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Zhao F, Chen Y, Zhou T, Tang C, Huang J, Zhang H, Kannengiesser S, Long L. Application of the magnetic resonance 3D multiecho Dixon sequence for quantifying hepatic iron overload and steatosis in patients with thalassemia. Magn Reson Imaging 2024; 111:28-34. [PMID: 38492786 DOI: 10.1016/j.mri.2024.03.015] [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: 01/26/2024] [Revised: 03/02/2024] [Accepted: 03/13/2024] [Indexed: 03/18/2024]
Abstract
OBJECTIVE To investigate the feasibility and diagnostic efficacy of a 3D multiecho Dixon (qDixon) research application for simultaneously quantifying the liver iron concentration (LIC) and steatosis in thalassemia patients. MATERIALS AND METHODS This prospective study enrolled participants with thalassemia who underwent 3 T MRI of the liver for the evaluation of hepatic iron overload. The imaging protocol including qDixon and conventional T2* mapping based on 2D multiecho gradient echo (ME GRE) sequences respectively. Regions of interest (ROIs) were drawn in the liver on the qDixon maps to obtain R2* and proton density fat fraction (PDFF). The reference R2* value was measured and calculated on conventional T2* mapping using the CMRtools software. Correlation analysis, Linear regression analysis, and Bland-Altman analysis were performed. RESULTS 84 patients were finally included in this study. The median R2*-ME-GRE was 366.97 (1/s), range [206.68 (1/s), 522.20 (1/s)]. 8 patients had normal hepatic iron deposition, 16 had Insignificant, 42 had mild, 18 had moderate. The median of R2*-qDixon was 376.88 (1/s) [219.33 (1/s), 491.75 (1/s)]. A strong correlation was found between the liver R2*-qDixon and the R2*-ME-GRE (r = 0.959, P < 0.001). The median value of PDFF was 1.76% (1.10%, 2.95%). 8 patients had mild fatty liver, and 1 had severe fatty liver. CONCLUSION MR qDixon research sequence can rapidly and accurately quantify liver iron overload, that highly consistent with the measured via conventional GRE sequence, and it can also simultaneously detect hepatic steatosis, this has great potential for clinical evaluation of thalassemia patients.
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Affiliation(s)
- Fanyu Zhao
- Department of Radiology, Minzu Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, 530001, China
| | - Yidi Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
| | - Ting Zhou
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530001, China
| | - Cheng Tang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530001, China
| | - Jiang Huang
- Department of Radiology, Minzu Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, 530001, China
| | - Huiting Zhang
- MR Research Collaboration, Siemens Healthineers Ltd., Wuhan, China.
| | | | - Liling Long
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530001, China.
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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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Singh SP, Jagia P, Ojha V, Seth T, Naik N, Ganga KP, Kumar S. Diagnostic Value of T1 Mapping in Detecting Iron Overload in Indian Patients with Thalassemia Major: A Comparison with T2* Mapping. Indian J Radiol Imaging 2024; 34:54-59. [PMID: 38106847 PMCID: PMC10723946 DOI: 10.1055/s-0043-1772467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023] Open
Abstract
Purpose T2* is the gold standard for iron quantification in liver as well as myocardium. In this study, we evaluated the diagnostic accuracy of myocardial T1 mapping for the assessment of myocardial iron overload (MIO) as compared to the T2* mapping in patients with thalassemia major (TM). Methods Consecutive TM patients attending the thalassemia clinic were prospectively enrolled. Magnetic resonance imaging was performed on a 1.5 T scanner (Siemens Healthineers, Germany) using a gradient echo T2* as well as a T1 mapping (MOLLI) sequence done at a mid-ventricular short-axis single 8 mm slice of the left ventricle. Values were analyzed by manually drawing a region of interest in the mid-septum. T2*less than 20ms was used as the cutoff for significant MIO. Results One-hundred three patients (58 males, mean age: 17 ± 7.8 years, mean ferritin: 2009.5 µg/L) underwent cardiovascular magnetic resonance. Median T2* of myocardium was 33.45ms. Nineteen patients (18.4%) had T2*less than 20ms. T1 value was low (<850ms) in all the patients with T2* less than 20 ms. Receiver operating characteristic curve analysis revealed the best cutoff of native T1 mapping value as 850 ms which had high specificity (95.2%), sensitivity (94.2%) and negative predictive value (98.8%) for T2* less than 20ms. There was excellent agreement between T1 and T2* for diagnosis of MIO (Kappa-0.848, p <0.001). We did not find any patient who had normal T1 mapping values but had MIO on T2*. Conclusion T1 and T2* correlate well and normal T1 values may rule out presence of MIO. T1 mapping can act as additional imaging marker for MIO and may be helpful in centers with nonavailability or limited experience of T2*.
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Affiliation(s)
- Surya Pratap Singh
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
| | - Priya Jagia
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
| | - Vineeta Ojha
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
| | - Tulika Seth
- Department of Haematology, All India Institute of Medical Sciences, New Delhi, India
| | - Nitish Naik
- Department of Cardiology, All India Institute of Medical Sciences, New Delhi, India
| | - Kartik P. Ganga
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
| | - Sanjeev Kumar
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
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Neupane P, Shrestha U, Brasher S, Abramson Z, Tipirneni-Sajja A. Simulation of a virtual liver iron overload model and R 2 * estimation using multispectral fat-water models for GRE and UTE acquisitions at 1.5 T and 3 T. NMR IN BIOMEDICINE 2023; 36:e5018. [PMID: 37539770 PMCID: PMC10838367 DOI: 10.1002/nbm.5018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/05/2023]
Abstract
R2 *-MRI has emerged as a noninvasive alternative to liver biopsy for assessment of hepatic iron content (HIC). Multispectral fat-water R2 * modeling techniques such as the nonlinear least squares (NLSQ) fitting and autoregressive moving average (ARMA) models have been proposed for the accurate assessment of iron overload by also considering fat, which can otherwise confound R2 *-based HIC measurements in conditions of coexisting iron overload and steatosis. However, the R2 * estimation by these multispectral models has not been systematically investigated for various acquisition methods in iron overload only conditions and across the full clinically relevant range of HICs (0-40 mg Fe/g dry liver weight). The purpose of this study is to evaluate the R2 * accuracy and precision of multispectral models for various multiecho gradient echo (GRE) and ultrashort echo time (UTE) imaging acquisitions by constructing virtual iron overload models based on true histology and synthesizing MRI signals via Monte Carlo simulations at 1.5 T and 3 T, and comparing their results with monoexponential model and published in vivo R2 *-HIC calibrations. The signals were synthesized with TE1 = 1.0 ms for GRE and TE1 = 0.1 ms for UTE acquisition for varying echo spacing, ΔTE (0.1, 0.5, 1, 2 ms), and maximum echo time, TEmax (2, 4, 6, 10 ms). An iron-doped phantom study is also conducted to validate the simulation results in experimental GRE (TE1 = 1.2 ms, ΔTE = 0.72 ms, TEmax = 6.24 ms) and UTE (TE1 = 0.1 ms, ΔTE = 0.5 ms, TEmax = 6.1 ms) acquisitions. For GRE acquisitions, the multispectral ARMA and NLSQ models produced higher slopes (0.032-0.035) compared with the monoexponential model and published in vivo R2 *-HIC calibrations (0.025-0.028). However, for UTE acquisition for shorter echo spacing (≤0.5 ms) and longer maximum echo time, TEmax (≥6 ms), the multispectral and monoexponential signal models produced similar R2 *-HIC slopes (1.5 T, 0.028-0.032; 3 T, 0.014-0.016) and precision values (coefficient of variation < 25%) across the full clinical spectrum of HICs at both 1.5 T and 3 T. The phantom analysis also showed that all signal models demonstrated a significant improvement in R2 * estimation for UTE acquisition compared with GRE, confirming our simulation findings. Future work should investigate the performance of multispectral fat-water models by simulating liver models in coexisting conditions of iron overload and steatosis for accurate R2 * and fat quantification.
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Affiliation(s)
- Prasiddhi Neupane
- Biomedical Engineering, The University of Memphis, TN, United States
| | - Utsav Shrestha
- Biomedical Engineering, The University of Memphis, TN, United States
| | - Sarah Brasher
- Biomedical Engineering, The University of Memphis, TN, United States
| | - Zachary Abramson
- St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Aaryani Tipirneni-Sajja
- Biomedical Engineering, The University of Memphis, TN, United States
- St. Jude Children’s Research Hospital, Memphis, TN, United States
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5
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Xu F, Li D, Tang C, Liang B, Guan K, Liu R, Peng P. Magnetic resonance imaging assessment of the changes of cardiac and hepatic iron load in thalassemia patients before and after hematopoietic stem cell transplantation. Sci Rep 2023; 13:19652. [PMID: 37950037 PMCID: PMC10638442 DOI: 10.1038/s41598-023-46524-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 11/02/2023] [Indexed: 11/12/2023] Open
Abstract
To investigate the value of T2* technique on 3.0 T magnetic resonance imaging (MRI) in evaluating the changes of cardiac and hepatic iron load before and after hematopoietic stem cell transplantation (HSCT) in patients with thalassemia (TM), the 141 TM patients were divided into 6 group for subgroup analysis: 6, 12, 18, 24 and > 24 months group, according to the postoperative interval. The T2* values of heart and liver (H-T2*, L-T2*) were quantified in TM patients before and after HSCT using 3.0 T MRI T2* technology, and the corresponding serum ferritin (SF) was collected at the same time, and the changes of the three before and after HSCT were compared. The overall H-T2* (P = 0.001) and L-T2* (P = 0.041) of patients after HSCT were higher than those before HSCT (mean relative changes = 19.63%, 7.19%). The H-T2* (P < 0.001) and L-T2* (P < 0.001) > 24 months after HSCT were significantly higher than those before HSCT (mean relative changes = 69.19%, 93.73%). The SF of 6 months (P < 0.001), 12 months (P = 0.008), 18 months (P = 0.002) and > 24 months (P = 0.001) were significantly higher than those before HSCT (mean relative changes = 57.93%, 73.84%, 128.51%, 85.47%). There was no significant improvement in cardiac and liver iron content in TM patients within 24 months after HSCT, while the reduction of cardiac and liver iron content in patients is obvious when > 24 months after HSCT.
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Affiliation(s)
- Fengming Xu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Da Li
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Cheng Tang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Bumin Liang
- School of International Education, Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Kaiming Guan
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Rongrong Liu
- Department of Haematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Peng Peng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
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Dmochowska N, Milanova V, Mukkamala R, Chow KK, Pham NTH, Srinivasarao M, Ebert LM, Stait-Gardner T, Le H, Shetty A, Nelson M, Low PS, Thierry B. Nanoparticles Targeted to Fibroblast Activation Protein Outperform PSMA for MRI Delineation of Primary Prostate Tumors. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2204956. [PMID: 36840671 DOI: 10.1002/smll.202204956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 01/23/2023] [Indexed: 05/25/2023]
Abstract
Accurate delineation of gross tumor volumes remains a barrier to radiotherapy dose escalation and boost dosing in the treatment of solid tumors, such as prostate cancer. Magnetic resonance imaging (MRI) of tumor targets has the power to enable focal dose boosting, particularly when combined with technological advances such as MRI-linear accelerator. Fibroblast activation protein (FAP) is overexpressed in stromal components of >90% of epithelial carcinomas. Herein, the authors compare targeted MRI of prostate specific membrane antigen (PSMA) with FAP in the delineation of orthotopic prostate tumors. Control, FAP, and PSMA-targeting iron oxide nanoparticles were prepared with modification of a lymphotropic MRI agent (FerroTrace, Ferronova). Mice with orthotopic LNCaP tumors underwent MRI 24 h after intravenous injection of nanoparticles. FAP and PSMA nanoparticles produced contrast enhancement on MRI when compared to control nanoparticles. FAP-targeted MRI increased the proportion of tumor contrast-enhancing black pixels by 13%, compared to PSMA. Analysis of changes in R2 values between healthy prostates and LNCaP tumors indicated an increase in contrast-enhancing pixels in the tumor border of 15% when targeting FAP, compared to PSMA. This study demonstrates the preclinical feasibility of PSMA and FAP-targeted MRI which can enable targeted image-guided focal therapy of localized prostate cancer.
