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Lian Z, Lu Q, Lin B, Chen L, Gong J, Hu Q, Wang H, Feng Y. A fully automatic parenchyma extraction method for MRI T2* relaxometry of iron loaded liver in transfusion-dependent patients. Magn Reson Imaging 2024; 109:18-26. [PMID: 38430975 DOI: 10.1016/j.mri.2024.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 02/28/2024] [Accepted: 02/28/2024] [Indexed: 03/05/2024]
Abstract
PURPOSE To develop a fully automatic parenchyma extraction method for the T2* relaxometry of iron overload liver. METHODS A retrospective multicenter collection of liver MR examinations from 177 transfusion-dependent patients was conducted. The proposed method extended a semiautomatic parenchyma extraction algorithm to a fully automatic approach by introducing a modified TransUNet on the R2* (1/T2*) map for liver segmentation. Axial liver slices from 129 patients at 1.5 T were allocated to training (85%) and internal test (15%) sets. Two external test sets separately included 1.5 T data from 20 patients and 3.0 T data from 28 patients. The final T2* measurement was obtained by fitting the average signal of the extracted liver parenchyma. The agreement between T2* measurements using fully and semiautomatic parenchyma extraction methods was assessed using coefficient of variation (CoV) and Bland-Altman plots. RESULTS Dice of the deep network-based liver segmentation was 0.970 ± 0.019 on the internal dataset, 0.960 ± 0.035 on the external 1.5 T dataset, and 0.958 ± 0.014 on the external 3.0 T dataset. The mean difference bias between T2* measurements of the fully and semiautomatic methods were separately 0.12 (95% CI: -0.37, 0.61) ms, 0.04 (95% CI: -1.0, 1.1) ms, and 0.01 (95% CI: -0.25, 0.23) ms on the three test datasets. The CoVs between the two methods were 4.2%, 4.8% and 2.0% on the internal test set and two external test sets. CONCLUSIONS The developed fully automatic parenchyma extraction approach provides an efficient and operator-independent T2* measurement for assessing hepatic iron content in clinical practice.
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Affiliation(s)
- Zifeng Lian
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong Joint Laboratory for Psychiatric Disorders, Southern Medical University, Guangzhou, China
| | - Qiqi Lu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong Joint Laboratory for Psychiatric Disorders, Southern Medical University, Guangzhou, China
| | - Bingquan Lin
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Lingjian Chen
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Jian Gong
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Qiugen Hu
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Huafeng Wang
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong Joint Laboratory for Psychiatric Disorders, Southern Medical University, Guangzhou, China; Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China.
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Sussman MS, Jhaveri KS. A short-TR single-echo spin-echo breath-hold method for assessing liver T2. MAGMA (NEW YORK, N.Y.) 2024; 37:101-113. [PMID: 38071698 DOI: 10.1007/s10334-023-01132-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 10/27/2023] [Accepted: 10/28/2023] [Indexed: 02/21/2024]
Abstract
OBJECTIVE Conventional single-echo spin-echo T2 mapping used for liver iron quantification is too long for breath-holding. This study investigated a short TR (~100 ms) single-echo spin-echo T2 mapping technique wherein each image (corresponding to a single TE) could be acquired in ~17 s-short enough for a breath-hold. TE images were combined for T2 fitting. To avoid T1 bias, each TE acquisition incremented TR to maintain a constant TR-TE. MATERIALS AND METHODS Experiments at 1.5T validated the technique's accuracy in phantoms, 9 healthy volunteers, and 5 iron overload patients. In phantoms and healthy volunteers, the technique was compared to the conventional approach of constant TR for all TEs. Iron overload results were compared to FerriScan. RESULTS In phantoms, the constant TR-TE technique provided unbiased estimates of T2, while the conventional constant TR approach underestimated it. In healthy volunteers, there was no significant discrepancy at the 95% confidence level between constant TR-TE and reference T2 values, whereas there was for constant TR scans. In iron overload patients, there was a high correlation between constant TR-TE and FerriScan T2 values (r2 = 0.95), with a discrepancy of 0.6+/- 1.4 ms. DISCUSSION The short-TR single-echo breath-hold spin-echo technique provided unbiased estimates of T2 in phantoms and livers.
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Affiliation(s)
- Marshall S Sussman
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, 585 University Avenue, Room NUW-1-141D, Toronto, ON, M5G 2N2, Canada.
| | - Kartik S Jhaveri
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, 585 University Avenue, Room NUW-1-141D, Toronto, ON, M5G 2N2, Canada
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3
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Velikina JV, Zhao R, Buelo CJ, Samsonov AA, Reeder SB, Hernando D. Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping. Magn Reson Med 2023; 90:385-399. [PMID: 36929781 PMCID: PMC11057046 DOI: 10.1002/mrm.29644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 02/24/2023] [Accepted: 03/05/2023] [Indexed: 03/18/2023]
Abstract
PURPOSE To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM. METHODS An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC). The proposed method was compared to the previously proposed and validated approach in liver QSM for two multi-echo spoiled gradient-recalled echo protocols with different acquisition parameters at 3T. Linear regression was used for evaluation of QSM methods against a reference FDA-approvedR 2 $$ {R}_2 $$ -based LIC measure andR 2 ∗ $$ {R}_2^{\ast } $$ measurements; repeatability/reproducibility were assessed by Bland-Altman analysis. RESULTS The data-adaptive method produced susceptibility maps with higher subjective quality due to reduced shading artifacts. For both acquisition protocols, higher linear correlation with bothR 2 $$ {R}_2 $$ - andR 2 ∗ $$ {R}_2^{\ast } $$ -based measurements were observed for the data-adaptive method (r 2 = 0 . 74 / 0 . 69 $$ {r}^2=0.74/0.69 $$ forR 2 $$ {R}_2 $$ ,0 . 97 / 0 . 95 $$ 0.97/0.95 $$ forR 2 ∗ $$ {R}_2^{\ast } $$ ) than the standard method (r 2 = 0 . 60 / 0 . 66 $$ {r}^2=0.60/0.66 $$ and0 . 79 / 0 . 88 $$ 0.79/0.88 $$ ). For both protocols, the data-adaptive method enabled better test-retest repeatability (repeatability coefficients 0.19/0.30 ppm for the data-adaptive method, 0.38/0.47 ppm for the standard method) and reproducibility across protocols (reproducibility coefficient 0.28 vs. 0.53ppm) than the standard method. CONCLUSIONS The proposed data-adaptive QSM algorithm may enable quantification of LIC with improved repeatability/reproducibility across different acquisition parameters as 3T.
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Affiliation(s)
- Julia V Velikina
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Ruiyang Zhao
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Collin J Buelo
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Alexey A Samsonov
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin, Madison, WI, USA
- Department of Emergency Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
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4
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Zhao R, Velikina J, Reeder SB, Vasanawala S, Jeng M, Hernando D. Validation of liver quantitative susceptibility mapping across imaging parameters at 1.5 T and 3.0 T using SQUID susceptometry as reference. Magn Reson Med 2023; 89:1418-1428. [PMID: 36408802 PMCID: PMC9892291 DOI: 10.1002/mrm.29529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 10/02/2022] [Accepted: 10/28/2022] [Indexed: 11/22/2022]
Abstract
PURPOSE To validate QSM-based biomagnetic liver susceptometry (BLS) to measure liver iron overload at 1.5 T and 3.0 T using superconducting quantum interference devices (SQUID)-based BLS as reference. METHODS Subjects with known or suspected iron overload were recruited for QSM-BLS at 1.5 T and 3.0 T using eight different protocols. SQUID-BLS was also obtained in each subject to provide susceptibility reference. A recent QSM method based on data-adaptive regularization was used to obtain susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps. Measurements of susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were obtained in the right liver lobe. Linear mixed-effects analysis was used to estimate the contribution of specific acquisition parameters to QSM-BLS. Linear regression and Bland-Altman analyses were used to assess the relationship between QSM-BLS and SQUID-BLS/ R 2 * $$ {\mathrm{R}}_2^{\ast } $$ . RESULTS Susceptibility maps showed high subjective quality for each acquisition protocol across different iron levels. High linear correlation was observed between QSM-BLS and SQUID-BLS at 1.5 T (r2 range, [0.82, 0.84]) and 3.0 T (r2 range, [0.77, 0.85]) across different acquisition protocols. QSM-BLS and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were highly correlated at both field strengths (r2 range at 1.5 T, [0.94, 0.99]; 3.0 T, [0.93, 0.99]). High correlation (r2 = 0.99) between 1.5 T and 3.0 T QSM-BLS, with narrow reproducibility coefficients (range, [0.13, 0.21] ppm) were observed for each protocol. CONCLUSION This work evaluated the feasibility and performance of liver QSM-BLS across iron levels and acquisition protocols at 1.5 T and 3.0 T. High correlation and reproducibility were observed between QSM-BLS and SQUID-BLS across protocols and field strengths. In summary, QSM-BLS may enable reliable and reproducible quantification of liver iron concentration.
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Affiliation(s)
- Ruiyang Zhao
- Department of Radiology, University of Wisconsin, Madison, WI, 53705, USA,Department of Medical Physics, University of Wisconsin, Madison, WI, 53705, USA
| | - Julia Velikina
- Department of Radiology, University of Wisconsin, Madison, WI, 53705, USA
| | - Scott B. Reeder
- Department of Radiology, University of Wisconsin, Madison, WI, 53705, USA,Department of Medical Physics, University of Wisconsin, Madison, WI, 53705, USA,Department of Biomedical Engineering, University of Wisconsin, Madison, WI, 53705,Department of Medicine, University of Wisconsin, Madison, WI, 53705, USA,Department of Emergency Medicine, University of Wisconsin, Madison, WI, 53705, USA
| | | | - Michael Jeng
- Department of Pediatrics, Stanford University, Stanford, CA, 94305, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, WI, 53705, USA,Department of Medical Physics, University of Wisconsin, Madison, WI, 53705, USA
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5
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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: 17] [Impact Index Per Article: 17.0] [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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6
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Cascade of Denoising and Mapping Neural Networks for MRI R2* Relaxometry of Iron-Loaded Liver. Bioengineering (Basel) 2023; 10:bioengineering10020209. [PMID: 36829703 PMCID: PMC9952355 DOI: 10.3390/bioengineering10020209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 02/09/2023] Open
Abstract
MRI of effective transverse relaxation rate (R2*) measurement is a reliable method for liver iron concentration quantification. However, R2* mapping can be degraded by noise, especially in the case of iron overload. This study aimed to develop a deep learning method for MRI R2* relaxometry of an iron-loaded liver using a two-stage cascaded neural network. The proposed method, named CadamNet, combines two convolutional neural networks separately designed for image denoising and parameter mapping into a cascade framework, and the physics-based R2* decay model was incorporated in training the mapping network to enforce data consistency further. CadamNet was trained using simulated liver data with Rician noise, which was constructed from clinical liver data. The performance of CadamNet was quantitatively evaluated on simulated data with varying noise levels as well as clinical liver data and compared with the single-stage parameter mapping network (MappingNet) and two conventional model-based R2* mapping methods. CadamNet consistently achieved high-quality R2* maps and outperformed MappingNet at varying noise levels. Compared with conventional R2* mapping methods, CadamNet yielded R2* maps with lower errors, higher quality, and substantially increased efficiency. In conclusion, the proposed CadamNet enables accurate and efficient iron-loaded liver R2* mapping, especially in the presence of severe noise.
