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Yagobian SD, Dasyam N, Minervini M, Tublin M, Behari J, Furlan A. Accuracy of Ultrasound-Guided Attenuation Parameter for Diagnosing Hepatic Steatosis. Ultrasound Q 2025; 41:e00702. [PMID: 39715185 DOI: 10.1097/ruq.0000000000000702] [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: 12/25/2024]
Abstract
ABSTRACT The purpose of this study is to investigate the diagnostic accuracy of a new noninvasive imaging technique, ultrasound-guided attenuation parameter (UGAP), in diagnosing hepatic steatosis. This single-center retrospective study included 81 UGAP studies performed to guide therapy between July 2022 and June 2023 at a large academic medical center. Patients with either liver biopsy or Magnetic resonance-based proton-density fat fraction (MRI-PDFF) within 12 months of US-UGAP imaging, irrespective of order, were included. Patient demographics, body mass index, liver function tests, UGAP values, MRI-PDFF values, and liver biopsy results were obtained from a review of the medical records. Presence of steatosis was defined as PDFF >5.2% or >5% of hepatocytes with steatosis at pathology. Area under the ROC curve (AUROC) was used to measure UGAP accuracy for the detection of hepatic steatosis with statistical significance P < 0.05. There was a significant positive correlation between UGAP and MRI-PDFF (r = 0.463; P < 0.001; confidence interval [CI]: 0.220;0.651). The AUROC to differentiate absence of steatosis (n = 21) from presence of steatosis (n = 32) for UGAP with MRI as the gold standard was 0.760 (P < 0.001; CI: 0.623;0.867). A UGAP value >0.66 had 78% sensitivity and 67% specificity to identify steatosis presence on MRI-PDFF. The AUROC to differentiate absence of steatosis (n = 11) from presence of steatosis (n = 21) for UGAP with pathology as the gold standard was 0.894 (P < 0.001; CI: 0.734;0.974). A UGAP value >0.57 had 100% sensitivity and 64% specificity to identify steatosis presence at pathology. UGAP is an accurate measure for detecting the presence of hepatic steatosis and may be a noninvasive method for metabolic dysfunction-associated steatotic liver disease diagnosis and follow-up.
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Qi R, Lu L, He T, Zhang L, Lin Y, Bao L. Comparing ultrasound-derived fat fraction and MRI-PDFF for quantifying hepatic steatosis: a real-world prospective study. Eur Radiol 2024:10.1007/s00330-024-11119-2. [PMID: 39414658 DOI: 10.1007/s00330-024-11119-2] [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: 06/05/2024] [Revised: 07/24/2024] [Accepted: 09/10/2024] [Indexed: 10/18/2024]
Abstract
OBJECTIVE To compare the agreement between ultrasound-derived fat fraction (UDFF) with magnetic resonance proton density fat fraction (MRI-PDFF) for quantification of hepatic steatosis and verify its reliability and diagnostic performance by comparing with MRI-PDFF as the reference standard. METHODS This prospective study included a primary analysis of 191 patients who underwent MRI-PDFF and UDFF from February 2023 to February 2024. MRI-PDFF were derived from three liver segment measurements with calculation of an overall median PDFF. UDFF was performed by two different sonographers for each of the six measurements, and the median was taken. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to assess agreement. Receiver operating characteristics (ROC) curves were used to evaluate the diagnostic performance of UDFF in detecting different degrees of hepatic steatosis. RESULTS A total of 176 participants were enrolled in the final cohort of this study (median age, 36.0 years; 82 men, 94 women). The median MRI-PDFF value was 11.3% (interquartile range (IQR) 7.5-18.9); 84.7% patients had a median MRI-PDFF value ≥ 6.4%. The median UDFF measured by different sonographers were 9.5% (IQR: 5.0-18.0) and 9.0% (IQR: 5.0-18.0), respectively. The interobserver agreement