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Affiliation(s)
- Nicole Dmochowska
- Future Industries Institute, University of South Australia, Adelaide, South Australia, 5095, Australia
| | - Valentina Milanova
- Future Industries Institute, University of South Australia, Adelaide, South Australia, 5095, Australia
| | - Ramesh Mukkamala
- Department of Chemistry and Institute for Drug Discovery, Purdue University, West Lafayette, IN, 47907, USA
| | - Kwok Keung Chow
- Future Industries Institute, University of South Australia, Adelaide, South Australia, 5095, Australia
| | - Nguyen T H Pham
- Key Centre for Polymers and Colloids, School of Chemistry, The University of Sydney, Sydney, New South Wales, 2006, Australia
| | - Madduri Srinivasarao
- Department of Chemistry and Institute for Drug Discovery, Purdue University, West Lafayette, IN, 47907, USA
| | - Lisa M Ebert
- Centre for Cancer Biology, University of South Australia; SA Pathology; Cancer Clinical Trials Unit, Royal Adelaide Hospital; Adelaide Medical School, University of Adelaide, Adelaide, South Australia, 5000, Australia
| | - Timothy Stait-Gardner
- Nanoscale Organisation and Dynamics Group, Western Sydney University, Sydney, New South Wales, 2560, Australia
| | - Hien Le
- Department of Radiation Oncology, Royal Adelaide Hospital, Adelaide, South Australia, 5000, Australia
| | - Anil Shetty
- Ferronova Pty Ltd, Mawson Lakes, South Australia, 5095, Australia
| | - Melanie Nelson
- Ferronova Pty Ltd, Mawson Lakes, South Australia, 5095, Australia
| | - Philip S Low
- Department of Chemistry and Institute for Drug Discovery, Purdue University, West Lafayette, IN, 47907, USA
| | - Benjamin Thierry
- Future Industries Institute, University of South Australia, Adelaide, South Australia, 5095, Australia
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7
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Xu F, Luo C, Li M, Guan K, Peng F, Yang G, Peng P. Quantification of cardiac iron in patients with thalassemia with 3-T MRI calibrated by 1.5-T MRI. Acta Radiol 2023; 64:2096-2103. [PMID: 37032518 DOI: 10.1177/02841851231165283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
BACKGROUND Due to the small sample size of many studies, it remained unclear what standardized reference range the T2* cutoff at 3 T would be used to assess the severity of cardiac iron load. In addition, the number of patients with moderate to severe cardiac iron load was small in some studies, especially the sample of patients with severe cardiac iron load. PURPOSE To explore the feasibility, reproducibility, and reliability of using T2* values in quantifying cardiac iron load in patients with thalassemia at 3 T. MATERIAL AND METHODS A total of 122 patients with thalassemia underwent cardiac T2* imaging at both 1.5 T and 3 T. Cardiac R2* (1000/T2*) values of the 100 patients at 3 T were fitted against the values at 1.5 T using linear regression and the prediction equation was derived. The remaining 22 cases were used to test the prediction accuracy of the equation. RESULTS The combined R2* values exhibited a strong linear relationship between 1.5 T and 3 T (r = 0.830,P<0.001). At the center, it had a slope of 1.348 and an intercept of 37.279. According to the equation, the truncated T2* values of cardiac iron overload and cardiac heavy iron overload at 3 T were <10 ms and <6 ms, respectively. The two truncated T2* values were used to diagnose different levels of cardiac iron overloaded of 22 patients at 3 T; the accuracy rates were 95.5% and 100.0%, respectively. CONCLUSION T2* quantification of cardiac iron load at 3 T MRI resulted to be feasible, reproducible, and reliable.
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Affiliation(s)
- Fengming Xu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
| | - Chaotian Luo
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
| | - Meicheng Li
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
| | - Kaiming Guan
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
| | - Fei Peng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
| | - Gaohui Yang
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
- Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
| | - Peng Peng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, PR China
- NHC Key Laboratory of Thalassemia Medicine (Guangxi Medical University), Nanning, Guangxi Zhuang Autonomous Region, PR China
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8
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Reeder SB, Yokoo T, França M, Hernando D, Alberich-Bayarri Á, Alústiza JM, Gandon Y, Henninger B, Hillenbrand C, Jhaveri K, Karçaaltıncaba M, Kühn JP, Mojtahed A, Serai SD, Ward R, Wood JC, Yamamura J, Martí-Bonmatí L. Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR. Radiology 2023; 307:e221856. [PMID: 36809220 PMCID: PMC10068892 DOI: 10.1148/radiol.221856] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 10/20/2022] [Accepted: 11/16/2022] [Indexed: 02/23/2023]
Abstract
Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.
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Affiliation(s)
- Scott B. Reeder
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Takeshi Yokoo
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Manuela França
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Diego Hernando
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Ángel Alberich-Bayarri
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - José María Alústiza
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Yves Gandon
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Benjamin Henninger
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Claudia Hillenbrand
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Kartik Jhaveri
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Musturay Karçaaltıncaba
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Jens-Peter Kühn
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Amirkasra Mojtahed
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Suraj D. Serai
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Richard Ward
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - John C. Wood
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Jin Yamamura
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
| | - Luis Martí-Bonmatí
- From the Departments of Radiology (S.B.R., D.H.), Medical Physics
(S.B.R., D.H.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and
Emergency Medicine (S.B.R.), University of Wisconsin, Room 2472, 1111 Highland
Ave, Madison, WI 53705; Department of Radiology and Advanced Imaging Research
Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.);
Department of Radiology, Centro Hospitalar Universitário do Porto,
Oporto, Portugal (M.F.); Biomedical Imaging Research Group (GIBI230-PREBI),
Instituto de Investigación Sanitaria La Fe, Valencia, Spain
(Á.A.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL,
Valencia, Spain (Á.A.B.); Osatek, Magnetic Resonance Unit, Donostia
University Hospital, San Sebastián, Spain (J.M.A.); Department of
Radiology, University Hospital and University of Rennes 1, Rennes, France
(Y.G.); Department of Radiology, Medical University of Innsbruck, Innsbruck,
Austria (B.H.); Research Imaging NSW, Division of Research & Enterprise,
University of New South Wales, Sydney, Australia (C.H.); Joint Department of
Medical Imaging (K.J.) and Department of Medicine (R.W.), University Health
Network, University of Toronto, Toronto, Canada; Liver Imaging Team, Department
of Radiology, Hacettepe University School of Medicine, Ankara, Turkey (M.K.);
Institute and Policlinic for Diagnostic and Interventional Radiology, University
Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden,
Germany (J.P.K.); Department of Radiology, Division of Abdominal Imaging,
Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.);
Department of Radiology, Children’s Hospital of Philadelphia, University
of Pennsylvania School of Medicine, Philadelphia, Pa (S.D.S.); Division of
Pediatric Cardiology, Children’s Hospital of Los Angeles, Los Angeles,
Calif (J.C.W.); Center of Radiology & Endoscopy, Department of Diagnostic
& Interventional Radiology, University Medical Center Hamburg-Eppendorf,
Hamburg, Germany (J.Y.); and Medical Imaging Department and Biomedical Imaging
Research Group, Hospital Universitario y Politécnico La Fe and Health
Research Institute, Valencia, Spain (L.M.B.)
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9
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Guzelbey T, Demirbaş ZE, Gurses B. The Evaluation of Renal Iron Deposition With a 3 Tesla MRI Device in Beta-Thalassemia Major Patients. Cureus 2023; 15:e36179. [PMID: 37065363 PMCID: PMC10103619 DOI: 10.7759/cureus.36179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/15/2023] [Indexed: 03/17/2023] Open
Abstract
Background and objective Beta-thalassemia is the most frequent monogenic disease in the world. In beta-thalassemia major (BTM) patients, blood transfusions for severe anemia usually cause iron overload, leading to increased morbidity and mortality. In this study, we aimed to examine the iron overload in the kidneys of BTM patients with a 3 Tesla (3T) MRI device and assess the relationship between iron overload in the liver and heart as well as serum ferritin levels. Methods This was a retrospective study covering the period between November 2014 and March 2015. MRI was performed on 21 patients with BTM who were receiving blood transfusions and chelation therapy. The control group (n=11) included healthy volunteers. A 3T MRI device (Ingenia, Philips, Best, The Netherlands) using a 16-channel phased array SENSE-compatible torso coil was used. Three-point DIXON (mDIXON) sequence and the relaxometry method were employed to measure iron overload. Both kidneys were analyzed via mDIXON sequence for atrophy or variations. Afterward, the images in which renal parenchyma could be distinguished best were selected. Iron deposition was analyzed via the relaxometry method using a unique software (CMR Tools, London, UK). All data were analyzed using IBM SPSS Statistics v.21 (IBM Corp., Armonk, NY). The Kolmogorov-Smirnov test, independent samples t-test, Mann-Whitney U test, and Pearson's and Spearman's rho correlation coefficient were used. A p-value <0.05 was considered statistically significant. Results There was a statistically significant relationship between beta-thalassemia patients who had cardiac iron deposition and those who did not in terms of T2* time (p=0.02). In contrast, there was no similar relationship for liver iron deposition (p>0.05). Renal T2* values were significantly different between the patient and control groups (p=0.029). T2* times were significantly different between patients who had ferritin levels below 2500 ng/ml and those with ferritin levels above 2500 ng/ml (p=0.042). Conclusion Based on our findings, 3T MRI is a safe and reliable tool for screening iron overload in BTM patients as it makes distinguishing between renal parenchyma and renal sinus much easier and as it is more sensitive to iron deposition.
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10
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Pickles E, Kumar S, Brady M, Telford A, Pavlides M, Bulte D. Comparison of liver iron concentration calculated from R2* at 1.5 T and 3 T. Abdom Radiol (NY) 2023; 48:865-873. [PMID: 36520162 PMCID: PMC9941222 DOI: 10.1007/s00261-022-03762-4] [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: 07/21/2022] [Revised: 11/29/2022] [Accepted: 12/01/2022] [Indexed: 12/23/2022]
Abstract
PURPOSE R2*, a measurement obtained using magnetic resonance imaging (MRI) can be used to estimate liver iron concentration (LIC). 3 T and 1.5 T scanners can be used but conversion of 3 T R2* to LIC is less well validated. In this study the aim was to compare 3 T-R2* LIC and 1.5 T-R2* LIC estimations to assess if they can be used interchangeably. METHODS Thirty participants were scanned at both 1.5 T and 3 T. R2* was measured at both field strengths. 3 T R2* and 1.5 R2* were compared using linear regression and were converted to LIC using different calibration curves. Pearson's rho and Intraclass Correlation Coefficients (ICCs) were used to assess correlation and agreement between 1.5 and 3 T LIC. Bland Altman plots were used to assess bias and limits of agreement. RESULTS All 1.5 T and 3 T LIC comparisons gave Pearson's rho of 0.99 (p < 0.001). ICC ranged from 0.83 (p = 0.005) to 0.96 (p < 0.001). Biases had magnitude of less than 0.2 mg/g dry weight. CONCLUSION Agreement and bias between 3 and 1.5 T-R2* LIC depended on the method used for conversion. There were instances when the agreement was excellent and bias was small, indicating that potentially 3 T-R2* LIC can be used alongside or instead of 1.5 T-R2* LIC but care needs to be taken over the conversion methods selected. TRIAL REGISTRATION NUMBER Clinicaltrials.gov NCT03743272, 16 November 2018.