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7
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Luo J, Collingwood JF. Effective R 2 relaxation rate, derived from dual-contrast fast-spin-echo MRI, enables detection of hemisphere differences in iron level and dopamine function in Parkinson's disease and healthy individuals. J Neurosci Methods 2022; 382:109708. [PMID: 36089168 DOI: 10.1016/j.jneumeth.2022.109708] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 08/26/2022] [Accepted: 09/06/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND Clinical estimates of brain iron concentration are achievable with quantitative transverse relaxation rate R2, via time-consuming multiple spin-echo (SE) sequences. The objective of this study was to investigate whether quantitative iron-sensitive information may be derived from 3.0 T dual-contrast fast-spin-echo (FSE) sequences (typically employed in anatomical non-quantitative evaluations), as a routinely-collected alternative to evaluate iron levels in healthy (HC) and Parkinson's disease (PD) brains. NEW METHOD MRI 3.0 T FSE data from the Parkinson's Progression Markers Initiative (PPMI) (12 PD, 12 age- and gender-matched HC subjects) were cross-sectionally and longitudinally evaluated. A new measure, 'effective R2', was calculated for bilateral subcortical grey matter (caudate nucleus, putamen, globus pallidus, red nucleus, substantia nigra). Linear regression analysis was performed to correlate 'effective R2' with models of age-dependent brain iron concentration and striatal dopamine transporter (DaT) receptor binding ratio. RESULTS Effective R2 was strongly correlated with estimated brain iron concentration. In PD, putaminal effective R2 difference was observed between the hemispheres contra-/ipsi-lateral to the predominantly symptomatic side at onset. This hemispheric difference was correlated with the putaminal DaT binding ratios in PD. COMPARISON WITH EXISTING METHOD(S) Effective R2, derived from rapid dual-contrast FSE sequences, showed viability as an alternative to R2 from SE sequences. Linear correlation of effective R2 with estimated iron concentration was comparable to documented iron-dependent R2. The effective R2 correlation coefficient was consistent with theoretical R2 iron-dependence at 3.0 T. CONCLUSIONS Effective R2 has clinical potential as a fast quantitative method, as an alternative to R2, to aid evaluation of brain iron levels and DaT function.
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Affiliation(s)
- Jierong Luo
- School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom
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8
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Comparison of T2 Quantification Strategies in the Abdominal-Pelvic Region for Clinical Use. Invest Radiol 2022; 57:412-421. [PMID: 34999669 DOI: 10.1097/rli.0000000000000852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES The aim of the study was to compare different magnetic resonance imaging (MRI) acquisition strategies appropriate for T2 quantification in the abdominal-pelvic area. The different techniques targeted in the study were chosen according to 2 main considerations: performing T2 measurement in an acceptable time for clinical use and preventing/correcting respiratory motion. MATERIALS AND METHODS Acquisitions were performed at 3 T. To select sequences for in vivo measurements, a phantom experiment was conducted, for which the T2 values obtained with the different techniques of interest were compared with the criterion standard (single-echo SE sequence, multiple acquisitions with varying echo time). Repeatability and temporal reproducibility studies for the different techniques were also conducted on the phantom. Finally, an in vivo study was conducted on 12 volunteers to compare the techniques that offer acceptable acquisition time for clinical use and either address or correct respiratory motion. RESULTS For the phantom study, the DESS and T2-preparation techniques presented the lowest precision (ρ2 = 0.9504 and ρ2 = 0.9849 respectively), and showed a poor repeatability/reproducibility compared with the other techniques. The strategy relying on SE-EPI showed the best precision and accuracy (ρ2 = 0.9994 and Cb = 0.9995). GRAPPATINI exhibited a very good precision (ρ2 = 0.9984). For the technique relying on radial TSE, the precision was not as good as GRAPPATINI (ρ2 = 0.9872). The in vivo study demonstrated good respiratory motion management for all of the selected techniques. It also showed that T2 estimate ranges were different from one method to another. For GRAPPATINI and radial TSE techniques, there were significant differences between all the different types of organs of interest. CONCLUSIONS To perform T2 measurement in the abdominal-pelvic region, one should favor a technique with acceptable acquisition time for clinical use, with proper respiratory motion management, with good repeatability, reproducibility, and precision. In this study, the techniques relying respectively on SE-EPI, radial TSE, and GRAPPATINI appeared as good candidates.
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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: 2] [Impact Index Per Article: 0.7] [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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10
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Wang Q, Xiao H, Yu X, Lin H, Yang B, Zhang Y, Feng D, Yan F, Wang H. R1ρ at high spin-lock frequency could be a complementary imaging biomarker for liver iron overload quantification. Magn Reson Imaging 2020; 75:141-148. [PMID: 33129937 DOI: 10.1016/j.mri.2020.10.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 10/25/2020] [Accepted: 10/26/2020] [Indexed: 01/16/2023]
Abstract
PURPOSE To compare the correlations among the R1ρ, R2, and R2* relaxation rates with liver iron concentration (LIC) in the assessment of rat liver iron content and explore the application potential of R1ρ in assessing liver iron content. METHODS Iron dextran (dosage of 0, 25, 50, 100, and 200 mg/kg body weight) was injected into 35 male rats to increase the amount of iron storage in the liver. After one week, all rats were euthanized with isoflurane. A portion of the largest hepatic lobe was extracted to quantify the LIC by inductively coupled plasma, and the remaining liver tissue was stored in 4% buffered paraformaldehyde for 24 h before MRI. Spin-lock preparation with a RARE (rapid acquisition with relaxation enhancement) readout (9 different spin-lock times and 7 different spin-lock frequencies (FSLs)) and multi-echo UTE (ultrashort TE) pulses were developed to quantify R1ρ and R2 * on a Bruker 11.7 T MR system. For comparisons with R1ρ and R2*, R2 was acquired using the CPMG sequence. RESULTS Mean R1ρ values displayed dispersion, with decrease in R1ρ at higher FSLs. Spearman's correlation analysis (two-tailed) indicated that the R1ρ values were significantly associated with LIC at FSL = 2000, 2500, and 3000 Hz (r = 0.365 and P = 0.031, r = 0.608 and P < 0.001, and r = 0.764 and P < 0.001, respectively), and were not significantly associated with LIC at FSL = 500, 1000, 1250, and 1500 Hz (all P > 0.05). R2 and R2* showed significant linear correlations with LIC (r = 0.787 and P < 0.001, and r = 0.859 and P < 0.001, respectively). Correlation analysis across R1ρ, R2, and R* also suggested that the correlation strength between R1ρ and R2 and between R1ρ and R* showed an increasing trend with increase in FSL. CONCLUSION In this study, a strong association was observed between R1ρ and LIC at high FSLs further confirming previous findings. The results demonstrated that R1ρ at high FSL might serve as a complementary imaging biomarker for liver iron overload quantification.
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Affiliation(s)
- Qianfeng Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Hong Xiao
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuchen Yu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Huimin Lin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Baofeng Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yuwen Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Danyang Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.
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11
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Hutter J, Jackson L, Ho A, Pietsch M, Story L, Chappell LC, Hajnal JV, Rutherford M. T2* relaxometry to characterize normal placental development over gestation in-vivo at 3T. Wellcome Open Res 2019. [DOI: 10.12688/wellcomeopenres.15451.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Background: T2* relaxometry has been identified as a non-invasive way to study the placenta in-vivo with good potential to identify placental insufficiency. Typical interpretation links T2* values to oxygen concentrations. This study aimed to comprehensively assess T2* maps as a marker of placental oxygenation in-vivo. Methods: A multi-echo gradient echo echo planar imaging sequence is used in a cohort of 84 healthy pregnant women. Special emphasis is put on spatial analysis: histogram measures, Histogram Asymmetry Measure (HAM) and lacunarity. Influences of maternal, fetal and placental factors and experimental parameters on the proposed measures are evaluated. Results: T2* maps were obtained from each placenta in less than 30sec. The previously reported decreasing trend in mean T2* with gestation was confirmed (3.45 ms decline per week). Factors such as maternal age, BMI, fetal sex, parity, mode of delivery and placental location were shown to be uncorrelated with T2* once corrected for gestational age. Robustness of the obtained values with regard to variation in segmentation and voxel-size were established. The proposed spatially resolved measures reveal a change in T2* in late gestation. Conclusions: T2* mapping is a robust and quick technique allowing quantification of both whole volume and spatial quantification largely independent of confounding factors.
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12
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Finnegan ME, Visanji NP, Romero-Canelon I, House E, Rajan S, Mosselmans JFW, Hazrati LN, Dobson J, Collingwood JF. Synchrotron XRF imaging of Alzheimer's disease basal ganglia reveals linear dependence of high-field magnetic resonance microscopy on tissue iron concentration. J Neurosci Methods 2019; 319:28-39. [PMID: 30851339 DOI: 10.1016/j.jneumeth.2019.03.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 03/02/2019] [Accepted: 03/02/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND Chemical imaging of the human brain has great potential for diagnostic and monitoring purposes. The heterogeneity of human brain iron distribution, and alterations to this distribution in Alzheimer's disease, indicate iron as a potential endogenous marker. The influence of iron on certain magnetic resonance imaging (MRI) parameters increases with magnetic field, but is under-explored in human brain tissues above 7 T. NEW METHOD Magnetic resonance microscopy at 9.4 T is used to calculate parametric images of chemically-unfixed post-mortem tissue from Alzheimer's cases (n = 3) and healthy controls (n = 2). Iron-rich regions including caudate nucleus, putamen, globus pallidus and substantia nigra are analysed prior to imaging of total iron distribution with synchrotron X-ray fluorescence mapping. Iron fluorescence calibration is achieved with adjacent tissue blocks, analysed by inductively coupled plasma mass spectrometry or graphite furnace atomic absorption spectroscopy. RESULTS Correlated MR images and fluorescence maps indicate linear dependence of R2, R2* and R2' on iron at 9.4 T, for both disease and control, as follows: [R2(s-1) = 0.072[Fe] + 20]; [R2*(s-1) = 0.34[Fe] + 37]; [R2'(s-1) = 0.26[Fe] + 16] for Fe in μg/g tissue (wet weight). COMPARISON WITH EXISTING METHODS This method permits simultaneous non-destructive imaging of most bioavailable elements. Iron is the focus of the present study as it offers strong scope for clinical evaluation; the approach may be used more widely to evaluate the impact of chemical elements on clinical imaging parameters. CONCLUSION The results at 9.4 T are in excellent quantitative agreement with predictions from experiments performed at lower magnetic fields.
