Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Abdominal Radiology
Published in: Abdominal Radiology 11/2020

Open Access 01-11-2020 | Magnetic Resonance Imaging | Special Section: Diffuse Liver Disease

Multiparametric MR mapping in clinical decision-making for diffuse liver disease

Authors: Helena B. Thomaides-Brears, Rita Lepe, Rajarshi Banerjee, Carlos Duncker

Published in: Abdominal Radiology | Issue 11/2020

Login to get access

Abstract

Accurate diagnosis, monitoring and treatment decisions in patients with chronic liver disease currently rely on biopsy as the diagnostic gold standard, and this has constrained early detection and management of diseases that are both varied and can be concurrent. Recent developments in multiparametric magnetic resonance imaging (mpMRI) suggest real potential to bridge the diagnostic gap between non-specific blood-based biomarkers and invasive and variable histological diagnosis. This has implications for the clinical care and treatment pathway in a number of chronic liver diseases, such as haemochromatosis, steatohepatitis and autoimmune or viral hepatitis. Here we review the relevant MRI techniques in clinical use and their limitations and describe recent potential applications in various liver diseases. We exemplify case studies that highlight how these techniques can improve clinical practice. These techniques could allow clinicians to increase their arsenals available to utilise on patients and direct appropriate treatments.
Literature
1.
2.
3.
4.
5.
6.
7.
8.
9.
Tapper E, Lok A (2017) Use of liver imaging and biopsy in clinical practice. N Engl J Med 377 (8): 756–768.PubMedCrossRef
10.
11.
European Association for Study of Liver; Asociacion Latinoamericana para el Estudio del Higado (2015) EASL-ALEH clinical practice guidelines: non-invasive tests for evaluation of liver disease severity and prognosis. Journal of Hepatololgy 63 (1): 237–264.CrossRef
12.
13.
14.
Myers R, Pomier-Layrargues G, Kirsch R et al. (2012) Feasibility and diagnostic performance of the FibroScan XL probe for liver stiffness measurement in overweight and obese patients. Hepatology 55 (1): 199–208.PubMedCrossRef
15.
de Lédinghen V, Vergniol J, Capdepont M et al. (2014) Controlled attenuation parameter (CAP) for the diagnosis of steatosis: a prospective study of 5323 examinations. Journal of Hepatology 60 (5): 1026–1031.PubMedCrossRef
16.
McDonald N, Eddowes P, Hodson J et al. (2018) Multiparametric magnetic resonance imaging for quantitation of liver disease: a two-centre cross-sectional observational study. Scientific Reports 8 (1): 9189.PubMedPubMedCentralCrossRef
17.
18.
19.
20.
21.
European Association for the Study of the Liver (2015) EASL Clinical Practice Guidelines: Autoimmune hepatitis. Journal of Hepatololgy 63 (4): 971–1004.CrossRef
22.
23.
Lee H, Ahn J, Kim W et al. (2019) A comparison between community and academic practices in the USA in the management of chronic hepatitis B patients receiving entecavir: results of the ENUMERATE study. Dig Dis Sci 64 (2): 358–366.PubMedCrossRef
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
Stoopen-Rometti M, Encinas-Escobar E, Ramirez-Carmona C et al. (2017) Diagnosis and quantification of fibrosis, steatosis, and hepatic siderosis through multiparametric magnetic resonance imaging. Rev Gastroenterol Mex 82 (1): 32–45.PubMed
34.
35.
36.
37.
Marino M, Helbich T, Baltzer P, Pinker-Domenig K (2018) Multiparametric MRI of the breast: a review. Journal Magnetic Resonance Imaging 47 (2): 301–315.CrossRef
38.
39.
Messroghli DR, Moon JC, Ferreira VM et al. (2017) Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: a consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imagi. Journal of Cardiovascular Magnetic Resonance 19 (1): 75. https://​doi.​org/​10.​1186/​s12968-017-0389-8CrossRefPubMedPubMedCentral
40.
41.
42.
Bachtiar V, Wilman H, Jacobs J et al. (2019) Reliability and reproducibility of multiparametric magnetic resonance imaging of the liver. PLOS ONE 14 (4): e0214921.PubMedPubMedCentralCrossRef
43.
Lee Y, Yoo Y, Jung Y et al. (2020) Multiparametric MR is a valuable modality for evaluating disease severity of nonalcoholic fatty liver disease. Clinical and Translational Gastroenterology 11 (4): e00157.PubMedPubMedCentralCrossRef
44.
45.
46.
Dennis A, Mouchti S, McKay A et al. (2020) Multi-parametric MRI as a composite biomarker with standard liver function tests for NASH with fibrosis. Scientific Reports submitted
47.
48.
