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Wang D, Miao J, Zhang L, Zhang L. Research advances in the diagnosis and treatment of MASLD/MASH. Ann Med 2025; 57. [DOI: 10.1080/07853890.2024.2445780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 12/01/2024] [Accepted: 12/02/2024] [Indexed: 01/06/2025] Open
Affiliation(s)
- Dekai Wang
- Department of General Practice, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Jinxian Miao
- Department of General Practice, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Lihua Zhang
- Department of General Practice, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Lin Zhang
- Department of General Practice, The First Affiliated Hospital of Kunming Medical University, Kunming, China
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2
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Ahn JH, Jeong YW, Choi YB, Kang Y. Efficacy of magnetic resonance imaging in managing glycogen storage disease. Orphanet J Rare Dis 2025; 20:144. [PMID: 40148892 PMCID: PMC11948790 DOI: 10.1186/s13023-025-03605-7] [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: 12/11/2024] [Accepted: 02/10/2025] [Indexed: 03/29/2025] Open
Abstract
BACKGROUND Glycogen storage disease (GSD) is a rare genetic disorder requiring continuous management. It poses a risk of progression to hepatocellular adenoma (HCA) and hepatocellular carcinoma. While ultrasonography is the primary imaging modality to monitor liver health, it has limitations in assessing liver size and detecting HCAs, which can be addressed by magnetic resonance imaging (MRI). This study was conducted to evaluate the efficacy of MRI in the proactive management of GSD and its ability to predict HCA. METHODS This study included 32 patients with GSD from Wonju Severance Christian Hospital, of whom 29 underwent MRI examinations. Baseline characteristics, such as sex, height, weight, and body surface area (BSA), were recorded, along with laboratory markers. The MRI protocols included T2-weighted axial and coronal imaging, proton magnetic resonance spectroscopy, multi-echo Dixon imaging, magnetic resonance elastography, and T1 mapping. The correlation between liver volumes and laboratory results was analyzed, and logistic regression was used to analyze the association between the liver volume/BSA ratio and adenoma occurrence. RESULTS A significant correlation was observed between a high liver volume-to-BSA ratio and the likelihood of HCA development. Receiver operating characteristic curve analysis showed an area under the curve of 0.816 for predicting HCAs and a C-index of 0.847, indicating that MRI had high predictive accuracy. For each unit increase in the liver volume-to-BSA ratio, the probability of HCA increased by 1.005. CONCLUSION MRI is valuable for assessing adenoma formation in patients with GSD. Although not intended for routine surveillance of all patients, MRI can be selectively used in high-risk cases to enable early detection and timely intervention, thereby reducing the risk of progression to malignant transformation.
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Affiliation(s)
- Jhii-Hyun Ahn
- Department of Radiology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Yong Whi Jeong
- Department of Medical Informatics and Biostatistics, Graduate School, Yonsei University, Wonju, Korea
| | - Yong Bok Choi
- Department of Radiology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Yunkoo Kang
- Department of Pediatrics, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea.
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3
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AbiMansour J, Yung-Lun Chin J, Kaur J, Vargas EJ, Abu Dayyeh BK, Law R, Garimella V, Levy MJ, Storm AC, Dierkhising R, Allen A, Venkatesh S, Chandrasekhara V. Endoscopic Ultrasound-based Shear Wave Elastography for Detection of Advanced Liver Disease. J Clin Gastroenterol 2025; 59:256-261. [PMID: 38648501 PMCID: PMC11496376 DOI: 10.1097/mcg.0000000000002013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/17/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND AND AIMS Endoscopic ultrasound shear wave elastography (EUS-SWE) is a novel modality for liver stiffness measurement. The aims of this study are to evaluate the performance and reliability of EUS-SWE for detecting advanced liver disease in a prospective cohort. METHODS EUS-SWE measurements were prospectively obtained from patients undergoing EUS between August 2020 and March 2023. Liver stiffness measurements were compared between patients with and without advanced liver disease (ALD), defined as stage ≥3, to determine diagnostic accuracy for advanced fibrosis and portal hypertension. Logistic regression was performed to identify variables that impact the reliability of EUS-SWE readings. Select patients underwent paired magnetic resonance elastography (MRE) for liver fibrosis correlation. RESULTS Patients with ALD demonstrated higher liver stiffness compared to healthy controls (left lobe: 17.6 vs. 12.7 kPa, P <0.001; median right lobe: 24.8 vs. 11.0 kPa, P <0.001). The area under the receiver operator characteristic (AUROC) for the detection of ALD was 0.73 and 0.80 for left and right lobe measurements, respectively. General anesthesia was associated with reliable EUS-SWE liver readings (odds ratio: 2.73, 95% CI: 1.07-7.39, P =0.040). Left lobe measurements correlated significantly with MRE with an increase of 0.11 kPa (95% CI: 0.05-0.17 kPA) for every 1 kPa increase on EUS-SWE. D. CONCLUSIONS SWE is a promising technology that can readily be incorporated into standard EUS examinations for the assessment of ALD.
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Affiliation(s)
- Jad AbiMansour
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jerry Yung-Lun Chin
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jyotroop Kaur
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Eric J. Vargas
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Barham K. Abu Dayyeh
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ryan Law
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Vishal Garimella
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael J. Levy
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andrew C. Storm
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ross Dierkhising
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Alina Allen
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Vinay Chandrasekhara
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
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Hegde S, Pierce TT, Heidari F, Ozturk A, Cheah E, Pope K, Blake MA, Shih A, Misdraji J, Samir AE. Noninvasive Assessment of Liver Fibrosis in Patients With Iron Overload. ULTRASOUND IN MEDICINE & BIOLOGY 2025; 51:551-558. [PMID: 39690040 PMCID: PMC11757052 DOI: 10.1016/j.ultrasmedbio.2024.11.017] [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: 07/03/2024] [Revised: 11/05/2024] [Accepted: 11/15/2024] [Indexed: 12/19/2024]
Abstract
OBJECTIVE We assessed the diagnostic performance of ultrasound two-dimensional shear wave elastography (US 2D-SWE) to predict clinically significant fibrosis (CSF) in patients with serologic iron overload (SIO) and the subgroup with histologic liver iron overload (LIO). METHODS A single-center retrospective cross-sectional study of adults with SIO (serum ferritin ≥ 200 ng/mL in females and ≥ 300 ng/mL in males) and suspected chronic liver disease with nonfocal liver biopsy results and US 2D-SWE exams within 1 year was performed. Histopathological fibrosis stage ≥2 and liver iron ≥2+ was considered CSF and LIO, respectively. Univariate logistic regression to assess prediction of CSF by Young's modulus (YM) and serum ferritin was performed. Sensitivity and specificity were reported at optimal YM threshold determined by the Youden Index. RESULTS 272 cases were included (211 (77.6%) females, 88 (32.4%) CSF cases) with mean (± standard deviation) age of 50.0 (13.6) years. Median YM predicted CSF in patients with SIO (AUC 0.73, 95% confidence intervals (CI) 0.66 -0.80, odds ratio (OR) 1.12), p < 0.001. Optimal YM threshold was 11 kPa (sensitivity 58%, specificity 79%). Subgroup analysis of 47 LIO cases (39 women, mean age 52.5 ± 11.6 years, 17 (36.2%) CSF) showed that median YM predicted CSF (AUC 0.85, 95% CI 0.73-0.97, OR 1.39), p < 0.001. Optimal YM threshold was 11 kPa (sensitivity 77%, specificity 87%). CONCLUSION 2D-SWE is a promising, widely available, and noninvasive tool for diagnosing liver fibrosis in iron overload, including when magnetic resonance elastography may be nondiagnostic due to iron-related artifact.
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Affiliation(s)
- Siddhi Hegde
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Theodore T Pierce
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Firouzeh Heidari
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Arinc Ozturk
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Eugene Cheah
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Kathleen Pope
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Maria A Blake
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | | | - Joseph Misdraji
- Yale School of Medicine, Yale New Haven Hospital, New Haven, CT, USA
| | - Anthony E Samir
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
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Odéen H, Payne AH, Parker DL. Magnetic Resonance Acoustic Radiation Force Imaging (MR-ARFI). J Magn Reson Imaging 2025. [PMID: 39842847 DOI: 10.1002/jmri.29712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Revised: 12/30/2024] [Accepted: 12/31/2024] [Indexed: 01/24/2025] Open
Abstract
This review covers the theoretical background, pulse sequence considerations, practical implementations, and multitudes of applications of magnetic resonance acoustic radiation force imaging (MR-ARFI) described to date. MR-ARFI is an approach to encode tissue displacement caused by the acoustic radiation force of a focused ultrasound field into the phase of a MR image. The displacement encoding is done with motion encoding gradients (MEG) which have traditionally been added to spin echo-type and gradient recalled echo-type pulse sequences. Many different types of MEG (monopolar, bipolar, tripolar etc.) have been described and pros and cons are discussed. We further review studies investigating the safety of MR-ARFI, as well as approaches to simulate the MR-ARFI displacement. Lastly, MR-ARFI applications such as for focal spot localization, tissue stiffness interrogation following thermal ablation, trans-skull aberration correction, and simultaneous MR-ARFI and MR thermometry are discussed. EVIDENCE LEVEL: N/A TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Henrik Odéen
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Allison H Payne
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Dennis L Parker
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
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6
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Ali R, Li H, Zhang H, Pan W, Reeder SB, Harris D, Masch W, Aslam A, Shanbhogue K, Bernieh A, Ranganathan S, Parikh N, Dillman JR, He L. Multi-site, multi-vendor development and validation of a deep learning model for liver stiffness prediction using abdominal biparametric MRI. Eur Radiol 2025:10.1007/s00330-024-11312-3. [PMID: 39779515 DOI: 10.1007/s00330-024-11312-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2024] [Revised: 11/04/2024] [Accepted: 11/24/2024] [Indexed: 01/11/2025]
Abstract
BACKGROUND Chronic liver disease (CLD) is a substantial cause of morbidity and mortality worldwide. Liver stiffness, as measured by MR elastography (MRE), is well-accepted as a surrogate marker of liver fibrosis. PURPOSE To develop and validate deep learning (DL) models for predicting MRE-derived liver stiffness using routine clinical non-contrast abdominal T1-weighted (T1w) and T2-weighted (T2w) data from multiple institutions/system manufacturers in pediatric and adult patients. MATERIALS AND METHODS We identified pediatric and adult patients with known or suspected CLD from four institutions, who underwent clinical MRI with MRE from 2011 to 2022. We used T1w and T2w data to train DL models for liver stiffness classification. Patients were categorized into two groups for binary classification using liver stiffness thresholds (≥ 2.5 kPa, ≥ 3.0 kPa, ≥ 3.5 kPa, ≥ 4 kPa, or ≥ 5 kPa), reflecting various degrees of liver stiffening. RESULTS We identified 4695 MRI examinations from 4295 patients (mean ± SD age, 47.6 ± 18.7 years; 428 (10.0%) pediatric; 2159 males [50.2%]). With a primary liver stiffness threshold of 3.0 kPa, our model correctly classified patients into no/minimal (< 3.0 kPa) vs moderate/severe (≥ 3.0 kPa) liver stiffness with AUROCs of 0.83 (95% CI: 0.82, 0.84) in our internal multi-site cross-validation (CV) experiment, 0.82 (95% CI: 0.80, 0.84) in our temporal hold-out validation experiment, and 0.79 (95% CI: 0.75, 0.81) in our external leave-one-site-out CV experiment. The developed model is publicly available ( https://github.com/almahdir1/Multi-channel-DeepLiverNet2.0.git ). CONCLUSION Our DL models exhibited reasonable diagnostic performance for categorical classification of liver stiffness on a large diverse dataset using T1w and T2w MRI data. KEY POINTS Question Can DL models accurately predict liver stiffness using routine clinical biparametric MRI in pediatric and adult patients with CLD? Findings DeepLiverNet2.0 used biparametric MRI data to classify liver stiffness, achieving AUROCs of 0.83, 0.82, and 0.79 for multi-site CV, hold-out validation, and external CV. Clinical relevance Our DeepLiverNet2.0 AI model can categorically classify the severity of liver stiffening using anatomic biparametric MR images in children and young adults. Model refinements and incorporation of clinical features may decrease the need for MRE.
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Affiliation(s)
- Redha Ali
- Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hailong Li
- Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Neurodevelopmental Disorders Prevention Center, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Artificial Intelligence Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Huixian Zhang
- Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Wen Pan
- Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, Biomedical Engineering, Medicine, Emergency Medicine, University of Wisconsin, Madison, WI, USA
| | - David Harris
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - William Masch
- Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA
| | - Anum Aslam
- Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA
| | | | - Anas Bernieh
- Division of Pathology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Nehal Parikh
- Neurodevelopmental Disorders Prevention Center, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jonathan R Dillman
- Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Artificial Intelligence Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
| | - Lili He
- Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Neurodevelopmental Disorders Prevention Center, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Artificial Intelligence Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Department of Computer Science, Biomedical Engineering, Biomedical Informatics, University of Cincinnati, Cincinnati, OH, USA.