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Affiliation(s)
- Mary E Finnegan
- Department of Imaging, Imperial College Healthcare NHS Trust, London, UK; Department of Bioengineering, Imperial College London, London, UK
| | - Naomi P Visanji
- The Edmond J Safra Program in Parkinson's Disease and the Morton & Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, Ontario, M5T 2S8, Canada
| | - Isolda Romero-Canelon
- School of Pharmacy, Institute of Clinical Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Emily House
- Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Surya Rajan
- School of Engineering, University of Warwick, Coventry, CV4 7AL, UK
| | | | | | - Jon Dobson
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Joanna F Collingwood
- School of Engineering, University of Warwick, Coventry, CV4 7AL, UK; Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32611, USA.
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13
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Barrera CA, Otero HJ, Hartung HD, Biko DM, Serai SD. Protocol optimization for cardiac and liver iron content assessment using MRI: What sequence should I use? Clin Imaging 2019; 56:52-57. [PMID: 30889418 DOI: 10.1016/j.clinimag.2019.02.012] [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: 12/17/2018] [Revised: 01/31/2019] [Accepted: 02/19/2019] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To determine the optimal MRI protocol and sequences for liver and cardiac iron estimation in children. METHODS We evaluated patients ≤18 years with cardiac and liver MRIs for iron content estimation. Liver T2 was determined by a third-party company. Cardiac and Liver T2* values were measured by an observer. Liver T2* values were calculated using the available liver parenchyma in the cardiac MRI. Linear correlations and Bland-Altman plots were run between liver T2 and T2*, cardiac T2* values; and liver T2* on dedicated cardiac and liver MRIs. RESULTS 139 patients were included. Mean liver T2 and T2* values were 8.6 ± 5.4 ms and 4.5 ± 4.1 ms, respectively. A strong correlation between liver T2 and T2* values was observed (r = 0.96, p < 0.001) with a bias (+4.1 ms). Mean cardiac bright- and dark-blood T2* values were 26.5 ± 12.9 ms and 27.2 ± 11.9 ms, respectively. Cardiac T2* values showed a strong correlation (r = 0.81, p < 0.001) with a low bias (-1.0 ms). The mean liver T2* on liver and cardiac MRIs were 4.9 ± 4.7 ms and 4.6 ± 3.9 ms, respectively. A strong correlation between T2* values was observed (r = 0.96, p < 0.001) with a small bias (-0.2 ms). CONCLUSION MRI protocols for iron concentration in the liver and the heart can be simplified to avoid redundant information and reduce scan time. In most patients, a single breath-hold GRE sequence can be used to evaluate the iron concentration in both the liver and heart.
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Affiliation(s)
- Christian A Barrera
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA.
| | - Hansel J Otero
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Helge D Hartung
- Department of Pediatrics, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - David M Biko
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Suraj D Serai
- Department of Radiology, The Children's Hospital of Philadelphia, 34th Street & Civic Center Boulevard, Philadelphia, PA 19104, USA
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Luntsi G, Eze CU. Reply to Comment on Sonographic Evaluation of Abdominal Organs in Sickle Cell Disease. J Med Ultrasound 2019; 26:227-228. [PMID: 30662159 PMCID: PMC6314095 DOI: 10.4103/jmu.jmu_67_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Affiliation(s)
- Geofery Luntsi
- Department of Medical Radiography, College of Medical Sciences, University of Maiduguri, Maiduguri, Borno State, Nigeria
| | - Charles Ugwoke Eze
- Department of Medical Radiography and Radiological Sciences, University of Nigeria, Enugu Campus, Enugu State, Nigeria
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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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16
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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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17
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Baranovicova E, Kantorova E, Kalenska D, Lichardusova L, Bittsan-sky M, Dobrota D. Thalamic paramagnetic iron by T2* relaxometry correlates with severity of multiple sclerosis. J Biomed Res 2017; 31:301-305. [PMID: 28808201 PMCID: PMC5548990 DOI: 10.7555/jbr.31.20160023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 12/03/2016] [Indexed: 11/03/2022] Open
Abstract
Iron can contribute to the pathogenesis and progression of multiple sclerosis (MS) due to its accumulation in the human brain. We focus on the thalamus as an information transmitter between various subcortical and cortical areas. Thalamic iron seems to follow different rules than iron in other deep gray matter structures and its relation to the clinical outcomes of MS is still indistinct. In our study, we investigated a connection between thalamic iron and patients' disability and course of the disease. The presence of paramagnetic substances in the tissues was tracked by T2* quantification. Twenty-eight subjects with definite MS and 15 age-matched healthy controls underwent MRI examination with a focus on gradient echo sequence. We observed a non-monotonous course of T2* values with age in healthy controls. Furthermore, T2* distribution in MS patients was significantly wider than that of age matched healthy volunteers (P<0.001). A strong significant correlation was demonstrated between T2* distribution spread and the expanded disability status scale (EDSS) (left thalamus:P<0.00005; right thalamus: P<0.005), and multiple sclerosis severity scale (MSSS) (left thalamus: P<0.05; right thalamus: P<0.005). The paramagnetic iron distribution in the thalamus in MS was not uniform and this inhomogeneity may be considered as an indicator of thalamic neurodegeneration in MS.
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Affiliation(s)
- Eva Baranovicova
- . Biomedical Centre BioMed, Division of Neuroscience, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 03601 Martin, Slovakia
| | - Ema Kantorova
- . Neurology Clinic, Jessenius Faculty of Medicine, Comenius University in Bratislava, Kollarova 2, 03601 Martin, Slovakia
| | - Dagmar Kalenska
- . Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 03601 Martin, Slovakia
| | - Lucia Lichardusova
- . Biomedical Centre BioMed, Division of Neuroscience, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 03601 Martin, Slovakia
| | - Michal Bittsan-sky
- . Biomedical Centre BioMed, Division of Neuroscience, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 03601 Martin, Slovakia
| | - Dusan Dobrota
- . Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 03601 Martin, Slovakia
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18
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Deistung A, Schweser F, Reichenbach JR. Overview of quantitative susceptibility mapping. NMR IN BIOMEDICINE 2017; 30:e3569. [PMID: 27434134 DOI: 10.1002/nbm.3569] [Citation(s) in RCA: 167] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 05/03/2016] [Accepted: 05/09/2016] [Indexed: 06/06/2023]
Abstract
Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Andreas Deistung
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, NY, USA
- MRI Clinical and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, NY, USA
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany
- Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University Jena, Jena, Germany
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Abstract
Absolute or functional iron (Fe) deficiency is an important determinant of anemia in hemodialysis patients and parenteral Fe is routinely used to treat this condition in conjunction with erythropoiesis stimulating agents. While restoration of hemoglobin toward the target range is a good outcome of Fe replacement, it is well known that Fe overload and toxicity may be adverse consequences of this therapy. Dialysis clinical practice guidelines recommend tailoring Fe therapy based on transferrin saturation and serum ferritin levels. Unfortunately, serum Fe markers may not accurately reflect the amount of Fe in the body, because factors such as infections, inflammation, or malignancy can alter serum ferritin levels. Some recent trials in dialysis patients receiving high intravenous Fe doses have shown increased cardiovascular morbidity and mortality and studies using magnetic resonance imaging (MRI) in this population have shown excessive tissue liver iron content (LIC) suggesting Fe overload. While LIC measured by MRI correlates well with LIC quantitated by liver biopsy, it only represents a surrogate marker for total body Fe and its clinical relevance in dialysis patients in terms of mortality and morbidity remains to be demonstrated. Nevertheless, these recent findings challenge the use of current serum Fe markers recommended by clinical guidelines to guide safe Fe therapy in dialysis patients. While not yet established for the routine screening of dialysis patients for Fe overload, MRI should be considered in patients who have received a high cumulative dose of intravenous Fe, or have long cumulative dialysis vintage. Further studies are needed to assess how MRI will alter management.
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Affiliation(s)
- Ganesh Ramanathan
- Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - John K Olynyk
- Department of Gastroenterology, Fiona Stanley and Fremantle Hospitals, Perth, Western Australia, Australia.,School of Veterinary Sciences, Murdoch University, Perth, Western Australia, Australia.,School of Biomedical Sciences and Curtin Health Innovation Research Institute, Curtin University, Perth, Western Australia, Australia.,Faculty of Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
| | - Paolo Ferrari
- Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia.,Clinical School, University of New South Wales, Sydney, New South Wales, Australia
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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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21
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Porter JB, Elalfy M, Taher A, Aydinok Y, Lee SH, Sutcharitchan P, El-Ali A, Han J, El-Beshlawy A. Limitations of serum ferritin to predict liver iron concentration responses to deferasirox therapy in patients with transfusion-dependent thalassaemia. Eur J Haematol 2017; 98:280-288. [PMID: 27859648 DOI: 10.1111/ejh.12830] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/11/2016] [Indexed: 01/02/2023]
Abstract
BACKGROUND In transfusion-dependent anaemias, while absolute serum ferritin levels broadly correlate with liver iron concentration (LIC), relationships between trends in these variables are unclear. These relationships are important because serum ferritin changes are often used to adjust or switch chelation regimens when liver magnetic resonance imaging (MRI) is unavailable. OBJECTIVES AND METHODS This post hoc analysis of the EPIC study compared serum ferritin and LIC in 317 patients with transfusion-dependent thalassaemia before and after 1 yr of deferasirox. RESULTS Serum ferritin responses (decreases) occurred in 73% of patients, 80% of whom also have decreased LIC. However, 52% of patients without a serum ferritin response did decrease LIC and by >1 mg Fe/g dw (median 3.9) in 77% of cases. Absolute serum ferritin and LIC values correlated significantly only when serum ferritin was <4000 ng/mL (r = 0.59; P < 0.0001) and not at higher levels (≥4000 ng/mL; r = 0.19). Serum ferritin response was accompanied by decreased LIC in 89% and 70% of cases when serum ferritin was <4000 or ≥4000 ng/mL, respectively. CONCLUSIONS As serum ferritin non-response was associated with LIC decrease in over half of patients, use of liver MRI may be particularly useful for differentiating true from apparent non-responders to deferasirox based on serum ferritin trends alone.
