1
|
Arif-Tiwari H, Porter KK, Kamel IR, Bashir MR, Fung A, Kaplan DE, McGuire BM, Russo GK, Smith EN, Solnes LB, Thakrar KH, Vij A, Wahab SA, Wardrop RM, Zaheer A, Carucci LR. ACR Appropriateness Criteria® Abnormal Liver Function Tests. J Am Coll Radiol 2023; 20:S302-S314. [PMID: 38040457 DOI: 10.1016/j.jacr.2023.08.023] [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: 08/15/2023] [Accepted: 08/22/2023] [Indexed: 12/03/2023]
Abstract
Liver function tests are commonly obtained in symptomatic and asymptomatic patients. Various overlapping lab patterns can be seen due to derangement of hepatocytes and bile ducts function. Imaging tests are pursued to identify underlying etiology and guide management based on the lab results. Liver function tests may reveal mild, moderate, or severe hepatocellular predominance and can be seen in alcoholic and nonalcoholic liver disease, acute hepatitis, and acute liver injury due to other causes. Cholestatic pattern with elevated alkaline phosphatase with or without elevated γ-glutamyl transpeptidase can be seen with various causes of obstructive biliopathy. Acute or subacute cholestasis with conjugated or unconjugated hyperbilirubinemia can be seen due to prehepatic, intrahepatic, or posthepatic causes. We discuss the initial and complementary imaging modalities to be used in clinical scenarios presenting with abnormal liver function tests. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
Collapse
Affiliation(s)
- Hina Arif-Tiwari
- University of Arizona, Banner University Medical Center, Tucson, Arizona.
| | | | - Ihab R Kamel
- Panel Chair, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | | | - Alice Fung
- Oregon Health & Science University, Portland, Oregon
| | - David E Kaplan
- Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania; American Association for the Study of Liver Diseases
| | - Brendan M McGuire
- University of Alabama at Birmingham, Birmingham, Alabama, Primary care physician
| | | | - Elainea N Smith
- University of Alabama at Birmingham Medical Center, Birmingham, Alabama
| | - Lilja Bjork Solnes
- Johns Hopkins Bayview Medical Center, Baltimore, Maryland; Commission on Nuclear Medicine and Molecular Imaging
| | | | - Abhinav Vij
- New York University Langone Medical Center, New York, New York
| | - Shaun A Wahab
- University of Cincinnati Medical Center, Cincinnati, Ohio
| | - Richard M Wardrop
- Cleveland Clinic, Cleveland, Ohio; American College of Physicians, Hospital Medicine
| | | | - Laura R Carucci
- Specialty Chair, Virginia Commonwealth University Medical Center, Richmond, Virginia
| |
Collapse
|
2
|
Naeem M, Schipf S, Bülow R, Werner N, Dörr M, Lerch MM, Kühn JP, Rathmann W, Nauck M, Paulista Markus MR, Targher G, Ittermann T, Völzke H. Association between hepatic iron overload assessed by magnetic resonance imaging and glucose intolerance states in the general population. Nutr Metab Cardiovasc Dis 2022; 32:1470-1476. [PMID: 35282980 DOI: 10.1016/j.numecd.2022.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 02/03/2022] [Accepted: 02/18/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND AND AIM While there is evidence that iron overload disorders are associated with type 2 diabetes, the relationship between hepatic iron overload and prediabetes remains unclear. We aimed to investigate the association between hepatic iron overload, as assessed by magnetic resonance imaging (MRI), and different glucose intolerance states in the population-based Study. METHODS AND RESULTS We included data from 1622 individuals with MRI data, who did not have known type 2 diabetes (T2DM). Using an oral glucose tolerance testing, participants were classified as having isolated impaired fasting glucose (i-IFG), isolated impaired glucose tolerance (i-IGT), combined IFG and IGT (IFG + IGT) or previously unknown T2DM. Hepatic iron and fat contents were assessed through quantitative MRI. We undertook linear and multinomial logistic regression models adjusted for potential confounders and MRI-assessed hepatic fat content to examine the association of hepatic iron overload with different glucose intolerance states or continuous markers of glucose metabolism. MRI-assessed hepatic iron overload was positively associated only with both 2-h plasma glucose (β = 0.32; 95%CI 0.04-0.60) and the combined IFG + IGT category (relative risk ratio = 1.87; 95%CI 1.15-3.06). No significant associations were found between hepatic iron overload and other glucose intolerance states or biomarkers of glucose metabolism, independently of potential confounders. CONCLUSIONS MRI-assessed hepatic iron overload was associated with higher 2-h glucose concentrations and the combined IFG + IGT category, but not with other glucose intolerance states. Our findings suggest a weak adverse impact of hepatic iron overload on glucose metabolism, but further studies are needed to confirm these findings.