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Hisatomi E, Tanaka S, Sato K, Goto N, Murayama R, Arima H, Takayama Y, Yoshimitsu K. Heterogeneous development of liver fibrosis in chronic hepatitis C patients; assessment by extracellular volume fraction map generated from routine clinical CT data. Eur J Radiol 2025; 182:111845. [PMID: 39616947 DOI: 10.1016/j.ejrad.2024.111845] [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: 08/12/2024] [Revised: 11/07/2024] [Accepted: 11/23/2024] [Indexed: 12/16/2024]
Abstract
OBJECTIVES To clarify the heterogeneous development of liver fibrosis in patients with chronic hepatitis C (CHC) using extracellular volume fraction (ECV) map obtained from routine clinical CT data. METHODS Between November 2012 and July 2020, patients with CHC were retrospectively recruited who had undergone four-phase CT and MR elastography (MRE) within one year. Patients were divided into 4 grades to represent different cirrhotic/fibrotic stage, using two different methods; one based on liver stiffness measured by MRE (MRE model), and the other by mALBI grades (mALBI model). Liver was anatomically divided into 16 sections, namely peripheral and central areas of each segment. ECV map was generated according to the previously reported method, and ECV was measured for the 16 sections. Estimated pathological fibrosis grade was assigned for each section based on the previously reported data. RESULTS There were 150 patients available. In each anatomical section, ECV significantly increases as cirrhotic /fibrotic stage progresses. The peripheral areas of segments 4,5 and 8 were the earliest to show F2 or F3-equivalent ECV (p < 0.05), followed by central areas or other segments. The central areas of segments 6 and 7 were the last to be involved by fibrosis both in MRE and mALBI models, finally almost all sections showing F4-equivalent ECV at the end stage fibrosis. CONCLUSION Fibrosis starts at the peripheral areas of segments 4, 5, and 8, and spreads towards other parts of the liver, with the central areas of segments 6 and 7 being the last, in patients with CHC.
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Affiliation(s)
- Eiko Hisatomi
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Shinji Tanaka
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Keisuke Sato
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Nahoko Goto
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Ryo Murayama
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Hisatomi Arima
- Department of Preventive Medicine and Public Health, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Yukihisa Takayama
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
| | - Kengo Yoshimitsu
- Department of Radiology, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
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Charoenchue P, Khorana J, Chitapanarux T, Inmutto N, Na Chiangmai W, Amantakul A, Pojchamarnwiputh S, Tantraworasin A. Two-Dimensional Shear-Wave Elastography: Accuracy in Liver Fibrosis Staging Using Magnetic Resonance Elastography as the Reference Standard. Diagnostics (Basel) 2024; 15:62. [PMID: 39795589 PMCID: PMC11719920 DOI: 10.3390/diagnostics15010062] [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: 12/03/2024] [Revised: 12/24/2024] [Accepted: 12/28/2024] [Indexed: 01/13/2025] Open
Abstract
Background: The accurate staging of liver fibrosis is crucial for managing chronic liver disease (CLD). Although magnetic resonance elastography (MRE) is the reference standard for noninvasive fibrosis assessment, its cost, specialized hardware, and operational demands restrict accessibility. In contrast, two-dimensional shear-wave elastography (2D-SWE) is more affordable, accessible, and widely integrated into routine ultrasound systems. Objective: Our aim was to determine the optimal 2D-SWE cut-offs for detecting significant fibrosis (≥F2) and evaluate its diagnostic performance across fibrosis stages. Methods: In this prospective study, 71 patients with suspected CLD underwent same-day MRE and 2D-SWE. MRE-defined cut-offs categorized fibrosis stages (≥3.5 kPa for significant fibrosis). Sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), and likelihood ratios were calculated for various 2D-SWE thresholds. Results: At a 2D-SWE cut-off of 7.0 kPa, sensitivity for detecting ≥F2 fibrosis was 100% with a specificity of 85.7% and a positive likelihood ratio (LR+) of 7.0. Increasing the threshold to 8.0 kPa improved specificity to 91.8% while maintaining a sensitivity of 86.4% and achieving an AUROC of 0.89. For cirrhosis, a cut-off of 11.0 kPa achieved 100% sensitivity and 96.9% specificity. A 5.0 kPa cut-off reliably excluded abnormal stiffness with 89.1% sensitivity. Conclusions: Two-dimensional SWE is a reliable method for staging liver fibrosis. Thresholds of 7.0 kPa for screening significant fibrosis, 8.0 kPa for confirmation, and 11.0 kPa for diagnosing cirrhosis demonstrate high diagnostic accuracy. A 5.0 kPa cut-off effectively excludes abnormal liver stiffness.
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Affiliation(s)
- Puwitch Charoenchue
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (P.C.); (N.I.); (W.N.C.); (A.A.)
| | - Jiraporn Khorana
- Department of Surgery, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand;
- Department of Biomedical Informatics and Clinical Epidemiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
- Clinical Surgical Research Center, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Taned Chitapanarux
- Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand;
| | - Nakarin Inmutto
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (P.C.); (N.I.); (W.N.C.); (A.A.)
| | - Wittanee Na Chiangmai
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (P.C.); (N.I.); (W.N.C.); (A.A.)
| | - Amonlaya Amantakul
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (P.C.); (N.I.); (W.N.C.); (A.A.)
| | - Suwalee Pojchamarnwiputh
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; (P.C.); (N.I.); (W.N.C.); (A.A.)
| | - Apichat Tantraworasin
- Department of Surgery, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand;
- Clinical Surgical Research Center, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
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9
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Gomes NBN, Torres US, Ferraz MLCG, D'Ippolito G. Advanced Magnetic Resonance Imaging for Detection of Liver Fibrosis and Inflammation in Autoimmune Hepatitis: A State-of-the-Art Review. Semin Ultrasound CT MR 2024; 45:464-475. [PMID: 39069278 DOI: 10.1053/j.sult.2024.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Autoimmune hepatitis is a rare chronic liver disease, associated with a high level of morbidity and high mortality; approximately 40% of patients with severe untreated disease die within 6 months of diagnosis. It should be treated to achieve complete biochemical and histologic resolution of the disease using corticosteroids and immunosuppression to prevent further progression to cirrhosis. The use of invasive liver biopsy is recommended for the staging and assessment of inflammation and fibrosis for treatment decision-making in the face of an unsatisfactory response or clinical remission, including being a determinant for withdrawal of immunosuppression. On the other hand, liver biopsy is invasive, costly, and not free of complications. It also has potential sampling error and poor interobserver agreement. The limitations of liver biopsy highlight the importance of developing new imaging biomarkers that allow accurate and non-invasive assessment of autoimmune hepatitis in terms of liver inflammation and fibrosis, developing the virtual biopsy concept. Therefore, we review the state-of-the-art of Magnetic Resonance Imaging sequences for the noninvasive evaluation of autoimmune hepatitis, including historical advances and future directions.
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Affiliation(s)
- Natália B N Gomes
- Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil; Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Ulysses S Torres
- Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil; Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.
| | - Maria Lucia C G Ferraz
- Department of Gastroenterology, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Giuseppe D'Ippolito
- Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil; Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
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10
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Hanedan Uslu G, Taşçı F. Impact of right-sided breast cancer adjuvant radiotherapy on the liver. Radiol Oncol 2024; 58:535-543. [PMID: 39608011 PMCID: PMC11604264 DOI: 10.2478/raon-2024-0059] [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: 08/06/2024] [Accepted: 09/17/2024] [Indexed: 11/30/2024] Open
Abstract
BACKGROUND In patients with right-sided breast cancer the liver can be partially irradiated during adjuvant radiotherapy (RT). We aimed to determine breast cancer RT effects on liver using with magnetic resonance elastography (MRE) and biological results. PATIENTS AND METHODS This retrospective study enrolled 34 patients diagnosed with right-sided breast cancer who underwent adjuvant RT. Liver segment assessments were conducted using MRE for all participants. Additionally, a complete blood count and liver enzyme analysis were performed for each patient. All measurements were taken both prior to the initiation and upon completion of RT. RESULTS A statistically significant difference was found in ALT (p = 0.015), ALP (p = 0.026), total protein (p = 0.037), and albumin (p = 0.004) levels before and after RT. The highest mean liver stiffness (kPa) value was recorded in segment 8, while the lowest was observed in segment 6. A weak but statistically significant positive correlation was found between segment 5 stiffness and liver volume (p = 0.039). Additionally, a statistically significant positive correlation was detected between ALP levels and the stiffness values in segment 4A (p = 0.020) and segment 6 (p = 0.003). Conversely, a weak negative correlation was observed between the stiffness values in segment 8 and post-RT total protein levels (p = 0.031). CONCLUSIONS MRE can help us identify the level of fibrotic stiffness in the liver segments within the RT area without establishing clinical symptoms. MRE can support the clinician in evaluating the liver functions of right breast cancer patients who underwent RT. We assume these results will facilitate new studies with a large number of patients on MRE imaging at certain intervals in the follow-up of patients with right breast cancer who received RT before the development of radiation-induced liver disease (RILD).
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Affiliation(s)
- Gonca Hanedan Uslu
- Department of Radiation Oncology, İstinye University, Faculty of Medicine, İstanbul, Turkey
| | - Filiz Taşçı
- Department of Radiology, Recep Tayyip Erdogan University Faculty of Medicine, Rize, Turkey
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11
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Low G, Chee RKW, Wong YJ, Tandon P, Manolea F, Locas S, Ferguson C, Tu W, Wilson MP. Abbreviated Multiparametric MR Solution (the "Liver Triple Screen"), the Future of Non-Invasive MR Quantification of Liver Fat, Iron, and Fibrosis. Diagnostics (Basel) 2024; 14:2373. [PMID: 39518341 PMCID: PMC11545674 DOI: 10.3390/diagnostics14212373] [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: 10/05/2024] [Revised: 10/18/2024] [Accepted: 10/23/2024] [Indexed: 11/16/2024] Open
Abstract
Background/Objectives: To review the findings of a multiparametric MRI (the "liver triple screen") solution for the non-invasive assessment of liver fat, iron, and fibrosis in patients with chronic liver disease (CLD). Methods: A retrospective evaluation of all consecutive triple screen MRI cases was performed at our institution over the last 32 months. Relevant clinical, laboratory, and radiologic data were analyzed using descriptive statistics. Results: There were 268 patients, including 162 (60.4%) males and 106 (39.6%) females. The mean age was 54 ± 15.2 years (range 16 to 71 years). The most common cause of CLD was metabolic dysfunction-associated steatotic liver disease (MASLD) at 45.5%. The most common referring physician group was Gastroenterology at 62.7%. In 23.9% of cases, the reason for ordering the MRI was a pre-existing failed or unreliable US elastography. There were 17 cases (6.3%) of MRI technical failure. Our analysis revealed liver fibrosis in 66% of patients, steatosis in 68.3%, and iron overload in 22.1%. Combined fibrosis and steatosis were seen in 28.7%, steatosis and iron overload in 16.8%, fibrosis and iron overload in 6%, and combined fibrosis, steatosis, and iron overload in 4.1%. A positive MEFIB index, a predictor of liver-related outcomes, was found in 57 (27.5%) of 207 patients. Incidental findings were found in 14.9% of all MRIs. Conclusions: The liver triple screen MRI is an effective tool for evaluating liver fat, iron, and fibrosis in patients with CLD. It provides essential clinical information and can help identify MASLD patients at risk for liver-related outcomes.
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Affiliation(s)
- Gavin Low
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
| | - Ryan K. W. Chee
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
| | - Yu Jun Wong
- Division of Gastroenterology (Liver Unit), University of Alberta, Edmonton, AB T6G 1C9, Canada; (Y.J.W.); (P.T.)
| | - Puneeta Tandon
- Division of Gastroenterology (Liver Unit), University of Alberta, Edmonton, AB T6G 1C9, Canada; (Y.J.W.); (P.T.)
| | - Florin Manolea
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
| | - Stephanie Locas
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
| | - Craig Ferguson
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
| | - Wendy Tu
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
| | - Mitchell P. Wilson
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB T6G 1C9, Canada (F.M.); (S.L.); (C.F.); (W.T.); (M.P.W.)
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12
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Guagliano G, Volpini C, Sardelli L, Briatico Vangosa F, Visai L, Petrini P. Bioinspired Bioinks for the Fabrication of Chemomechanically Relevant Standalone Disease Models of Hepatic Steatosis. Adv Healthc Mater 2024; 13:e2303349. [PMID: 38323754 DOI: 10.1002/adhm.202303349] [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: 10/02/2023] [Revised: 01/17/2024] [Indexed: 02/08/2024]
Abstract
Hepatotoxicity-related issues are poorly predicted during preclinical experimentation, as its relevance is limited by the inadequacy to screen all the non-physiological subclasses of the population. These pitfalls can be solved by implementing complex in vitro models of hepatic physiology and pathologies in the preclinical phase. To produce these platforms, extrusion-based bioprinting is focused on, since it allows to manufacture tridimensional cell-laden constructs with controlled geometries, in a high-throughput manner. Different bioinks, whose formulation is tailored to mimic the chemomechanical environment of hepatic steatosis, the most prevalent hepatic disorder worldwide, are proposed. Internally crosslinked alginate hydrogels are chosen as structural components of the inks. Their viscoelastic properties (G' = 512-730 Pa and G″ = 94-276 Pa, depending on frequency) are tuned to mimic those of steatotic liver tissue. Porcine hepatic ECM is introduced as a relevant biochemical cue. Sodium oleate is added to recall the accumulation of lipids in the tissue. Downstream analyses on 14-layered bioprinted structures cultured for 10 days reveal the establishment of steatotic-like features (intracellular lipid vesicles, viability decrease up to ≈50%) without needing external conditionings. The presented bioinks are thus suitable to fabricate complex models of hepatic steatosis to be implemented in a high-throughput experimental frame.