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Affiliation(s)
- John B Porter
- Department of Haematology, University College London, London, UK
| | - Mohsen Elalfy
- Thalassemia Center, Children's Hospital, Ain Shams University, Cairo, Egypt
| | - Ali Taher
- Department of Internal Medicine, American University of Beirut, Beirut, Lebanon
| | - Yesim Aydinok
- Department of Pediatric Hematology, Ege University Hospital, Izmir, Turkey
| | - Szu-Hee Lee
- Department of Haematology, St George Hospital, Sydney, NSW, Australia
| | - Pranee Sutcharitchan
- Division of Haematology, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | | | - Jackie Han
- Novartis Pharmaceuticals, East Hanover, NJ, USA
| | - Amal El-Beshlawy
- Hematology Department, Pediatric Hospital, Cairo University, Cairo, Egypt
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22
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Holman R, Olynyk JK, Kulkarni H, Ferrari P. Characterization of hepatic and cardiac iron deposition during standard treatment of anaemia in haemodialysis. Nephrology (Carlton) 2017; 22:114-117. [DOI: 10.1111/nep.12735] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2015] [Revised: 01/04/2016] [Accepted: 01/22/2016] [Indexed: 11/28/2022]
Affiliation(s)
- Richard Holman
- Department of Gastroenterology and Hepatology; Fiona Stanley Hospital; Murdoch Western Australia Australia
| | - John K. Olynyk
- Department of Gastroenterology and Hepatology; Fiona Stanley Hospital; Murdoch Western Australia Australia
- School of Veterinary and Life Sciences; Murdoch University, Murdoch and School of Biomedical Sciences; Bentley Western Australia
- Curtin Health Innovation Research Institute; Curtin University; Bentley Western Australia
| | - Hemant Kulkarni
- Department of Nephrology; Fremantle Hospital; Perth Western Australia
| | - Paolo Ferrari
- Department of Nephrology and Transplantation; Prince of Wales Hospital; Sydney New South Wales Australia
- Clinical School; University of New South Wales; Sydney New South Wales Australia
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23
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St. Pierre TG, House MJ, Bangma SJ, Pang W, Bathgate A, Gan EK, Ayonrinde OT, Bhathal PS, Clouston A, Olynyk JK, Adams LA. Stereological Analysis of Liver Biopsy Histology Sections as a Reference Standard for Validating Non-Invasive Liver Fat Fraction Measurements by MRI. PLoS One 2016; 11:e0160789. [PMID: 27501242 PMCID: PMC4976876 DOI: 10.1371/journal.pone.0160789] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 07/25/2016] [Indexed: 12/12/2022] Open
Abstract
Background and Aims Validation of non-invasive methods of liver fat quantification requires a reference standard. However, using standard histopathology assessment of liver biopsies is problematical because of poor repeatability. We aimed to assess a stereological method of measuring volumetric liver fat fraction (VLFF) in liver biopsies and to use the method to validate a magnetic resonance imaging method for measurement of VLFF. Methods VLFFs were measured in 59 subjects (1) by three independent analysts using a stereological point counting technique combined with the Delesse principle on liver biopsy histological sections and (2) by three independent analysts using the HepaFat-Scan® technique on magnetic resonance images of the liver. Bland Altman statistics and intraclass correlation (IC) were used to assess the repeatability of each method and the bias between the methods of liver fat fraction measurement. Results Inter-analyst repeatability coefficients for the stereology and HepaFat-Scan® methods were 8.2 (95% CI 7.7–8.8)% and 2.4 (95% CI 2.2–2.5)% VLFF respectively. IC coefficients were 0.86 (95% CI 0.69–0.93) and 0.990 (95% CI 0.985–0.994) respectively. Small biases (≤3.4%) were observable between two pairs of analysts using stereology while no significant biases were observable between any of the three pairs of analysts using HepaFat-Scan®. A bias of 1.4±0.5% VLFF was observed between the HepaFat-Scan® method and the stereological method. Conclusions Repeatability of the stereological method is superior to the previously reported performance of assessment of hepatic steatosis by histopathologists and is a suitable reference standard for validating non-invasive methods of measurement of VLFF.
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Affiliation(s)
- Tim G. St. Pierre
- School of Physics, The University of Western Australia, Crawley, Western Australia, Australia
- * E-mail:
| | - Michael J. House
- School of Physics, The University of Western Australia, Crawley, Western Australia, Australia
- Resonance Health Ltd, Claremont, Western Australia, Australia
| | | | - Wenjie Pang
- Resonance Health Ltd, Claremont, Western Australia, Australia
| | - Andrew Bathgate
- Resonance Health Ltd, Claremont, Western Australia, Australia
| | - Eng K. Gan
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Gastroenterology, Fremantle Hospital, Fremantle, Western Australia, Australia
| | - Oyekoya T. Ayonrinde
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Gastroenterology, Fremantle Hospital, Fremantle, Western Australia, Australia
- Faculty of Health Sciences, Curtin University of Technology, Bentley, Western Australia, Australia
| | - Prithi S. Bhathal
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Andrew Clouston
- Centre for Liver Disease Research, School of Medicine Translational Research Institute, The University of Queensland, Woolloongabba, Queensland, Australia
| | - John K. Olynyk
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Gastroenterology, Fremantle Hospital, Fremantle, Western Australia, Australia
- Faculty of Health Sciences, Curtin University of Technology, Bentley, Western Australia, Australia
- Institute for Immunology & Infectious Diseases, Murdoch University, Murdoch, Western Australia, Australia
| | - Leon A. Adams
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
- Liver Transplant Unit, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
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Yang JCT, Lu MY, Jaw FS, Peng SSF, Shih TTF. Breath-hold spin echosequence for assessing liver iron content. Magn Reson Imaging 2016; 34:1256-1263. [PMID: 27451406 DOI: 10.1016/j.mri.2016.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 05/05/2016] [Accepted: 07/17/2016] [Indexed: 10/21/2022]
Abstract
OBJECTIVE To compare a multiple breath-hold, multiecho, multiplanar spin-echo (BHMEMPSE) magnetic resonance (MR) sequence with a TR of 300ms with a traditional multiecho, multiplanar spin-echo (MEMPSE) MR sequence for assessing liver iron content. MATERIALS AND METHODS This study was approved by the institutional review board; informed consent was waived. Liver R2 measurement was derived from the mono-exponential model by BHMEMPSE and MEMPSE MR sequences of a 1.5T MR machine in 30 thalassemia patients (9men, 21women, aged 27.7±6.8years). Hepatic iron contents were estimated using Ferriscan in all patients. The inter- and intra-observer agreement of the 2 MR sequences was also evaluated. RESULTS MEMPSE R2 values significantly correlated with Ferriscan iron content values (r=0.895, p<0.001) and serum ferritin concentration (r=0.661, p<0.001). BHMEMPSE R2 values significantly correlated with Ferriscan values (r=0.914, p<0.001) and serum ferritin concentration (r=0.608, p<0.001). The distribution of MEMPSE R2 values against BHMEMPSE R2 values revealed an excellent linear relationship (r=0.978, p<0.001). The inter- and intra-observer agreement of the 2 MR sequences was excellent, with an interclass correlation coefficient exceeding 0.9. The distribution of Ferriscan against BHMEMPSE R2 values revealed a curvilinear relationship (r=0.935, p<0.001). CONCLUSIONS The BHMEMPSE sequence exhibited comparable estimation for assessing liver iron content, comparable repeatability and a shorter acquisition time compared with the MEMPSE sequence. The BHMEMPSE sequence can serve as an adjunctive sequence to assess liver iron content.
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Affiliation(s)
- Justin Cheng-Ta Yang
- Institute of Biomedical Engineering, College of Engineering and the College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Department of Radiology, National Taiwan University Hospital, Chu-Tung Branch, Hsinchu, Taiwan; Department of Radiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Meng-Yao Lu
- Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
| | - Fu-Shan Jaw
- Institute of Biomedical Engineering, College of Engineering and the College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Steven Shinn-Forng Peng
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Department of Radiology, National Taiwan University College of Medicine, Taipei, Taiwan.
| | - Tiffany Ting-Fang Shih
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Department of Radiology, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Medical Imaging, Taipei City Hospital, Taipei, Taiwan
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25
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Quinn CT, St Pierre TG. MRI Measurements of Iron Load in Transfusion-Dependent Patients: Implementation, Challenges, and Pitfalls. Pediatr Blood Cancer 2016; 63:773-80. [PMID: 26713769 PMCID: PMC5064750 DOI: 10.1002/pbc.25882] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Revised: 11/30/2015] [Accepted: 12/01/2015] [Indexed: 01/19/2023]
Abstract
Magnetic resonance imaging (MRI) has played a key role in studies of iron overload in transfusion-dependent patients, providing insights into the relations among liver and cardiac iron loading, iron chelator dose, and morbidity. Currently, there is rapid uptake of these methods into routine clinical practice as part of the management strategy for iron overload in regularly transfused patients. Given the manifold methods of data acquisition and analysis, there are several potential pitfalls that may result in inappropriate decision making. Herein, we review the challenges of establishing suitable MRI techniques for tissue iron measurement in regularly transfused patients.
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Affiliation(s)
- Charles T. Quinn
- Division of HematologyCincinnati Children's Hospital Medical CenterCincinnatiOhio
| | - Tim G. St Pierre
- School of PhysicsThe University of Western AustraliaCrawleyAustralia
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26
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Perihematomal Cerebral Tissue Iron Quantification on MRI Following Intracerebral Hemorrhage in Two Human Subjects: Proof of Principle. ACTA NEUROCHIRURGICA SUPPLEMENT 2016; 121:179-83. [DOI: 10.1007/978-3-319-18497-5_32] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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27
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Milford D, Rosbach N, Bendszus M, Heiland S. Mono-Exponential Fitting in T2-Relaxometry: Relevance of Offset and First Echo. PLoS One 2015; 10:e0145255. [PMID: 26678918 PMCID: PMC4683054 DOI: 10.1371/journal.pone.0145255] [Citation(s) in RCA: 74] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 11/30/2015] [Indexed: 11/18/2022] Open
Abstract
INTRODUCTION T2 relaxometry has become an important tool in quantitative MRI. Little focus has been put on the effect of the refocusing flip angle upon the offset parameter, which was introduced to account for a signal floor due to noise or to long T2 components. The aim of this study was to show that B1 imperfections contribute significantly to the offset. We further introduce a simple method to reduce the systematic error in T2 by discarding the first echo and using the offset fitting approach. MATERIALS AND METHODS Signal curves of T2 relaxometry were simulated based on extended phase graph theory and evaluated for 4 different methods (inclusion and exclusion of the first echo, while fitting with and without the offset). We further performed T2 relaxometry in a phantom at 9.4T magnetic resonance imaging scanner and used the same methods for post-processing as in the extended phase graph simulated data. Single spin echo sequences were used to determine the correct T2 time. RESULTS The simulation data showed that the systematic error in T2 and the offset depends on the refocusing pulse, the echo spacing and the echo train length. The systematic error could be reduced by discarding the first echo. Further reduction of the systematic T2 error was reached by using the offset as fitting parameter. The phantom experiments confirmed these findings. CONCLUSION The fitted offset parameter in T2 relaxometry is influenced by imperfect refocusing pulses. Using the offset as a fitting parameter and discarding the first echo is a fast and easy method to minimize the error in T2, particularly for low to intermediate echo train length.