Collapse
Affiliation(s)
- Muhammad Naeem
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; Department of Zoology, University of Malakand, 18800, Pakistan.
| | - Sabine Schipf
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Center for Diabetes Research (DZD), Partner Site Greifswald, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Germany
| | - Nicole Werner
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Germany
| | - Markus M Lerch
- Department of Gastroenterology, University Medicine Greifswald, Greifswald, Germany
| | - Jens-Peter Kühn
- Institute and Policlinic for Diagnostic and Interventional Radiology, University Hospital, Carl Gustav Carus University, TU Dresden, Dresden, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), Partner Site Greifswald, Germany; Institute for Biometrics and Epidemiology, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Matthias Nauck
- Institute for Laboratory Medicine and Clinical Chemistry, University Medicine Greifswald, Greifswald, Germany
| | - Marcello Ricardo Paulista Markus
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Germany; German Center for Diabetes Research (DZD), Partner Site Greifswald, Germany
| | - Giovanni Targher
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Verona, Verona, Italy
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Germany; German Center for Diabetes Research (DZD), Partner Site Greifswald, Germany
| |
Collapse
|
3
|
Duan T, Jiang HY, Ling WW, Song B. Noninvasive imaging of hepatic dysfunction: A state-of-the-art review. World J Gastroenterol 2022; 28:1625-1640. [PMID: 35581963 PMCID: PMC9048786 DOI: 10.3748/wjg.v28.i16.1625] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 07/17/2021] [Accepted: 03/27/2022] [Indexed: 02/06/2023] Open
Abstract
Hepatic dysfunction represents a wide spectrum of pathological changes, which can be frequently found in hepatitis, cholestasis, metabolic diseases, and focal liver lesions. As hepatic dysfunction is often clinically silent until advanced stages, there remains an unmet need to identify affected patients at early stages to enable individualized intervention which can improve prognosis. Passive liver function tests include biochemical parameters and clinical grading systems (e.g., the Child-Pugh score and Model for End-Stage Liver Disease score). Despite widely used and readily available, these approaches provide indirect and limited information regarding hepatic function. Dynamic quantitative tests of liver function are based on clearance capacity tests such as the indocyanine green (ICG) clearance test. However, controversial results have been reported for the ICG clearance test in relation with clinical outcome and the accuracy is easily affected by various factors. Imaging techniques, including ultrasound, computed tomography, and magnetic resonance imaging, allow morphological and functional assessment of the entire hepatobiliary system, hence demonstrating great potential in evaluating hepatic dysfunction noninvasively. In this article, we provide a state-of-the-art summary of noninvasive imaging modalities for hepatic dysfunction assessment along the pathophysiological track, with special emphasis on the imaging modality comparison and selection for each clinical scenario.