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Affiliation(s)
- Giuseppe Guagliano
- Department of Chemistry, Materials, and Chemical Engineering "G. Natta", Politecnico di Milano, P.zza L. Da Vinci 32, Milan, 20133, Italy
| | - Cristina Volpini
- Molecular Medicine Department (DMM), Center for Health Technologies (CHT), UdR INSTM, University of Pavia, Pavia, 65-27100, Italy
- Medicina Clinica-Specialistica, UOR5 Laboratorio Di Nanotecnologie, ICS Maugeri, IRCCS, Pavia, Via Boezio, Pavia, 28-27100, Italy
| | - Lorenzo Sardelli
- Department of Chemistry, Materials, and Chemical Engineering "G. Natta", Politecnico di Milano, P.zza L. Da Vinci 32, Milan, 20133, Italy
| | - Francesco Briatico Vangosa
- Department of Chemistry, Materials, and Chemical Engineering "G. Natta", Politecnico di Milano, P.zza L. Da Vinci 32, Milan, 20133, Italy
| | - Livia Visai
- Molecular Medicine Department (DMM), Center for Health Technologies (CHT), UdR INSTM, University of Pavia, Pavia, 65-27100, Italy
- Medicina Clinica-Specialistica, UOR5 Laboratorio Di Nanotecnologie, ICS Maugeri, IRCCS, Pavia, Via Boezio, Pavia, 28-27100, Italy
- Interuniversity Center for the promotion of the 3Rs principles in teaching and research (Centro 3R), Università di Pavia Unit, Pavia, 5-27100, Italy
| | - Paola Petrini
- Department of Chemistry, Materials, and Chemical Engineering "G. Natta", Politecnico di Milano, P.zza L. Da Vinci 32, Milan, 20133, Italy
- Interuniversity Center for the promotion of the 3Rs principles in teaching and research (Centro 3R), Politecnico di Milano Unit, Milano, 32-20133, Italy
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13
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Moura Cunha G, Fan B, Navin PJ, Olivié D, Venkatesh SK, Ehman RL, Sirlin CB, Tang A. Interpretation, Reporting, and Clinical Applications of Liver MR Elastography. Radiology 2024; 310:e231220. [PMID: 38470236 PMCID: PMC10982829 DOI: 10.1148/radiol.231220] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 11/21/2023] [Accepted: 11/24/2023] [Indexed: 03/13/2024]
Abstract
Chronic liver disease is highly prevalent and often leads to fibrosis or cirrhosis and complications such as liver failure and hepatocellular carcinoma. The diagnosis and staging of liver fibrosis is crucial to determine management and mitigate complications. Liver biopsy for histologic assessment has limitations such as sampling bias and high interreader variability that reduce precision, which is particularly challenging in longitudinal monitoring. MR elastography (MRE) is considered the most accurate noninvasive technique for diagnosing and staging liver fibrosis. In MRE, low-frequency vibrations are applied to the abdomen, and the propagation of shear waves through the liver is analyzed to measure liver stiffness, a biomarker for the detection and staging of liver fibrosis. As MRE has become more widely used in clinical care and research, different contexts of use have emerged. This review focuses on the latest developments in the use of MRE for the assessment of liver fibrosis; provides guidance for image acquisition and interpretation; summarizes diagnostic performance, along with thresholds for diagnosis and staging of liver fibrosis; discusses current and emerging clinical applications; and describes the latest technical developments.
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Affiliation(s)
- Guilherme Moura Cunha
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Boyan Fan
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Patrick J. Navin
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Damien Olivié
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Sudhakar K. Venkatesh
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Richard L. Ehman
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Claude B. Sirlin
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - An Tang
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
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14
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Zerunian M, Masci B, Caruso D, Pucciarelli F, Polici M, Nardacci S, De Santis D, Iannicelli E, Laghi A. Liver Magnetic Resonance Elastography: Focus on Methodology, Technique, and Feasibility. Diagnostics (Basel) 2024; 14:379. [PMID: 38396418 PMCID: PMC10887609 DOI: 10.3390/diagnostics14040379] [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: 12/28/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Magnetic resonance elastography (MRE) is an imaging technique that combines low-frequency mechanical vibrations with magnetic resonance imaging to create visual maps and quantify liver parenchyma stiffness. As in recent years, diffuse liver diseases have become highly prevalent worldwide and could lead to a chronic condition with different stages of fibrosis. There is a strong necessity for a non-invasive, highly accurate, and standardised quantitative assessment to evaluate and manage patients with different stages of fibrosis from diagnosis to follow-up, as the actual reference standard for the diagnosis and staging of liver fibrosis is biopsy, an invasive method with possible peri-procedural complications and sampling errors. MRE could quantitatively evaluate liver stiffness, as it is a rapid and repeatable method with high specificity and sensitivity. MRE is based on the propagation of mechanical shear waves through the liver tissue that are directly proportional to the organ's stiffness, expressed in kilopascals (kPa). To obtain a valid assessment of the real hepatic stiffness values, it is mandatory to obtain a high-quality examination. To understand the pearls and pitfalls of MRE, in this review, we describe our experience after one year of performing MRE from indications and patient preparation to acquisition, quality control, and image analysis.
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Affiliation(s)
- Marta Zerunian
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
- PhD School in Translational Medicine and Oncology, Department of Medical and Surgical Sciences and Translational Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Benedetta Masci
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Damiano Caruso
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Francesco Pucciarelli
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Michela Polici
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
- PhD School in Translational Medicine and Oncology, Department of Medical and Surgical Sciences and Translational Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Stefano Nardacci
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Domenico De Santis
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Elsa Iannicelli
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Andrea Laghi
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
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15
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Alharbi FM, Besbes FR, Almutairi BS, Alotaibi AT, Fatani FF, Besbes HR. Fusion of Magnetic Resonance Elastography Images With Computed Tomography and Magnetic Resonance Imaging Using the Human Visual System. Cureus 2023; 15:e45109. [PMID: 37842423 PMCID: PMC10569364 DOI: 10.7759/cureus.45109] [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] [Accepted: 09/12/2023] [Indexed: 10/17/2023] Open
Abstract
Magnetic resonance elastography (MRE) is used to assess the stiffness of the liver to rule out cirrhosis or fibrosis. The image, nevertheless, is regarded as shear-wave imaging and does not depict any anatomical features. Multimodality medical image fusion (MMIF), such as the fusion of MRE with computed tomography (CT) scan or magnetic resonance imaging (MRI), can help doctors optimize the advantages of each imaging technique. As a result, perceptions serve as valid and valuable assessment criteria. The contrast sensitivity function (CSF), which describes the rates of visual contrast sensitivity through the changing of spatial frequencies, is used mathematically to characterize the human visual system (HVS). As a result, we suggest novel methods for fusing images that use discrete wavelets transform (DWT) based on HVS and CSF models. Images from MRI or CT scan were combined with MRE images, and the outcomes were assessed both subjectively and objectively. Visual inspection of merging images was done throughout the qualitative analysis. The CT-MRE fused images in all four datasets were shown to be superior at maintaining bones and spatial resolution, despite the MRI-MRE being better at exhibiting soft tissues and contrast resolution. It is clear from all four datasets that the liver soft tissue in MRI and CT images mixed successfully with the red-colored stiffness distribution seen in MRE images. The proposed approach outperformed DWT, which produced visual artifacts such as signal loss. Quantitative evaluation using mean, standard deviation, and entropy showed that the generated images from the proposed technique performed better than the source images and DWT. Additionally, peak signal-to-noise ratio, mean square error, correlation coefficient, and structural similarity index measure were employed to compare the two fusion approaches, namely, MRI-MRE and CT-MRE. The comparison did not show the superiority of one approach over the other. In conclusion, both subjective and objective evaluation approaches revealed that the combined images contained more information and characteristics. Hence, the proposed method might be a useful procedure to diagnose and localize the stiffness regions on the liver soft tissue by fusion of MRE with MRI or CT.
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16
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Ciardullo S, Vergani M, Perseghin G. Nonalcoholic Fatty Liver Disease in Patients with Type 2 Diabetes: Screening, Diagnosis, and Treatment. J Clin Med 2023; 12:5597. [PMID: 37685664 PMCID: PMC10488336 DOI: 10.3390/jcm12175597] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/21/2023] [Accepted: 08/26/2023] [Indexed: 09/10/2023] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD), recently renamed metabolic dysfunction-associated steatotic liver disease (MASLD) affects ~70% of patients with type 2 diabetes (T2D), with ~20% showing signs of advanced liver fibrosis. Patients with T2D are at an increased risk of developing cirrhosis, liver failure, and hepatocellular carcinoma and their liver-related mortality is doubled compared with non-diabetic individuals. Nonetheless, the condition is frequently overlooked and disease awareness is limited both among patients and among physicians. Given recent epidemiological evidence, clinical practice guidelines recommend screening for NAFLD/MASLD and advanced liver fibrosis in patients with T2D. While many drugs are currently being tested for the treatment of NAFLD/MASLD, none of them have yet received formal approval from regulatory agencies. However, several classes of antidiabetic drugs (namely pioglitazone, sodium-glucose transporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and multi-agonists) have shown favorable effects in terms of liver enzymes, liver fat content and, in some occasions, on histologic features such as inflammation and fibrosis. Therefore, diabetologists have the opportunity to actively treat NAFLD/MASLD, with a concrete possibility of changing the natural history of the disease. In the present narrative review, we summarize evidence and clinical recommendations for NAFLD/MAFLD screening in the setting of T2D, as well as on the effect of currently available glucose-lowering drugs on hepatic endpoints.
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Affiliation(s)
- Stefano Ciardullo
- Department of Medicine and Rehabilitation, Policlinico di Monza, Via Modigliani 10, 20900 Monza, MB, Italy; (M.V.); (G.P.)
- Department of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, MI, Italy
| | - Michela Vergani
- Department of Medicine and Rehabilitation, Policlinico di Monza, Via Modigliani 10, 20900 Monza, MB, Italy; (M.V.); (G.P.)
- Department of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, MI, Italy
| | - Gianluca Perseghin
- Department of Medicine and Rehabilitation, Policlinico di Monza, Via Modigliani 10, 20900 Monza, MB, Italy; (M.V.); (G.P.)
- Department of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, MI, Italy
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17
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Obrzut M, Atamaniuk V, Ehman RL, Yin M, Cholewa M, Gutkowski K, Domka W, Ozga D, Obrzut B. Evaluation of Spleen Stiffness in Young Healthy Volunteers Using Magnetic Resonance Elastography. Diagnostics (Basel) 2023; 13:2738. [PMID: 37685274 PMCID: PMC10486410 DOI: 10.3390/diagnostics13172738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/16/2023] [Accepted: 08/20/2023] [Indexed: 09/10/2023] Open
Abstract
PURPOSE Magnetic resonance elastography (MRE) has been established as the most accurate noninvasive technique for diagnosing liver fibrosis. Recent publications have suggested that the measurement of splenic stiffness is useful in setting where portal hypertension may be present. The goal of the current study was to compile normative data for MRE-assessed stiffness measurements of the spleen in young adults. MATERIALS AND METHODS A total of 100 healthy young Caucasian volunteers (65 females and 35 males) in the age range of 20 to 32 years were enrolled in this study. The participants reported no history of chronic spleen and liver disease, normal alcohol consumption, and a normal diet. The MRE data were acquired by using a 1.5 T whole-body scanner and a 2D GRE pulse sequence with 60 Hz excitation. Spleen stiffness was calculated as a weighted mean of stiffness values in the regions of interest manually drawn by the radiologist on three to five spleen slices. RESULTS Mean spleen stiffness was 5.09 ± 0.65 kPa for the whole group. Male volunteers had slightly higher splenic stiffness compared to females: 5.28 ± 0.78 vs. 4.98 ± 0.51 kPa, however, this difference was not statistically significant (p = 0.12). Spleen stiffness did not correlate with spleen fat content and liver stiffness but a statistically significant correlation with spleen volume was found. CONCLUSIONS The findings of this study provide normative values for 2D MRE-based measurement of spleen stiffness in young adults, a basis for assessing the value of this biomarker in young patients with portal system pathologies.