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Affiliation(s)
- David Milford
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany
- * E-mail:
| | - Nicolas Rosbach
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany
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28
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Gutiérrez L, House MJ, Vasavda N, Drašar E, Gonzalez-Gascon y Marin I, Kulasekararaj AG, St Pierre TG, Thein SL. Tissue Iron Distribution Assessed by MRI in Patients with Iron Loading Anemias. PLoS One 2015; 10:e0139220. [PMID: 26406992 PMCID: PMC4583270 DOI: 10.1371/journal.pone.0139220] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Accepted: 09/09/2015] [Indexed: 12/31/2022] Open
Abstract
Bone marrow, spleen, liver and kidney proton transverse relaxation rates (R2), together with cardiac R2* from patients with sickle cell disease (SCD), paroxysmal nocturnal hemoglobinuria (PNH) and non-transfusion dependent thalassemia (NTDT) have been compared with a control group. Increased liver and bone marrow R2 values for the three groups of patients in comparison with the controls have been found. SCD and PNH patients also present an increased spleen R2 in comparison with the controls. The simultaneous measurement of R2 values for several tissue types by magnetic resonance imaging (MRI) has allowed the identification of iron distribution patterns in diseases associated with iron imbalance. Preferential liver iron loading is found in the highly transfused SCD patients, while the low transfused ones present a preferential iron loading of the spleen. Similar to the highly transfused SCD group, PNH patients preferentially accumulate iron in the liver. A reduced spleen iron accumulation in comparison with the liver and bone marrow loading has been found in NTDT patients, presumably related to the differential increased intestinal iron absorption. The correlation between serum ferritin and tissue R2 is moderate to good for the liver, spleen and bone marrow in SCD and PNH patients. However, serum ferritin does not correlate with NTDT liver R2, spleen R2 or heart R2*. As opposed to serum ferritin measurements, tissue R2 values are a more direct measurement of each tissue's iron loading. This kind of determination will allow a better understanding of the different patterns of tissue iron biodistribution in diseases predisposed to tissue iron accumulation.
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Affiliation(s)
- Lucía Gutiérrez
- Instituto de Ciencia de Materiales de Madrid, ICMM-CSIC, Cantoblanco, Madrid, Spain
- School of Physics, The University of Western Australia, Crawley, WA, Australia
- * E-mail:
| | - Michael J. House
- School of Physics, The University of Western Australia, Crawley, WA, Australia
| | - Nisha Vasavda
- King’s College London, Faculty of Life Sciences & Medicine, Molecular Haematology, London, United Kingdom
| | - Emma Drašar
- King’s College London, Faculty of Life Sciences & Medicine, Molecular Haematology, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, Department of Haematology, London, United Kingdom
| | - Isabel Gonzalez-Gascon y Marin
- King’s College London, Faculty of Life Sciences & Medicine, Molecular Haematology, London, United Kingdom
- Hospital Infanta Leonor, Department of Haematology, Madrid, Spain
| | - Austin G. Kulasekararaj
- King’s College London, Faculty of Life Sciences & Medicine, Molecular Haematology, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, Department of Haematology, London, United Kingdom
| | - Tim G. St Pierre
- School of Physics, The University of Western Australia, Crawley, WA, Australia
| | - Swee L. Thein
- King’s College London, Faculty of Life Sciences & Medicine, Molecular Haematology, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, Department of Haematology, London, United Kingdom
- NHLB/ NIH, Sickle Cell Branch, Bethesda, MD 20892, United States of America
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Wood JC, Pressel S, Rogers ZR, Odame I, Kwiatkowski JL, Lee MT, Owen WC, Cohen AR, St. Pierre T, Heeney MM, Schultz WH, Davis BR, Ware RE. Liver iron concentration measurements by MRI in chronically transfused children with sickle cell anemia: baseline results from the TWiTCH trial. Am J Hematol 2015; 90:806-10. [PMID: 26087998 DOI: 10.1002/ajh.24089] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 06/10/2015] [Accepted: 06/12/2015] [Indexed: 01/19/2023]
Abstract
Noninvasive, quantitative, and accurate assessment of liver iron concentration (LIC) by MRI is useful for patients receiving transfusions, but R2 and R2* MRI techniques have not been systematically compared in sickle cell anemia (SCA). We report baseline LIC results from the TWiTCH trial, which compares hydroxyurea with blood transfusion treatment for primary stroke prophylaxis assessed by transcranial Doppler sonography in pediatric SCA patients. Liver R2 was collected and processed using a FDA-approved commercial process (FerriScan®), while liver R2* quality control and processing were performed by a Core Laboratory blinded to clinical site and patient data. Baseline LIC studies using both MRI techniques were available for 120 participants. LICR2* and LICR2 results were highly correlated (r(2) = 0.93). A proportional bias of LIC(R2*)/LIC(R2), decreasing with average LIC, was observed. Systematic differences between LICR2* and LICR2 were also observed by MRI manufacturer. Importantly, LICR2* and LICR2 estimates had broad 95% limits of agreement with respect to each other. We recommend LICR2 and LICR2* not be used interchangeably in SCA patients to follow individual patient trends in iron burden.
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Affiliation(s)
- John C. Wood
- Children's Hospital Los Angeles; Los Angeles California
| | - Sara Pressel
- The University of Texas Health Science Center; Houston Texas
| | - Zora R. Rogers
- University of Texas Southwestern Medical Center; Dallas Texas
| | - Isaac Odame
- Division of Haematology/Oncology, University of Toronto, The Hospital for Sick Children; Toronto Canada
| | | | | | - William C. Owen
- Children's Hospital of the King's Daughters; Norfolk Virginia
| | - Alan R. Cohen
- School of Physics; University of Western Australia; Crawley Australia
| | | | | | | | - Barry R. Davis
- The University of Texas Health Science Center; Houston Texas
| | - Russell E. Ware
- Cincinnati Children's Hospital Medical Center; Cincinnati Ohio
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30
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Hoad CL, Palaniyappan N, Kaye P, Chernova Y, James MW, Costigan C, Austin A, Marciani L, Gowland PA, Guha IN, Francis ST, Aithal GP. A study of T₁ relaxation time as a measure of liver fibrosis and the influence of confounding histological factors. NMR IN BIOMEDICINE 2015; 28:706-14. [PMID: 25908098 DOI: 10.1002/nbm.3299] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Revised: 03/04/2015] [Accepted: 03/11/2015] [Indexed: 05/25/2023]
Abstract
Liver biopsy is the standard test for the assessment of fibrosis in liver tissue of patients with chronic liver disease. Recent studies have used a non-invasive measure of T1 relaxation time to estimate the degree of fibrosis in a single slice of the liver. Here, we extend this work to measure T1 of the whole liver and investigate the effects of additional histological factors such as steatosis, inflammation and iron accumulation on the relationship between liver T1 and fibrosis. We prospectively enrolled patients who had previously undergone liver biopsy to have MR scans. A non-breath-holding, fast scanning protocol was used to acquire MR relaxation time data (T1 and T2*), and blood serum was used to determine the enhanced liver fibrosis (ELF) score. Areas under the receiver operator curves (AUROCs) for T1 to detect advanced fibrosis and cirrhosis were derived in a training cohort and then validated in a second cohort. Combining the cohorts, the influence of various histology factors on liver T1 relaxation time was investigated. The AUROCs (95% confidence interval (CI)) for detecting advanced fibrosis (F ≥ 3) and cirrhosis (F = 4) for the training cohort were 0.81 (0.65-0.96) and 0.92 (0.81-1.0) respectively (p < 0.01). Inflammation and iron accumulation were shown to significantly alter T1 in opposing directions in the absence of advanced fibrosis; inflammation increasing T1 and iron decreasing T1. A decision tree model was developed to allow the assessment of early liver disease based on relaxation times and ELF, and to screen for the need for biopsy. T1 relaxation time increases with advanced fibrosis in liver patients, but is also influenced by iron accumulation and inflammation. Together with ELF, relaxation time measures provide a marker to stratify patients with suspected liver disease for biopsy.
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Affiliation(s)
- Caroline L Hoad
- SPMIC, School of Physics and Astronomy, University of Nottingham, UK
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
| | - Naaventhan Palaniyappan
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
| | - Philip Kaye
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
- Department of Cellular Pathology, Nottingham University Hospitals NHS Trust, UK
| | - Yulia Chernova
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
| | - Martin W James
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
| | - Carolyn Costigan
- SPMIC, School of Physics and Astronomy, University of Nottingham, UK
| | | | - Luca Marciani
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
| | - Penny A Gowland
- SPMIC, School of Physics and Astronomy, University of Nottingham, UK
| | - Indra N Guha
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
| | - Susan T Francis
- SPMIC, School of Physics and Astronomy, University of Nottingham, UK
| | - Guruprasad P Aithal
- NIHR Nottingham Digestive Diseases Biomedical Research Unit at the Nottingham University Hospitals NHS Trust and University of Nottingham, UK
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31
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Alexiou E. Methodologies and Tools Used Today for Measuring Iron Load. THALASSEMIA REPORTS 2014. [DOI: 10.4081/thal.2014.4861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Iron overload is a matter of an extreme clinical importance, in the overall management of Thalassaemia. Magnetic Resonance Imaging (MRI), has evolved in a novel tool for iron quantification during the last decade and it is considered as a validated, accurate and noninvasive method with worldwide distribution. The MRI scanner exploits the intrinsic magnetic properties of the hydrogen nuclei in order to discriminate the tissue characteristics. The presence of iron in a tissue causes a faster dephasing of the protons and a reduction in T2* and T2. R2 and R2* represent the reciprocal of T2 and T2*. In order to measure the signal intensity and quantify iron concentration the Gradient Echo (GRE) T2* and the Spin Echo (SE) T2 sequence are used. There are two broad groups of techniques to quantify the iron. The signal intensity ratio (SIR) methods and the relaxometry methods. The later are sub grouped in the R2 (T2) relaxometry methods with the predominant of this category being the FerriScan® and the R2* (T2*) methods. CMR Gradient Echo T2* pulse sequence is the preferred technique for the quantification of iron in the heart. The R2 and R2* methodologies are both very accurate in predicting the true LIC with high levels of sensitivity and specificity in the range of clinically important LIC thresholds and can be both used over a wide clinical range, individually.