Collapse
Affiliation(s)
- Ting Duan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Han-Yu Jiang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Wen-Wu Ling
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
| |
Collapse
|
4
|
Schneider E, Remer EM, Obuchowski NA, McKenzie CA, Ding X, Navaneethan SD. Long-term inter-platform reproducibility, bias, and linearity of commercial PDFF MRI methods for fat quantification: a multi-center, multi-vendor phantom study. Eur Radiol 2021; 31:7566-7574. [PMID: 33768291 DOI: 10.1007/s00330-021-07851-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/10/2021] [Accepted: 03/02/2021] [Indexed: 01/29/2023]
Abstract
OBJECTIVES Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors. METHODS Over 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject's examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed. RESULTS Three hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (p < 0.001) and field strength (p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%). CONCLUSIONS This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength-dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference. KEY POINTS • Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated. • Non-linear effects were negligible (linear slope of 0.94) over 0-100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0-100 weight% fat, respectively. • Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems.
Collapse
Affiliation(s)
- Erika Schneider
- Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, A21, Cleveland, OH, 44195, USA
| | - Erick M Remer
- Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, A21, Cleveland, OH, 44195, USA. .,Glickman Urological and Kidney Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA.
| | - Nancy A Obuchowski
- Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, A21, Cleveland, OH, 44195, USA.,Department of Quantitative Health Sciences, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Charles A McKenzie
- CAnatomical Research Services and Medical Biophysics, University of Western Ontario, London, Ontario, Canada
| | - Xiaobo Ding
- Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, A21, Cleveland, OH, 44195, USA.,Department of Radiology, First Hospital of Jilin University, Changchun, 130021, China
| | - Sankar D Navaneethan
- Glickman Urological and Kidney Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA.,Department of Medicine-Nephrology, Baylor College of Medicine, Houston, TX, USA
| |
Collapse
|
5
|
Dinani AM, Lewis S, Branch AD, Perumalswami P. Working Up an Incidental Finding of Hepatic Steatosis on Imaging. Clin Liver Dis (Hoboken) 2020; 16:58-62. [PMID: 32922751 PMCID: PMC7474143 DOI: 10.1002/cld.926] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 01/08/2020] [Indexed: 02/04/2023] Open
Affiliation(s)
- Amreen M. Dinani
- Division of Liver DiseasesIcahn School of Medicine at Mount SinaiNew YorkNY
| | - Sara Lewis
- Department of RadiologyIcahn School of MedicineNew YorkNY
| | - Andrea D. Branch
- Division of Liver DiseasesIcahn School of Medicine at Mount SinaiNew YorkNY
| | - Ponni Perumalswami
- Division of Liver DiseasesIcahn School of Medicine at Mount SinaiNew YorkNY
| |
Collapse
|
6
|
Cruz M, Ferreira AA, Papanikolaou N, Banerjee R, Alves FC. New boundaries of liver imaging: from morphology to function. Eur J Intern Med 2020; 79:12-22. [PMID: 32571581 DOI: 10.1016/j.ejim.2020.06.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/20/2020] [Accepted: 06/04/2020] [Indexed: 12/12/2022]
Abstract
From an invisible organ to one of the most explored non-invasively, the liver is, today, one of the cornerstones for current cross-sectional imaging techniques and minimally invasive procedures. After the achievements of US, CT and, most recently, MRI in providing highly accurate morphological and structural information about the organ, a significant scientific development has gained momentum for the last decades, coupling morphology to liver function and contributing far most to what we know today as precision medicine. In fact, dedicated tailor-made investigations are now possible in order to detect and, most of all, quantify physiopathological processes with unprecedented certitude. It is the intention of this review to provide a better insight to the reader of several functional imaging techniques applied to liver imaging. Contrast enhanced imaging, diffusion weighted imaging, elastography, spectral computed tomography and fat and iron assessment techniques are commonly performed clinically. Diffusion kurtosis imaging, magnetic resonance spectroscopy, T1 relaxometry and radiomics remain largely limited to advanced clinical research. Each of them has its own value and place on the diagnostic armamentarium and provide unique qualitative and quantitative information regarding the pathophysiology of diseases, contributing at a large scale to model therapeutic decisions and patient follow-up. Therefore, state-of-the-art liver imaging acts today as a non-invasive surrogate biomarker of many focal and diffuse liver diseases.