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Affiliation(s)
- Elisabeth Pickles
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, Oxford, OX3 7DQ, UK. .,Perspectum Ltd, Oxford, UK. .,Medical Physics, Guy's and St Thomas' NHS Foundation Trust, London, UK. .,Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | | | | | | | - Michael Pavlides
- Oxford Centre for Magnetic Resonance, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.,Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK.,Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Daniel Bulte
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, Oxford, OX3 7DQ, UK
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11
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Cardiac Magnetic Resonance Strain in Beta Thalassemia Major Correlates with Cardiac Iron Overload. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10020271. [PMID: 36832400 PMCID: PMC9955453 DOI: 10.3390/children10020271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 01/17/2023] [Accepted: 01/27/2023] [Indexed: 02/05/2023]
Abstract
BACKGROUND Beta thalassemia major (Beta-TM) is an inherited condition which presents at around two years of life. Patients with Beta-;TM may develop cardiac iron toxicity secondary to transfusion dependence. Cardiovascular magnetic resonance (CMR) T2*, a technique designed to quantify myocardial iron deposition, is a driving component of disease management. A decreased T2* value represents increasing cardiac iron overload. The clinical manifestation is a decline in ejection fraction (EF). However, there may be early subclinical changes in cardiac function that are not detected by changes in EF. CMR-derived strain assesses myocardial dysfunction prior to decline in EF. Our primary aim was to assess the correlation between CMR strain and T2* in the Beta-TM population. METHODS Circumferential and longitudinal strain was analyzed. Pearson's correlation was calculated for T2* values and strain in the Beta-TM population. RESULTS We identified 49 patients and 18 controls. Patients with severe disease (low T2*) were found to have decreased global circumferential strain (GCS) in comparison to other T2* groups. A correlation was identified between GCS and T2* (r = 0.5; p < 0.01). CONCLUSION CMR-derived strain can be a clinically useful tool to predict early myocardial dysfunction in Beta-TM.
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12
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Chang S, Park J, Yang YJ, Beck KS, Kim PK, Choi BW, Jung JI. Myocardial T2* Imaging at 3T and 1.5T: A Pilot Study with Phantom and Normal Myocardium. J Cardiovasc Dev Dis 2022; 9:jcdd9080271. [PMID: 36005435 PMCID: PMC9410052 DOI: 10.3390/jcdd9080271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/06/2022] [Accepted: 08/12/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Myocardial T2* mapping at 1.5T remains the gold standard, but the use of 3T scanners is increasing. We aimed to determine the conversion equations in different scanners with clinically available, vendor-provided T2* mapping sequences using a phantom and evaluated the feasibility of the phantom-based conversion method. Methods: T2* of a phantom with FeCl3 (five samples, 3.53–20.09 mM) were measured with 1.5T (MR-A1) and 3T scanners (MR-A2, A3, B), and the site-specific equation was determined. T2* was measured in the interventricular septum of three healthy volunteers at 1.5T (T2*1.5T, MR-A1) and 3T (T2*3.0T, MR-B). T2*3.0T was converted based on the equation derived from the phantom (T2*eq). Results: R2* at 1.5T and 3T showed linear association, but a different relationship was observed according to the scanners (MR-A2, R2*1.5T = 0.76 × R2*3.0T − 2.23, R2 = 0.999; MR-A3, R2*1.5T = 0.95 × R2*3.0T − 34.28, R2 = 0.973; MR-B, R2*1.5T = 0.76 × R2*3.0T − 3.02, R2 = 0.999). In the normal myocardium, T2*eq and T2*1.5T showed no significant difference (35.5 ± 3.5 vs. 34.5 ± 1.2, p = 0.340). The mean squared error between T2*eq and T2*1.5T was 16.33, and Bland–Altman plots revealed a small bias (−0.94, 95% limits of agreement: −8.86–6.99). Conclusions: a phantom-based, site-specific equation can be utilized to estimate T2* values at 1.5T in centers where only 3T scanners are available.
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Affiliation(s)
- Suyon Chang
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
| | | | | | - Kyongmin Sarah Beck
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
| | | | - Byoung Wook Choi
- Phantomics, Inc., Seoul 07803, Korea
- Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Korea
| | - Jung Im Jung
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
- Correspondence: ; Tel.: +82-2-2258-1431
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13
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Amin K, Mileto A, Kolokythas O. MRI for Liver Iron Quantification: Concepts and Current Methods. Semin Ultrasound CT MR 2022; 43:364-370. [PMID: 35738822 DOI: 10.1053/j.sult.2022.03.006] [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]
Abstract
Liver Iron content is best correlated to total body iron stores and is thus the organ of choice for evaluation in iron overload diseases. Liver biopsy was the historic standard for iron evaluation, but the evaluation is localized, comes with increased risks due to its invasiveness, and is costly. MRI is now widely used for liver iron evaluation. The superparamagnetic properties of iron cause a disturbance in magnetic resonance imaging, which can be evaluated with various techniques. These include signal intensity ratio (SIR), T2 relaxometry, T2* relaxometry, and Dixon-based solutions. Each of the methods has its own advantages and disadvantages, and factors such as availability, ease of use, accuracy, reproducibility, and cost can all play a role in the ultimate technique used for liver iron quantification. Quantitative susceptibility mapping, and ultrashort TE sequences are promising supplemental methods, but are primarily used as research sequences. These may become more clinically accepted in the near future. Dual energy CT is also being explored as an alternative but is still in the nascent stages. Overall, accurate liver iron concentration is feasible with the current tools available at most MR imaging centers and is highly valuable for evaluation of iron overload diseases.
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Affiliation(s)
- Kathan Amin
- Department of Radiology, University of Washington, Seattle, WA.
| | - Achille Mileto
- Department of Radiology, University of Washington, Seattle, WA
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14
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Branisso PPF, de Oliveira CPMS, Filho HML, Lima FR, Santos AS, Mancini MC, de Melo ME, Carrilho FJ, Rocha MDS, Clark P, Branisso HJP, Cercato C. Non-invasive methods for iron overload evaluation in dysmetabolic patients. Ann Hepatol 2022; 27:100707. [PMID: 35477031 DOI: 10.1016/j.aohep.2022.100707] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/04/2022] [Accepted: 03/22/2022] [Indexed: 02/04/2023]
Abstract
INTRODUCTION Although hyperferritinemia may reflect the inflammatory status of patients with non-alcoholic fatty liver disease (NAFLD), approximately 33% of hyperferritinemia cases reflect real hepatic iron overload. AIM To evaluate a non-invasive method for assessing mild iron overload in patients with NAFLD using 3T magnetic resonance imaging (MRI) relaxometry, serum hepcidin, and the expression of ferritin subunits. METHODS This cross-sectional study assessed patients with biopsy-proven NAFLD. MRI relaxometry was performed using a 3T scanner in all patients, and the results were compared with iron content determined by liver biopsy. Ferritin, hepcidin, and ferritin subunits were assessed and classified according to ferritin levels and to siderosis identified by liver biopsy. RESULTS A total of 67 patients with NAFLD were included in the study. MRI revealed mild iron overload in all patients (sensitivity, 73.5%; specificity, 70%). For mild (grade 1) siderosis, the transverse relaxation rate (R2*) threshold was 58.9 s-1 and the mean value was 72.5 s-1 (SD, 33.9), while for grades 2/3 it was 88.2 s-1 (SD, 31.9) (p < 0.001). The hepcidin threshold for siderosis was > 30.2 ng/mL (sensitivity, 87%; specificity, 82%). Ferritin H and ferritin L subunits were expressed similarly in patients with NAFLD, regardless of siderosis. There were no significant differences in laboratory test results between the groups, including glucose parameters and liver function tests. CONCLUSIONS MRI relaxometry and serum hepcidin accurately assessed mild iron overload in patients with dysmetabolic iron overload syndrome.
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Affiliation(s)
- Paula Pessin Fábrega Branisso
- Obesity and metabolic syndrome study group, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil.
| | | | - Hilton Muniz Leão Filho
- Radiology department, InRad, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Fabiana Roberto Lima
- Patology department, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Aritânia Sousa Santos
- Laboratory of Carbohydrates and Raioimmunoassay (LIM/18), Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Marcio Correa Mancini
- Obesity and metabolic syndrome study group, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Maria Edna de Melo
- Radiology department, InRad, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Flair José Carrilho
- Gastroenterology department, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Manoel de Souza Rocha
- Radiology department, InRad, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Paul Clark
- Magnepath digital health company, Perth, Australia
| | | | - Cintia Cercato
- Obesity and metabolic syndrome study group, Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, Brazil
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15
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Ali Mohamed Aboughonaim A, Naguib Ettaby A, Ibrahim El-Noueum K, Hassab H, Emara DM. Dual gradient echo in-phase and out of phase sequences in assessment of hepatic iron overload in patients with beta-thalassemia, would be better? Eur J Radiol 2022; 154:110412. [PMID: 35724580 DOI: 10.1016/j.ejrad.2022.110412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 06/09/2022] [Accepted: 06/11/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE To evaluate the diagnostic accuracy of the dual gradient-echo (GRE) in- and out-of-phase sequences as a quantitative tool for hepatic iron overload in comparison with MRI R2* relaxometry in paediatric patients with beta-thalassemia. METHOD Sixty-three patients with beta-thalassemia major (transfusion-dependent) or beta-thalassemia intermedia (transfusion- and non-transfusion-dependent) were referred from the paediatric department (haematology unit) to the radiology department at a university hospital. The paediatrician conducted a clinical examination for the studied group, assessed their laboratory data, conducted R2* relaxometry and dual gradient echo sequences to calculate R2* and relative signal intensity index at the axial mid-section of the liver, and studied their correlation. A 1.5 Tesla MR scanner was used (Achieva; Philips Medical Systems, the Netherlands). Data were fed to the computer and analysed using the IBM SPSS software package version 20.0 (Armonk, NY: IBM Corp). The Kolmogorov-Smirnov test was used to verify the normality of distribution. The significance of the results was determined at the 5% level. The Chi-square, Fisher's exact correction, Pearson coefficient, and Bland-Altman tests were used. RESULTS Dual gradient-echo in- and out-of-phase sequences using visual assessment accurately assessed 93.65% of our patient group with hepatic iron overload. A significant correlation was found between the relative signal intensity index and hepatic MRI R2* relaxometry (p < 0.001, r = 0.861). CONCLUSIONS Dual gradient-echo in and out-of-phase sequences are good imaging tools for hepatic iron detection and quantification. These sequences showed good correlation with R2* relaxometry (r = 0.861, p < 0.001).
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Affiliation(s)
| | | | | | - Hoda Hassab
- Department of Pediatrics (hematology unit), Faculty of medicine, Alexandria University, Egypt
| | - Doaa M Emara
- Department of radiodiagnosis, Faculty of medicine, Alexandria University, Egypt
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16
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Meloni A, Positano V, Pistoia L, Cademartiri F. Pancreatic iron quantification with MR imaging: a practical guide. Abdom Radiol (NY) 2022; 47:2397-2407. [PMID: 35596775 DOI: 10.1007/s00261-022-03552-y] [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: 02/10/2022] [Revised: 05/02/2022] [Accepted: 05/02/2022] [Indexed: 11/30/2022]
Abstract
Accurate determination of pancreatic iron status is crucial for preventing impairment of the exocrine and endocrine function of the pancreas and for prospectively stratifying the cardiac iron risk. The following article should be a sort of practical guide for radiologists interested in quantifying pancreatic iron overload by Magnetic Resonance Imaging (MRI). After a brief background on iron-deposition diseases, we will describe basic principles and relative advantages and disadvantages of the more widely used and clinically feasible MRI-based techniques for pancreatic iron assessment. These methods can be classified into signal intensity ratio (SIR) and relaxometry methods. We will examine different technical aspects representing the key for accurate and precise relaxation time measurement.