of UDFF measurement was excellent agreement (ICC = 0.951 [95% CI: 0.934-0.964], p < 0.001). UDFF was positively strongly correlated with MRI-PDFF with ICC of 0.899 (95% CI: 0.852-0.930). The Bland-Altman analysis showed high agreement between UDFF and MRI-PDFF measurements, with a mean bias of 1.7% (95% LOA, -8.7 to 12.2%). The optimal UDFF cutoff values were 5.5%, 15.5% and 17.5% for detecting MRI-PDFF at historic thresholds of 6.4%, 17.4%, and 22.1%, with AUC of 0.851, 0.952, and 0.948, respectively. The sensitivity was 79.2%, 87.5%, 88.9%, and specificity was 81.5%, 90.6%, 90.0%, respectively. CONCLUSIONS UDFF is a reliable and accurate method for quantification and classification of hepatic steatosis, with strong agreement to MRI-PDFF. The UDFF cutoff values of 5.5%, 15.5%, and 17.5% provide high sensitivity and specificity for the detection of mild, moderate, and severe hepatic steatosis, respectively. KEY POINTS Question Is ultrasound-derived fat fraction (UDFF) reliable for the quantitative detection of hepatic steatosis compared to MRI proton density fat fraction (MRI-PDFF)? Findings UDFF cutoff values of 5.5%, 15.5%, and 17.5% provided high sensitivity and specificity for the detection of mild, moderate, and severe hepatic steatosis, respectively. Clinical relevance UDFF is a reliable and accurate method for quantification and classification of hepatic steatosis, with strong agreement to MRI-PDFF and high reproducibility of liver fat content by different sonographers.
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Affiliation(s)
- Ruixiang Qi
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Liren Lu
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Ting He
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Liqing Zhang
- Department of Radiology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Yiting Lin
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Lingyun Bao
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China.
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Zhang LX, Dioguardi B, Vilgrain V, Fang C, Sidhu PS, Cloutier G, Tang A. Quantitative Ultrasound and Ultrasound-Based Elastography for Chronic Liver Disease: Practical Guidance, From the AJR Special Series on Quantitative Imaging. AJR Am J Roentgenol 2024. [PMID: 39259009 DOI: 10.2214/ajr.24.31709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2024]
Abstract
Quantitative ultrasound (QUS) and ultrasound-based elastography techniques are emerging as non-invasive effective methods for assessing chronic liver disease. They are more accurate than B-mode imaging alone and more accessible than MRI as alternatives to liver biopsy. Early detection and monitoring of diffuse liver processes such as steatosis, inflammation, and fibrosis play an important role in guiding patient management. The most widely available and validated techniques are attenuation-based QUS techniques and shear-wave elastography techniques that measure shear-wave speed. Other techniques are supported by a growing body of evidence and are increasingly commercialized. This review explains general physical concepts of QUS and ultrasound-based elastography techniques for evaluating chronic liver disease. The first section describes QUS techniques relying on attenuation, backscatter, and speed of sound. The second section discusses ultrasound-based elastography techniques analyzing shear-wave speed, shear-wave dispersion, and shear-wave attenuation. With an emphasis on clinical implementation, each technique's diagnostic performance along with thresholds for various clinical applications are summarized, to provide guidance on analysis and reporting for radiologists. Measurement methods, advantages, and limitations are also discussed. The third section explores developments in quantitative contrast-enhanced and vascular ultrasound that are relevant to chronic liver disease evaluation.