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Sharma SD, Hernando D, Horng DE, Reeder SB. Quantitative susceptibility mapping in the abdomen as an imaging biomarker of hepatic iron overload. Magn Reson Med 2014; 74:673-83. [PMID: 25199788 DOI: 10.1002/mrm.25448] [Citation(s) in RCA: 84] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Revised: 08/19/2014] [Accepted: 08/20/2014] [Indexed: 01/19/2023]
Abstract
PURPOSE The purpose of this work was to develop and demonstrate feasibility and initial clinical validation of quantitative susceptibility mapping (QSM) in the abdomen as an imaging biomarker of hepatic iron overload. THEORY AND METHODS In general, QSM is faced with the challenges of background field removal and dipole inversion. Respiratory motion, the presence of fat, and severe iron overload further complicate QSM in the abdomen. We propose a technique for QSM in the abdomen that addresses these challenges. Data were acquired from 10 subjects without hepatic iron overload and 33 subjects with known or suspected iron overload. The proposed technique was used to estimate the susceptibility map in the abdomen, from which hepatic iron overload was measured. As a reference, spin-echo data were acquired for R2-based LIC estimation. Liver R2* was measured for correlation with liver susceptibility estimates. RESULTS Correlation between susceptibility and R2-based LIC estimation was R(2) = 0.76 at 1.5 Tesla (T) and R(2) = 0.83 at 3T. Furthermore, high correlation between liver susceptibility and liver R2* (R(2) = 0.94 at 1.5T; R(2) = 0.93 at 3T) was observed. CONCLUSION We have developed and demonstrated initial validation of QSM in the abdomen as an imaging biomarker of hepatic iron overload.
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Affiliation(s)
- Samir D Sharma
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - Debra E Horng
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
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Hocq A, Luhmer M, Saussez S, Louryan S, Gillis P, Gossuin Y. Effect of magnetic field and iron content on NMR proton relaxation of liver, spleen and brain tissues. CONTRAST MEDIA & MOLECULAR IMAGING 2014; 10:144-52. [PMID: 24954138 DOI: 10.1002/cmmi.1610] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2014] [Revised: 05/02/2014] [Accepted: 05/22/2014] [Indexed: 12/13/2022]
Abstract
Iron accumulation is observed in liver and spleen during hemochromatosis and important neurodegenerative diseases involve iron overload in brain. Storage of iron is ensured by ferritin, which contains a magnetic core. It causes a darkening on T2 -weighted MR images. This work aims at improving the understanding of the NMR relaxation of iron-loaded human tissues, which is necessary to develop protocols of iron content measurements by MRI. Relaxation times measurements on brain, liver and spleen samples were realized at different magnetic fields. Iron content was determined by atomic emission spectroscopy. For all samples, the longitudinal relaxation rate (1/T1 ) of tissue protons decreases with the magnetic field up to 1 T, independently of iron content, while their transverse relaxation rate (1/T2 ) strongly increases with the field, either linearly or quadratically, or a combination thereof. The extent of the inter-echo time dependence of 1/T2 also varies according to the sample. A combination of theoretical models is necessary to describe the relaxation of iron-containing tissues. This can be due to the presence, inside tissues, of ferritin clusters of different sizes and densities. When considering all samples, a correlation (r(2) = 0.6) between 1/T1 and iron concentration is observed at 7.0 T. In contrast the correlation between 1/T2 and iron content is poor, even at high field (r(2) = 0.14 at 7.0 T). Our results show that MRI methods based on T1 or T2 measurements will easily detect an iron overloading at high magnetic field, but will not provide an accurate quantification of tissue iron content at low iron concentrations.
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Affiliation(s)
- Aline Hocq
- Biomedical Physics Department, UMONS, 7000, Mons, Belgium
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Wood JC, Zhang P, Rienhoff H, Abi-Saab W, Neufeld E. R2 and R2* are equally effective in evaluating chronic response to iron chelation. Am J Hematol 2014; 89:505-8. [PMID: 24452753 DOI: 10.1002/ajh.23673] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2013] [Revised: 01/14/2014] [Accepted: 01/16/2014] [Indexed: 01/19/2023]
Abstract
MRI relaxometry (R2, R2*) has generally replaced liver biopsy for estimation of liver iron stores in response to iron chelation, but there have been no longitudinal studies comparing R2 and R2* techniques. We use R2 and R2* liver iron concentration (LIC) estimates, transfusional iron burdens, and drug compliance data to calculate iron chelation efficiency (ICE) in patients undergoing a Phase II trial of SPD602. Fifty-one patients underwent a baseline examination, 39 patients completed 1 year, and 26 patients completed 2 years. Baseline LICR2 and LICR2* estimates were unbiased, but had limits of agreement exceeding 50%, suggesting that these techniques cannot be interchanged with one another in the same patient. However, ICE estimates across the two techniques compared more favorably, with r(2) values reaching 0.89 at 2 years. 95 confidence intervals for efficiency estimates were 0.0 ± 4.1%. These data indicate that clinical trial and clinical effectiveness data calculated using LICR2 and LICR2* estimates can be compared to one another, even though LIC estimates may be disparate on cross-sectional analysis. While the choice of MRI assessment technique for clinical trials and for clinical management depends on many logistical considerations, one can have confidence comparing conclusions on clinical effectiveness.
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Affiliation(s)
- John C. Wood
- Department of Pediatrics and Radiology; Children's Hospital; Los Angeles California
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Brown GC, Patton WN, Tapp HE, Taylor DJ, St Pierre TG. Spin density projection-assisted R2 magnetic resonance imaging of the liver in the management of body iron stores in patients receiving multiple red blood cell transfusions: an audit and retrospective study in South Australia. Intern Med J 2014; 42:990-6. [PMID: 22647084 DOI: 10.1111/j.1445-5994.2012.02845.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
AIM To assess the impact of non-invasive monitoring of liver iron concentration (LIC) on management of body iron stores in patients receiving multiple blood transfusions. METHOD A retrospective audit was conducted on clinical data from 40 consecutive subjects with haemolytic anaemias or ineffective haematopoiesis who had been monitored non-invasively for LIC over a period of at least 1 year. LIC was measured with spin density projection-assisted proton transverse relaxation rate-magnetic resonance imaging. RESULTS Nineteen clinical decisions were explicitly documented in the case notes as being based on LIC results. Decisions comprised initiation of chelation therapy, increasing chelator dose, decreasing chelator dose and change of mode of delivery of deferioxamine from subcutaneous to intravenous. The geometrical mean LIC for the cohort dropped significantly (P= 0.008) from 6.8 mg Fe/g dry tissue at initial measurement to 4.8 mg Fe/g dry tissue at final measurement. The proportion of subjects with LIC in the range associated with greatly increased risk of cardiac disease and death (>15 mg Fe/g dry tissue) dropped significantly (P= 0.01) from 14 of 40 subjects at initial measurement to 5 of 40 subjects at final measurement. No significant changes in the geometrical mean of serum ferritin or the proportion of subjects with serum ferritin above 2500 or 1500 µg/L were observed. CONCLUSIONS The data are consistent with previous observations that introduction of non-invasive monitoring of LIC can contribute to a decreased body iron burden through improved clinical decision making and improved feedback to patients and hence improved adherence to chelation therapy.
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Wang C, He T, Liu X, Zhong S, Chen W, Feng Y. Rapid look-up table method for noise-corrected curve fitting in the R2* mapping of iron loaded liver. Magn Reson Med 2014; 73:865-71. [PMID: 24706563 DOI: 10.1002/mrm.25184] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Revised: 01/24/2014] [Accepted: 01/27/2014] [Indexed: 12/22/2022]
Abstract
PURPOSE Fitting the measured decay signal to the first moment in the presence of noncentral chi noise (M(1) NCM) can correctly address the effect of noise on the effective transverse relaxation rate (R2*) relaxometry of iron loaded liver. However, this method requires intensive computation, which restricts its application to R2* mapping. This work aims to develop a rapid implementation of the M(1) NCM method for R2* mapping. METHODS The computation of the confluent hypergeometric function in the M(1) NCM model was approximated using cubic spline interpolation with breakpoints and coefficients precalculated and stored in a look-up table (M(1) NCM-LUT). The performance of the proposed M(1) NCM-LUT method was evaluated through simulation and based on in vivo liver R2* relaxometry data. RESULTS In both simulation and in vivo studies, the maximum absolute difference between R2* maps generated by the M(1) NCM and M(1) NCM-LUT methods was nearly 10(-3) s(-1) or less, and the M(1) NCM-LUT method obtained a R2* map in approximately 1 s and achieved an acceleration of approximately five orders of magnitude. CONCLUSION The proposed M(1) NCM-LUT method can significantly increase the speed of the liver R2* mapping using the M(1) NCM model. This development is important in promoting application of this R2* mapping technique for tissue iron quantification.
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Affiliation(s)
- Changqing Wang
- School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China; School of Biomedical Engineering, Southern Medical University, Guangzhou, China
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Abstract
Liver fat, iron, and combined overload are common manifestations of diffuse liver disease and may cause lipotoxicity and iron toxicity via oxidative hepatocellular injury, leading to progressive fibrosis, cirrhosis, and eventually, liver failure. Intracellular fat and iron cause characteristic changes in the tissue magnetic properties in predictable dose-dependent manners. Using dedicated magnetic resonance pulse sequences and postprocessing algorithms, fat and iron can be objectively quantified on a continuous scale. In this article, we will describe the basic physical principles of magnetic resonance fat and iron quantification and review the imaging techniques of the "past, present, and future." Standardized radiological metrics of fat and iron are introduced for numerical reporting of overload severity, which can be used toward objective diagnosis, grading, and longitudinal disease monitoring. These noninvasive imaging techniques serve an alternative or complimentary role to invasive liver biopsy. Commercial solutions are increasingly available, and liver fat and iron quantitative imaging is now within reach for routine clinical use and may soon become standard of care.
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Affiliation(s)
- Takeshi Yokoo
- From the *Department of Radiology, †Advanced Imaging Research Center, and ‡Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX
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Hernando D, Levin YS, Sirlin CB, Reeder SB. Quantification of liver iron with MRI: state of the art and remaining challenges. J Magn Reson Imaging 2014; 40:1003-21. [PMID: 24585403 DOI: 10.1002/jmri.24584] [Citation(s) in RCA: 178] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2013] [Accepted: 01/14/2014] [Indexed: 12/11/2022] Open
Abstract
Liver iron overload is the histological hallmark of hereditary hemochromatosis and transfusional hemosiderosis, and can also occur in chronic hepatopathies. Iron overload can result in liver damage, with the eventual development of cirrhosis, liver failure, and hepatocellular carcinoma. Assessment of liver iron levels is necessary for detection and quantitative staging of iron overload and monitoring of iron-reducing treatments. This article discusses the need for noninvasive assessment of liver iron and reviews qualitative and quantitative methods with a particular emphasis on magnetic resonance imaging (MRI). Specific MRI methods for liver iron quantification include signal intensity ratio as well as R2 and R2* relaxometry techniques. Methods that are in clinical use, as well as their limitations, are described. Remaining challenges, unsolved problems, and emerging techniques to provide improved characterization of liver iron deposition are discussed.
