnostic yield is greater with the use of these adjuncts. While a number of non-invasive liver fibrosis markers are now used in routine practice, a steady stream of innovative approaches exists. With improvement in the reliability, reproducibility and feasibility of these markers, their potential role in disease management is increasing. Moreover, their adoption into clinical trials as outcome measures reflects their validity and dynamic nature. This review will summarize and appraise the current and novel non-invasive markers of liver fibrosis, both blood and imaging based, and look at their prospective application in everyday clinical care.
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Affiliation(s)
- Jun L Chin
- School of Medicine and Medical Science, University College Dublin Dublin, Ireland
| | - Michael Pavlides
- Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford Oxford, UK
| | - Ahmad Moolla
- Radcliffe Department of Medicine, University of Oxford Oxford, UK
| | - John D Ryan
- Translational Gastroenterology Unit, University of Oxford Oxford, UK
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Saliba AN, El Rassi F, Taher AT. Clinical monitoring and management of complications related to chelation therapy in patients with β-thalassemia. Expert Rev Hematol 2015; 9:151-68. [DOI: 10.1586/17474086.2016.1126176] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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41
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Wood JC, Zhang P, Rienhoff H, Abi-Saab W, Neufeld EJ. Liver MRI is more precise than liver biopsy for assessing total body iron balance: a comparison of MRI relaxometry with simulated liver biopsy results. Magn Reson Imaging 2015; 33:761-7. [PMID: 25708262 DOI: 10.1016/j.mri.2015.02.016] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Revised: 01/14/2015] [Accepted: 02/16/2015] [Indexed: 02/06/2023]
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42
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Radmard AR, Poustchi H, Dadgostar M, Yoonessi A, Kooraki S, Jafari E, Hashemi Taheri AP, Malekzadeh R, Merat S. Liver enzyme levels and hepatic iron content in Fatty liver: a noninvasive assessment in general population by T2* mapping. Acad Radiol 2015; 22:714-21. [PMID: 25754799 DOI: 10.1016/j.acra.2015.01.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 01/17/2015] [Accepted: 01/30/2015] [Indexed: 12/16/2022]
Abstract
RATIONALE AND OBJECTIVES Existing evidence suggests potential contribution of iron in pathogenesis of nonalcoholic fatty liver disease (NAFLD). We aimed to investigate whether hepatic iron content correlates with liver enzyme levels in NAFLD using a noninvasive magnetic resonance imaging (MRI) technique. MATERIALS AND METHODS Subjects from Golestan Cohort Study were randomly selected. Diagnosis of NAFLD was made by combination of ultrasound and MRI. Subjects with NAFLD were divided into two groups with high (H-NAFLD) and low (L-NAFLD) enzyme level according to 95th percentile of alanine aminotransferase (ALT) value in normal population. Quantitative T2* maps of entire cross-sectional area of liver were calculated on pixel-by-pixel basis using a semiautomated software. RESULTS A total of 207 subjects were enrolled. Mean T2* values were significantly lower in NAFLD group than controls (P < .001) indicating higher iron content. Male subjects with H-NAFLD had statistically lower T2* values than those with L-NAFLD in multivariate analysis (odds ratio, 0.74; 95% confidence interval [CI], 0.58-0.95), whereas this was not observed in women. Unlike women, there was significant negative correlation between ALT levels and T2* values in men with H-NAFLD (r = -0.66, P = .01). Every 1-millisecond decrement in T2* value was associated with 6.37 IU/L increase in ALT level (95% CI, 1.8-10.9, P = .01) in men with H-NAFLD. CONCLUSIONS Higher hepatic iron in men with H-NAFLD, estimated by T2* mapping, may support the role of iron in possible progression of simple steatosis to nonalcoholic steatohepatitis. Lack of such correlation in women could be attributed to relatively lower iron storage or other mechanisms rather than iron.