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Affiliation(s)
- Li Xin Zhang
- Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Canada
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Canada
| | - Burgio Dioguardi
- Department of Radiology, Hôpital Beaujon, Assistance Publique Hôpitaux de Paris, Clichy, France
- Research Center on Inflammation, Université Paris Cité, Paris, France
| | - Valérie Vilgrain
- Department of Radiology, Hôpital Beaujon, Assistance Publique Hôpitaux de Paris, Clichy, France
| | - Cheng Fang
- Department of Radiology, King's College Hospital NHS Foundation Trust, Denmark Hill, London, SE5 9RS UK
- Department of Imaging Sciences, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, SE17EH UK
| | - Paul S Sidhu
- Department of Radiology, King's College Hospital NHS Foundation Trust, Denmark Hill, London, SE5 9RS UK
- Department of Imaging Sciences, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, SE17EH UK
| | - Guy Cloutier
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Canada
- Institute of Biomedical Engineering, Université de Montréal, Montréal, Canada
- Research Center, Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada
| | - An Tang
- Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Canada
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Canada
- Institute of Biomedical Engineering, Université de Montréal, Montréal, Canada
- Research Center, Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada
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Hajibonabi F, Riedesel EL, Taylor SD, Linam LE, Alazraki AL, Zhang C, Khanna G. Ultrasound-estimated hepatorenal index: diagnostic performance and interobserver agreement for pediatric liver fat quantification. Pediatr Radiol 2024; 54:1653-1660. [PMID: 39136769 DOI: 10.1007/s00247-024-06021-4] [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: 01/07/2024] [Revised: 07/30/2024] [Accepted: 07/31/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND Semiquantitative and quantitative sonographic techniques have the potential for screening and surveillance of children at risk of nonalcoholic fatty liver disease. OBJECTIVE To determine diagnostic performance and interobserver agreement of hepatorenal index (HRI) for pediatric ultrasound-based liver fat quantification. MATERIALS AND METHODS In an institutional review board (IRB)-approved retrospective study (April 2014 to April 2023), children (< 18 years) with clinically performed magnetic resonance imaging (MRI) scans for liver fat quantification were assessed. Inclusion criteria required availability of abdominal ultrasound within 3 months of quantitative MRI. Three blinded readers subjectively assessed for sonographic hepatic steatosis and calculated HRI. MRI proton density fat fraction (PDFF) was the reference standard. Interobserver agreement, correlation with PDFF, and optimal HRI (using ROC analysis) values were analyzed. The significance level was set at p < 0.05. RESULTS A total of 41 patients (25 male) with median (interquartile range (IQR)) age of 13 (10-15) years were included. Median (IQR) MRI PDFF was 11.30% (2.70-17.95%). Hepatic steatosis distribution by MRI PDFF included grade 0 (34%), grade 1 (15%), grade 2 (22%), and grade 3 (29%) patients. Intraclass correlation coefficient for HRI among the three readers was 0.61 (95% CI 0.43-0.75) (p < 0.001). Moderate correlation was observed between manually estimated HRI and PDFF for each reader (r = 0.62, 0.67, and 0.67; p < 0.001). Optimal HRI cutoff was found to be 1.99 to diagnose hepatic steatosis (sensitivity 89%, specificity 93%). Median (IQR) HRI for each MRI grade of hepatic steatosis (0-4) was as follows: 1.2 (1.1-1.5), 2.6 (1.1-3.3), 3.6 (2.6-5.4), 5.6 (2.6-10.9), respectively (p < 0.001). CONCLUSION Ultrasound-estimated HRI has moderate interobserver agreement and moderate correlation with MRI-derived PDFF. HRI of 1.99 maximizes accuracy for identifying pediatric liver fat.
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Affiliation(s)
- Farid Hajibonabi
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA.
| | - Erica L Riedesel
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Susan D Taylor
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Leann E Linam
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Adina L Alazraki
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Chao Zhang
- Biostatistics Shared Resource, Winship Cancer Institute of Emory University, Atlanta, USA
| | - Geetika Khanna
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
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Qi Y, Vianna P, Cadrin-Chênevert A, Blanchet K, Montagnon E, Belilovsky E, Wolf G, Mullie LA, Cloutier G, Chassé M, Tang A. Simulating federated learning for steatosis detection using ultrasound images. Sci Rep 2024; 14:13253. [PMID: 38858500 PMCID: PMC11164945 DOI: 10.1038/s41598-024-63969-x] [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: 02/24/2024] [Accepted: 06/04/2024] [Indexed: 06/12/2024] Open
Abstract
We aimed to implement four data partitioning strategies evaluated with four federated learning (FL) algorithms and investigate the impact of data distribution on FL model performance in detecting steatosis using B-mode US images. A private dataset (153 patients; 1530 images) and a public dataset (55 patient; 550 images) were included in this retrospective study. The datasets contained patients with metabolic dysfunction-associated fatty liver disease (MAFLD) with biopsy-proven steatosis grades and control individuals without steatosis. We employed four data partitioning strategies to simulate FL scenarios and we assessed four FL algorithms. We investigated the impact of class imbalance and the mismatch between the global and local data distributions on the learning outcome. Classification performance was assessed with area under the receiver operating characteristic curve (AUC) on a separate test set. AUCs were 0.93 (95% CI 0.92, 0.94) for source-based partitioning scenario with FedAvg, 0.90 (95% CI 0.89, 0.91) for a centralized model, and 0.83 (95% CI 0.81, 0.85) for a model trained in a single-center scenario. When data was perfectly balanced on the global level and each site had an identical data distribution, the model yielded an AUC of 0.90 (95% CI 0.88, 0.92). When each site contained data exclusively from one single class, irrespective of the global data distribution, the AUC fell in the range of 0.34-0.70. FL applied to B-mode US images provide performance comparable to a centralized model and higher than single-center scenario. Global data imbalance and local data heterogeneity influenced the learning outcome.