Collapse
Affiliation(s)
- Manuel Cruz
- Department of Radiology, Faculty of Medicine, University Hospital Coimbra and CIBIT/ICNAS research center, University of Coimbra, Coimbra, Portugal.
| | - Ana Aguiar Ferreira
- Department of Radiology, Faculty of Medicine, University Hospital Coimbra and CIBIT/ICNAS research center, University of Coimbra, Coimbra, Portugal
| | - Nikolaos Papanikolaou
- Computational Clinical Imaging Group, Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal
| | - Rajarshi Banerjee
- Department of Acute Medicine, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | - Filipe Caseiro Alves
- Department of Radiology, Faculty of Medicine, University Hospital Coimbra and CIBIT/ICNAS research center, University of Coimbra, Coimbra, Portugal
| |
Collapse
|
7
|
Lee O, Lee SJ, Yu SM. Determination of an Optimized Weighting Factor of Liver Parenchyma for Six-point Interference Dixon Fat Percentage Imaging Accuracy in Nonalcoholic Fatty Liver Disease Rat Model. Acad Radiol 2018; 25:1595-1602. [PMID: 29803754 DOI: 10.1016/j.acra.2018.03.029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 03/22/2018] [Accepted: 03/25/2018] [Indexed: 01/14/2023]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to determine the optimal weighting factor (WF) for precise quantification using six-point interference Dixon fat percentage imaging by analyzing changes in WFs of fatty acid metabolites (FMs) in high-fat-induced fatty liver disease rat model. MATERIALS AND METHODS Individual FM-related WFs were calculated based on concentration ratios of integrated areas of seven peak FMs with four phantom series. Ten 8-week-old male Sprague-Dawley rats were used for baseline quantification of fat in liver magnetic resonance imaging or magnetic resonance spectroscopy data. These seven lipid metabolites were then quantitatively analyzed. Spearman test was used for correlation analysis of different lipid proton concentrations. The most accurate WF for six-point interference Dixon fat percentage imaging was then determined. RESULTS The seven lipid resonance WF values obtained from magnetic resonance spectroscopy data for three different oils (oleic, linoleic, and soybean) were different from each other. In lipid phantoms, except for the phantom containing oleic acid, changes in FP values were significantly different when WFs were changed in six-point interference Dixon fat percentage image. The seven lipid resonance WF values for the nonalcoholic fatty liver animal model were different from human subcutaneous adipose tissue lipid WF values. CONCLUSIONS WF affected the calculation of six-point interference Dixon-based fat percentage imaging value in phantom experiment. If WF of liver parenchyma FM which is specific to each liver disease is applied, the accuracy of six-point interference Dixon fat percentage imaging can be further increased.
Collapse
Affiliation(s)
- Onseok Lee
- Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, Asan City, Chungnam, Republic of Korea
| | - Suk-Jun Lee
- Department of Biomedical Laboratory Science, College of Health Science, Cheongju University, Cheongju City 28503, Republic of Korea.
| | - Seung-Man Yu
- Department of Radiological Science, College of Health Science, Gimcheon University, Gimcheon City 39528, Republic of Korea.
| |
Collapse
|
8
|
Chartampilas E. Imaging of nonalcoholic fatty liver disease and its clinical utility. Hormones (Athens) 2018; 17:69-81. [PMID: 29858854 DOI: 10.1007/s42000-018-0012-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 12/04/2017] [Indexed: 12/21/2022]
Abstract
The prevalence of nonalcoholic fatty liver disease has been continuously rising over the last three decades and is projected to become the most common indication for liver transplantation in the near future. Its pathophysiology and complex interplay with diabetes and the metabolic syndrome are not as yet fully understood despite growing scientific interest and research. Modern imaging techniques offer significant assistance in this field by enabling the study of the liver noninvasively and evaluation of the degree of both steatosis and fibrosis, and even in attempting to diagnose the presence of inflammation (steatohepatitis). The derived measurements are highly precise, accurate and reproducible, performing better than biopsy in terms of quantification. In this article, these imaging techniques are overviewed and their performance regarding diagnosis, stratification and monitoring are evaluated. Their expanding role both in the research arena and in clinical practice along with their limitations is also discussed.