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Affiliation(s)
- Marzanna Obrzut
- Institute of Health Sciences, Medical College, University of Rzeszow, Warzywna 1a, 35-310 Rzeszow, Poland; (M.O.)
| | - Vitaliy Atamaniuk
- Department of Biophysics, Institute of Physics, College of Natural Sciences, University of Rzeszow, Prof. Stanisława Pigonia Str. 1, 35-310 Rzeszow, Poland; (V.A.); (M.C.)
| | - Richard L. Ehman
- Department of Radiology, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA
| | - Marian Cholewa
- Department of Biophysics, Institute of Physics, College of Natural Sciences, University of Rzeszow, Prof. Stanisława Pigonia Str. 1, 35-310 Rzeszow, Poland; (V.A.); (M.C.)
| | - Krzysztof Gutkowski
- Institute of Medical Sciences, Medical College, University of Rzeszow, Rejtana 16C, 35-959 Rzeszow, Poland;
| | - Wojciech Domka
- Department of Otolaryngology, Institute of Medical Sciences, Medical College, University of Rzeszow, Rejtana 16C, 35-959 Rzeszow, Poland;
| | - Dorota Ozga
- Institute of Health Sciences, Medical College, University of Rzeszow, Warzywna 1a, 35-310 Rzeszow, Poland; (M.O.)
| | - Bogdan Obrzut
- Department of Obstetrics and Gynecology, Institute of Medical Sciences, Medical College, University of Rzeszow, Rejtana 16C, 35-959 Rzeszow, Poland
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18
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Bresnahan R, Duarte R, Mahon J, Beale S, Chaplin M, Bhattacharyya D, Houten R, Edwards K, Nevitt S, Maden M, Boland A. Diagnostic accuracy and clinical impact of MRI-based technologies for patients with non-alcoholic fatty liver disease: systematic review and economic evaluation. Health Technol Assess 2023; 27:1-115. [PMID: 37839810 PMCID: PMC10591209 DOI: 10.3310/kgju3398] [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] [Indexed: 10/17/2023] Open
Abstract
Background Magnetic resonance imaging-based technologies are non-invasive diagnostic tests that can be used to assess non-alcoholic fatty liver disease. Objectives The study objectives were to assess the diagnostic test accuracy, clinical impact and cost-effectiveness of two magnetic resonance imaging-based technologies (LiverMultiScan and magnetic resonance elastography) for patients with non-alcoholic fatty liver disease for whom advanced fibrosis or cirrhosis had not been diagnosed and who had indeterminate results from fibrosis testing, or for whom transient elastography or acoustic radiation force impulse was unsuitable, or who had discordant results from fibrosis testing. Data sources The data sources searched were MEDLINE, MEDLINE Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Database of Controlled Trials, Database of Abstracts of Reviews of Effects and the Health Technology Assessment. Methods A systematic review was conducted using established methods. Diagnostic test accuracy estimates were calculated using bivariate models and a summary receiver operating characteristic curve was calculated using a hierarchical model. A simple decision-tree model was developed to generate cost-effectiveness results. Results The diagnostic test accuracy review (13 studies) and the clinical impact review (11 studies) only included one study that provided evidence for patients who had indeterminate or discordant results from fibrosis testing. No studies of patients for whom transient elastography or acoustic radiation force impulse were unsuitable were identified. Depending on fibrosis level, relevant published LiverMultiScan diagnostic test accuracy results ranged from 50% to 88% (sensitivity) and from 42% to 75% (specificity). No magnetic resonance elastography diagnostic test accuracy data were available for the specific population of interest. Results from the clinical impact review suggested that acceptability of LiverMultiScan was generally positive. To explore how the decision to proceed to biopsy is influenced by magnetic resonance imaging-based technologies, the External Assessment Group presented cost-effectiveness analyses for LiverMultiScan plus biopsy versus biopsy only. Base-case incremental cost-effectiveness ratio per quality-adjusted life year gained results for seven of the eight diagnostic test strategies considered showed that LiverMultiScan plus biopsy was dominated by biopsy only; for the remaining strategy (Brunt grade ≥2), the incremental cost-effectiveness ratio per quality-adjusted life year gained was £1,266,511. Results from threshold and scenario analyses demonstrated that External Assessment Group base-case results were robust to plausible variations in the magnitude of key parameters. Limitations Diagnostic test accuracy, clinical impact and cost-effectiveness data for magnetic resonance imaging-based technologies for the population that is the focus of this assessment were limited. Conclusions Magnetic resonance imaging-based technologies may be useful to identify patients who may benefit from additional testing in the form of liver biopsy and those for whom this additional testing may not be necessary. However, there is a paucity of diagnostic test accuracy and clinical impact data for patients who have indeterminate results from fibrosis testing, for whom transient elastography or acoustic radiation force impulse are unsuitable or who had discordant results from fibrosis testing. Given the External Assessment Group cost-effectiveness analyses assumptions, the use of LiverMultiScan and magnetic resonance elastography for assessing non-alcoholic fatty liver disease for patients with inconclusive results from previous fibrosis testing is unlikely to be a cost-effective use of National Health Service resources compared with liver biopsy only. Study registration This study is registered as PROSPERO CRD42021286891. Funding Funding for this study was provided by the Evidence Synthesis Programme of the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 27, No. 10. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Rebecca Bresnahan
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Rui Duarte
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - James Mahon
- Coldingham Analytical Services, Berwickshire, UK
| | | | - Marty Chaplin
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | | | - Rachel Houten
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Katherine Edwards
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Sarah Nevitt
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Michelle Maden
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Angela Boland
- LRiG, Department of Health Data Science, University of Liverpool, Liverpool, UK
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19
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Guglielmo FF, Barr RG, Yokoo T, Ferraioli G, Lee JT, Dillman JR, Horowitz JM, Jhaveri KS, Miller FH, Modi RY, Mojtahed A, Ohliger MA, Pirasteh A, Reeder SB, Shanbhogue K, Silva AC, Smith EN, Surabhi VR, Taouli B, Welle CL, Yeh BM, Venkatesh SK. Liver Fibrosis, Fat, and Iron Evaluation with MRI and Fibrosis and Fat Evaluation with US: A Practical Guide for Radiologists. Radiographics 2023; 43:e220181. [PMID: 37227944 DOI: 10.1148/rg.220181] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. © RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Flavius F Guglielmo
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Richard G Barr
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Takeshi Yokoo
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Giovanna Ferraioli
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - James T Lee
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Jonathan R Dillman
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Jeanne M Horowitz
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Kartik S Jhaveri
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Frank H Miller
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Roshan Y Modi
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Amirkasra Mojtahed
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Michael A Ohliger
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Ali Pirasteh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Scott B Reeder
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Krishna Shanbhogue
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Alvin C Silva
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Elainea N Smith
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Venkateswar R Surabhi
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Bachir Taouli
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Christopher L Welle
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Benjamin M Yeh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Sudhakar K Venkatesh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
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20
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Martin de Miguel I, Kamath PS, Egbe AC, Jain CC, Cetta F, Connolly HM, Miranda WR. Haemodynamic and prognostic associations of liver fibrosis scores in Fontan-associated liver disease. Heart 2023; 109:619-625. [PMID: 36581444 DOI: 10.1136/heartjnl-2022-321435] [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: 05/23/2022] [Accepted: 11/17/2022] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVES Fontan-associated liver disease (FALD) is universal post-Fontan palliation; however, its impact on survival remains controversial and current diagnostic tools have limitations. We aimed to assess the prognostic role of liver fibrosis scores (aminotransferase to platelet ratio [APRI] and fibrosis-4 [FIB-4]) and their association with haemodynamics and other markers of liver disease. METHODS 159 adults (age ≥18 years) post-Fontan undergoing catheterisation at Mayo Clinic, Minnesota, between 1999 and 2017 were included. Invasive haemodynamics and FALD-related laboratory, imaging and pathology data were documented. RESULTS Mean age was 31.5±9.3 years, while median age at Fontan procedure was 7.5 years (4-14). Median APRI score (n=159) was 0.49 (0.33-0.61) and median FIB-4 score (n=94) was 1.12 (0.71-1.65). Correlations between APRI and FIB-4 scores and Fontan pressures (r=0.30, p=0.0002; r=0.34, p=0.0008, respectively) and pulmonary arterial wedge pressure (r=0.25, p=0.002; r=0.30, p=0.005, respectively) were weak. Median average hepatic stiffness by magnetic resonance elastography was 4.9 kPa (4.3-6.0; n=26) and 24 (77.4%) showed stage 3 or 4 liver fibrosis on biopsy; these variables were not associated with APRI/FIB-4 scores. On multivariable analyses, APRI and FIB-4 scores were independently associated with overall mortality (HR 1.31 [1.07-1.55] per unit increase, p=0.003; HR 2.15 [1.31-3.54] per unit increase, p=0.003, respectively). CONCLUSIONS APRI and FIB-4 scores were associated with long-term all-cause mortality in Fontan patients independent of other prognostic markers. Correlations between haemodynamic status and liver scores were weak; furthermore, most markers of liver fibrosis failed to correlate with non-invasive indices, underscoring the complexity of FALD.
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Affiliation(s)
| | - Patrick S Kamath
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Alexander C Egbe
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - C Charles Jain
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Frank Cetta
- Division of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Heidi M Connolly
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - William R Miranda
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
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21
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Yoon D, Ruding M, Guertler CA, Okamoto RJ, Bayly PV. Design and characterization of 3-D printed hydrogel lattices with anisotropic mechanical properties. J Mech Behav Biomed Mater 2023; 138:105652. [PMID: 36610282 PMCID: PMC10159757 DOI: 10.1016/j.jmbbm.2023.105652] [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: 11/10/2022] [Revised: 12/20/2022] [Accepted: 01/01/2023] [Indexed: 01/04/2023]
Abstract
The goal of this study was to design, fabricate, and characterize hydrogel lattice structures with consistent, controllable, anisotropic mechanical properties. Lattices, based on three unit-cell types (cubic, diamond, and vintile), were printed using stereolithography (SLA) of polyethylene glycol diacrylate (PEGDA). To create structural anisotropy in the lattices, unit cell design files were scaled by a factor of two in one direction in each layer and then printed. The mechanical properties of the scaled lattices were measured in shear and compression and compared to those of the unscaled lattices. Two apparent shear moduli of each lattice were measured by dynamic shear tests in two planes: (1) parallel and (2) perpendicular to the scaling direction, or cell symmetry axis. Three apparent Young's moduli of each lattice were measured by compression in three different directions: (1) the "build" direction or direction of added layers, (2) the scaling direction, and (3) the unscaled direction perpendicular to both scaling and build directions. For shear deformation in unscaled lattices, the apparent shear moduli were similar in the two perpendicular directions. In contrast, scaled lattices exhibit clear differences in apparent shear moduli. In compression of unscaled lattices, apparent Young's moduli were independent of direction in cubic and vintile lattices; in diamond lattices Young's moduli differed in the build direction, but were similar in the other two directions. Scaled lattices in compression exhibited additional differences in apparent Young's moduli in the scaled and unscaled directions. Notably, the effects of scaling on apparent modulus differed between each lattice type (cubic, diamond, or vintile) and deformation mode (shear or compression). Scaling of 3D-printed, hydrogel lattices may be harnessed to create tunable, structures of desired shape, stiffness, and mechanical anisotropy, in both shear and compression.
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Affiliation(s)
- Daniel Yoon
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, Missouri, USA
| | - Margrethe Ruding
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, Missouri, USA
| | - Charlotte A Guertler
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, Missouri, USA
| | - Ruth J Okamoto
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, Missouri, USA
| | - Philip V Bayly
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, Missouri, USA.
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22
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Guagliano G, Volpini C, Sardelli L, Bloise N, Briatico-Vangosa F, Cornaglia AI, Dotti S, Villa R, Visai L, Petrini P. Hep3Gel: A Shape-Shifting Extracellular Matrix-Based, Three-Dimensional Liver Model Adaptable to Different Culture Systems. ACS Biomater Sci Eng 2023; 9:211-229. [PMID: 36525369 PMCID: PMC9832437 DOI: 10.1021/acsbiomaterials.2c01226] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Drug-induced hepatotoxicity is a leading cause of clinical trial withdrawal. Therefore, in vitro modeling the hepatic behavior and functionalities is not only crucial to better understand physiological and pathological processes but also to support drug development with reliable high-throughput platforms. Different physiological and pathological models are currently under development and are commonly implemented both within platforms for standard 2D cultures and within tailor-made chambers. This paper introduces Hep3Gel: a hybrid alginate-extracellular matrix (ECM) hydrogel to produce 3D in vitro models of the liver, aiming to reproduce the hepatic chemomechanical niche, with the possibility of adapting its shape to different manufacturing techniques. The ECM, extracted and powdered from porcine livers by a specifically set-up procedure, preserved its crucial biological macromolecules and was embedded within alginate hydrogels prior to crosslinking. The viscoelastic behavior of Hep3Gel was tuned, reproducing the properties of a physiological organ, according to the available knowledge about hepatic biomechanics. By finely tuning the crosslinking kinetics of Hep3Gel, its dualistic nature can be exploited either by self-spreading or adapting its shape to different culture supports or retaining the imposed fiber shape during an extrusion-based 3D-bioprinting process, thus being a shape-shifter hydrogel. The self-spreading ability of Hep3Gel was characterized by combining empirical and numerical procedures, while its use as a bioink was experimentally characterized through rheological a priori printability evaluations and 3D printing tests. The effect of the addition of the ECM was evident after 4 days, doubling the survival rate of cells embedded within control hydrogels. This study represents a proof of concept of the applicability of Hep3Gel as a tool to develop 3D in vitro models of the liver.
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Affiliation(s)
- Giuseppe Guagliano
- Department
of Chemistry, Materials, and Chemical Engineering “G. Natta”, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133Milan, Italy
| | - Cristina Volpini
- Molecular
Medicine Department (DMM), Center for Health Technologies (CHT), UdR
INSTM, University of Pavia, 27100Pavia, Italy
| | - Lorenzo Sardelli
- Department
of Chemistry, Materials, and Chemical Engineering “G. Natta”, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133Milan, Italy
| | - Nora Bloise
- Molecular
Medicine Department (DMM), Center for Health Technologies (CHT), UdR
INSTM, University of Pavia, 27100Pavia, Italy
| | - Francesco Briatico-Vangosa
- Department
of Chemistry, Materials, and Chemical Engineering “G. Natta”, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133Milan, Italy
| | - Antonia Icaro Cornaglia
- Department
of Public Health, Experimental and Forensic Medicine, Histology and
Embryology Unit, University of Pavia, 27100Pavia, Italy
| | - Silvia Dotti
- National
Reference Center for Alternative Methods, Welfare and Care of Laboratory
Animals, Istituto Zooprofilattico Sperimentale
della Lomabardia ed Emilia Romagna, 25124Brescia, Italy
| | - Riccardo Villa
- National
Reference Center for Alternative Methods, Welfare and Care of Laboratory
Animals, Istituto Zooprofilattico Sperimentale
della Lomabardia ed Emilia Romagna, 25124Brescia, Italy
| | - Livia Visai
- Molecular
Medicine Department (DMM), Center for Health Technologies (CHT), UdR
INSTM, University of Pavia, 27100Pavia, Italy,Medicina
Clinica-Specialistica, UOR5 Laboratorio Di Nanotecnologie, ICS Maugeri, IRCCS, Pavia, Via Boezio, 28-27100Pavia, Italy,Interuniversity
Center for the Promotion of the 3Rs Principles in Teaching and Research
(Centro 3R), Università di Pavia
Unit, 27100Pavia, Italy
| | - Paola Petrini
- Department
of Chemistry, Materials, and Chemical Engineering “G. Natta”, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133Milan, Italy,Interuniversity
Center for the Promotion of the 3Rs Principles in Teaching and Research
(Centro 3R), Politecnico di Milano Unit, 20133Milan, Italy,
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Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1147111. [PMID: 36619303 PMCID: PMC9812615 DOI: 10.1155/2022/1147111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/10/2022] [Accepted: 12/12/2022] [Indexed: 12/29/2022]
Abstract
Diffuse liver diseases are highly prevalent conditions around the world, including pathological liver changes that occur when hepatocytes are damaged and liver function declines, often leading to a chronic condition. In the last years, Magnetic Resonance Imaging (MRI) is reaching an important role in the study of diffuse liver diseases moving from qualitative to quantitative assessment of liver parenchyma. In fact, this can allow noninvasive accurate and standardized assessment of diffuse liver diseases and can represent a concrete alternative to biopsy which represents the current reference standard. MRI approach already tested for other pathologies include diffusion-weighted imaging (DWI) and radiomics, able to quantify different aspects of diffuse liver disease. New emerging MRI quantitative methods include MR elastography (MRE) for the quantification of the hepatic stiffness in cirrhotic patients, dedicated gradient multiecho sequences for the assessment of hepatic fat storage, and iron overload. Thus, the aim of this review is to give an overview of the technical principles and clinical application of new quantitative MRI techniques for the evaluation of diffuse liver disease.