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Affiliation(s)
- Yue Qi
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Pedro Vianna
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
- Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada
- Laboratory of Biorheology and Medical Ultrasonics - CRCHUM, Montréal, QC, Canada
| | - Alexandre Cadrin-Chênevert
- Radiology, Radiation Oncology and Nuclear Medicine Department, Université de Montréal, Montréal, QC, Canada
- CISSS de Lanaudière, Joliette, QC, Canada
| | - Katleen Blanchet
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Emmanuel Montagnon
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
- Clinical Laboratory of Image Processing - CRCHUM, Montréal, QC, Canada
| | - Eugene Belilovsky
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada
- Concordia University, Montréal, QC, Canada
| | - Guy Wolf
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, QC, Canada
| | - Louis-Antoine Mullie
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada
- Department of Medicine, Division of Critical Care Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, QC, Canada
- Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Guy Cloutier
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
- Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada
- Laboratory of Biorheology and Medical Ultrasonics - CRCHUM, Montréal, QC, Canada
- Radiology, Radiation Oncology and Nuclear Medicine Department, Université de Montréal, Montréal, QC, Canada
- Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Michaël Chassé
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
- Department of Medicine, Division of Critical Care Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, QC, Canada
- Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - An Tang
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada.
- Clinical Laboratory of Image Processing - CRCHUM, Montréal, QC, Canada.
- Faculty of Medicine, Université de Montréal, Montréal, QC, Canada.
- Département de Radiologie, Centre Hospitalier de l'Université de Montréal (CHUM), 1058 Rue Saint-Denis, Montréal, QC, H2X 3J4, Canada.
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Kubale R, Schneider G, Lessenich CPN, Buecker A, Wassenberg S, Torres G, Gurung A, Hall T, Labyed Y. Ultrasound-Derived Fat Fraction for Hepatic Steatosis Assessment: Prospective Study of Agreement With MRI PDFF and Sources of Variability in a Heterogeneous Population. AJR Am J Roentgenol 2024; 222:e2330775. [PMID: 38506537 DOI: 10.2214/ajr.23.30775] [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] [Indexed: 03/21/2024]
Abstract
BACKGROUND. Metabolic dysfunction-associated steatotic liver disease is a growing global public health concern. Quantitative ultrasound measurements, such as ultrasound-derived fat fraction (UDFF), could provide noninvasive, cost-effective, and portable steatosis evaluation. OBJECTIVE. The purpose of this article was to evaluate utility of UDFF for steatosis assessment using proton density fat fraction (PDFF) as reference in patients undergoing liver MRI for heterogeneous indications and to assess UDFF variability. METHODS. This prospective study included a primary analysis of 187 patients (mean age, 53.8 years; 112 men, 75 women) who underwent 3-T liver MRI for any clinical indication from December 2020 to July 2021. Patients underwent investigational PDFF measurement, including determination of PDFFwhole-liver (mean PDFF of entire liver), and PDFFvoxel (PDFF in single voxel within right lobe, measured by MR spectroscopy), as well as investigational ultrasound with UDFF calculation (mean of five inter-costal measurements) within 1 hour after MRI. In a subanalysis, 21 of these patients underwent additional UDFF measurements 1, 3, and 5 hours after meal consumption. The study also included repeatability and reproducibility analysis of 30 patients (mean age, 26.3 years; 10 men, 20 women) who underwent clinical abdominal ultrasound between November 2022 and January 2023; in these patients, three operators sequentially performed UDFF measurements. RESULTS. In primary analysis, UDFF and PDFFwhole-liver measurements showed intra-class correlation