Collapse
|
9
|
Armstrong T, Dregely I, Stemmer A, Han F, Natsuaki Y, Sung K, Wu HH. Free-breathing liver fat quantification using a multiecho 3D stack-of-radial technique. Magn Reson Med 2017; 79:370-382. [PMID: 28419582 DOI: 10.1002/mrm.26693] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 02/22/2017] [Accepted: 03/09/2017] [Indexed: 12/11/2022]
Abstract
PURPOSE The diagnostic gold standard for nonalcoholic fatty liver disease is an invasive biopsy. Noninvasive Cartesian MRI fat quantification remains limited to a breath-hold (BH). In this work, a novel free-breathing 3D stack-of-radial (FB radial) liver fat quantification technique is developed and evaluated in a preliminary study. METHODS Phantoms and healthy subjects (n = 11) were imaged at 3 Tesla. The proton-density fat fraction (PDFF) determined using FB radial (with and without scan acceleration) was compared to BH single-voxel MR spectroscopy (SVS) and BH 3D Cartesian MRI using linear regression (correlation coefficient ρ and concordance coefficient ρc ) and Bland-Altman analysis. RESULTS In phantoms, PDFF showed significant correlation (ρ > 0.998, ρc > 0.995) and absolute mean differences < 2.2% between FB radial and BH SVS, as well as significant correlation (ρ > 0.999, ρc > 0.998) and absolute mean differences < 0.6% between FB radial and BH Cartesian. In the liver and abdomen, PDFF showed significant correlation (ρ > 0.986, ρc > 0.985) and absolute mean differences < 1% between FB radial and BH SVS, as well as significant correlation (ρ > 0.996, ρc > 0.995) and absolute mean differences < 0.9% between FB radial and BH Cartesian. CONCLUSION Accurate 3D liver fat quantification can be performed in 1 to 2 min using a novel FB radial technique. Magn Reson Med 79:370-382, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Collapse
Affiliation(s)
- Tess Armstrong
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Isabel Dregely
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Biomedical Engineering, King's College London, London, United Kingdom
| | | | - Fei Han
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
| | | | - Kyunghyun Sung
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Holden H Wu
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| |
Collapse
|
10
|
Nozaki T, Tasaki A, Horiuchi S, Ochi J, Starkey J, Hara T, Saida Y, Yoshioka H. Predicting Retear after Repair of Full-Thickness Rotator Cuff Tear: Two-Point Dixon MR Imaging Quantification of Fatty Muscle Degeneration—Initial Experience with 1-year Follow-up. Radiology 2016; 280:500-9. [DOI: 10.1148/radiol.2016151789] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
11
|
Agostini A, Kircher MF, Do RKG, Borgheresi A, Monti S, Giovagnoni A, Mannelli L. Magnetic Resonanance Imaging of the Liver (Including Biliary Contrast Agents)-Part 2: Protocols for Liver Magnetic Resonanance Imaging and Characterization of Common Focal Liver Lesions. Semin Roentgenol 2016; 51:317-333. [PMID: 27743568 DOI: 10.1053/j.ro.2016.05.016] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Andrea Agostini
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY; Department of Radiology, School of Radiology, Università Politecnica delle Marche, Ancona, Italy
| | - Moritz F Kircher
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - Richard K G Do
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - Alessandra Borgheresi
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY; Department of Radiology, School of Radiology, Università degli Studi di Firenze, Firenze, Italy
| | | | - Andrea Giovagnoni
- Department of Radiology, School of Radiology, Università Politecnica delle Marche, Ancona, Italy
| | - Lorenzo Mannelli
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY.
| |
Collapse
|
12
|
|