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Gao S, Zhang Y, Sun W, Jin K, Dai Y, Wang F, Qian X, Han J, Sheng R, Zeng M. Assessment of an
MR
Elastography‐Based Nomogram as a Potential Imaging Biomarker for Predicting Microvascular Invasion of Hepatocellular Carcinoma. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.28553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022] Open
Affiliation(s)
- Shanshan Gao
- Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
- Central Research Institute United Imaging Healthcare Shanghai China
| | - Yunfei Zhang
- Central Research Institute United Imaging Healthcare Shanghai China
- Shanghai Institute of Medical Imaging Shanghai China
| | - Wei Sun
- Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
- Central Research Institute United Imaging Healthcare Shanghai China
| | - Kaipu Jin
- Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
- Central Research Institute United Imaging Healthcare Shanghai China
| | - Yongming Dai
- Shanghai Institute of Medical Imaging Shanghai China
| | - Feihang Wang
- Central Research Institute United Imaging Healthcare Shanghai China
- Department of Interventional Radiology, Zhongshan Hospital Fudan University Shanghai China
| | - Xianling Qian
- Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
- Central Research Institute United Imaging Healthcare Shanghai China
| | - Jing Han
- Department of Pathology, Zhongshan Hospital Fudan University Shanghai China
| | - Ruofan Sheng
- Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
- Department of Radiology, Zhongshan Hospital (Xiamen) Fudan University Xiamen China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
- Central Research Institute United Imaging Healthcare Shanghai China
- Department of Cancer Center, Zhongshan Hospital Fudan University Shanghai China
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25
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The effects of geometry on stiffness measurements in high-field magnetic resonance elastography: A study on rodent cardiac phantoms. J Mech Behav Biomed Mater 2022; 133:105302. [DOI: 10.1016/j.jmbbm.2022.105302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/06/2022] [Accepted: 05/27/2022] [Indexed: 11/18/2022]
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Ozturk A, Olson MC, Samir AE, Venkatesh SK. Liver fibrosis assessment: MR and US elastography. Abdom Radiol (NY) 2022; 47:3037-3050. [PMID: 34687329 PMCID: PMC9033887 DOI: 10.1007/s00261-021-03269-4] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 08/31/2021] [Accepted: 09/01/2021] [Indexed: 01/18/2023]
Abstract
Elastography has emerged as a preferred non-invasive imaging technique for the clinical assessment of liver fibrosis. Elastography methods provide liver stiffness measurement (LSM) as a surrogate quantitative biomarker for fibrosis burden in chronic liver disease (CLD). Elastography can be performed either with ultrasound or MRI. Currently available ultrasound-based methods include strain elastography, two-dimensional shear wave elastography (2D-SWE), point shear wave elastography (pSWE), and vibration-controlled transient elastography (VCTE). MR Elastography (MRE) is widely available as two-dimensional gradient echo MRE (2D-GRE-MRE) technique. US-based methods provide estimated Young's modulus (eYM) and MRE provides magnitude of the complex shear modulus. MRE and ultrasound methods have proven to be accurate methods for detection of advanced liver fibrosis and cirrhosis. Other clinical applications of elastography include liver decompensation prediction, and differentiation of non-alcoholic steatohepatitis (NASH) from simple steatosis (SS). In this review, we briefly describe the different elastography methods, discuss current clinical applications, and provide an overview of advances in the field of liver elastography.
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Affiliation(s)
- Arinc Ozturk
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Michael C Olson
- Division of Abdominal Imaging, Radiology, Mayo Clinic Rochester, 200, First Street SW, Rochester, MN, 55905, USA
| | - Anthony E Samir
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Sudhakar K Venkatesh
- Division of Abdominal Imaging, Radiology, Mayo Clinic Rochester, 200, First Street SW, Rochester, MN, 55905, USA.
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Yadav Y, Dunagan K, Khot R, Venkatesh SK, Port J, Galderisi A, Cobelli C, Wegner C, Basu A, Carter R, Basu R. Inhibition of 11β-Hydroxysteroid dehydrogenase-1 with AZD4017 in patients with nonalcoholic steatohepatitis or nonalcoholic fatty liver disease: A randomized, double-blind, placebo-controlled, phase II study. Diabetes Obes Metab 2022; 24:881-890. [PMID: 35014156 PMCID: PMC9135169 DOI: 10.1111/dom.14646] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 01/05/2022] [Accepted: 01/06/2022] [Indexed: 11/29/2022]
Abstract
AIM To evaluate whether short-term treatment with a selective 11β-Hydroxysteroid dehydrogenase-1 (11β-HSD1) inhibitor, AZD4017, would block hepatic cortisol production and thereby decrease hepatic fat in patients with nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH), with or without type 2 diabetes (T2D). MATERIALS AND METHODS This was a randomized, double-blind, placebo-controlled, phase 2 study conducted at two sites. Key inclusion criteria were the presence of NAFLD or NASH on magnetic resonance imaging (MRI) or recent biopsy positive for NASH. Enrolled patients were randomly assigned (1:1) to AZD4017 or placebo for 12 weeks. Primary outcomes were between-group differences in mean change from baseline to week 12 in liver fat fraction (LFF) and conversion of 13 C cortisone to 13 C cortisol in the liver. RESULTS A total of 93 patients were randomized; 85 patients completed treatment. The mean (standard deviation [SD]) change in LFF was -0.667 (5.246) and 0.139 (4.323) in the AZD4017 and placebo groups (P = 0.441). For patients with NASH and T2D, the mean (SD) change in LFF was significantly improved in the AZD4017 versus the placebo group (-1.087 [5.374] vs. 1.675 [3.318]; P = 0.033). Conversion of 13 C cortisone to 13 C cortisol was blocked in all patients in the AZD4017 group. There were no significant between-group differences (AZD4017 vs. placebo) in changes in fibrosis, weight, levels of liver enzymes or lipids, or insulin sensitivity. CONCLUSION Although the study did not meet one of the primary outcomes, AZD4017 blocked the conversion of 13 C cortisone to 13 C cortisol in the liver in all patients who received the drug. In patients with NASH and T2D, AZD4017 improved liver steatosis versus placebo.
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Affiliation(s)
- Yogesh Yadav
- Division of EndocrinologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Kelly Dunagan
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Rachita Khot
- Division of Body Imaging, Department of Radiology and Medical ImagingUniversity of VirginiaCharlottesvilleVirginiaUSA
| | | | - John Port
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Alfonso Galderisi
- Department of Woman and Child's healthUniversity of PadovaPadovaVenetoItaly
| | - Claudio Cobelli
- Department of Woman and Child's healthUniversity of PadovaPadovaVenetoItaly
| | - Craig Wegner
- Retired from Emerging & Open Innovations Unit, IMED Biotech UnitAstraZenecaUSA
| | - Ananda Basu
- Division of EndocrinologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Rickey Carter
- Department of Quantitative Health SciencesMayo ClinicJacksonvilleFloridaUSA
| | - Rita Basu
- Division of EndocrinologyUniversity of VirginiaCharlottesvilleVirginiaUSA
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28
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Intra-patient comparison of 3D and 2D magnetic resonance elastography techniques for assessment of liver stiffness. Abdom Radiol (NY) 2022; 47:998-1008. [PMID: 34982182 DOI: 10.1007/s00261-021-03355-7] [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: 08/27/2021] [Revised: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To evaluate performance of 3D magnetic resonance elastography (MRE) using spin-echo echo-planar imaging (seEPI) for assessment of hepatic stiffness compared with 2D gradient-recalled echo (GRE) and 2D seEPI sequences. METHODS Fifty-seven liver MRE examinations including 2D GRE, 2D seEPI, and 3D seEPI sequences were retrospectively evaluated. Elastograms were analyzed by 2 radiologists and polygonal regions of interests (ROIs) were drawn in 2 different fashions: "curated" ROI (avoiding liver edge, major vessels, and areas of wave interferences) and "non-curated" ROI (including largest cross section of liver, to assess the contribution of artifacts). Liver stiffness measurement (LSM) was calculated as the arithmetic mean of individual stiffness values for each technique. For 3D MRE, LSMs were also calculated based on 4 slices ("abbreviated LSM"). Intra-patient variations in LSMs and different methods of ROI placement were assessed by univariate tests. A p-value of < 0.05 was set as a statistically significant difference. RESULTS Mean surface areas of the ROIs were 50,723 mm2, 12,669 mm2, 5814 mm2, and 10,642 mm2 for 3D MRE, abbreviated 3D MRE, 2D GRE, and 2D seEPI, respectively. 3D LSMs based on curated and non-curated ROIs showed no clinically significant difference, with a mean difference less than 0.1 kPa. Abbreviated 3D LSMs had excellent correlation with 3D LSMs based on all slices (r = 0.9; p < 0.001) and were not significantly different (p = 0.927). CONCLUSION 3D MRE allows more reproducible measurements due to its lower susceptibility to artifacts and provides larger areas of parenchyma, enabling a more comprehensive evaluation of the liver.
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29
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Ciardullo S, Perseghin G. Advances in fibrosis biomarkers in nonalcoholic fatty liver disease. Adv Clin Chem 2022; 106:33-65. [PMID: 35152974 DOI: 10.1016/bs.acc.2021.09.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Nonalcoholic fatty liver disease (NAFLD) affects a quarter of the adult world population and the degree of liver fibrosis represents the best predictor of the development of liver-related outcomes. Easily applicable and well performing non-invasive fibrosis tests can overcome the limitations of liver biopsy and are of paramount importance to identify at-risk subjects in clinical practice. While tests with optimal performance and ease of use do not exist at this stage, available markers can be divided in three broad groups: simple serum tests, complex serum tests and elastographic methods. Simple scores (such as Fibrosis-4 and NAFLD Fibrosis Score) are based on readily available biochemical data and clinical features, while complex/proprietary tests (such as Fibrotest, Enhanced Liver Fibrosis and Hepascore) directly measure markers of fibrogenesis and fibrolysis, but have higher costs. Elastography techniques estimate the degree of fibrosis from liver stiffness and are based on either ultrasound or magnetic resonance (MR) imaging. MR elastography has better performance compared with sonographic techniques and is not affected by obesity and inflammation, but is highly costly and less available. In general, non-invasive tests are able to exclude the presence of fibrosis, but their positive predictive value is low to moderate and they lead to a high number of indeterminate results. In this context, a combination of different tests might increase accuracy while reducing gray-zone results. Their ability to predict future events and response to treatment is suboptimal and needs to be studied further. Finally, recent studies have tried different approaches, spanning from "omics" to the microbiome and micro-RNAs, with some promising results.
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Affiliation(s)
- Stefano Ciardullo
- Department of Medicine and Rehabilitation, Policlinico di Monza, Monza, Italy; School of Medicine and Surgery, University of Milano Bicocca, Milan, Italy
| | - Gianluca Perseghin
- Department of Medicine and Rehabilitation, Policlinico di Monza, Monza, Italy; School of Medicine and Surgery, University of Milano Bicocca, Milan, Italy.
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30
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Wang L, Ke J, Hu X, Zhu M, Yu Y. Preliminary Findings on the Potential Use of Magnetic Resonance Elastography to Diagnose Lacunar Infarction. Neuropsychiatr Dis Treat 2022; 18:1583-1591. [PMID: 35937715 PMCID: PMC9355338 DOI: 10.2147/ndt.s371404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 07/27/2022] [Indexed: 12/03/2022] Open
Abstract
PURPOSE Lacunar infarction is usually diagnosed by conventional technologies, such as CT and diffusion weighted imaging (DWI). To improve the accuracy of diagnosis, neurocognitive screening is still needed. Therefore, additional imaging methods that can assist and provide more accurate and rapid diagnostics are urgently needed. As an initial step towards potentially using MR elastography (MRE) for such diagnostic purposes, we tested the hypothesis that the mechanical properties of tissue in the vicinity of cerebral vasculature change following lacunar infarction in a way that can be quantified using MRE. PATIENTS AND METHODS MRE and MR angiography (MRA) images from 51 patients diagnosed with lacunar infarction and 54 healthy volunteers were acquired on a 3T scanner. All diagnoses were confirmed by matching neurocognitive test results to locations of flow obstruction in MRA. ROIs of the cerebral vessels segmented on the MRA images were mapped to the MRE images. Interpolation-based inversion was applied to estimate the regional biomechanical properties of ROIs that included cerebral vessels. The effects of lacunar infarction, sex, and age were analyzed using analysis of covariance (ANOCOVA). RESULTS Shear moduli over vessel ROIs were significantly lower for the lacunar infarction group than those of the healthy control group. A positive correlation between modulus over vessel ROIs and age was observed. However, no significant correlation was found between sex and the regional biomechanical properties of the vessel ROIs. CONCLUSION Results supported the hypothesis and suggest that biomechanical properties may be of utility in diagnosis of lacunar infarction.