coefficient (ICC) of 0.79. In Bland-Altman analysis, UDFF and PDFFvoxel measurements showed mean difference of 1.5% (95% CI, 0.6-2.4%), with 95% limits of agreement from -11.0% to 14.0%. UDFF measurements exhibited AUC for detecting PDFFvoxel at historic thresholds of 6.5% and greater, 17.4% and greater, and 22.1% and greater of 0.90, 0.95, and 0.95, respectively. In subanalysis, mean UDFF was not significantly different across time points with respect to meal consumption (p = .21). In repeatability and reproducibility analysis, ICC for intraoperator repeatability ranged from 0.98 to 0.99 and for interoperator reproducibility from 0.90 to 0.96. Visual assessment of patient-level data plots indicated increasing variability of mean UDFF measurements across operators and of intercostal measurements within individual patients with increasing steatosis. CONCLUSION. UDFF showed robust agreement with PDFF, diagnostic performance for steatosis grades, and intraoperator repeatability and interoperator reproducibility. Nonetheless, UDFF exhibited bias toward slightly larger values versus PDFF; intraoperator and interoperator variation increased with increasing steatosis. CLINICAL IMPACT. UDFF shows promise for steatosis assessment across diverse populations, although continued optimization remains warranted.
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Affiliation(s)
- Reinhard Kubale
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | - Guenther Schneider
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | - Carl P N Lessenich
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | - Arno Buecker
- Clinic of Diagnostic and Interventional Radiology, Saarland University Hospital, Kirrberger Strasse Geb. 50.1, 66424 Homburg, Germany
| | | | | | - Arati Gurung
- Siemens Healthineers Ultrasound Division, Issaquah, WA
| | - Timothy Hall
- Department of Medical Physics, University of Wisconsin, Madison, WI
| | - Yassin Labyed
- Siemens Healthineers Ultrasound Division, Issaquah, WA
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Kalisz K, Navin PJ, Itani M, Agarwal AK, Venkatesh SK, Rajiah PS. Multimodality Imaging in Metabolic Syndrome: State-of-the-Art Review. Radiographics 2024; 44:e230083. [PMID: 38329901 DOI: 10.1148/rg.230083] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Metabolic syndrome comprises a set of risk factors that include abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, low high-density lipoprotein levels, and high blood pressure, at least three of which must be fulfilled for diagnosis. Metabolic syndrome has been linked to an increased risk of cardiovascular disease and type 2 diabetes mellitus. Multimodality imaging plays an important role in metabolic syndrome, including diagnosis, risk stratification, and assessment of complications. CT and MRI are the primary tools for quantification of excess fat, including subcutaneous and visceral adipose tissue, as well as fat around organs, which are associated with increased cardiovascular risk. PET has been shown to detect signs of insulin resistance and may detect ectopic sites of brown fat. Cardiovascular disease is an important complication of metabolic syndrome, resulting in subclinical or symptomatic coronary artery disease, alterations in cardiac structure and function with potential progression to heart failure, and systemic vascular disease. CT angiography provides comprehensive evaluation of the coronary and systemic arteries, while cardiac MRI assesses cardiac structure, function, myocardial ischemia, and infarction. Liver damage results from a spectrum of nonalcoholic fatty liver disease ranging from steatosis to fibrosis and possible cirrhosis. US, CT, and MRI are useful in assessing steatosis and can be performed to detect and grade hepatic fibrosis, particularly using elastography techniques. Metabolic syndrome also has deleterious effects on the pancreas, kidney, gastrointestinal tract, and ovaries, including increased risk for several malignancies. Metabolic syndrome is associated with cerebral infarcts, best evaluated with MRI, and has been linked with cognitive decline. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Pickhardt in this issue.