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Affiliation(s)
- Antonella Meloni
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, Via Moruzzi, 1, 56124, Pisa, Italy
- U.O.C. Bioingegneria, Fondazione G. Monasterio CNR-Regione Toscana, Pisa, Italy
| | - Vincenzo Positano
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, Via Moruzzi, 1, 56124, Pisa, Italy
- U.O.C. Bioingegneria, Fondazione G. Monasterio CNR-Regione Toscana, Pisa, Italy
| | - Laura Pistoia
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, Via Moruzzi, 1, 56124, Pisa, Italy
| | - Filippo Cademartiri
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, Via Moruzzi, 1, 56124, Pisa, Italy.
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17
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Triadyaksa P, Overbosch J, Oudkerk M, Sijens PE. T2* assessment of the three coronary artery territories of the left ventricular wall by different monoexponential truncation methods. MAGNETIC RESONANCE MATERIALS IN PHYSICS, BIOLOGY AND MEDICINE 2022; 35:749-763. [PMID: 35437686 PMCID: PMC9463254 DOI: 10.1007/s10334-022-01008-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 02/04/2022] [Accepted: 03/18/2022] [Indexed: 11/28/2022]
Abstract
Abstract
Objectives
This study aimed at evaluating left ventricular myocardial pixel-wise T2* using two truncation methods for different iron deposition T2* ranges and comparison of segmental T2* in different coronary artery territories.
Material and methods
Bright blood multi-gradient echo data of 30 patients were quantified by pixel-wise monoexponential T2* fitting with its R2 and SNR truncation. T2* was analyzed at different iron classifications. At low iron classification, T2* values were also analyzed by coronary artery territories.
Results
The right coronary artery has a significantly higher T2* value than the other coronary artery territories. No significant difference was found in classifying severe iron by the two truncation methods in any myocardial region, whereas in moderate iron, it is only apparent at septal segments. The R2 truncation produces a significantly higher T2* value than the SNR method when low iron is indicated.
Conclusion
Clear T2* differentiation between the three coronary territories by the two truncation methods is demonstrated. The two truncation methods can be used interchangeably in classifying severe and moderate iron deposition at the recommended septal region. However, in patients with low iron indication, different results by the two truncation methods can mislead the investigation of early iron level progression.
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Affiliation(s)
- Pandji Triadyaksa
- University of Groningen, 9700 RB, Groningen, The Netherlands.
- Departemen Fisika, Universitas Diponegoro, Fakultas Sains Dan Matematika, Prof. Sudharto street, Semarang, 50275, Indonesia.
| | - Jelle Overbosch
- Department of Radiology, University of Groningen, University Medical Center Groningen, EB45, PO Box 30001, 9700 RB, Groningen, The Netherlands
| | - Matthijs Oudkerk
- University of Groningen, 9700 RB, Groningen, The Netherlands
- Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Paul Eduard Sijens
- University of Groningen, 9700 RB, Groningen, The Netherlands
- Department of Radiology, University of Groningen, University Medical Center Groningen, EB45, PO Box 30001, 9700 RB, Groningen, The Netherlands
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18
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Chen XL, Chen GW, Zhou P, Li H. Association of the Liver and Spleen Signal Intensity on MRI with Anemia in Gynecological Cancer. Curr Med Imaging 2022; 18:931-938. [PMID: 35255792 DOI: 10.2174/1568026622666220307123736] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/25/2021] [Accepted: 12/20/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE This study is to investigate the association of the liver and spleen signal intensity on MRI with anemia in patients with gynecologic cancer. METHODS 332 patients with gynecological cancer and 78 healthy women underwent MRI examination. Liver and spleen MRI parameters and laboratory tests were obtained within 1 week. The signal intensity ratios of liver and spleen to the paraspinous muscle were calculated on gradient echo T1-weighted images (T1WI) and T2-weighted images (T2WI) in both patients and healthy women, respectively. RESULTS The ratios of liver and spleen to paraspinous muscle on T1WI and T2WI were lower in patients than in the healthy women, respectively (all P<0.0001). The ratios of the liver and spleen to paraspinous muscle on T1WI and T2WI decreased with the increasing stage of anemia and decreasing of the hemoglobin levels (all P<0.001). The ratios of the liver to paraspinous muscle on T1WI, spleen to paraspinous muscle on T1WI, and the liver and spleen to paraspinous muscle on T2WI could predict anemia stage≥1 (AUC=0.576, 0.643, 0.688, and 0.756, respectively), ≥2 (AUC=0.743, 0.714, 0.891, and 0.922, respectively) and 3 (AUC=0.851, 0.822, 0.854, and 0.949, respectively). CONCLUSION T2WI-based spleen signal intensity ratios showed the highest potential for noninvasive evaluation of anemia in gynecological cancer.
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Affiliation(s)
- Xiao-Li Chen
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China
| | - Guang-Wen Chen
- Department of Radiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People\'s Hospital
| | - Peng Zhou
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China
| | - Hang Li
- Department of Radiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People\'s Hospital
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19
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Kaban S, Damar Ç. Interrelationship between liver T2*-weighted magnetic resonance imaging and acoustic radiation force impulse elastography measurement results and plasma ferritin levels in children with β-thalassemia major. JOURNAL OF CLINICAL ULTRASOUND : JCU 2022; 50:108-116. [PMID: 34716933 DOI: 10.1002/jcu.23095] [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: 07/17/2021] [Revised: 10/12/2021] [Accepted: 10/16/2021] [Indexed: 06/13/2023]
Abstract
PURPOSE To evaluate correlation and agreement between T2*-weighted magnetic resonance imaging (T2*-wMRI), acoustic radiation force impulse elastography (ARFI-e) measurement results of liver and plasma ferritin levels (PFLs) in children with β-thalassemia major (β-TM). METHODS The study included 40 pediatric patients (aged 64-216 months; 14 girls, 26 boys) receiving blood transfusion and chelation therapy. To detect the severity of liver iron overload (LIO) and concomitant parenchymal fibrosis, T2*-wMRI and ARFI-e measurements were performed from the right lobe segments. Student's t-test, Mann-Whitney U, ANOVA, Spearman's test and ICC were used for statistical analysis. RESULTS After the measurements of T2*-wMRI, patients were grouped as normal in 4 (10%), mild in 11 (27.5%), moderate in 21 (52.5%), and severe in 4 (10%) cases in terms of LIO. Combined moderate and severe groups had significantly higher ARFI-e and PFL values than the combination of other groups (p = .001, p = .040). The ARFI-e measurements of boys were found to be significantly higher than those of girls (p = .023). A strong negative correlation between T2*-wMRI and ARFI-e and a moderate negative correlation between T2*-wMRI and PFL were detected (p;r = 0.001;-0.606, p;r = 0.009; -0.407). A strong positive correlation was found between ARFI-e values and PFL (p;r = 0.001; 0.659). The optimal cut-off value of ARFI-e to predict liver fibrosis because of moderate&severe LIO was determined to be 1.29 M/s (80% sensitivity and 88% specificity). A moderate agreement was observed between the T2*-wMRI and ARFI-e methods [ICC: 0.680, 95% CI: (0.470 to 0.817)]. CONCLUSION Given the strong correlation and moderate agreement between ARFI-e and T2*-wMRI, ARFI -e could be used to monitor LIO in children with β-TM.
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Affiliation(s)
- Selami Kaban
- Faculty of Medicine, Department of Radiology, Gaziantep University, Gaziantep, Turkey
| | - Çağrı Damar
- Faculty of Medicine, Department of Radiology, Gaziantep University, Gaziantep, Turkey
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20
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Peng H, Cheng C, Wan Q, Jia S, Wang S, Lv J, Liang D, Liu W, Liu X, Zheng H, Zou C. Fast multi-parametric imaging in abdomen by B 1 + corrected dual-flip angle sequence with interleaved echo acquisition. Magn Reson Med 2021; 87:2194-2208. [PMID: 34888911 DOI: 10.1002/mrm.29127] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 11/28/2021] [Accepted: 11/29/2021] [Indexed: 11/07/2022]
Abstract
PURPOSE To achieve simultaneous T1, w /proton density fat fraction (PDFF)/ R 2 ∗ mapping in abdomen within a single breadth-hold, and validate the accuracy using state-of-art measurement. THEORY AND METHODS An optimized multiple echo gradient echo (GRE) sequence with dual flip-angle acquisition was used to realize simultaneous water T1 (T1, w )/PDFF/ R 2 ∗ quantification. A new method, referred to as "solving the fat-water ambiguity based on their T1 difference" (SORT), was proposed to address the fat-water separation problem. This method was based on the finding that compared to the true solution, the wrong (or aliased) solution to fat-water separation problem showed extra dependency on the applied flip angle due to the T1 difference between fat and water. The B 1 + measurement sequence was applied to correct the B 1 + inhomogeneity for T1, w relaxometry. The 2D parallel imaging was incorporated to enable the acquisition within a single breath-hold in abdomen. RESULTS The multi-parametric quantification results of the proposed method were consistent with the results of reference methods in phantom experiments (PDFF quantification: R2 = 0.993, mean error 0.73%; T1, w quantification: R2 = 0.999, mean error 4.3%; R 2 ∗ quantification: R2 = 0.949, mean error 4.07 s-1 ). For volunteer studies, robust fat-water separation was achieved without evident fat-water swaps. Based on the accurate fat-water separation, simultaneous T1, w /PDFF/ R 2 ∗ quantification was realized for whole liver within a single breath-hold. CONCLUSION The proposed method accurately quantified T1, w /PDFF/ R 2 ∗ for the whole liver within a single breath-hold. This technique serves as a quantitative tool for disease management in patients with hepatic steatosis.
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Affiliation(s)
- Hao Peng
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chuanli Cheng
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Qian Wan
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Sen Jia
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Shuai Wang
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jianxun Lv
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Dong Liang
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Wenzhong Liu
- School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, China
| | - Xin Liu
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Hairong Zheng
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Chao Zou
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advance Technology, Chinese Academy of Sciences, Shenzhen, China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
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21
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Wang C, Reeder SB, Hernando D. Relaxivity-iron calibration in hepatic iron overload: Reproducibility and extension of a Monte Carlo model. NMR IN BIOMEDICINE 2021; 34:e4604. [PMID: 34462976 PMCID: PMC9019851 DOI: 10.1002/nbm.4604] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 07/12/2021] [Accepted: 08/01/2021] [Indexed: 05/04/2023]
Abstract
The aim of this study was to reproduce relaxivity-iron calibration in hepatic iron overload using a Monte Carlo model, and further extend the model with multiple spin echo (MSE) imaging. As previously reported, relationships between relaxation rates ( R2* and single spin echo R2 ) and liver iron concentration (LIC) can be characterized by a Monte Carlo model incorporating realistic liver structure, iron distribution, and proton mobility. In this study, relaxivity-iron calibration curves at 1.5 and 3.0 T were simulated using the Monte Carlo model. Furthermore, the model was extended with MSE imaging, and iron calibrations were evaluated using two different fitting models: mononexponential with a constant offset and nonmonoexponential. Results consistent with previous empirical calibrations and Monte Carlo predictions were accurately reproduced for relaxivity-iron calibration. The predicted R2* and single spin echo R2 increased by a factor of 2.00 and 1.51, respectively, at 1.5 versus 3.0 T. MSE signals and their corresponding R2 depended strongly on LIC, interecho time, and field strength. Preliminary results showed that a nonmonoexponential model accurately characterizes the simulated MSE signals, and that strong correlations were found between predicted relaxation parameters and LIC. In conclusion, relaxivity-iron calibration is reproducible using the proposed Monte Carlo model. Furthermore, this model can be readily extended to other important applications, including predicting signal behavior for MSE imaging.