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Affiliation(s)
- Amir Reza Radmard
- Department of Radiology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran; Digestive Tract Image Processing Research Group, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Poustchi
- Liver and Pancreatobiliary Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Shariati Hospital, North Kargar Avenue, Tehran 14117-13135, Iran
| | - Mehrdad Dadgostar
- Digestive Tract Image Processing Research Group, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran; Department of Electrical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Ali Yoonessi
- Digestive Tract Image Processing Research Group, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran; Neuroscience Department, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Soheil Kooraki
- Department of Radiology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Elham Jafari
- Liver and Pancreatobiliary Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Shariati Hospital, North Kargar Avenue, Tehran 14117-13135, Iran
| | | | - Reza Malekzadeh
- Liver and Pancreatobiliary Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Shariati Hospital, North Kargar Avenue, Tehran 14117-13135, Iran
| | - Shahin Merat
- Liver and Pancreatobiliary Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Shariati Hospital, North Kargar Avenue, Tehran 14117-13135, Iran.
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Yokoo T, Yuan Q, Sénégas J, Wiethoff AJ, Pedrosa I. Quantitative R2* MRI of the liver with rician noise models for evaluation of hepatic iron overload: Simulation, phantom, and early clinical experience. J Magn Reson Imaging 2015; 42:1544-59. [PMID: 25996989 DOI: 10.1002/jmri.24948] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2014] [Accepted: 04/28/2015] [Indexed: 12/11/2022] Open
Abstract
PURPOSE To compare Rician and non-Rician noise models for quantitative R2 * magnetic resonance imaging (MRI), in a simulation, phantom, and human study. MATERIALS AND METHODS Synthetic 12-echo spoiled GRE (SGRE) datasets were generated with various R2 * rates (0-2000 sec(-1) ) at a signal-to-noise ratio (SNR) of 50, 20, 10, and 5. Phantoms of different MnCl2 concentrations (0-25 mM) were constructed and imaged using a 12-echo 3D SGRE sequence at 1.5T. Increasing levels of synthetic noise was added to the original data to simulate sequentially lower SNR conditions. Sixteen patients with suspected or known iron overload were imaged using 12-echo 3D SGRE at 1.5T. Various R2 * quantification methods, based on Rician and non-Rician noise models, were compared in the simulation, phantom, and human datasets. RESULTS Non-Rician R2 * estimates were variably inaccurate in the high R2 * range (>500 sec(-1) ), with SNR-dependent linear goodness-of-fit statistic (R(2) ) of 0.373-0.999. Rician R2 * estimates were accurate even in the high R2 * range, with high R(2) of 0.940-0.999 regardless of SNR. Non-Rician R2 * estimates were variably nonlinear at high MnCl2 concentrations, with SNR-dependent R(2) of 0.345-0.994. Rician R2 * estimates were linear even at high MnCl2 concentrations, with high R(2) of 0.923-0.994 regardless of SNR. Between-method agreement of the R2 * estimates was excellent in patients with low ferritin but poor in patients with high ferritin. Rician R2 * estimates had excellent correlation with ferritin (r = 0.966 P < 0.001). CONCLUSION Rician R2 * estimates were most consistent in the high R2 * conditions and under varying SNR, and may be more reliable when high iron load is suspected.
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Affiliation(s)
- Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Qing Yuan
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | - Andrea J Wiethoff
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Briarcliff Manor, New York, USA
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Sofue K, Mileto A, Dale BM, Zhong X, Bashir MR. Interexamination repeatability and spatial heterogeneity of liver iron and fat quantification using MRI-based multistep adaptive fitting algorithm. J Magn Reson Imaging 2015; 42:1281-90. [PMID: 25920074 DOI: 10.1002/jmri.24922] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Accepted: 04/06/2015] [Indexed: 12/12/2022] Open
Abstract
PURPOSE To assess the interexamination repeatability and spatial heterogeneity of liver iron and fat measurements using a magnetic resonance imaging (MRI)-based multistep adaptive fitting algorithm. MATERIALS AND METHODS This prospective observational study was Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant. Written informed consent was waived. In all, 150 subjects were imaged on 3T MRI systems. A whole-liver volume acquisition was performed twice using a six-echo 3D spoiled gradient echo sequence during two immediately adjacent examinations. Colocalized regions of interest (ROIs) in three different hepatic segments were placed for R2 * and proton density fat fraction (PDFF) measurements by two readers independently. Mean R2 * and PDFF values between readers and acquisitions were compared using the Wilcoxon signed-rank test, intraclass correlation coefficients (ICCs), linear regression, Bland-Altman analysis, and analysis of variance (ANOVA). RESULTS The mean R2 * and PDFF values across all ROIs and measurements were 51.2 ± 25.2 s(-1) and 6.9 ± 6.4%, respectively. Mean R2 * and PDFF values showed no significant differences between the two acquisitions (P = 0.05-0.87). Between the two acquisitions, R2 * and PDFF values demonstrated almost perfect agreement (ICCs = 0.979-0.994) and excellent correlation (R(2) = 0.958-0.989). Bland-Altman analysis also demonstrated excellent agreement. In the ANOVA, the individual patient and ROI location were significant effects for both R2 * and PDFF values (P < 0.05). CONCLUSION MRI-based R2 * and PDFF measurements are repeatable between examinations. Between-measurement changes in R2 * of more than 10.1 s(-1) and in PDFF of more than 1.7% are likely due to actual tissue changes. Liver iron and fat content are variable between hepatic segments.