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Affiliation(s)
- Kevin Kalisz
- From the Duke University School of Medicine, Durham, NC (K.K.); Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 559905 (P.J.N., S.K.V., P.S.R.); Mallinckrodt Institute of Radiology, Washington University, St. Louis, Mo (M.I.); and Mayo Clinic, Jacksonville, Fla (A.K.A.)
| | - Patrick J Navin
- From the Duke University School of Medicine, Durham, NC (K.K.); Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 559905 (P.J.N., S.K.V., P.S.R.); Mallinckrodt Institute of Radiology, Washington University, St. Louis, Mo (M.I.); and Mayo Clinic, Jacksonville, Fla (A.K.A.)
| | - Malak Itani
- From the Duke University School of Medicine, Durham, NC (K.K.); Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 559905 (P.J.N., S.K.V., P.S.R.); Mallinckrodt Institute of Radiology, Washington University, St. Louis, Mo (M.I.); and Mayo Clinic, Jacksonville, Fla (A.K.A.)
| | - Amit Kumar Agarwal
- From the Duke University School of Medicine, Durham, NC (K.K.); Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 559905 (P.J.N., S.K.V., P.S.R.); Mallinckrodt Institute of Radiology, Washington University, St. Louis, Mo (M.I.); and Mayo Clinic, Jacksonville, Fla (A.K.A.)
| | - Sudhakar K Venkatesh
- From the Duke University School of Medicine, Durham, NC (K.K.); Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 559905 (P.J.N., S.K.V., P.S.R.); Mallinckrodt Institute of Radiology, Washington University, St. Louis, Mo (M.I.); and Mayo Clinic, Jacksonville, Fla (A.K.A.)
| | - Prabhakar Shantha Rajiah
- From the Duke University School of Medicine, Durham, NC (K.K.); Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 559905 (P.J.N., S.K.V., P.S.R.); Mallinckrodt Institute of Radiology, Washington University, St. Louis, Mo (M.I.); and Mayo Clinic, Jacksonville, Fla (A.K.A.)
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Adeghate EA. GLP-1 receptor agonists in the treatment of diabetic non-alcoholic steatohepatitis patients. Expert Opin Pharmacother 2024; 25:223-232. [PMID: 38458647 DOI: 10.1080/14656566.2024.2328796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/06/2024] [Indexed: 03/10/2024]
Abstract
INTRODUCTION Nonalcoholic fatty liver disease (NAFLD) is the most common hepatic disease affecting almost 30% of the world population. Approximately 25% of people with NAFLD develop nonalcoholic steatohepatitis (NASH), the fulminant version of the disease. Diabetes mellitus is present in 22.5% of people with NAFLD and 44.60% of individuals with NASH. This review was undertaken to examine the current contribution of glucagon-like peptide 1 (GLP-1) receptor agonists to the pharmacotherapy of diabetic nonalcoholic steatohepatitis. AREAS COVERED The author analyzed the current status of GLP-1 receptor agonists for pharmacotherapy of diabetic NASH. Research data and literature reports were taken from the database and or websites of Diabetes UK, American Diabetes Association, ClinicalTrials.gov, PubMed, and Scopus. The keywords utilized included type 2 diabetes, GLP-1, NASH, NAFLD, and clinical trials. EXPERT OPINION Since diabetic NASH is associated with obesity, diabetes mellitus, oxidative stress and inflammation, drugs capable of mitigating all of these conditions simultaneously, are most ideal for the treatment of diabetic NASH. These drugs include (in order of relevance), GLP-1 receptor agonists, GLP-1 and GIP dual receptor agonists, sodium-glucose co-transporter-2 (SGLT2) inhibitors, and pioglitazone. The future, FDA-approved drug for diabetic NASH treatment will likely be GLP-1 agonist, which could be used as monotherapy or in combination with other drugs.