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Affiliation(s)
- Changqing Wang
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
- 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, Wisconsin, 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
- Corresponding author: Diego Hernando, PhD, Room 2474, Wisconsin Institutes for Medical Research (WIMR-2), 1111 Highland Avenue, Madison, WI 53705, (608) 265-7590,
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22
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Evaluation of liver T1 using MOLLI gradient echo readout under the influence of fat. Magn Reson Imaging 2021; 85:57-63. [PMID: 34678435 DOI: 10.1016/j.mri.2021.10.020] [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: 06/26/2021] [Revised: 10/14/2021] [Accepted: 10/16/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The effect of hepatic steatosis on the gradient-echo (GRE) based Modified Look-Locker Inversion Recovery (MOLLI) technique for T1 mapping has not been evaluated. The purpose of this study was to evaluate a GRE based MOLLI technique for hepatic T1 mapping and determine the relationship of T1 differences (ΔT1) on in-phase (IP) and out-of-phase (OP) to fat fraction (FF) measurement. MATERIALS AND METHODS 3 T MRI included MOLLI T1 mapping with TE = 1.3 (OP), 2.4 (IP), and 1.8 ms, and chemical-shift-encoded sequence with spectral modeling of fat to generate FF map as a reference. Bloch simulations and oil/water phantoms were used to characterize the response of the MOLLI T1 in various FF < 30% since MOLLI T1 estimation was erratic beyond this limit. Curve fit between ΔT1 and FF from simulation was applied to validate the phantom and the in-vivo results. Thirty-eight normal volunteers were included (16 women, Age 44 ± 12 years, BMI 27 ± 5.3 kg/m2). MOLLI water images were reconstructed by the average of OP and IP images, and the T1 values on water images served as the reference for T1 bias calculation defined as the percent difference between OP, IP, TE = 1.8 ms and the referenced water T1. Linear regression was performed to correlate the FF quantified by the reference and MOLLI methods. RESULTS Phantom results were consistent with the Bloch simulations. The simulated relationship between FF (0-30%) and ΔT1 could be modeled precisely by a cubic equation with R2 = 1. In-vivo MOLLI ΔT1 and estimated FF were correlated to the reference FF (both R2 ≥ 0.96 and P < 0.001). TE = 1.8 ms demonstrated less T1 bias (-1.34%) compared to TE = OP (5.32%) or IP (-3.8%, both P < 0.001). CONCLUSION At 3 T, TE of 1.8 ms can be used to reduce the T1 bias and deliver consistent T1 values when FF is <30%.
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23
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Simchick G, Zhao R, Hamilton G, Reeder SB, Hernando D. Spectroscopy-based multi-parametric quantification in subjects with liver iron overload at 1.5T and 3T. Magn Reson Med 2021; 87:597-613. [PMID: 34554595 DOI: 10.1002/mrm.29021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 08/13/2021] [Accepted: 09/07/2021] [Indexed: 01/02/2023]
Abstract
PURPOSE To evaluate the precision profile (repeatability and reproducibility) of quantitative STEAM-MRS and to determine the relationships between multiple MR biomarkers of chronic liver disease in subjects with iron overload at both 1.5 Tesla (T) and 3T. METHODS MRS data were acquired in patients with known or suspected liver iron overload. Two STEAM-MRS sequences (multi-TE and multi-TE-TR) were acquired at both 1.5T and 3T (same day), including test-retest acquisition. Each acquisition enabled estimation of R1, R2, and FWHM (each separately for water and fat); and proton density fat fraction. The test-retest repeatability and reproducibility across acquisition modes (multi-TE vs. multi-TE-TR) of the estimates were evaluated using intraclass correlation coefficients, linear regression, and Bland-Altman analyses. Multi-parametric relationships between parameters at each field strength, across field strengths, and with liver iron concentration were also evaluated using linear and nonlinear regression. RESULTS Fifty-six (n = 56) subjects (10 to 73 years, 37 males/19 females) were successfully recruited. Both STEAM-MRS sequences demonstrated good-to-excellent precision (intraclass correlation coefficient ≥ 0.81) for the quantification of R1water , R2water , FWHMwater , and proton density fat fraction at both 1.5T and 3T. Additionally, several moderate (R2 = 0.50 to 0.69) to high (R2 ≥ 0.70) correlations were observed between biomarkers, across field strengths, and with liver iron concentration. CONCLUSIONS Over a broad range of liver iron concentration, STEAM-MRS enables rapid and precise measurement of multiple biomarkers of chronic liver disease. By evaluating the multi-parametric relationships between biomarkers, this work may advance the comprehensive MRS-based assessment of chronic liver disease and may help establish biomarkers of chronic liver disease.
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Affiliation(s)
- Gregory Simchick
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ruiyang Zhao
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Gavin Hamilton
- Department of Radiology, University of California, San Diego, California, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
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24
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Auti OB, Bandekar K, Kamat N, Raj V. Cardiac magnetic resonance techniques: Our experience on wide bore 3 tesla magnetic resonance system. Indian J Radiol Imaging 2021; 27:404-412. [PMID: 29379234 PMCID: PMC5761166 DOI: 10.4103/ijri.ijri_503_16] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Cardiovascular magnetic resonance (CMR) has become a widely adapted imaging modality in the diagnosis and management of patients with cardiovascular diseases. It provides unparalleled data of cardiac function and myocardial morphology. Majority of CMR imaging is currently being performed on 1.5 Tesla (T) MR systems. Over the last many years, the cardiac imaging protocols have been standardized and optimized in the 1.5T systems. 3T MR systems are now being used more and more in small and large institutions in our country due to their proven advantages in the field of neuro, body, and musculoskeletal imaging. Cardiac imaging on 3T system can be a double-edged sword. On one hand, it may provide nondiagnostic images due to significant artifacts, and on the other hand, it may complete the examination in quick time and provide excellent quality images. It is therefore important for the user to be aware of the potential pitfalls of CMR in 3T systems and also the necessary steps to avoid them. In this study, we discuss various challenges and advantages of performing CMR in a 3T system. We also present potential technical solutions to improve the image quality.
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Affiliation(s)
- Onkar B Auti
- Department of Radio-diagnosis, Narayana Health City, Bengaluru, Karnataka, India.,Department of Radio-diagnosis, Jupiter Hospital, Thane, Maharashtra, India
| | - Kalashree Bandekar
- Department of Radio-diagnosis, Jupiter Hospital, Thane, Maharashtra, India
| | - Nikhil Kamat
- Department of Radio-diagnosis, Jupiter Hospital, Thane, Maharashtra, India
| | - Vimal Raj
- Department of Radio-diagnosis, Narayana Health City, Bengaluru, Karnataka, India
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25
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Gassenmaier S, Kähm K, Walter SS, Machann J, Nikolaou K, Bongers MN. Quantification of liver and muscular fat using contrast-enhanced Dual Source Dual Energy Computed Tomography compared to an established multi-echo Dixon MRI sequence. Eur J Radiol 2021; 142:109845. [PMID: 34271430 DOI: 10.1016/j.ejrad.2021.109845] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/17/2021] [Accepted: 07/02/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE To investigate the feasibility of liver fat quantification in contrast-enhanced dual source dual energy computed tomography (DECT) using multi-echo Dixon magnetic resonance imaging (MRI) as reference standard. METHOD Patients who underwent MRI of the liver including a multi-echo Dixon sequence for estimation of proton density fat fraction in 2017 as well as contrast-enhanced DECT imaging of the abdomen were included in this retrospective, monocentric IRB approved study. Furthermore, patients with a hepatic fat amount >5% who were examined in 2018 with MRI and DECT were included. The final study group consisted of 81 patients with 90 pairs of examinations. Analysis of parameter maps was performed manually using congruent regions of interest which were placed in the liver parenchyma, in the erector spinae muscles, and psoas major muscles. RESULTS Mean patient age was 61 ± 13 years. Median time between MRI and DECT was 48 days. MRI liver fat quantification resulted in a median of 3.8% (IQR: 2.2-8.2%) compared to 1.8% (IQR: 0-6.3%) in DECT (p < 0.001), with a Spearman correlation of 0.73. Bland-Altman analysis resulted in a systematic underestimation of liver fat in DECT, with a mean difference of -1.7%. Fat quantification in the erector spinae muscles (p = 0.257) and the psoas major muscles (p = 0.208) was not significantly different in DECT compared to MRI. CONCLUSIONS Liver and muscular fat quantification in portal-venous phase DECT is feasible with good to excellent correlation compared to a multi-echo Dixon MRI sequence analysis. While there is an underestimation of the liver fat content in DECT, there are no significant differences between DECT and MRI fat quantification of the erector spinae and psoas major muscles.
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Affiliation(s)
- Sebastian Gassenmaier
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany
| | - Karin Kähm
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany
| | - Sven S Walter
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany
| | - Jürgen Machann
- Section of Experimental Radiology, Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany; Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Centre Munich at the University of Tübingen, Tübingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany
| | - Malte N Bongers
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany.
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26
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Pituitary Volume and Iron Overload Evaluation by 3T MRI in Thalassemia. Indian J Pediatr 2021; 88:656-662. [PMID: 33675027 DOI: 10.1007/s12098-020-03629-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 12/16/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To evaluate pituitary volume and iron overload in beta thalassemia major, with the objective of assessing the reliability of this method in predicting hypogonadism. METHODS 3T MRI was used to measure pituitary R2 and T2* in 57 beta thalassemia major patients and 30 controls. Anterior pituitary volume was evaluated by MRI planimetry. Cardiac, hepatic, and pancreatic iron overload were also assessed using MRI T2*. Mean serum ferritin was estimated by sandwich immuno-assay. Short stature was defined as height < 3 rd percentile for age, and clinical hypogonadism defined as absence of secondary sexual characteristics at ages ≥ 13 y for females and ≥ 14 y for males. RESULTS Short stature was present in 32 patients (56.1%). Of the 47 patients in the pubertal age group, 11(23.4%) had hypogonadism. Serum ferritin correlated positively with pituitary R2 (p = 0.004) and negatively with anterior pituitary volume (p = 0.006), whereas pituitary R2 correlated negatively with cardiac T2* (p = 0.001). Patients with hypogonadism had lower pituitary R2 (p = 0.186), T2* (p = 0.048), and anterior pituitary volumes (p = 0.012) compared to those with normal sexual maturity. Regardless of stature, no significant difference was observed between pituitary R2 (p = 0.267) and T2* (p = 0.451). Mean pituitary R2 in patients (78.99 Hz) was higher than in controls (20.8 Hz) (p = 0.0001). Anterior pituitary volume was lower in patients (264.83 mm3) than in controls (380.87 mm3) (p = 0.0001). A threshold value of 22.85 Hz for pituitary R2 gave a sensitivity of 84.2% and a specificity of 73.3% in distinguishing pituitary iron content of patients from controls, with an area of 0.864 under the ROC curve. CONCLUSIONS 3T MRI is a reliable method to detect pituitary iron overload and predict risk of hypogonadism in beta Thalassemia.
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Abstract
Iron overload is a common clinical problem resulting from hereditary hemochromatosis or secondary hemosiderosis (mainly associated with transfusion therapy), being also associated with chronic liver diseases and metabolic disorders. Excess of iron accumulates in organs like the liver, pancreas and heart. Without treatment, patients with iron overload disorders will develop liver cirrhosis, diabetes and cardiomyopathy. Iron quantification is therefore crucial not only for diagnosis of iron overload but also to monitor iron-reducing therapies. Liver iron concentration is considered the surrogate marker of total body iron stores. Because liver biopsy is invasive and prone to high variability and sampling bias, MR imaging has emerged as a non-invasive method and gained wide acceptance, now being considered the standard of care for assessing iron overload. Nevertheless, there are different MR techniques for iron quantification and there is still no consensus about the best technique or postprocessing tool for hepatic iron quantification, with the choice of imaging technique depending mainly on the local expertise as well on the available equipment and software. Because different methods should not be used interchangeably, it is important to choose one method and use the same one when following up patients over time.
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Affiliation(s)
- Manuela França
- Radiology Department - Centro Hospitalar Universitário do Porto, Largo Prof Abel Salazar, 4099-001, Porto, Portugal.
- Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, I3S, Instituto de Investigação e Inovação em Saúde, Porto, Portugal.
| | - João Gomes Carvalho
- Radiology Department - Centro Hospitalar Universitário do Porto, Largo Prof Abel Salazar, 4099-001, Porto, Portugal
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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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Mojtahed A, Gee MS, Yokoo T. Pearls and Pitfalls of Metabolic Liver Magnetic Resonance Imaging in the Pediatric Population. Semin Ultrasound CT MR 2020; 41:451-461. [DOI: 10.1053/j.sult.2020.05.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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Real-World Experience Measurement of Liver Iron Concentration by R2 vs. R2 Star MRI in Hemoglobinopathies. Diagnostics (Basel) 2020; 10:diagnostics10100768. [PMID: 33003498 PMCID: PMC7601611 DOI: 10.3390/diagnostics10100768] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 09/16/2020] [Accepted: 09/23/2020] [Indexed: 01/19/2023] Open
Abstract
Background: Non-invasive determination of liver iron concentration (LIC) is a valuable tool that guides iron chelation therapy in transfusion-dependent patients. Multiple methods have been utilized to measure LIC by MRI. The purpose of this study was to compare free breathing R2* (1/T2*) to whole-liver Ferriscan R2 method for estimation of LIC in a pediatric and young adult population who predominantly have hemoglobinopathies. Methods: Clinical liver and cardiac MRI scans from April 2016 to May 2018 on a Phillips 1.5 T scanner were reviewed. Free breathing T2 and T2* weighted images were acquired on each patient. For T2, multi-slice spin echo sequences were obtained. For T2*, a single mid-liver slice fast gradient echo was performed starting at 0.6 ms with 1.2 ms increments with signal averaging. R2 measurements were performed by Ferriscan analysis. R2* measurements were performed by quantitative T2* map analysis. Results: 107 patients underwent liver scans with the following diagnoses: 76 sickle cell anemia, 20 Thalassemia, 9 malignancies and 2 Blackfan Diamond anemia. Mean age was 12.5 ± 4.5 years. Average scan time for R2 sequences was 10 min, while R2* sequence time was 20 s. R2* estimation of LIC correlated closely with R2 with a correlation coefficient of 0.94. Agreement was strongest for LIC < 15 mg Fe/g dry weight. Overall bias from Bland–Altman plot was 0.66 with a standard deviation of 2.8 and 95% limits of agreement −4.8 to 6.1. Conclusion: LIC estimation by R2* correlates well with R2-Ferriscan in the pediatric age group. Due to the very short scan time of R2*, it allows imaging without sedation or anesthesia. Cardiac involvement was uncommon in this cohort.
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Complex confounder-corrected R2* mapping for liver iron quantification with MRI. Eur Radiol 2020; 31:264-275. [PMID: 32785766 DOI: 10.1007/s00330-020-07123-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 06/05/2020] [Accepted: 07/30/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES MRI-based R2* mapping may enable reliable and rapid quantification of liver iron concentration (LIC). However, the performance and reproducibility of R2* across acquisition protocols remain unknown. Therefore, the objective of this work was to evaluate the performance and reproducibility of complex confounder-corrected R2* across acquisition protocols, at both 1.5 T and 3.0 T. METHODS In this prospective study, 40 patients with suspected iron overload and 10 healthy controls were recruited with IRB approval and informed written consent and imaged at both 1.5 T and 3.0 T. For each subject, acquisitions included four different R2* mapping protocols at each field strength, and an FDA-approved R2-based method performed at 1.5 T as a reference for LIC. R2* maps were reconstructed from the complex data acquisitions including correction for noise effects and fat signal. For each subject, field strength, and R2* acquisition, R2* measurements were performed in each of the nine liver Couinaud segments and the spleen. R2* measurements were compared across protocols and field strength (1.5 T and 3.0 T), and R2* was calibrated to LIC for each acquisition and field strength. RESULTS R2* demonstrated high reproducibility across acquisition protocols (p > 0.05 for 96/108 pairwise comparisons across 2 field strengths and 9 liver segments, ICC > 0.91 for each field strength/segment combination) and high predictive ability (AUC > 0.95 for four clinically relevant LIC thresholds). Calibration of R2* to LIC was LIC = - 0.04 + 2.62 × 10-2 R2* at 1.5 T and LIC = 0.00 + 1.41 × 10-2 R2* at 3.0 T. CONCLUSIONS Complex confounder-corrected R2* mapping enables LIC quantification with high reproducibility across acquisition protocols, at both 1.5 T and 3.0 T. KEY POINTS • Confounder-corrected R2* of the liver provides reproducible R2* across acquisition protocols, including different spatial resolutions, echo times, and slice orientations, at both 1.5 T and 3.0 T. • For all acquisition protocols, high correlation with R2-based liver iron concentration (LIC) quantification was observed. • The calibration between confounder-corrected R2* and LIC, at both 1.5 T and 3.0 T, is determined in this study.
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Yoon H, Shin HJ, Kim MJ, Lee MJ. Quantitative Imaging in Pediatric Hepatobiliary Disease. Korean J Radiol 2020; 20:1342-1357. [PMID: 31464113 PMCID: PMC6715564 DOI: 10.3348/kjr.2019.0002] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Accepted: 06/11/2019] [Indexed: 02/07/2023] Open
Abstract
Pediatric hepatobiliary imaging is important for evaluation of not only congenital or structural disease but also metabolic or diffuse parenchymal disease and tumors. A variety of ultrasonography and magnetic resonance imaging (MRI) techniques can be used for these assessments. In ultrasonography, conventional ultrasound imaging as well as vascular imaging, elastography, and contrast-enhanced ultrasonography can be used, while in MRI, fat quantification, T2/T2* mapping, diffusion-weighted imaging, magnetic resonance elastography, and dynamic contrast-enhanced MRI can be performed. These techniques may be helpful for evaluation of biliary atresia, hepatic fibrosis, nonalcoholic fatty liver disease, sinusoidal obstruction syndrome, and hepatic masses in children. In this review, we discuss each tool in the context of management of hepatobiliary disease in children, and cover various imaging techniques in the context of the relevant physics and their clinical applications for patient care.
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Affiliation(s)
- Haesung Yoon
- Department of Radiology, Severance Hospital, Severance Pediatric Liver Disease Research Group, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Hyun Joo Shin
- Department of Radiology, Severance Hospital, Severance Pediatric Liver Disease Research Group, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Myung Joon Kim
- Department of Radiology, Severance Hospital, Severance Pediatric Liver Disease Research Group, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea
| | - Mi Jung Lee
- Department of Radiology, Severance Hospital, Severance Pediatric Liver Disease Research Group, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea.
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Analysis and correction of off‐resonance artifacts in echo‐planar cardiac diffusion tensor imaging. Magn Reson Med 2020; 84:2561-2576. [DOI: 10.1002/mrm.28318] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 04/18/2020] [Accepted: 04/20/2020] [Indexed: 01/19/2023]
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Ma Q, Hu J, Yang W, Hou Y. Dual-layer detector spectral CT versus magnetic resonance imaging for the assessment of iron overload in myelodysplastic syndromes and aplastic anemia. Jpn J Radiol 2020; 38:374-381. [PMID: 31989387 DOI: 10.1007/s11604-020-00921-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Accepted: 01/09/2020] [Indexed: 11/28/2022]
Abstract
BACKGROUND The purpose of this study is to investigate the performance of dual-layer detector spectral CT for iron deposition compared to magnetic resonance imaging (MRI) T2* imaging. METHODS Thirty-one patients with a clinical history of myelodysplastic syndromes and aplastic anemia underwent liver and cardiac T2*-weighted unenhanced MRI on a three-tesla MRI scanner, and underwent unenhanced CT scan laterally on a 128-row spectral detector CT. R2* values of the liver, septal muscle, and paraspinal muscle were calculated. Attenuation differences (ΔH) in the liver and myocardium were calculated between the lower (50 keV) and higher (120 keV) energy levels. RESULTS The liver and cardiac T2* values were 9.54 ± 5.63 ms and 21.41 ± 2.44 ms, respectively. The liver-to-muscle and myocardium-to-muscle T2* value ratios were 0.37 ± 0.23 and 0.79 ± 0.19, respectively. The liver and cardiac ΔH were - 1.13 ± 4.24 HU and 2.22 ± 4.41 HU, respectively. There was a strong linear correlation between the liver R2* and ΔH (r = - 0.832, P < 0.001), but weak correlation existed between the cardiac R2* and ΔH (P = 0.041). CONCLUSIONS Dual-layer detector spectral unenhanced CT seemed to be equally valuable to MRI T2* imaging for evaluating liver iron overload.
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Affiliation(s)
- Quanmei Ma
- Department of Radiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, 110004, Liaoning, People's Republic of China
| | - Juan Hu
- Department of Hematology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, 110004, Liaoning, People's Republic of China
| | - Wei Yang
- Department of Hematology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, 110004, Liaoning, People's Republic of China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, 110004, Liaoning, People's Republic of China.
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Menacho K, Abdel-Gadir A, Moon JC, Fernandes JL. T2* Mapping Techniques: Iron Overload Assessment and Other Potential Clinical Applications. Magn Reson Imaging Clin N Am 2020; 27:439-451. [PMID: 31279448 DOI: 10.1016/j.mric.2019.04.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
T2* mapping techniques has evolved significantly since their introduction in the early 2000s and a significant amount of evidence has been gathered to support their clinical routine use for iron overload assessment. This article focuses on the most important aspects of how to perform T2* imaging, from acquisition, to postprocessing, to analyzing the data with clinical concentration. Newer techniques have made T2* mapping more robust and accurate, allowing a broader use of this technique for noncontrast ischemia imaging based on blood oxygen levels, in addition to evaluation of intramyocardial hemorrhage and microvascular obstruction.
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Affiliation(s)
- Katia Menacho
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit, Institute of Cardiovascular Science, University College London, St Bartholomew's Hospital, 2nd Floor, King George V Block, West Smithfiled, London EC1A 7BE, UK
| | - Amna Abdel-Gadir
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E6BT, UK; Barts Heart Centre, St Bartholomew's Hospital, 2nd Floor, King George V Block, London EC1A 7BE, UK
| | - James C Moon
- The Cardiovascular Magnetic Resonance Imaging Unit, The Inherited Cardiovascular Diseases Unit, Barts Heart Centre, St Bartholomew's Hospital, 2nd Floor, King George V Block, West Smithfield, London EC1A 7BE, UK
| | - Juliano Lara Fernandes
- Jose Michel Kalaf Research Institute, Radiologia Clinica de Campinas, Av Jose de Souza Campos 840, Campinas, São Paulo 13092-100, Brazil.
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Triadyaksa P, Oudkerk M, Sijens PE. Cardiac T 2 * mapping: Techniques and clinical applications. J Magn Reson Imaging 2019; 52:1340-1351. [PMID: 31837078 PMCID: PMC7687175 DOI: 10.1002/jmri.27023] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 11/25/2019] [Indexed: 12/12/2022] Open
Abstract
Cardiac T2* mapping is a noninvasive MRI method that is used to identify myocardial iron accumulation in several iron storage diseases such as hereditary hemochromatosis, sickle cell disease, and β‐thalassemia major. The method has improved over the years in terms of MR acquisition, focus on relative artifact‐free myocardium regions, and T2* quantification. Several improvement factors involved include blood pool signal suppression, the reproducibility of T2* measurement as affected by scanner hardware, and acquisition software. Regarding the T2* quantification, improvement factors include the applied curve‐fitting method with or without truncation of the signals acquired at longer echo times and whether or not T2* measurement focuses on multiple segmental regions or the midventricular septum only. Although already widely applied in clinical practice, data processing still differs between centers, contributing to measurement outcome variations. State of the art T2* measurement involves pixelwise quantification providing better spatial iron loading information than region of interest‐based quantification. Improvements have been proposed, such as on MR acquisition for free‐breathing mapping, the generation of fast mapping, noise reduction, automatic myocardial contour delineation, and different T2* quantification methods. This review deals with the pro and cons of different methods used to quantify T2* and generate T2* maps. The purpose is to recommend a combination of MR acquisition and T2* mapping quantification techniques for reliable outcomes in measuring and follow‐up of myocardial iron overload. The clinical application of cardiac T2* mapping for iron overload's early detection, monitoring, and treatment is addressed. The prospects of T2* mapping combined with different MR acquisition methods, such as cardiac T1 mapping, are also described. Level of Evidence: 4 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019.