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Affiliation(s)
- Diego Hernando
- Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
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House MJ, Bangma SJ, Thomas M, Gan EK, Ayonrinde OT, Adams LA, Olynyk JK, St Pierre TG. Texture-based classification of liver fibrosis using MRI. J Magn Reson Imaging 2013; 41:322-8. [PMID: 24347292 DOI: 10.1002/jmri.24536] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2013] [Accepted: 11/15/2013] [Indexed: 12/23/2022] Open
Abstract
PURPOSE To investigate the ability of texture analysis of MRI images to stage liver fibrosis. Current noninvasive approaches for detecting liver fibrosis have limitations and cannot yet routinely replace biopsy for diagnosing significant fibrosis. MATERIALS AND METHODS Forty-nine patients with a range of liver diseases and biopsy-confirmed fibrosis were enrolled in the study. For texture analysis all patients were scanned with a T2 -weighted, high-resolution, spin echo sequence and Haralick texture features applied. The area under the receiver operating characteristics curve (AUROC) was used to assess the diagnostic performance of the texture analysis. RESULTS The best mean AUROC achieved for separating mild from severe fibrosis was 0.81. The inclusion of age, liver fat and liver R2 variables into the generalized linear model improved AUROC values for all comparisons, with the F0 versus F1-4 comparison the highest (0.91). CONCLUSION Our results suggest that a combination of MRI measures, that include selected texture features from T2 -weighted images, may be a useful tool for excluding fibrosis in patients with liver disease. However, texture analysis of MRI performs only modestly when applied to the classification of patients in the mild and intermediate fibrosis stages.
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Affiliation(s)
- Michael J House
- School of Physics, The University of Western Australia, Crawley, Western Australia, Australia
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Castiella A, Alústiza JM, Zapata E, Emparanza JI. Is MRI becoming the new gold standard for diagnosing iron overload in hemochromatosis and other liver iron disorders? ACTA ACUST UNITED AC 2013. [DOI: 10.2217/iim.13.60] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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Feng S, Chen D, Kushmerick M, Lee D. Multiparameter MRI analysis of the time course of induced muscle damage and regeneration. J Magn Reson Imaging 2013; 40:779-88. [PMID: 24923472 DOI: 10.1002/jmri.24417] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Accepted: 08/26/2013] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To test the ability of different magnetic resonance imaging (MRI) modalities to discriminate the time course of damage and regeneration in a model of acute, toxin-induced muscle damage. MATERIALS AND METHODS We analyzed the time course of tissue and cellular changes in mouse lower limb musculature following localized injection of myotoxin by T2 , magnetization transfer (MT), and diffusion-weighted MRI. We also used T1 -weighted imaging to measure leg muscle volume. In addition, postmortem histological analysis of toxin-injected muscles was compared to uninjected controls. RESULTS The damages detected by the MRI modalities are transient and recover within 3 weeks. Muscle water diffusivity and edema measured by leg volume increased within the first hours after injection of the toxin. The rate constant for volume increase was 0.65 ± 0.11 hr(-1) , larger than the increase in T2 (0.045 ± 0.013 hr(-1) ) and change in MT ratio (0.028 ± 0.021 hr(-1) ). During repair phase, the rate constants were much smaller: 0.022 ± 0.004 hr(-1) , 0.013 ± 0.0019 hr(-1) and 0.0042 ± 0.0016 hr(-1) for volume, T2 , and MT ratio, respectively. Histological analyses confirmed the underlying cellular changes that matched the progression of MR images. CONCLUSION The kinetics of change in the MRI measurements during the progression of damage and repair shows MRI modalities can be used to distinguish these processes.
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Affiliation(s)
- Shu Feng
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
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Feng Y, Feng M, Gao H, Zhang X, Xin X, Feng Q, Chen W, He T. A novel semiautomatic parenchyma extraction method for improved MRI R2* relaxometry of iron loaded liver. J Magn Reson Imaging 2013; 40:67-78. [PMID: 24677406 DOI: 10.1002/jmri.24331] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2013] [Accepted: 07/10/2013] [Indexed: 01/05/2023] Open
Abstract
PURPOSE To propose and evaluate an automatic method of extracting parenchyma from a manually delineated whole liver for the R2* measurement of iron load. MATERIALS AND METHODS In all, 108 transfusion-dependent patients with a wide range of hepatic iron content were scanned with a multiecho gradient-echo sequence. The R2* was measured by fitting the average signal of liver parenchyma, extracted by the proposed semiautomatic parenchyma extraction (SAPE), traditional manually delineated multiple regions-of-interest (mROIs), and T2* thresholding methods to the noise-corrected monoexponential model. The R2* measurement accuracy of the SAPE method was evaluated through simulation; the intra- and interobserver reproducibility of SAPE, mROI, and T2* thresholding were assessed from the in vivo data using coefficient of variation (CoV). RESULTS In the simulation, the mean absolute percentage error of R2* measurement using SAPE was 0.23% (range 0.01%-1.09%). In vivo study, the CoVs of intra- and interobserver reproducibility were 0.83%, 1.39% for SAPE, 3.63%, 6.28% for mROI, and 1.62%, 2.66% for T2* thresholding, respectively. CONCLUSION The SAPE method provides an accurate and reliable approach to assessing the overall hepatic iron content. The improved magnetic resonance imaging (MRI) R2* reproducibility using the SAPE method may lead to more accurate tissue characterization and increased diagnostic confidence.
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Affiliation(s)
- Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
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Chan WC, Tejani Z, Budhani F, Massey C, Haider MA. R2* as a surrogate measure of ferriscan iron quantification in thalassemia. J Magn Reson Imaging 2013; 39:1007-11. [PMID: 24123694 DOI: 10.1002/jmri.24216] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2012] [Accepted: 04/16/2013] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To determine whether R2* values are a consistent predictor of hepatic iron concentration (HIC) in thalassemia patients by demonstrating a correlation between R2* relaxation rates and FerriScan-determined HIC. MATERIALS AND METHODS Eighty-eight patients with thalassemia major were retrospectively evaluated. All patients underwent FerriScan imaging and multiecho gradient echo imaging. The results from FerriScan analysis were fitted against R2* estimates using linear regression. RESULTS There was a very strong linear correlation between R2* values and FerriScan-determined HIC (Spearman correlation of 0.976; 95% confidence interval [CI]: 0.963, 0.984). CONCLUSION R2* values can predict HIC determined by FerriScan using a linear calibration curve. This technique may provide a potentially cost-saving alternative for hepatic iron determination and improve acceptance by referring physicians.
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Affiliation(s)
- Wesley C Chan
- Department of Radiology, Health Sciences Centre, Memorial University, St. John's, NL, Canada
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Hernando D, Cook RJ, Diamond C, Reeder SB. Magnetic susceptibility as a B0 field strength independent MRI biomarker of liver iron overload. Magn Reson Med 2013; 70:648-56. [PMID: 23801540 PMCID: PMC3883906 DOI: 10.1002/mrm.24848] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2012] [Revised: 05/20/2013] [Accepted: 05/28/2013] [Indexed: 01/19/2023]
Abstract
PURPOSE MR-based quantification of liver magnetic susceptibility may enable field strength-independent measurement of liver iron concentration (LIC). However, susceptibility quantification is challenging, due to nonlocal effects of susceptibility on the B0 field. The purpose of this work is to demonstrate feasibility of susceptibility-based LIC quantification using a fat-referenced approach. METHODS Phantoms consisting of vials with increasing iron concentrations immersed between oil/water layers, and 27 subjects (9 controls/18 subjects with liver iron overload) were scanned. Ferriscan (1.5 T) provided R2-based reference LIC. Multiecho three-dimensional-SPGR (1.5 T/3 T) enabled fat-water, B0- and R2*-mapping. Phantom iron concentration (mg Fe L(-1)) was estimated from B0 differences (ΔB0) between vials and neighboring oil. Liver susceptibility and LIC (mg Fe g(-1) dry tissue) was estimated from ΔB0 between the lateral right lobe of the liver and adjacent subcutaneous adipose tissue. RESULTS Estimated phantom iron concentrations had good correlation with true iron concentrations (1.5 T:slope = 0.86, intercept = 0.72, r(2) = 0.98; 3 T:slope = 0.85, intercept = 1.73, r(2) = 0.98). In liver, ΔB0 correlated strongly with R2* (1.5 T:r(2) = 0.86; 3 T:r(2) = 0.93) and B0-LIC had good agreement with Ferriscan-LIC (slopes/intercepts nearly 1.0/0.0, 1.5 T:r(2) = 0.67, slope = 0.93 ± 0.13, P ≈ 0.50, intercept = 1.93 ± 0.78, P ≈ 0.02; 3 T:r(2) = 0.84, slope = 1.01 ± 0.09, P ≈ 0.90, intercept = 0.23 ± 0.52, P ≈ 0.68). DISCUSSION Fat-referenced, susceptibility-based LIC estimation is feasible at both field strengths. This approach may enable improved susceptibility mapping in the abdomen.
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Affiliation(s)
- Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
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Low prevalence of cardiac siderosis in heavily iron loaded Egyptian thalassemia major patients. Ann Hematol 2013; 93:375-9. [PMID: 23949317 DOI: 10.1007/s00277-013-1876-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2013] [Accepted: 08/04/2013] [Indexed: 01/19/2023]
Abstract
Myocardial siderosis in thalassemia major remains the leading cause of death in developing countries. Once heart failure develops, the outlook is usually poor with precipitous deterioration and death. Cardiovascular magnetic resonance (CMR) can measure cardiac iron deposition directly using the magnetic relaxation time T2*. This allows earlier diagnosis and treatment and helps to reduce mortality from this cardiac affection. This study aims to determine the prevalence of cardiac siderosis in Egyptian patients who are heavily iron loaded and its relation to liver iron concentration, serum ferritin, and left ventricular ejection fraction. Eighty-nine β-thalassemia patients receiving chelation therapy (mean age of 20.8 ± 6.4 years) were recruited in this study. Tissue iron levels were determined by CMR with cardiac T2* and liver R2*. The mean ± standard deviation (range) of cardiac T2* was 28.5 ± 11.7 ms (4.3 to 53.8 ms), the left ventricular ejection fraction (LVEF) was 67.7 ± 4.7 % (55 to 78 %), and the liver iron concentration (LIC) was 26.1 ± 13.4 mg Fe/g dry weight (dw) (1.5 to 56 mg Fe/g dw). The mean serum ferritin was 4,510 ± 2,847 ng/ml (533 to 22,360 ng/ml), and in 83.2 %, the serum ferritin was >2,500 ng/ml. The prevalence of myocardial siderosis (T2* of <20 ms) was 24.7 % (mean age 20.9 ± 7.5 years), with mean T2* of 12.7 ± 4.4 ms, mean LVEF of 68.6 ±5.8 %, mean LIC of 30.9 ± 13 mg Fe/g dw, and median serum ferritin of 4,996 ng/ml. There was no correlation between T2* and age, LVEF, LIC, and serum ferritin (P = 0.65, P = 0.085, P = 0.99, and P = 0.63, respectively). Severe cardiac siderosis (T2* of <10 ms) was present in 7.9 %, with a mean age of 18.4 ± 4.4 years. Although these patients had a mean T2* of 7.8 ± 1.7 ms, the LVEF was 65.1 ± 6.2 %, and only one patient had heart failure (T2* of 4.3 ms and LVEF of 55 %). LIC and serum ferritin results were 29.8 ± 17.0 mg/g and 7,200 ± 6,950 ng/ml, respectively. In this group of severe cardiac siderosis, T2* was also not correlated to age (P = 0.5), LVEF (P = 0.14), LIC (P = 0.97), or serum ferritin (P = 0.82). There was a low prevalence of myocardial siderosis in the Egyptian thalassemia patients in spite of very high serum ferritin and high LIC. T2* is the best test that can identify at-risk patients who can be managed with optimization of their chelation therapy. The possibility of a genetic component for the resistance to cardiac iron loading in our population should be considered.