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Affiliation(s)
- Ernest A Adeghate
- Department of Anatomy, College of Medicine & Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
- Zayed Centre for Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
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Maheshwari S, Gu CN, Caserta MP, Kezer CA, Shah VH, Torbenson MS, Menias CO, Fidler JL, Venkatesh SK. Imaging of Alcohol-Associated Liver Disease. AJR Am J Roentgenol 2024; 222:e2329917. [PMID: 37729554 DOI: 10.2214/ajr.23.29917] [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] [Indexed: 09/22/2023]
Abstract
Alcohol-associated liver disease (ALD) continues to be a global health concern, responsible for a significant number of deaths worldwide. Although most individuals who consume alcohol do not develop ALD, heavy drinkers and binge drinkers are at increased risk. Unfortunately, ALD is often undetected until it reaches advanced stages, frequently associated with portal hypertension and hepatocellular carcinoma (HCC). ALD is now the leading indication for liver transplant. The incidence of alcohol-associated hepatitis (AH) surged during the COVID-19 pandemic. Early diagnosis of ALD is therefore important in patient management and determination of prognosis, as abstinence can halt disease progression. The spectrum of ALD includes steatosis, steatohepatitis, and cirrhosis, with steatosis the most common manifestation. Diagnostic techniques including ultrasound, CT, and MRI provide useful information for identifying ALD and excluding other causes of liver dysfunction. Heterogeneous steatosis and transient perfusion changes on CT and MRI in the clinical setting of alcohol-use disorder are diagnostic of severe AH. Elastography techniques are useful for assessing fibrosis and monitoring treatment response. These various imaging modalities are also useful in HCC surveillance and diagnosis. This review discusses the imaging modalities currently used in the evaluation of ALD, highlighting their strengths, limitations, and clinical applications.
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Affiliation(s)
- Sharad Maheshwari
- Department of Radiology, Kokilaben Dhirubhai Ambani Hospital, Mumbai, India
| | - Chris N Gu
- Department of Radiology, Division of Abdominal Imaging, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
| | - Melanie P Caserta
- Department of Radiology, Division of Abdominal Imaging, Mayo Clinic, Jacksonville, FL
| | - Camille A Kezer
- Department of Internal Medicine, Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Vijay H Shah
- Department of Internal Medicine, Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Michael S Torbenson
- Department of Laboratory Medicine and Pathology, Division of Anatomic Pathology, Mayo Clinic, Rochester, MN
| | - Christine O Menias
- Department of Radiology, Division of Abdominal Imaging, Mayo Clinic, Scottsdale, AZ
| | - Jeff L Fidler
- Department of Radiology, Division of Abdominal Imaging, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
| | - Sudhakar K Venkatesh
- Department of Radiology, Division of Abdominal Imaging, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
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Wang X, Bamber JC, Esquivel-Sirvent R, Ormachea J, Sidhu PS, Thomenius KE, Schoen S, Rosenzweig S, Pierce TT. Ultrasonic Sound Speed Estimation for Liver Fat Quantification: A Review by the AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2327-2335. [PMID: 37550173 DOI: 10.1016/j.ultrasmedbio.2023.06.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 06/23/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a significant cause of diffuse liver disease, morbidity and mortality worldwide. Early and accurate diagnosis of NALFD is critical to identify patients at risk of disease progression. Liver biopsy is the current gold standard for diagnosis and prognosis. However, a non-invasive diagnostic tool is desired because of the high cost and risk of complications of tissue sampling. Medical ultrasound is a safe, inexpensive and widely available imaging tool for diagnosing NAFLD. Emerging sonographic tools to quantitatively estimate hepatic fat fraction, such as tissue sound speed estimation, are likely to improve diagnostic accuracy, precision and reproducibility compared with existing qualitative and semi-quantitative techniques. Various pulse-echo ultrasound speed of sound estimation methodologies have been investigated, and some have been recently commercialized. We review state-of-the-art in vivo speed of sound estimation techniques, including their advantages, limitations, technical sources of variability, biological confounders and existing commercial implementations. We report the expected range of hepatic speed of sound as a function of liver steatosis and fibrosis that may be encountered in clinical practice. Ongoing efforts seek to quantify sound speed measurement accuracy and precision to inform threshold development around meaningful differences in fat fraction and between sequential measurements.
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Affiliation(s)
- Xiaohong Wang
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Jeffrey C Bamber
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK
| | | | | | - Paul S Sidhu
- Department of Radiology, King's College Hospital, London, UK
| | - Kai E Thomenius
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Scott Schoen
- 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; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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