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Affiliation(s)
- Pandji Triadyaksa
- University of Groningen, Groningen, The Netherlands.,Universitas Diponegoro, Department of Physics, Faculty of Science and Mathematics, Semarang, Indonesia
| | - Matthijs Oudkerk
- University of Groningen, Groningen, The Netherlands.,Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Paul E Sijens
- University of Groningen, Groningen, The Netherlands.,University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands
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A hybrid (iron–fat–water) phantom for liver iron overload quantification in the presence of contaminating fat using magnetic resonance imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 33:385-392. [DOI: 10.1007/s10334-019-00795-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/29/2019] [Accepted: 10/30/2019] [Indexed: 12/19/2022]
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Wáng YXJ, Wang X, Wu P, Wang Y, Chen W, Chen H, Li J. Topics on quantitative liver magnetic resonance imaging. Quant Imaging Med Surg 2019; 9:1840-1890. [PMID: 31867237 DOI: 10.21037/qims.2019.09.18] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.
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Affiliation(s)
- Yì Xiáng J Wáng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, New Territories, Hong Kong SAR, China
| | | | - Peng Wu
- Philips Healthcare (Suzhou) Co., Ltd., Suzhou 215024, China
| | - Yajie Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Weibo Chen
- Philips Healthcare, Shanghai 200072, China.,Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jianqi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
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Zhan C, Olsen S, Zhang HC, Kannengiesser S, Chandarana H, Shanbhogue KP. Detection of hepatic steatosis and iron content at 3 Tesla: comparison of two-point Dixon, quantitative multi-echo Dixon, and MR spectroscopy. Abdom Radiol (NY) 2019; 44:3040-3048. [PMID: 31286208 DOI: 10.1007/s00261-019-02118-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
PURPOSE To compare qualitative results obtained from computer-aided dual-ratio analysis on T1-weighted two-point Dixon, with T2*-corrected multi-echo Dixon and T2-corrected multi-echo single-voxel MR spectroscopy sequence (MRS) for evaluation of liver fat and iron at 3T. METHODS AND MATERIALS This retrospective, HIPAA-compliant, IRB-approved study included 479 patients with known or suspected liver disease. Two-point Dixon, multi-echo Dixon, and MR spectroscopy sequences were performed for each patient at 3T. A receiver-operating characteristic analysis was performed to compare the diagnostic performance in 80 patients using biopsy as the standard. Sensitivity, specificity, PPV, and NPV of qualitative two-point Dixon results, multi-echo Dixon (PDFF and R2*), and MRS (fat fraction and R2 water) for detection of hepatic steatosis and siderosis were assessed. RESULTS Fat fractions obtained from MRS and multi-echo Dixon have equivalent accuracy for detection of hepatic steatosis (AUC, sensitivity and specificity: 0.90 vs 0.88, 0.77 vs. 0.82, and 0.90 vs. 0.82), but the optimal cutoff value is higher for MRS (6.05% vs. 3.4%). The dual-ratio Dixon discrimination technique showed high negative predictive value for detection of hepatic steatosis and siderosis (0.90 and 0.94, respectively). R2* from multi-echo Dixon and R2water from MRS have equivalent accuracy for detection of iron overload at 3T (AUC 0.89 vs. 0.88). The optimal cutoff for R2* and R2water are 60.5 s-1 and 40.85 s-1, respectively. CONCLUSION The computer-aided dual-ratio discrimination with two-point Dixon is a useful qualitative screening tool with high negative predictive value for hepatic steatosis and iron overload. Multi-echo Dixon and MRS have similar accuracy for detection of hepatic steatosis and iron overload at 3 Tesla.
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Affiliation(s)
- Chenyang Zhan
- Department of Radiology, NYU Langone Health, 660 First Ave, New York, NY, 10016, USA
| | - Sonja Olsen
- Department of Hepatology, NYU Langone Health, New York, NY, USA
| | - Hoi Cheung Zhang
- Department of Radiology, NYU Langone Health, 660 First Ave, New York, NY, 10016, USA
| | | | - Hersh Chandarana
- Department of Radiology, NYU Langone Health, 660 First Ave, New York, NY, 10016, USA
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Kim TH, Jeong CW, Jun HY, Kim YR, Kim JY, Lee YH, Yoon KH. Noninvasive Differential Diagnosis of Liver Iron Contents in Nonalcoholic Steatohepatitis and Simple Steatosis Using Multiecho Dixon Magnetic Resonance Imaging. Acad Radiol 2019; 26:766-774. [PMID: 30143402 DOI: 10.1016/j.acra.2018.06.022] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 06/26/2018] [Accepted: 06/26/2018] [Indexed: 12/19/2022]
Abstract
RATIONALE AND OBJECTIVES The roles of iron stores in nonalcoholic fatty liver disease have not yet been clearly identified, and it is lack of uniform criteria and a standardized study design for assessing the liver iron content (LIC) in nonalcoholic steatohepatitis (NASH). This study was to compare LICs in biopsy-proven simple steatosis (SS) and NASH based on T2⁎-relaxometry. MATERIAL AND METHODS A total of 32 subjects divided to three groups, consisting of 10 healthy controls, 12 SS and 10 NASH. All MRI examinations were performed on a 3 T MRI with a 32-channel body coil. To measure T2⁎-value, we used a gradient echo sequence with six multiechoes within a single breath-hold. Hepatic iron contents among three groups were compared using Kruskal-Wallis H test and Mann-Whitney's posthoc tests. Diagnostic accuracy was determined by calculating the area under the receiver operating characteristics curve. To identify the reliability of iron measurements in the different region of interests, coefficient of variance (CV) was calculated overall CV values for the variability of measurements. Interobserver agreement and reliability were estimated by calculating the intraclass correlation coefficient. RESULTS The variations of all LIC measurements are not exceeded 20%, as a mean CV value 18.3%. intraclass correlation coefficients were higher than 0.9. Mean T2⁎-values at localized region of interests were healthy controls 45.42 ± 7.19 ms, SS 20.96 ± 4.28 ms, and NASH 15.49 ± 2.87 ms. The mean T2⁎-value in NASH is significantly shorter than that in SS (p = 0.008). The area under the receiver operating characteristics curve to distinguish NASH from SS was 0.908 (95% confidence interval 0.775-1.000, p = 0.001) at a cut-off of iron contents greater than 17.95 ms, and its diagnostic accuracy had 0.833 sensitivity and 0.800 specificity. CONCLUSION This study demonstrates that the T2⁎ calculation can help to differentially diagnose NASH.
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Affiliation(s)
- Tae-Hoon Kim
- Medical Convergence Research Center, Wonkwang University, Iksan, Republic of Korea
| | - Chang-Won Jeong
- Medical Convergence Research Center, Wonkwang University, Iksan, Republic of Korea
| | - Hong Young Jun
- Medical Convergence Research Center, Wonkwang University, Iksan, Republic of Korea
| | - Youe Ree Kim
- Department of Radiology, Wonkwang University School of Medicine, Iksan, Republic of Korea
| | - Ju Young Kim
- Medical Convergence Research Center, Wonkwang University, Iksan, Republic of Korea
| | - Young Hwan Lee
- Medical Convergence Research Center, Wonkwang University, Iksan, Republic of Korea; Department of Radiology, Wonkwang University School of Medicine, Iksan, Republic of Korea
| | - Kwon-Ha Yoon
- Medical Convergence Research Center, Wonkwang University, Iksan, Republic of Korea; Department of Radiology, Wonkwang University School of Medicine, Iksan, Republic of Korea.
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Ghoz HM, Kröner PT, Stancampiano FF, Bowman AW, Vishnu P, Heckman MG, Diehl NN, McLeod E, Nikpour N, Palmer WC. Hepatic iron overload identified by magnetic resonance imaging-based T2* is a predictor of non-diagnostic elastography. Quant Imaging Med Surg 2019; 9:921-927. [PMID: 31367546 DOI: 10.21037/qims.2019.05.13] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background Magnetic resonance elastography (MRE) is a non-invasive test used to assess liver stiffness and fibrosis in chronic liver disease, which includes systemic iron overload. However, iron deposition by itself is associated with technical failure of MRE of the liver which necessitates the use of invasive liver biopsy as an alternative monitoring method for these patients. T2*-weighted magnetic resonance imaging (T2*) is a reliable modality to asses for hepatic as well as total body iron overload. Therefore, we aimed to determine a cutoff value on the T2* reading at which MRE would no longer provide accurate stiffness measurements in patients with iron overload. Methods Ninety-five patients with iron overload who underwent MRE at our institution, between 2010 and 2017 were reviewed retrospectively. We compared T2* values between patients with adequate elastography (N=63) versus those with non-diagnostic elastography (N=32). We additionally examined the ability of T2* to predict the likelihood of non-diagnostic elastography by estimating area under the ROC curve (AUC). Results T2* was significantly different between patients with and without an adequate elastography (P<0.0001) and predicted occurrence of non-diagnostic elastography with an AUC of 0.95. All patients with a non-diagnostic elastography had a T2* value below 20 milliseconds (ms), and correspondingly 55% of the patients with a T2* value below 20 ms had a non-diagnostic elastography. The subgroups of patients with a T2* value ≤10, ≤8, and ≤6 ms, had a higher likelihood of non-diagnostic elastography (87%, 92%, and 95%, respectively). Conclusions T2* can be used to accurately predict which patients are most likely to have a non-diagnostic elastography reading. T2* of 20 ms or lower reflects a higher likelihood of non-diagnostic elastography.
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Affiliation(s)
- Hassan M Ghoz
- Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA
| | - Paul T Kröner
- Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA
| | | | | | - Prakash Vishnu
- Department of Hematology/Oncology, Mayo Clinic, Jacksonville, FL, USA
| | - Michael G Heckman
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Jacksonville, FL, USA
| | - Nancy N Diehl
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Jacksonville, FL, USA
| | - Ethan McLeod
- Clinical Research Internship Study Program (CRISP), Mayo Clinic, Jacksonville, FL, USA
| | - Naveed Nikpour
- Clinical Research Internship Study Program (CRISP), Mayo Clinic, Jacksonville, FL, USA
| | - William C Palmer
- Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA
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Multiple unilateral subcapsular cortical hemorrhagic cystic disease of the kidney: CT and MRI findings and clinical characteristic. Eur Radiol 2019; 29:4843-4850. [PMID: 30806804 DOI: 10.1007/s00330-019-06057-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 01/31/2019] [Indexed: 10/27/2022]
Abstract
PURPOSE The aim of this study was to clarify the radiologic and clinical characteristics of multiple unilateral subcapsular cortical hemorrhagic cystic disease of the kidney. METHOD Fourteen patients with unique and characteristic multiple hemorrhagic subcapsular cortical cysts of the kidney, not categorized in any existing renal cystic diseases, were retrospectively reviewed. The clinical information including age, sex, symptom, family history of renal or renal cystic disease, and laboratory data were collected. CT and MRI findings including distribution, number and size of cysts, and CT attenuation and signal intensity on T1- and T2-weighted MRI of cysts were analyzed. RESULTS All patients except one were young and none had a family history of renal or renal cystic disease. Common clinical symptoms were flank or abdominal pain and hematuria. In all cases, only the left kidney was involved at initial presentation. Cysts were small (median cyst size, 4-15 mm), numerous, and distributed mainly along the subcapsular cortex of the kidney. Cysts were hyper-attenuated on unenhanced CT, extremely hypointense on T2-weighted MRI, and mildly hyperintense on T1-weighted MRI. All patients except one had normal renal function. Imaging follow-up revealed stable or mildly progressive disease in seven patients. Two patients developed several hemorrhagic subcapsular cortical cysts in the right kidney at follow-up. Three of five patients with a renal pathology specimen showed concurrent IgA nephropathy. CONCLUSION We have identified a unique renal cystic disease with multiple unilateral subcapsular cortical hemorrhagic cystic disease of the kidney that has a characteristic manifestation both radiologically and clinically. KEY POINTS • Multiple unilateral subcapsular cortical hemorrhagic cystic disease of the kidney is a unique non-familial renal cystic disease with a characteristic manifestation both radiologically and clinically. • Most cases of multiple unilateral subcapsular cortical hemorrhagic cystic disease of the kidney are stable or slowly progressive, and do not require invasive intervention.