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St Pierre TG, El-Beshlawy A, Elalfy M, Al Jefri A, Al Zir K, Daar S, Habr D, Kriemler-Krahn U, Taher A. Multicenter validation of spin-density projection-assisted R2-MRI for the noninvasive measurement of liver iron concentration. Magn Reson Med 2013; 71:2215-23. [PMID: 23821350 PMCID: PMC4238736 DOI: 10.1002/mrm.24854] [Citation(s) in RCA: 80] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Revised: 05/29/2013] [Accepted: 05/31/2013] [Indexed: 12/12/2022]
Abstract
Purpose Magnetic resonance imaging (MRI)-based techniques for assessing liver iron concentration (LIC) have been limited by single scanner calibration against biopsy. Here, the calibration of spin-density projection-assisted (SDPA) R2-MRI (FerriScan®) in iron-overloaded β-thalassemia patients treated with the iron chelator, deferasirox, for 12 months is validated. Methods SDPA R2-MRI measurements and percutaneous needle liver biopsy samples were obtained from a subgroup of patients (n = 233) from the ESCALATOR trial. Five different makes and models of scanner were used in the study. Results LIC, derived from mean of MRI- and biopsy-derived values, ranged from 0.7 to 50.1 mg Fe/g dry weight. Mean fractional differences between SDPA R2-MRI- and biopsy-measured LIC were not significantly different from zero. They were also not significantly different from zero when categorized for each of the Ishak stages of fibrosis and grades of necroinflammation, for subjects aged 3 to <8 versus ≥8 years, or for each scanner model. Upper and lower 95% limits of agreement between SDPA R2-MRI and biopsy LIC measurements were 74 and −71%. Conclusion The calibration curve appears independent of scanner type, patient age, stage of liver fibrosis, grade of necroinflammation, and use of deferasirox chelation therapy, confirming the clinical usefulness of SDPA R2-MRI for monitoring iron overload. Magn Reson Med 71:2215–2223, 2014. © 2013 Wiley Periodicals, Inc.
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Affiliation(s)
- Tim G St Pierre
- Biomedical Physics, School of Physics, The University of Western Australia, Crawley, Australia
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Tang H, Jensen JH, Sammet CL, Sheth S, Swaminathan SV, Hultman K, Kim D, Wu EX, Brown TR, Brittenham GM. MR characterization of hepatic storage iron in transfusional iron overload. J Magn Reson Imaging 2013; 39:307-16. [PMID: 23720394 DOI: 10.1002/jmri.24171] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2012] [Accepted: 03/15/2013] [Indexed: 01/09/2023] Open
Abstract
PURPOSE To quantify the two principal forms of hepatic storage iron, diffuse, soluble iron (primarily ferritin), and aggregated, insoluble iron (primarily hemosiderin) using a new MRI method in patients with transfusional iron overload. MATERIALS AND METHODS Six healthy volunteers and 20 patients with transfusion-dependent thalassemia syndromes and iron overload were examined. Ferritin- and hemosiderin-like iron were determined based on the measurement of two distinct relaxation parameters: the "reduced" transverse relaxation rate, RR2 , and the "aggregation index," A, using three sets of Carr-Purcell-Meiboom-Gill (CPMG) datasets with different interecho spacings. Agarose phantoms, simulating the relaxation and susceptibility properties of tissue with different concentrations of dispersed (ferritin-like) and aggregated (hemosiderin-like) iron, were used for validation. RESULTS Both phantom and in vivo human data confirmed that transverse relaxation components associated with the dispersed and aggregated iron could be separated using the two-parameter (RR2 , A) method. The MRI-determined total hepatic storage iron was highly correlated (r = 0.95) with measurements derived from biopsy or biosusceptometry. As total hepatic storage iron increased, the proportion stored as aggregated iron became greater. CONCLUSION This method provides a new means for noninvasive MRI determination of the partition of hepatic storage iron between ferritin and hemosiderin in iron overload disorders.
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Affiliation(s)
- Haiying Tang
- Imaging, Discovery Medicine & Clinical Pharmacology, Bristol Myers Squibb, Princeton, New Jersey, USA
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House MJ, Gan EK, Adams LA, Ayonrinde OT, Bangma SJ, Bhathal PS, Olynyk JK, St Pierre TG. Diagnostic performance of a rapid magnetic resonance imaging method of measuring hepatic steatosis. PLoS One 2013; 8:e59287. [PMID: 23555650 PMCID: PMC3605443 DOI: 10.1371/journal.pone.0059287] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Accepted: 02/13/2013] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVES Hepatic steatosis is associated with an increased risk of developing serious liver disease and other clinical sequelae of the metabolic syndrome. However, visual estimates of steatosis from histological sections of biopsy samples are subjective and reliant on an invasive procedure with associated risks. The aim of this study was to test the ability of a rapid, routinely available, magnetic resonance imaging (MRI) method to diagnose clinically relevant grades of hepatic steatosis in a cohort of patients with diverse liver diseases. MATERIALS AND METHODS Fifty-nine patients with a range of liver diseases underwent liver biopsy and MRI. Hepatic steatosis was quantified firstly using an opposed-phase, in-phase gradient echo, single breath-hold MRI methodology and secondly, using liver biopsy with visual estimation by a histopathologist and by computer-assisted morphometric image analysis. The area under the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of the MRI method against the biopsy observations. RESULTS The MRI approach had high sensitivity and specificity at all hepatic steatosis thresholds. Areas under ROC curves were 0.962, 0.993, and 0.972 at thresholds of 5%, 33%, and 66% liver fat, respectively. MRI measurements were strongly associated with visual (r(2) = 0.83) and computer-assisted morphometric (r(2) = 0.84) estimates of hepatic steatosis from histological specimens. CONCLUSIONS This MRI approach, using a conventional, rapid, gradient echo method, has high sensitivity and specificity for diagnosing liver fat at all grades of steatosis in a cohort with a range of liver diseases.
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Affiliation(s)
- Michael J House
- School of Physics, The University of Western Australia, Crawley, Australia.
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Sammet CL, Swaminathan SV, Tang H, Sheth S, Jensen JH, Nunez A, Hultman K, Kim D, Wu EX, Brittenham GM, Brown TR. Measurement and correction of stimulated echo contamination in T2-based iron quantification. Magn Reson Imaging 2012; 31:664-8. [PMID: 23260394 DOI: 10.1016/j.mri.2012.10.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2012] [Revised: 10/11/2012] [Accepted: 10/30/2012] [Indexed: 11/17/2022]
Abstract
The purpose of this study was to characterize the effects of stimulated echo contamination on MR-based iron measurement derived from quantitative T2 images and develop a method for retrospective correction. Two multiple spin-echo (MSE) pulse sequences were implemented with different amounts of stimulated echo contamination. Agarose-based phantoms were constructed that simulate the relaxation and susceptibility properties of tissue with different concentrations of dispersed (ferritin-like) and aggregated (hemosiderin-like) iron. Additionally, myocardial iron was assessed in nine human subjects with transfusion iron overload. These data were used to determine the influence of stimulated echoes on iron measurements made by an MR-based iron quantification model that can separately measure dispersed and aggregated iron. The study found that stimulated echo contamination caused an underestimation of dispersed (ferritin-like) iron and an overestimation of aggregated (hemosiderin-like) iron when applying this model. The relationship between the measurements made with and without stimulated echo appears to be linear. The findings suggest that while it is important to use MSE sequences with minimal stimulated echo in T2-based iron quantification, it appears that data acquired with sub-optimal sequences can be retrospectively corrected using the methodology described here.
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Porter JB, Elalfy MS, Taher AT, Aydinok Y, Chan LL, Lee SH, Sutcharitchan P, Habr D, Martin N, El-Beshlawy A. Efficacy and safety of deferasirox at low and high iron burdens: results from the EPIC magnetic resonance imaging substudy. Ann Hematol 2012; 92:211-9. [PMID: 23086508 PMCID: PMC3542426 DOI: 10.1007/s00277-012-1588-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2012] [Accepted: 09/23/2012] [Indexed: 01/19/2023]
Abstract
The effect of deferasirox dosing tailored for iron burden and iron loading based on liver iron concentration (LIC) was assessed over 1 year in less versus more heavily iron-overloaded patients in a substudy of the Evaluation of Patients' Iron Chelation with Exjade®. Deferasirox starting dose was 10-30 mg/kg/day, depending on blood transfusion frequency, with recommended dose adjustments every 3 months. Therapeutic goals were LIC maintenance or reduction in patients with baseline LIC <7 or ≥7 mg Fe/g dry weight (dw), respectively. Changes in LIC (R2-magnetic resonance imaging) and serum ferritin after 1 year were assessed. Adverse events (AEs) and laboratory parameters were monitored throughout. Of 374 patients, 71 and 303 had baseline LIC <7 and ≥7 mg Fe/g dw, respectively; mean deferasirox doses were 20.7 and 27.1 mg/kg/day (overall average time to dose increase, 24 weeks). At 1 year, mean LIC and median serum ferritin levels were maintained in the low-iron cohort (-0.02 ± 2.4 mg Fe/g dw, -57 ng/mL; P = not significant) and significantly decreased in the high-iron cohort (-6.1 ± 9.1 mg Fe/g dw, -830 ng/mL; P < 0.0001). Drug-related gastrointestinal AEs, mostly mild to moderate, were more frequently reported in the <7 versus ≥7 mg Fe/g dw cohort (39.4 versus 20.8 %; P = 0.001) and were not confounded by diagnosis, dosing, ethnicity, or hepatitis B and/or C history. Reported serum creatinine increases did not increase in low- versus high-iron cohort patients. Deferasirox doses of 20 mg/kg/day maintained LIC <7 mg Fe/g dw and doses of 30 mg/kg/day were required for net iron reduction in the high-iron cohort, with clinically manageable safety profiles. The higher incidence of gastrointestinal AEs at lower iron burdens requires further investigation.
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Affiliation(s)
- J B Porter
- UCL Cancer Institute, Department of Haematology, University College London, 72 Huntley Street, London, UK.
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