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Affiliation(s)
- Lingjie Wang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, People's Republic of China
| | - Jun Ke
- Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, People's Republic of China
| | - Xiaoyin Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, People's Republic of China
| | - Mo Zhu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, People's Republic of China
| | - Yixing Yu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, People's Republic of China
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31
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Pepin KM, Welle CL, Guglielmo FF, Dillman JR, Venkatesh SK. Magnetic resonance elastography of the liver: everything you need to know to get started. Abdom Radiol (NY) 2022; 47:94-114. [PMID: 34725719 PMCID: PMC9538666 DOI: 10.1007/s00261-021-03324-0] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/17/2021] [Accepted: 10/18/2021] [Indexed: 12/17/2022]
Abstract
Magnetic resonance elastography (MRE) of the liver has emerged as the non-invasive standard for the evaluation of liver fibrosis in chronic liver diseases (CLDs). The utility of MRE in the evaluation of different CLD in both adults and children has been demonstrated in several studies, and MRE has been recommended by several clinical societies. Consequently, the clinical indications for evaluation of CLD with MRE have increased, and MRE is currently used as an add-on test during routine liver MRI studies or as a standalone test. To meet the increasing clinical demand, MRE is being installed in many academic and private practice imaging centers. There is a need for a comprehensive practical guide to help these practices to deliver high-quality liver MRE studies as well as troubleshoot the common issues with MRE to ensure smooth running of the service. This comprehensive clinical practice review summarizes the indications and provides an overview on why to use MRE, technical requirements, system set-up, patient preparation, acquiring the data, and interpretation.
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Affiliation(s)
- Kay M Pepin
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, USA
- Resoundant Inc, Rochester, MN, USA
| | - Christopher L Welle
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, USA
| | | | - Jonathan R Dillman
- Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Roy A, Darapureddy A, Kumar Y. Noninvasive assessment of liver fibrosis by magnetic resonance elastography in patients with rheumatic disease on long-term methotrexate treatment. INDIAN JOURNAL OF RHEUMATOLOGY 2022. [DOI: 10.4103/injr.injr_186_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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Mullikin TC, Pepin KM, Evans JE, Venkatesh SK, Ehman RL, Merrell KW, Haddock MG, Harmsen WS, Herman MG, Hallemeier CL. Evaluation of Pretreatment Magnetic Resonance Elastography for the Prediction of Radiation-Induced Liver Disease. Adv Radiat Oncol 2021; 6:100793. [PMID: 34820550 PMCID: PMC8601961 DOI: 10.1016/j.adro.2021.100793] [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: 06/08/2021] [Accepted: 08/26/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose Magnetic resonance (MR) elastography (E) is a noninvasive technique for quantifying liver stiffness (LS) for fibrosis. This study evaluates whether LS is associated with risk of developing radiation-induced liver disease (RILD) in patients receiving liver-directed radiation therapy (RT). Methods and Materials Based on prior studies, LS ≤3 kPa was considered normal and LS >3.0 kPa as representing fibrosis. RILD was defined as an increase in Child-Pugh (CP) score of ≥2 from baseline within 1 year of RT. Univariate and multivariate Cox models were used to assess correlation. Results One hundred two patients, 51 with primary liver tumors and 51 with liver metastases, were identified with sufficient follow-up. In univariate models, pre-RT LS >3.0 kPa (hazard ratio [HR] 4.9; 95% confidence interval [CI], 1.6-14; P = .004), body mass index (BMI), clinical cirrhosis, CP score, albumin-bilirubin (ALBI) grade 2, primary liver tumor, and mean liver dose were significantly associated with risk of post-RT RILD. In a multivariate analysis, LS >3.0 and mean liver dose both were significantly associated with RILD risk. Conclusions Elevated pre-RT LS is associated with an increased risk of RILD in patients receiving liver-directed RT.
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Affiliation(s)
- Trey C Mullikin
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Kay M Pepin
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Jaden E Evans
- Department of Radiation Oncology, Intermountain Health Care, Ogden, Utah
| | | | | | | | | | - William S Harmsen
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Michael G Herman
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
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Ballard DH, Ludwig DR, Fraum TJ, Salter A, Narra VR, Shetty AS. Quality Control of Magnetic Resonance Elastography Using Percent Measurable Liver Volume Estimation. J Magn Reson Imaging 2021; 55:1890-1899. [PMID: 34704644 DOI: 10.1002/jmri.27976] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 10/17/2021] [Accepted: 10/19/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Although studies have described factors associated with failed magnetic resonance elastography (MRE), little is known about what factors influence usable elastography data. PURPOSE To identify factors that have a negative impact on percent measurable liver volume (pMLV), defined as the proportion of usable liver elastography data relative to the volume of imaged liver in patients undergoing MRE. STUDY TYPE Retrospective. SUBJECTS A total of 264 patients (n = 132 males, n = 132 females; mean age = 57 years) with suspected or known chronic liver disease underwent MRE paired with a liver protocol MRI. FIELD STRENGTH/SEQUENCE MRE was performed on a single 1.5 T scanner using a two-dimensional gradient-recalled echo phase-contrast sequence with a passive acoustic driver overlying the right hemiliver. ASSESSMENT Stiffness maps (usable data at 95% confidence) and liver contours on magnitude images of the MRE acquisition were manually traced and used to assess mean stiffness and pMLV. Hepatic fat fraction and R2 * values were also calculated. The distance from the acoustic wave generator on the skin surface to the liver edge was measured. Two radiologists performed the MR analyses with 50 overlapping cases for inter-reader analysis. STATISTICAL TESTS Linear regression was performed to identify factors significantly associated with pMLV. Intraclass correlation was performed for inter-reader reliability. RESULTS pMLV was 31% ± 20% (range 0%-86%). Complete MRE failure (i.e. pMLV = 0%) occurred in 10 patients (4%). Multivariate linear regression identified higher hepatic fat fraction, R2 *, BMI, and driver-to-liver surface distance; male sex; and lower mean liver stiffness was significantly independently associated with lower pMLV. Intraclass correlation for pMLV was 0.96, suggestive of excellent reliability. DATA CONCLUSION Higher fat fraction, R2 *, BMI, driver-to-liver surface distance, male sex, and lower mean liver stiffness were associated with lower pMLV. Optimization of image acquisition parameters and driver placement may improve MRE quality, and pMLV likely serves as a diagnostic utility quality control metric. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Daniel R Ludwig
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tyler J Fraum
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Amber Salter
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Vamsi R Narra
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Anup S Shetty
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
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35
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Joshi A, Muthe MM, Firke V, Badgujar H. Preliminary experience with 3T magnetic resonance elastography imaging of the liver. SA J Radiol 2021; 25:2072. [PMID: 34192073 PMCID: PMC8182447 DOI: 10.4102/sajr.v25i1.2072] [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] [Received: 12/25/2020] [Accepted: 03/10/2021] [Indexed: 11/06/2022] Open
Abstract
Background Magnetic resonance elastography (MRE) is a promising non-invasive technique for the identification and quantification of hepatic fibrosis. This manuscript describes our early experience with MRE for the assessment of the presence and staging of liver fibrosis on a 3T magnetic resonance imaging (MRI) system. Objectives The purpose of this study was to describe the MRE physics, procedure, interpretation and drawbacks, along with a few recommendations as per our experience. Method Magnetic resonance elastography was performed on 85 patients with a 3T MRI and the images were analysed both qualitatively and quantitatively. Liver stiffness was assessed by drawing freehand geographic regions of interest on the elastograms to cover the maximum portion of the hepatic parenchyma within the 95% confidence maps on each slice. Correlation with histopathology was performed whenever available. Results Of the 80 patients who met the inclusion criteria, 41 patients displayed a normal liver stiffness measurement (LSM) and 39 patients had a raised LSM. In the patients who had a raised LSM, 14 patients had Stage I–II fibrosis, 8 patients had Stage II–III fibrosis, 6 patients had Stage III–IV fibrosis, 4 patients had Stage IV fibrosis or cirrhosis and 7 patients had non-alcoholic steatohepatitis. The mean thickness of the waves increased with increasing stages of fibrosis. The waves became gradually darker medially in patients with normal LSM as compared to the patients with raised LSM. Histopathology with METAVIR scoring was available in 46 patients, which agreed with the MRE findings in all except two patients. Conclusion Magnetic resonance elastography is a suitable non-invasive modality for the identification and quantification of hepatic fibrosis.
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Affiliation(s)
- Anagha Joshi
- Department of Radiology, Lokmanya Tilak Municipal Medical College, Lokmanya Tilak Municipal General Hospital, Mumbai, India
| | - Mridula M Muthe
- Department of Radiology, Lokmanya Tilak Municipal Medical College, Lokmanya Tilak Municipal General Hospital, Mumbai, India
| | - Vikrant Firke
- Department of Radiology, Lokmanya Tilak Municipal Medical College, Lokmanya Tilak Municipal General Hospital, Mumbai, India
| | - Harshal Badgujar
- Department of Radiology, Lokmanya Tilak Municipal Medical College, Lokmanya Tilak Municipal General Hospital, Mumbai, India
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Ahn JH, Yu JS, Park KS, Kang SH, Huh JH, Chang JS, Lee JH, Kim MY, Nickel MD, Kannengiesser S, Kim JY, Koh SB. Effect of hepatic steatosis on native T1 mapping of 3T magnetic resonance imaging in the assessment of T1 values for patients with non-alcoholic fatty liver disease. Magn Reson Imaging 2021; 80:1-8. [PMID: 33798658 DOI: 10.1016/j.mri.2021.03.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/18/2021] [Accepted: 03/18/2021] [Indexed: 02/09/2023]
Abstract
PURPOSE This study investigated whether T1 values in native T1 mapping of 3T magnetic resonance imaging (MRI) of the liver were affected by the fatty component. METHODS This prospective study involved 340 participants from a population-based cohort study between May 8, 2018 and August 8, 2019. Data obtained included: (1) hepatic stiffness according to magnetic resonance elastography (MRE); (2) T1 value according to T1 mapping; (3) fat fraction and iron concentration from multi-echo Dixon; and (4) clinical indices of hepatic steatosis including body mass index, waist circumference, history of diabetes, aspartate aminotransferase, alanine aminotransferase, gamma-glutamyl transpeptidase, and triglycerides. The correlations between T1 value and fat fraction, and between T1 value and liver stiffness were assessed using Pearson's correlation coefficient. The independent two-sample t-test was used to evaluate the differences in T1 values according to the presence or absence of hepatic steatosis, and the one-way analysis of variance was used to evaluate the difference in T1 value by grading of hepatic steatosis according to MRI-based proton density fat fraction (PDFF). In addition, univariate and multivariate linear regression analyses were performed to determine whether other variables influenced the T1 value. RESULTS T1 value showed a positive correlation with the fat fraction obtained from PDFF (r = 0.615, P < 0.001) and with the liver stiffness obtained from MRE (r = 0.370, P < 0.001). Regardless of the evaluation method, the T1 value was significantly increased in subjects with hepatic steatosis (P < 0.001). When comparing hepatic steatosis grades based on MRI-PDFF, the mean T1 values were significantly different in all grades, and the T1 value tended to increase as the grade increased (P < 0.001, P for trend <0.001). On multiple linear regression analysis, the T1 value was influenced by MRI-PDFF, calculated liver iron concentration, liver stiffness, and serum aspartate aminotransferase level. CONCLUSION The T1 value obtained by current T1 mapping of 3T MRI was affected by the liver fat component and several other factors such as liver stiffness, iron concentration, and inflammation.
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Affiliation(s)
- Jhii-Hyun Ahn
- Department of Radiology, Wonju Severance Christian Hospital, Yonsei University College of Medicine, Republic of Korea
| | - Jeong-Sik Yu
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Kyu-Sang Park
- Mitohormesis Research Center, Department of Physiology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Seong Hee Kang
- Department of Internal Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Ji Hye Huh
- Department of Internal Medicine, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Jae Seung Chang
- Mitohormesis Research Center, Department of Physiology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Jong-Han Lee
- Department of Laboratory Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Moon Young Kim
- Department of Internal Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | | | | | - Jang-Young Kim
- Department of Internal Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Sang-Baek Koh
- Department of Preventive Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
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Imaging Biomarkers of Hepatic Fibrosis: Reliability and Accuracy of Hepatic Periportal Space Widening and Other Morphologic Features on MRI. AJR Am J Roentgenol 2021; 216:1229-1239. [PMID: 33729883 DOI: 10.2214/ajr.20.23099] [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] [Indexed: 12/18/2022]
Abstract
OBJECTIVE. The purpose of this article was to assess the reliability and accuracy of hepatic periportal space widening and other qualitative imaging features for the prediction of hepatic fibrosis. MATERIALS AND METHODS. This single-center retrospective study identified consecutive patients who had undergone liver MR elastography. Two abdominal radiologists independently reviewed anatomic images, assessing multiple qualitative features of chronic liver disease (CLD) including periportal space widening. Each reader also measured the periportal space at the main portal vein (MPV) and right portal vein (RPV). Interrater reliability analysis was then performed. Sensitivity and specificity were determined for the detection of any hepatic fibrosis (stage I or higher) and of advanced fibrosis (stage III or higher) using stiffness on MR elastography as the reference standard. RESULTS. Of 229 subjects, 157 (69%) had fibrosis and 78 (34%) had advanced fibrosis. Agreement for periportal space widening was moderate (κ = 0.47), and agreement for remaining features was moderate to substantial (κ = 0.42-0.80). Agreement for the periportal space at the MPV was moderate (ICC, 0.55), and agreement for the periportal space at the RPV was near perfect (ICC, 0.83). Periportal space widening had the highest sensitivity (83.0%) for any fibrosis, with limited specificity (61.3%). Surface nodularity had the highest specificity (94.4%) for any fibrosis, with limited sensitivity (51.6%). Periportal space widening plus one or more additional imaging feature of CLD or the presence of surface nodularity alone had sensitivity of 72.6% and specificity of 76.1%. A periportal space at the MPV greater than 9.5 mm had substantial agreement with qualitative periportal space widening (κ = 0.74). CONCLUSION. Periportal space widening has a high sensitivity for hepatic fibrosis, with moderate specificity when combined with additional anatomic features of CLD.