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Mozes FE, Tunnicliffe EM, Moolla A, Marjot T, Levick CK, Pavlides M, Robson MD. Mapping tissue water T 1 in the liver using the MOLLI T 1 method in the presence of fat, iron and B 0 inhomogeneity. NMR IN BIOMEDICINE 2019; 32:e4030. [PMID: 30462873 PMCID: PMC6492199 DOI: 10.1002/nbm.4030] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 09/11/2018] [Accepted: 09/20/2018] [Indexed: 05/11/2023]
Abstract
Modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences can be useful in cardiac and liver tissue characterization, but determining underlying water T1 is confounded by iron, fat and frequency offsets. This article proposes an algorithm that provides an independent water MOLLI T1 (referred to as on-resonance water T1 ) that would have been measured if a subject had no fat and normal iron, and imaging had been done on resonance. Fifteen NiCl2 -doped agar phantoms with different peanut oil concentrations and 30 adults with various liver diseases, nineteen (63.3%) with liver steatosis, were scanned at 3 T using the shortened MOLLI (shMOLLI) T1 mapping, multiple-echo spoiled gradient-recalled echo and 1 H MR spectroscopy sequences. An algorithm based on Bloch equations was built in MATLAB, and water shMOLLI T1 values of both phantoms and human participants were determined. The quality of the algorithm's result was assessed by Pearson's correlation coefficient between shMOLLI T1 values and spectroscopically determined T1 values of the water, and by linear regression analysis. Correlation between shMOLLI and spectroscopy-based T1 values increased, from r = 0.910 (P < 0.001) to r = 0.998 (P < 0.001) in phantoms and from r = 0.493 (for iron-only correction; P = 0.005) to r = 0.771 (for iron, fat and off-resonance correction; P < 0.001) in patients. Linear regression analysis revealed that the determined water shMOLLI T1 values in patients were independent of fat and iron. It can be concluded that determination of on-resonance water (sh)MOLLI T1 independent of fat, iron and macroscopic field inhomogeneities was possible in phantoms and human subjects.
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Affiliation(s)
- Ferenc E. Mozes
- The University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe HospitalOxfordUK
| | - Elizabeth M. Tunnicliffe
- The University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe HospitalOxfordUK
| | - Ahmad Moolla
- The University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe HospitalOxfordUK
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM)University of Oxford, Churchill HospitalOxfordUK
| | - Thomas Marjot
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM)University of Oxford, Churchill HospitalOxfordUK
| | - Christina K. Levick
- The University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe HospitalOxfordUK
- Translational Gastroenterology UnitUniversity of Oxford, John Radcliffe HospitalOxfordUK
| | - Michael Pavlides
- The University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe HospitalOxfordUK
- Translational Gastroenterology UnitUniversity of Oxford, John Radcliffe HospitalOxfordUK
- Oxford NIHR Biomedical Research CentreOxfordUK
| | - Matthew D. Robson
- The University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe HospitalOxfordUK
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Abstract
MRI is a key tool in the current management of patients with thalassemia. Given its capability of assessing iron overload in different organs noninvasively and without contrast, it has significant advantages over other metrics, including serum ferritin. Liver iron concentration can be measured either with relaxometry methods T2*/T2 or signal intensity ratio techniques. Myocardial iron can be assessed in the same examination through T2* imaging. In this review, we focus on showing how MRI evaluates iron in both organs and the clinical applications as well as practical approaches to using this tool by clinicians taking care of patients with thalassemia.
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Using IVIM-MRI and R2⁎ Mapping to Differentiate Early Stage Liver Fibrosis in a Rat Model of Radiation-Induced Liver Fibrosis. BIOMED RESEARCH INTERNATIONAL 2018; 2018:4673814. [PMID: 30627558 PMCID: PMC6304485 DOI: 10.1155/2018/4673814] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Revised: 11/09/2018] [Accepted: 11/21/2018] [Indexed: 12/17/2022]
Abstract
Rationale and Objectives To investigate the utility of intravoxel incoherent motion MRI (IVIM-MRI) and R2⁎ mapping in diagnosing early stage liver fibrosis in a radiation-induced rat model. Materials and Methods Thirty rats were randomly divided into three groups with 10 rats in each group. Liver fibrosis was induced by exposure of right lobe of liver in each animal to 20 Gy of radiation. MRI examination was conducted at baseline, one month, two months, and three months after radiation using T1WI, T2WI, IVIM-DWI, and R2⁎ sequences. The pathological examination included hematoxylin eosin, masson trichrome, and prussian blue staining. D, D⁎, f, and R2⁎ values were measured in both left and right lobes for quantitative analysis. Results Regarding the surviving 23 rats, eight rats were diagnosed with stage F0, ten with stage F1, and five with stage F2 liver fibrosis using METAVIR Scores. The D values of right lobes decreased (P<0.05), and R2⁎ values increased (P<0.01) significantly as fibrosis levels increased. But there was no statistical difference in D⁎ (P=0.970) and f values (P=0.079). R2⁎ value showed a strong positive correlation (r=0.819, P<0.001), while D value showed a negative correlation with fibrosis stages (r=-0.424, P<0.001). D⁎ (r=0.029, P=0.744) and f values (r=-0.055, P=0.536) were poorly correlated with fibrosis levels. Conclusion IVIM-MRI and R2⁎ mapping are useful techniques for evaluating the severity of liver fibrosis in a radiation-induced rat model, and R2⁎ value is the most sensitive parameter in detecting early stage fibrosis.
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Palmer WC, Vishnu P, Sanchez W, Aqel B, Riegert-Johnson D, Seaman LAK, Bowman AW, Rivera CE. Diagnosis and Management of Genetic Iron Overload Disorders. J Gen Intern Med 2018; 33:2230-2236. [PMID: 30225768 PMCID: PMC6258594 DOI: 10.1007/s11606-018-4669-2] [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] [Received: 11/09/2017] [Revised: 05/23/2018] [Accepted: 09/07/2018] [Indexed: 12/12/2022]
Abstract
Iron overload disorders lead to excess iron deposition in the body, which can occur as a result of genetic or secondary causes. Genetic iron overload, referred to as hereditary hemochromatosis, may present as a common autosomal recessive mutation or as one of several uncommon mutations. Secondary iron overload may result from frequent blood transfusions, exogenous iron intake, or certain hematological diseases such as dyserythropoietic syndrome or chronic hemolytic anemia. Iron overload may be asymptomatic, or may present with significant diseases of the liver, heart, endocrine glands, joints, or other organs. If treated appropriately prior to end-organ damage, life expectancy has been shown to be similar compared to matched populations. Alongside clinical assessment, diagnostic studies involve blood tests, imaging, and in some cases liver biopsy. The mainstay of therapy is periodic phlebotomy, although oral chelation is an option for selected patients.
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Affiliation(s)
- William C Palmer
- Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA.
| | - Prakash Vishnu
- Department of Hematology/Oncology, Mayo Clinic, Jacksonville, FL, USA
| | - William Sanchez
- Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Bashar Aqel
- Department of Gastroenterology and Hepatology, Mayo Clinic, Scottsdale, AZ, USA
| | - Doug Riegert-Johnson
- Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA
| | | | | | - Candido E Rivera
- Department of Hematology/Oncology, Mayo Clinic, Jacksonville, FL, USA
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Simchick G, Liu Z, Nagy T, Xiong M, Zhao Q. Assessment of MR-based R2* and quantitative susceptibility mapping for the quantification of liver iron concentration in a mouse model at 7T. Magn Reson Med 2018; 80:2081-2093. [PMID: 29575047 PMCID: PMC6107404 DOI: 10.1002/mrm.27173] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 02/15/2018] [Accepted: 02/15/2018] [Indexed: 01/19/2023]
Abstract
PURPOSE To assess the feasibility of quantifying liver iron concentration (LIC) using R2* and quantitative susceptibility mapping (QSM) at a high field strength of 7 Tesla (T). METHODS Five different concentrations of Fe-dextran were injected into 12 mice to produce various degrees of liver iron overload. After mice were sacrificed, blood and liver samples were harvested. Ferritin enzyme-linked immunosorbent assay (ELISA) and inductively coupled plasma mass spectrometry were performed to quantify serum ferritin concentration and LIC. Multiecho gradient echo MRI was conducted to estimate R2* and the magnetic susceptibility of each liver sample through complex nonlinear least squares fitting and a morphology enabled dipole inversion method, respectively. RESULTS Average estimates of serum ferritin concentration, LIC, R2*, and susceptibility all show good linear correlations with injected Fe-dextran concentration; however, the standard deviations in the estimates of R2* and susceptibility increase with injected Fe-dextran concentration. Both R2* and susceptibility measurements also show good linear correlations with LIC (R2 = 0.78 and R2 = 0.91, respectively), and a susceptibility-to-LIC conversion factor of 0.829 ppm/(mg/g wet) is derived. CONCLUSION The feasibility of quantifying LIC using MR-based R2* and QSM at a high field strength of 7T is demonstrated. Susceptibility quantification, which is an intrinsic property of tissues and benefits from being field-strength independent, is more robust than R2* quantification in this ex vivo study. A susceptibility-to-LIC conversion factor is presented that agrees relatively well with previously published QSM derived results obtained at 1.5T and 3T.
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Affiliation(s)
- Gregory Simchick
- Physics and Astronomy, University of Georgia, Athens, GA, United States
- Bio-Imaging Research Center, University of Georgia, Athens, GA, United States
| | - Zhi Liu
- Pharmaceutical & Biomedical Sciences, University of Georgia, Athens, GA United States
| | - Tamas Nagy
- Pathology, College of Veterinary Medicine, University of Georgia, Athens, GA United States
| | - May Xiong
- Pharmaceutical & Biomedical Sciences, University of Georgia, Athens, GA United States
| | - Qun Zhao
- Physics and Astronomy, University of Georgia, Athens, GA, United States
- Bio-Imaging Research Center, University of Georgia, Athens, GA, United States
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Liver MR Elastography at 3 T: Agreement Across Pulse Sequences and Effect of Liver R2* on Image Quality. AJR Am J Roentgenol 2018; 211:588-594. [DOI: 10.2214/ajr.17.19288] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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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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Quantifying iron content in magnetic resonance imaging. Neuroimage 2018; 187:77-92. [PMID: 29702183 DOI: 10.1016/j.neuroimage.2018.04.047] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 04/13/2018] [Accepted: 04/20/2018] [Indexed: 01/19/2023] Open
Abstract
Measuring iron content has practical clinical indications in the study of diseases such as Parkinson's disease, Huntington's disease, ferritinopathies and multiple sclerosis as well as in the quantification of iron content in microbleeds and oxygen saturation in veins. In this work, we review the basic concepts behind imaging iron using T2, T2*, T2', phase and quantitative susceptibility mapping in the human brain, liver and heart, followed by the applications of in vivo iron quantification in neurodegenerative diseases, iron tagged cells and ultra-small superparamagnetic iron oxide (USPIO) nanoparticles.
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