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Affiliation(s)
- Keitaro Sofue
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Achille Mileto
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Brian M Dale
- Siemens Healthcare, Morrisville, North Carolina, USA
| | | | - Mustafa R Bashir
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, North Carolina, USA
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Abstract
Iron overload is becoming an increasing problem as haemoglobinopathy patients gain greater access to good medical care and as therapies for myelodysplastic syndromes improve. Therapeutic options for iron chelation therapy have increased and many patients now receive combination therapies. However, optimal utilization of iron chelation therapy requires knowledge not only of the total body iron burden but the relative iron distribution among the different organs. The physiological basis for extrahepatic iron deposition is presented in order to help identify patients at highest risk for cardiac and endocrine complications. This manuscript reviews the current state of the art for monitoring global iron overload status as well as its compartmentalization. Plasma markers, computerized tomography, liver biopsy, magnetic susceptibility devices and magnetic resonance imaging (MRI) techniques are all discussed but MRI has come to dominate clinical practice. The potential impact of recent pancreatic and pituitary MRI studies on clinical practice are discussed as well as other works-in-progress. Clinical protocols are derived from experience in haemoglobinopathies but may provide useful guiding principles for other iron overload disorders, such as myelodysplastic syndromes.
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Affiliation(s)
- John C Wood
- Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
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46
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Urru SAM, Tandurella I, Capasso M, Usala E, Baronciani D, Giardini C, Visani G, Angelucci E. Reproducibility of liver iron concentration measured on a biopsy sample: a validation study in vivo. Am J Hematol 2015; 90:87-90. [PMID: 25345839 DOI: 10.1002/ajh.23878] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2014] [Revised: 10/21/2014] [Accepted: 10/24/2014] [Indexed: 12/20/2022]
Abstract
Determination of liver iron concentration is essential to predict iron related tissue damage and to guide chelation therapy. To assess the reliability of a single biopsy iron concentration determination in representing the whole liver iron concentration, we conducted a prospective study performing two immediately successive liver biopsies from 61 noncirrhotic, iron overloaded thalassemia patients, directing the needle to different direction from the same skin cut. The correlation among sample biopsies was determined by both regression analysis and the Bland-Altman method. The results showed that overall correlation between the two samples was high (Pearson's coefficient of correlation r = 0.970, P < 0.0001; 95% CI 0.951-0.981; R(2) = 0.941). To evaluate if sample dimension had an impact on the analysis we analyzed separately biopsy couples were both sample gross weight were ≥1 mg dry weight (n = 16) from the others [one or both had a specimen gross weight <1 mg dry weight (n = 45)]. In the first case, correlation coefficient r was equal to 0.998 (P < 0.0001; 95% CI: 0.995-0.999; R(2) = 0.996) while in the latter was 0.960 (P < 0.0001; 95% CI: 0.928-0.977; R(2) = 0.921). In no instance second specimen prediction interval was outside the interval implying different prognostic and therapeutic decision if both liver samples gross weight were ≥1 mg dry weight. The Bland-Altman plot analysis showed the same trend observed using Pearson's correlation coefficient in the analyzed sample categories. Hepatic iron concentration determined in "good quality" biopsy specimen (i.e. sample gross weight ≥1 mg dry weight) is a reliable indicator of whole liver iron concentration.