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Li W, Li P, Li N, Du Y, Lü S, Elad D, Long M. Matrix stiffness and shear stresses modulate hepatocyte functions in a fibrotic liver sinusoidal model. Am J Physiol Gastrointest Liver Physiol 2021; 320:G272-G282. [PMID: 33296275 PMCID: PMC8609567 DOI: 10.1152/ajpgi.00379.2019] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Extracellular matrix (ECM) rigidity has important effects on cell behaviors and increases sharply in liver fibrosis and cirrhosis. Hepatic blood flow is essential in maintaining hepatocytes' (HCs) functions. However, it is still unclear how matrix stiffness and shear stresses orchestrate HC phenotype in concert. A fibrotic three-dimensional (3-D) liver sinusoidal model is constructed using a porous membrane sandwiched between two polydimethylsiloxane (PDMS) layers with respective flow channels. The HCs are cultured in collagen gels of various stiffnesses in the lower channel, whereas the upper channel is pre-seeded with liver sinusoidal endothelial cells (LSECs) and accessible to shear flow. The results reveal that HCs cultured within stiffer matrices exhibit reduced albumin production and cytochrome P450 (CYP450) reductase expression. Low shear stresses enhance synthetic and metabolic functions of HC, whereas high shear stresses lead to the loss of HC phenotype. Furthermore, both mechanical factors regulate HC functions by complementing each other. These observations are likely attributed to mechanically induced mass transport or key signaling molecule of hepatocyte nuclear factor 4α (HNF4α). The present study results provide an insight into understanding the mechanisms of HC dysfunction in liver fibrosis and cirrhosis, especially from the viewpoint of matrix stiffness and blood flow.NEW & NOTEWORTHY A fibrotic three-dimensional (3-D) liver sinusoidal model was constructed to mimic different stages of liver fibrosis in vivo and to explore the cooperative effects of matrix stiffness and shear stresses on hepatocyte (HC) functions. Mechanically induced alterations of mass transport mainly contributed to HC functions via typical mechanosensitive signaling.
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Affiliation(s)
- Wang Li
- 1Center for Biomechanics and Bioengineering, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,2Key Laboratory of Microgravity (National Microgravity Laboratory), Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,3Beijing Key Laboratory of Engineered Construction and Mechanobiology, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,4School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Peiwen Li
- 1Center for Biomechanics and Bioengineering, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,2Key Laboratory of Microgravity (National Microgravity Laboratory), Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,3Beijing Key Laboratory of Engineered Construction and Mechanobiology, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,4School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Ning Li
- 1Center for Biomechanics and Bioengineering, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,2Key Laboratory of Microgravity (National Microgravity Laboratory), Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,3Beijing Key Laboratory of Engineered Construction and Mechanobiology, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,4School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Yu Du
- 1Center for Biomechanics and Bioengineering, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,2Key Laboratory of Microgravity (National Microgravity Laboratory), Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,3Beijing Key Laboratory of Engineered Construction and Mechanobiology, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,4School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Shouqin Lü
- 1Center for Biomechanics and Bioengineering, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,2Key Laboratory of Microgravity (National Microgravity Laboratory), Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,3Beijing Key Laboratory of Engineered Construction and Mechanobiology, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,4School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - David Elad
- 5Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Mian Long
- 1Center for Biomechanics and Bioengineering, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,2Key Laboratory of Microgravity (National Microgravity Laboratory), Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,3Beijing Key Laboratory of Engineered Construction and Mechanobiology, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China,4School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing, People’s Republic of China
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Ali M, Payne SL. Biomaterial-based cell delivery strategies to promote liver regeneration. Biomater Res 2021; 25:5. [PMID: 33632335 PMCID: PMC7905561 DOI: 10.1186/s40824-021-00206-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/05/2021] [Indexed: 02/08/2023] Open
Abstract
Chronic liver disease and cirrhosis is a widespread and untreatable condition that leads to lifelong impairment and eventual death. The scarcity of liver transplantation options requires the development of new strategies to attenuate disease progression and reestablish liver function by promoting regeneration. Biomaterials are becoming an increasingly promising option to both culture and deliver cells to support in vivo viability and long-term function. There is a wide variety of both natural and synthetic biomaterials that are becoming established as delivery vehicles with their own unique advantages and disadvantages for liver regeneration. We review the latest developments in cell transplantation strategies to promote liver regeneration, with a focus on the use of both natural and synthetic biomaterials for cell culture and delivery. We conclude that future work will need to refine the use of these biomaterials and combine them with novel strategies that recapitulate liver organization and function in order to translate this strategy to clinical use.
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Affiliation(s)
- Maqsood Ali
- Department of Regenerative Medicine, College of Medicine, Soonchunhyang University, Cheonan, South Korea
| | - Samantha L Payne
- Department of Biomedical Engineering, School of Engineering, Tufts University, Medford, MA, 02155, USA.
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Zou LQ, Zhao F, Zhang H, Zhang K, Xing W. Staging liver fibrosis on multiparametric MRI in a rabbit model with elastography, susceptibility-weighted imaging and T1ρ imaging: a preliminary study. Acta Radiol 2021; 62:155-163. [PMID: 32326722 DOI: 10.1177/0284185120917117] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Magnetic resonance elastography (MRE), susceptibility-weighted imaging (SWI), and T1ρ are three techniques for staging of liver fibrosis (LF). PURPOSE To assess the value of MRE, SWI, and T1ρ imaging in staging LF. MATERIAL AND METHODS Sixty rabbits were injected with 50% CCl4oil solution, whereas 20 rabbits were given normal saline. All rabbits underwent pathological examination to determine LF stages. The liver stiffness (LS), liver-to-muscle signal intensity ratio (SIR), and T1ρ values were measured from MRE, SWI, and T1ρ imaging, respectively. RESULTS The number of rabbits was 14, 11, 10, 9, and 11 for F0, F1, F2, F3, and F4, respectively. LS (r = 0.91) and T1ρ (r = 0.51) positively correlated with LF stages, while negative correlation was present for SIR (r = -0.81). Among the three parameters, the LS values revealed the best diagnostic efficacy in staging LF, with an AUC value of 0.95 for ≥F1, 0.95 for ≥F2, 0.99 for ≥F3, and 0.98 for ≥F4. The combination of LS and SIR could best predict LF stages ≥F1, ≥F2, ≥F3 and ≥F4, with AUC values of 0.97, 0.98, 0.99, and 0.99, respectively, which were greater than those of the other two-paired parameters. A multiparametric analysis showed that the combination of all three parameters had AUC values of 0.97, 0.98, 1.00, and 1.00 for staging ≥F1, ≥F2, ≥F3, and ≥F4, respectively. CONCLUSION Multiparametric MR imaging was superior to individual imaging for LF staging.
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Affiliation(s)
- Li-Qiu Zou
- Department of Radiology, The Sixth Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, PR China
| | - Feng Zhao
- Department of Radiation Oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, PR China
| | - Hao Zhang
- Department of Radiology, Affiliated Shenzhen Sixth Hospital of Guangdong Medical University, Shenzhen, PR China
| | - Kai Zhang
- Department of Radiology, Affiliated Shenzhen Sixth Hospital of Guangdong Medical University, Shenzhen, PR China
| | - Wei Xing
- Department of Radiology, Third Affiliated Hospital of Soochow University & Changzhou First People’s Hospital, Changzhou, Jiangsu, PR China
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Tamargo JA, Sherman KE, Campa A, Martinez SS, Li T, Hernandez J, Teeman C, Mandler RN, Chen J, Ehman RL, Baum MK. Food insecurity is associated with magnetic resonance-determined nonalcoholic fatty liver and liver fibrosis in low-income, middle-aged adults with and without HIV. Am J Clin Nutr 2021; 113:593-601. [PMID: 33515016 PMCID: PMC7948863 DOI: 10.1093/ajcn/nqaa362] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 11/11/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Nonalcoholic fatty liver disease (NAFLD) is the most prevalent liver disease in the United States. Food-insecure individuals often depend on low-cost, energy-dense but nutritionally poor foods, resulting in obesity and chronic diseases related to NAFLD. OBJECTIVES To determine whether food insecurity is associated with NAFLD in a cohort of HIV and hepatitis C virus (HCV) infected and uninfected adults. METHODS We conducted a cross-sectional analysis of low-income, middle-aged adults from the Miami Adult Studies on HIV (MASH) cohort without a history of excessive alcohol consumption. Food security was assessed with the USDA's Household Food Security Survey. MRIs were used to assess liver steatosis and fibrosis. Metabolic parameters were assessed from fasting blood, anthropometrics, and vitals. RESULTS Of the total 603 participants, 32.0% reported food insecurity. The prevalences of NAFLD, fibrosis, and advanced fibrosis were 16.1%, 15.1%, and 4.6%, respectively. For every 5 kg/m2 increase in BMI, the odds of NAFLD increased by a factor of 3.83 (95% CI, 2.37-6.19) in food-insecure participants compared to 1.32 (95% CI, 1.04-1.67) in food-secure participants. Food insecurity was associated with increased odds for any liver fibrosis (OR, 1.65; 95% CI, 1.01-2.72) and advanced liver fibrosis (OR, 2.82; 95% CI, 1.22-6.54), adjusted for confounders. HIV and HCV infections were associated with increased risks for fibrosis, but the relationship between food insecurity and liver fibrosis did not differ between infected and uninfected participants. CONCLUSIONS Among low-income, middle-aged adults, food insecurity exacerbated the risk for NAFLD associated with a higher BMI and independently increased the risk for advanced liver fibrosis. People who experience food insecurity, particularly those vulnerable to chronic diseases and viral infections, may be at increased risk for liver-related morbidity and mortality. Improving access to adequate nutrition and preventing obesity among low-income groups may lessen the growing burden of NAFLD and other chronic diseases.
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Affiliation(s)
| | | | | | | | - Tan Li
- Florida International University, Miami, FL, USA
| | | | - Colby Teeman
- Florida International University, Miami, FL, USA
| | | | - Jun Chen
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Navin PJ, Olson MC, Knudsen JM, Venkatesh SK. Elastography in the evaluation of liver allograft. Abdom Radiol (NY) 2021; 46:96-110. [PMID: 31950204 DOI: 10.1007/s00261-019-02400-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Elastography is an established technique in the evaluation of chronic liver diseases. While there is a large clinical experience and data available regarding the performance of elastography in native liver, elastography experience with liver grafts is limited and still growing. Both ultrasound-based elastography techniques and MR Elastography (MRE) are useful in the assessment of liver fibrosis in liver transplants. Technical modifications for performing elastography will be required for optimum evaluation of the graft. In general, caution needs to be exercised regarding the use of elastography immediately following transplantation as post-operative changes, perioperative conditions/complications, inflammation, and rejection can cause increased stiffness in the graft. In the follow-up, detection of increased stiffness with elastography is useful for predicting development of fibrosis in the graft. Adjunctive MRI or ultrasound with Doppler also provides comprehensive evaluation of anatomy, vascular anastomosis and patency, biliary tree, and stiffness for fibrosis. In this review, we provide a brief overview of elastography techniques available followed by the literature review of elastography in the evaluation of grafts and illustration with clinical examples.
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Abstract
Application of MRE for noninvasive evaluation of renal fibrosis has great potential for noninvasive assessment in patients with chronic kidney disease (CKD). CKD leads to severe complications, which require dialysis or kidney transplant and could even result in death. CKD in native kidneys and interstitial fibrosis in allograft kidneys are the two major kidney fibrotic pathologies where MRE may be clinically useful. Both these conditions can lead to extensive morbidity, mortality, and high health care costs. Currently, biopsy is the standard method for renal fibrosis staging. This method of diagnosis is painful, invasive, limited by sampling bias, exhibits inter- and intraobserver variability, requires prolonged hospitalization, poses risk of complications and significant bleeding, and could even lead to death. MRE based methods can potentially be useful to noninvasively detect, stage, and monitor renal fibrosis, reducing the need for renal biopsy. In this chapter, we describe experimental procedure and step by step instructions to run MRE along with some illustrative applications. We also includes sections on how to perform data quality check and analysis methods.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.