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Affiliation(s)
| | - Igor Tandurella
- UO Ematologia e Centro Trapianti; Dipartimento Oncologia Medica; Ospedale Oncologico di Riferimento Regionale “Armando Businco”; Cagliari Italy
| | - Mario Capasso
- Dipartimento di Medicina Molecolare e Biotecnologie Mediche; Università degli Studi di Napoli Federico II; Naples Italy
- CEINGE Biotecnologie Avanzate; Napoli Italy
| | - Emilio Usala
- UO Ematologia e Centro Trapianti; Dipartimento Oncologia Medica; Ospedale Oncologico di Riferimento Regionale “Armando Businco”; Cagliari Italy
| | - Donatella Baronciani
- UO Ematologia e Centro Trapianti; Dipartimento Oncologia Medica; Ospedale Oncologico di Riferimento Regionale “Armando Businco”; Cagliari Italy
| | | | - Giuseppe Visani
- UO Ematologia e Centro Trapianti; Dipartimento Onco-Ematologico; Ospedali Marche Nord; Pesaro Italy
| | - Emanuele Angelucci
- UO Ematologia e Centro Trapianti; Dipartimento Oncologia Medica; Ospedale Oncologico di Riferimento Regionale “Armando Businco”; Cagliari Italy
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47
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Brittenham GM. Reference method for measurement of the hepatic iron concentration. Am J Hematol 2015; 90:85-6. [PMID: 25488360 DOI: 10.1002/ajh.23914] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2014] [Accepted: 12/02/2014] [Indexed: 12/13/2022]
Affiliation(s)
- Gary M. Brittenham
- Department of Pediatrics; Columbia University College of Physicians and Surgeons; New York New York
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48
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Luersen GF, Bhosale P, Szklaruk J. State-of-the-art cross-sectional liver imaging: beyond lesion detection and characterization. J Hepatocell Carcinoma 2015; 2:101-17. [PMID: 27508199 PMCID: PMC4918289 DOI: 10.2147/jhc.s85201] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Cross-sectional imaging with computed tomography or magnetic resonance imaging is routinely used to detect and diagnose liver lesions; however, these examinations can provide additional important information. The improvement of equipment and techniques has allowed outstanding evaluation of the vascular and biliary anatomy, which is practicable in most routine examinations. Anatomical variants may exclude patients from certain therapeutic options and may be the cause of morbidity or mortality after surgery or interventional procedures. Diffuse liver disease, such as steatosis, hemochromatosis, or fibrosis, must be diagnosed and quantified. Usually these conditions are silent until the late stages, and imaging plays an important role in detecting them early. Additionally, a background of diffuse disease may interfere in a focal lesion systematic reasoning. The diagnostic probability of a particular nodule varies according to the background liver disease. Nowadays, most diffuse liver diseases can be easily and accurately quantified by imaging, which has allowed better understanding of these diseases and improved patient management. Finally, cross-sectional imaging can calculate total and partial liver volumes and estimate the future liver remnant after hepatectomy. This information helps to select patients for portal vein embolization and reduces postoperative complications. Use of a specific hepatic contrast agent on magnetic resonance imaging, in addition to improving detection and characterization of focal lesions, provides functional global and segmental information about the liver parenchyma.
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Affiliation(s)
- Gustavo Felipe Luersen
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Priya Bhosale
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Janio Szklaruk
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Alústiza JM, Emparanza JI, Castiella A, Casado A, Garrido A, Aldazábal P, San Vicente M, Garcia N, Asensio AB, Banales J, Salvador E, Moyua A, Arozena X, Zarco M, Jauregui L, Vicente O. Measurement of liver iron concentration by MRI is reproducible. BIOMED RESEARCH INTERNATIONAL 2015; 2015:294024. [PMID: 25874207 PMCID: PMC4385637 DOI: 10.1155/2015/294024] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2014] [Accepted: 09/14/2014] [Indexed: 02/08/2023]
Abstract
PURPOSE The objectives were (i) construction of a phantom to reproduce the behavior of iron overload in the liver by MRI and (ii) assessment of the variability of a previously validated method to quantify liver iron concentration between different MRI devices using the phantom and patients. MATERIALS AND METHODS A phantom reproducing the liver/muscle ratios of two patients with intermediate and high iron overload. Nine patients with different levels of iron overload were studied in 4 multivendor devices and 8 of them were studied twice in the machine where the model was developed. The phantom was analysed in the same equipment and 14 times in the reference machine. RESULTS FeCl3 solutions containing 0.3, 0.5, 0.6, and 1.2 mg Fe/mL were chosen to generate the phantom. The average of the intramachine variability for patients was 10% and for the intermachines 8%. For the phantom the intramachine coefficient of variation was always below 0.1 and the average of intermachine variability was 10% for moderate and 5% for high iron overload. CONCLUSION The phantom reproduces the behavior of patients with moderate or high iron overload. The proposed method of calculating liver iron concentration is reproducible in several different 1.5 T systems.