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Affiliation(s)
- Suraj D Serai
- Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Abstract
Magnetic resonance elastography (MRE) is an emerging imaging modality that maps the elastic properties of tissue such as the shear modulus. It allows for noninvasive assessment of stiffness, which is a surrogate for fibrosis. MRE has been shown to accurately distinguish absent or low stage fibrosis from high stage fibrosis, primarily in the liver. Like other elasticity imaging modalities, it follows the general steps of elastography: (1) apply a known cyclic mechanical vibration to the tissue; (2) measure the internal tissue displacements caused by the mechanical wave using magnetic resonance phase encoding method; and (3) infer the mechanical properties from the measured mechanical response (displacement), by generating a simplified displacement map. The generated map is called an elastogram.While the key interest of MRE has traditionally been in its application to liver, where in humans it is FDA approved and commercially available for clinical use to noninvasively assess degree of fibrosis, this is an area of active research and there are novel upcoming applications in brain, kidney, pancreas, spleen, heart, lungs, and so on. A detailed review of all the efforts is beyond the scope of this chapter, but a few specific examples are provided. Recent application of MRE for noninvasive evaluation of renal fibrosis has great potential for noninvasive assessment in patients with chronic kidney diseases. Development and applications of MRE in preclinical models is necessary primarily to validate the measurement against "gold-standard" invasive methods, to better understand physiology and pathophysiology, and to evaluate novel interventions. Application of MRE acquisitions in preclinical settings involves challenges in terms of available hardware, logistics, and data acquisition. This chapter will introduce the concepts of MRE and provide some illustrative applications.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by another separate chapter describing the experimental protocol and data analysis.
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Affiliation(s)
- Suraj D Serai
- Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Obmann VC, Berzigotti A, Catucci D, Ebner L, Gräni C, Heverhagen JT, Christe A, Huber AT. T1 mapping of the liver and the spleen in patients with liver fibrosis-does normalization to the blood pool increase the predictive value? Eur Radiol 2020; 31:4308-4318. [PMID: 33313965 PMCID: PMC8128789 DOI: 10.1007/s00330-020-07447-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/03/2020] [Accepted: 10/29/2020] [Indexed: 02/07/2023]
Abstract
Purpose To analyze whether the T1 relaxation time of the liver is a good predictor of significant liver fibrosis and whether normalization to the blood pool improves the predictive value. Methods This prospective study was conducted between 03/2016 and 02/2018. One hundred seventy-three patients underwent multiparametric liver MRI at 3 T. The T1 relaxation time was measured in the liver and the spleen, in the aorta, the portal vein, and the inferior vena cava (IVC). T1 relaxation times with and without normalization to the blood pool were compared between patients with (n = 26) and without (n = 141) significant liver fibrosis, based on a cutoff value of 3.5 kPa in MRE as the noninvasive reference standard. For statistics, Student’s t test, receiver operating characteristic (ROC) curve analysis, and Pearson’s correlation were used. Results The T1 relaxation time of the liver was significantly longer in patients with liver fibrosis, both with and without blood pool normalization (p < 0.001). T1 relaxation time of the liver allowed prediction of significant liver fibrosis (AUC = 0.88), while normalization to the IVC resulted in a slightly lower performance (AUC = 0.82). The lowest performance was achieved when the T1 relaxation times of the liver were normalized to the aorta (AUC = 0.66) and to the portal vein (AUC = 0.62). The T1 relaxation time of the spleen detected significant liver fibrosis with an AUC of 0.68, and 0.51–0.64 with normalization to the blood pool. Conclusion The T1 relaxation time of the liver is a good predictor of significant liver fibrosis. However, normalization of the blood pool did not improve the predictive value. Key Points • The T1 relaxation time of the liver is a good predictor of significant liver fibrosis. • Normalization to the blood pool did not improve the predictive value of T1 mapping. • If the blood pool normalization was weighted 30% to the aorta and 70% to the portal vein, the performance was better than normalization to the aorta alone but still lower than normalization to the IVC.
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Affiliation(s)
- Verena Carola Obmann
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, 3010, Bern, Switzerland
| | - Annalisa Berzigotti
- Hepatology, Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Damiano Catucci
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, 3010, Bern, Switzerland
| | - Lukas Ebner
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, 3010, Bern, Switzerland
| | - Christoph Gräni
- Department of Cardiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Johannes Thomas Heverhagen
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, 3010, Bern, Switzerland
| | - Andreas Christe
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, 3010, Bern, Switzerland
| | - Adrian Thomas Huber
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, 3010, Bern, Switzerland.
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Novel imaging-based approaches for predicting the hepatic venous pressure gradient in a porcine model of liver cirrhosis and portal hypertension. Life Sci 2020; 264:118710. [PMID: 33144188 DOI: 10.1016/j.lfs.2020.118710] [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: 05/20/2020] [Revised: 10/21/2020] [Accepted: 10/30/2020] [Indexed: 01/06/2023]
Abstract
AIMS Hepatic venous pressure gradient (HVPG) is critical for staging and prognosis prediction of portal hypertension (PH). However, HVPG measurement has limitations (e.g., invasiveness). This study examined the value of non-invasive, imaging-based approaches including magnetic resonance elastography (MRE) and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for the prediction of HVPG in a porcine model of liver cirrhosis and PH. MAIN METHODS Male Bama miniature pigs were used to establish a porcine model of liver cirrhosis and PH induced by embolization. They were randomly assigned to an experimental group (n = 12) and control group (n = 3). HVPG was examined before and after transjugular intrahepatic portosystemic shunt (TIPS). MRE and IVIM-DWI were performed to obtain quantitative parameters including liver stiffness (LS) in MRE, tissue diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) in IVIM-DWI. The correlation between HVPG and the parameters was assessed. KEY FINDINGS LS values were significantly greater in the experimental group, while f values were significantly decreased at 4, 8, and 12 weeks after embolization compared to the control group. Furthermore, HVPG was significantly lower immediately after versus before TIPS. In parallel, LS and f values showed significant alterations after TIPS, and these changes were consistent with a reduction in HVPG. Spearman analysis revealed a significant correlation between the parameters (LS and f) and HVPG. The equation was eventually generated for prediction of HVPG. SIGNIFICANCE The findings show a good correlation between HVPG and the quantitative parameters; thus, imaging-based techniques have potential as non-invasive methods for predicting HVPG.
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MR elastography of liver: current status and future perspectives. Abdom Radiol (NY) 2020; 45:3444-3462. [PMID: 32705312 DOI: 10.1007/s00261-020-02656-7] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 07/06/2020] [Accepted: 07/09/2020] [Indexed: 02/08/2023]
Abstract
Non-invasive evaluation of liver fibrosis has evolved over the last couple of decades. Currently, elastography techniques are the most widely used non-invasive methods for clinical evaluation of chronic liver disease (CLD). MR elastography (MRE) of the liver has been used in the clinical practice for nearly a decade and continues to be widely accepted for detection and staging of liver fibrosis. With MRE, one can directly visualize propagating shear waves through the liver and an inversion algorithm in the scanner automatically converts the shear wave properties into an elastogram (stiffness map) on which liver stiffness can be calculated. The commonly used MRE method, two-dimensional gradient recalled echo (2D-GRE) sequence has produced excellent results in the evaluation of liver fibrosis in CLD from various etiologies and newer clinical indications continue to emerge. Advances in MRE technique, including 3D MRE, automated liver elasticity calculation, improvements in shear wave delivery and patient experience, are promising to provide a faster and more reliable MRE of liver. Innovations, including evaluation of mechanical parameters, such as loss modulus, displacement, and volumetric strain, are promising for comprehensive evaluation of CLD as well as understanding pathophysiology, and in differentiating various etiologies of CLD. In this review, the current status of the MRE of liver in CLD are outlined and followed by a brief description of advanced techniques and innovations in MRE of liver.
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Campos-Murguía A, Ruiz-Margáin A, González-Regueiro JA, Macías-Rodríguez RU. Clinical assessment and management of liver fibrosis in non-alcoholic fatty liver disease. World J Gastroenterol 2020; 26:5919-5943. [PMID: 33132645 PMCID: PMC7584064 DOI: 10.3748/wjg.v26.i39.5919] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 05/24/2020] [Accepted: 09/22/2020] [Indexed: 02/06/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is among the most frequent etiologies of cirrhosis worldwide, and it is associated with features of metabolic syndrome; the key factor influencing its prognosis is the progression of liver fibrosis. This review aimed to propose a practical and stepwise approach to the evaluation and management of liver fibrosis in patients with NAFLD, analyzing the currently available literature. In the assessment of NAFLD patients, it is important to identify clinical, genetic, and environmental determinants of fibrosis development and its progression. To properly detect fibrosis, it is important to take into account the available methods and their supporting scientific evidence to guide the approach and the sequential selection of the best available biochemical scores, followed by a complementary imaging study (transient elastography, magnetic resonance elastography or acoustic radiation force impulse) and finally a liver biopsy, when needed. To help with the selection of the most appropriate method a Fagan's nomogram analysis is provided in this review, describing the diagnostic yield of each method and their post-test probability of detecting liver fibrosis. Finally, treatment should always include diet and exercise, as well as controlling the components of the metabolic syndrome, +/- vitamin E, considering the presence of sleep apnea, and when available, allocate those patients with advanced fibrosis or high risk of progression into clinical trials. The final end of this approach should be to establish an opportune diagnosis and treatment of liver fibrosis in patients with NAFLD, aiming to decrease/stop its progression and improve their prognosis.
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Affiliation(s)
- Alejandro Campos-Murguía
- Department of Gastroenterology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City 14080, Mexico
| | - Astrid Ruiz-Margáin
- Department of Gastroenterology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City 14080, Mexico
| | - José A González-Regueiro
- Department of Gastroenterology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City 14080, Mexico
| | - Ricardo U Macías-Rodríguez
- Department of Gastroenterology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City 14080, Mexico
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Park SJ, Yoon JH, Lee DH, Lim WH, Lee JM. Tumor Stiffness Measurements on MR Elastography for Single Nodular Hepatocellular Carcinomas Can Predict Tumor Recurrence After Hepatic Resection. J Magn Reson Imaging 2020; 53:587-596. [PMID: 32914909 DOI: 10.1002/jmri.27359] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 08/27/2020] [Accepted: 08/27/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Tumor stiffness (TS), measured by magnetic resonance elastography (MRE), could be associated with tumor mechanical properties and tumor grade. PURPOSE To determine whether TS obtained using MRE is associated with survival in patients with single nodular hepatocellular carcinoma (HCC) after hepatic resection (HR). STUDY TYPE Retrospective. POPULATION In all, 95 patients with pathologically confirmed HCCs. FIELD STRENGTH/SEQUENCE 1.5T/3D spin-echo echo-planar imaging MRE. ASSESSMENT TS values of the whole tumor (TS-WT) and of a solid portion of the tumor (TS-SP) after excluding the necrotic area were measured on stiffness maps. Known imaging prognostic factors of HCC were also analyzed. After surgery, pathologic findings were evaluated from resected pathology specimens. STATISTICAL TESTS Fisher's exact test and the Mann-Whitney U-test were performed to determine the significance of differences according to the tumor grade. Overall survival (OS) / recurrence-free survival (RFS) analyses were performed using Kaplan-Meier analyses and Cox multivariable models. RESULTS The average TS-WT was 2.14 ± 0.74 kPa, and the average TS-SP was 2.51 ± 1.07 kPa. The cumulative incidence of RFS was 73.1%, 63.1%, and 57.3% at 1, 3, and 5 years, respectively. The TS-WT, TS-SP, and tumor size (≥5 cm) were significant prognostic factors for RFS (P < 0.001; P < 0.001; P = 0.017, respectively). The estimated overall 1-, 3-, and 5-year survival rates were 95.7%, 86.9%, and 80.8%, respectively. The alpha-fetoprotein changes, platelets, tumor size (≥5 cm), and vascular invasion in pathology were significant predictive factors for overall survival (all P < 0.05). Tumor necrosis, TS-WT, TS-SP, and vascular invasion in pathology were significantly correlated with poorly differentiated HCC (all P < 0.05). DATA CONCLUSION The TS-WT, TW-SP, and tumor size (≥5 cm) were significant predictive factors of RFS after HR in patients with HCC. Level of Evidence Technical Efficacy Stage 5 J. MAGN. RESON. IMAGING 2021;53:587-596.
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Affiliation(s)
- Sae-Jin Park
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Jeong Hee Yoon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Woo Hyeon Lim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea
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Potigailo V, Kohli A, Pakpoor J, Cain DW, Passi N, Mohsen N. Recent Advances in Computed Tomography and MR Imaging. PET Clin 2020; 15:381-402. [PMID: 32888544 DOI: 10.1016/j.cpet.2020.07.001] [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: 11/29/2022]
Abstract
Numerous advanced MR imaging and computed tomographic techniques have been developed and implemented in clinical practice over the past several years resulting in increased diagnostic accuracy and improved patient care. In this article, the authors highlight recent and emerging imaging techniques in functional and structural MR imaging, perfusion and vascular imaging, standardization of imaging practices, and selected applications of artificial intelligence in clinical practice.
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Affiliation(s)
- Valeria Potigailo
- Department of Radiology, University of Colorado Anschutz Medical Center, 12401 East 17th Avenue, Leprino, Mail Stop L954, Aurora, CO 80045, USA
| | - Ajay Kohli
- Department of Radiology, University of Pennsylvania, Hospital of the University of Pennsylvania, 1 Silverstein Suite 130, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Jina Pakpoor
- Department of Radiology, University of Pennsylvania, Hospital of the University of Pennsylvania, 1 Silverstein Suite 130, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Donald Wesley Cain
- Department of Radiology, University of Colorado Anschutz Medical Center, 12401 East 17th Avenue, Leprino, Mail Stop L954, Aurora, CO 80045, USA
| | - Neena Passi
- University of Pennsylvania, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Nancy Mohsen
- Department of Radiology, University of Pennsylvania, Hospital of the University of Pennsylvania, 1 Silverstein Suite 130, 3400 Spruce Street, Philadelphia, PA 19104, USA.
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