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Affiliation(s)
- José María Alústiza
- 1Osatek, Donostia Universitary Hospital, P. Dr. Beguiristain 109, 20014 Donostia/San Sebastián, Spain
- *José María Alústiza:
| | - José I. Emparanza
- 2Clinical Epidemiology, Donostia Universitary Hospital, P. Dr. Beguiristain 117, 20080 Donostia/San Sebastián, Spain
| | - Agustín Castiella
- 3Gastroenterology, Mendaro Hospital, Mendarozabal s/n, Mendaro, Spain
| | - Alfonso Casado
- 4Basque Country University, Avenida Tolosa 54, 20018 Donostia/San Sebastián, Spain
| | - Adolfo Garrido
- 5Biochemical Laboratory, Donostia Universitary Hospital, P. Dr. Beguiristain 117, 20080 Donostia/San Sebastián, Spain
| | - Pablo Aldazábal
- 6Experimental Department, Donostia Universitary Hospital, P. Dr. Beguiristain 117, 20080 Donostia/San Sebastián, Spain
| | - Manuel San Vicente
- 1Osatek, Donostia Universitary Hospital, P. Dr. Beguiristain 109, 20014 Donostia/San Sebastián, Spain
| | - Nerea Garcia
- 6Experimental Department, Donostia Universitary Hospital, P. Dr. Beguiristain 117, 20080 Donostia/San Sebastián, Spain
| | - Ana Belén Asensio
- 6Experimental Department, Donostia Universitary Hospital, P. Dr. Beguiristain 117, 20080 Donostia/San Sebastián, Spain
| | - Jesús Banales
- 7Liver Diseases Unit, Biodonostia Research Institute, P. Dr. Beguiristain s/n, 20014 Donostia/San Sebastián, Spain
| | - Emma Salvador
- 1Osatek, Donostia Universitary Hospital, P. Dr. Beguiristain 109, 20014 Donostia/San Sebastián, Spain
| | - Aranzazu Moyua
- 8Policlínica Gipúzkoa, Paseo Miramón 174, 20014 Donostia/San Sebastián, Spain
| | - Xabier Arozena
- 9Radiology, Quirón Donostia Hospital, Alkolea Parkea 7, 20012 Donostia/San Sebastián, Spain
| | - Miguel Zarco
- 9Radiology, Quirón Donostia Hospital, Alkolea Parkea 7, 20012 Donostia/San Sebastián, Spain
| | - Lourdes Jauregui
- 10Onkologikoa, P. Dr. Beguiristain s/n, 20011 Donostia/San Sebastián, Spain
| | - Ohiana Vicente
- 10Onkologikoa, P. Dr. Beguiristain s/n, 20011 Donostia/San Sebastián, Spain
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Abstract
Abstract
Both primary and secondary iron overload are increasingly prevalent in the United States because of immigration from the Far East, increasing transfusion therapy in sickle cell disease, and improved survivorship of hematologic malignancies. This chapter describes the use of historical data, serological measures, and MRI to estimate somatic iron burden. Before chelation therapy, transfusional volume is an accurate method for estimating liver iron burden, whereas transferrin saturation reflects the risk of extrahepatic iron deposition. In chronically transfused patients, trends in serum ferritin are helpful, inexpensive guides to relative changes in somatic iron stores. However, intersubject variability is quite high and ferritin values may change disparately from trends in total body iron load over periods of several years. Liver biopsy was once used to anchor trends in serum ferritin, but it is invasive and plagued by sampling variability. As a result, we recommend annual liver iron concentration measurements by MRI for all patients on chronic transfusion therapy. Furthermore, it is important to measure cardiac T2* by MRI every 6-24 months depending on the clinical risk of cardiac iron deposition. Recent validation data for pancreas and pituitary iron assessments are also presented, but further confirmatory data are suggested before these techniques can be recommended for routine clinical use.
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