Li, R. K., Zeng, M. S., Qiang, J. W., Palmer, S. L., Chen, F., Rao, S. X., Chen, L. L., & Dai YM (2017) Improving detection of iron deposition in cirrhotic liver using susceptibility-weighted imaging with emphasis on histopathological correlation. Journal of Computer Assisted Tomography 41 (1): 18–24.PubMedCrossRef
49.
50.
Welle C, Guglielmo F, Venkatesh S (2020) MRI of the liver: choosing the right contrast agent. Abdominal Radiology 45 (2): 384–392.PubMedCrossRef
51.
52.
Lin H, Fu C, Kannengiesser S et al. (2018) Quantitative analysis of hepatic iron in patients suspected of coexisting iron overload and steatosis using multi-echo single-voxel magnetic resonance spectroscopy: Comparison with fat-saturated multi-echo gradient echo sequence. Journal of Magnetic Resonance Imaging 48 (1): 205–213. https://​doi.​org/​10.​1002/​jmri.​25967CrossRefPubMed
53.
Siegelman E, Mitchell D, Semelka R (1996) Abdominal iron deposition: metabolism, MR findings, and clinical importance. Radiology 199 (1): 13–22.PubMedCrossRef
54.
55.
Bashir M, Wolfson T, Gamst A et al. (2019) Hepatic R2* is more strongly associated with proton density fat fraction than histologic liver iron scores in patients with nonalcoholic fatty liver disease. J Magn Reson Imaging 49 (5): 1456–1466.PubMedCrossRef
56.
57.
58.
Bydder M, de Rochefort L, Hamilton G et al. (2018) The change in R2* with PDFF in liver can be explained by the water/fat susceptibility difference. Jt. Annu. Meet. ISMRM-ESMRMB, Paris, 16–21 June 2018
59.
60.
Reeder S, Pineda A, Wen Z et al. (2005) Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging. Magnetic Resonance in Medicine 54 (3): 636–644.PubMedCrossRef
61.
Reeder S, McKenzie C, Pineda A et al. (2007) Water-fat separation with IDEAL gradient-echo imaging. J Magn Reson Imaging 25 (3): 644–652.PubMedCrossRef
62.
63.
Yokoo T, Pirasteh A, Bashir M et al. (2016) Proton-Density Fat Fraction Biomarker Committee: a meta-analysis interim report 2016. Radiol. Soc. North Am. 102nd Sci. Assem. Annu. Meet. Chicago, 27 November–2 December 2016
64.
Yokoo T, Serai S, Pirasteh A et al. (2018) Linearity, bias, and precision of hepatic proton density fat fraction measurements by using MR imaging: a meta-analysis. Radiology 286 (2): 486–498.PubMedCrossRef
65.
66.
67.
Liu C, McKenzie C, Yu H et al. (2007) Fat quantification with IDEAL gradient echo imaging: correction of bias from T(1) and noise. Magnetic Resonance in Medicine 58 (2): 354–364.PubMedCrossRef
68.
Leporq B, Ratiney H, Pilleul F, Beuf O (2013) Liver fat volume fraction quantification with fat and water T1 and T2* estimation and accounting for NMR multiple components in patients with chronic liver disease at 1.5 and 3.0 T. Eur Radiol 23 (8): 2175–2186.PubMedCrossRef
69.
70.
71.
Glover G, Schneider E (1991) Three-point Dixon technique for true water/fat decomposition with B0 inhomogeneity correction. Magnetic Resonance in Medicine 18 (2): 371–383.PubMedCrossRef
72.
Reeder S, Wen Z, Yu H et al. (2004) Multicoil Dixon chemical species separation with an iterative least-squares estimation method. Magnetic Resonance in Medicine 51 (1): 35–45.PubMedCrossRef
73.
74.
75.
Heba ER, Desai A, Zand KA et al. (2016) Accuracy and the effect of possible subject-based confounders of magnitude-based MRI for estimating hepatic proton density fat fraction in adults, using MR spectroscopy as reference. Journal of Magnetic Resonance Imaging: JMRI 43 (2): 398–406. https://​doi.​org/​10.​1002/​jmri.​25006CrossRefPubMed
76.
Dennis A, Kelly M, Fernandes C et al. (2020) Correlations between MRI biomarkers PDFF and cT1 with histopathological features of non-alcoholic steatohepatitis. Frontiers in Endocrinology. submitted
77.
Wagner M, Corcuera-Solano I, Lo G et al. (2017) Technical failure of MR elastography examinations of the liver: experience from a large single-center ttudy. Radiology 284 (2): 401–412.PubMedCrossRef
78.
79.
80.
81.
82.
83.
84.
85.
Harrison S, Roberts K, Paredes AH et al. (2017) Prospective prevalence study of adult NAFLD/NASH utilising multi-modality imaging compared with liver biopsy. EASL Int. Liver Congr. Brussels, 19–23 April
86.
Huwart L, Sempoux C, Vicaut E et al. (2008) Magnetic resonance elastography for the noninvasive staging of liver fibrosis. Gastroenterology 135 (1): 32–40.PubMedCrossRef
87.
88.
Harrison S, Dennis A, Fiore M et al. (2018) Utility and variability of three non-invasive liver fibrosis imaging modalities to evaluate efficacy of GR-MD-02 in subjects with NASH and bridging fibrosis during a Phase 2 controlled study. PLOS ONE 13 (9): e0203054.PubMedPubMedCentralCrossRef
89.
90.
91.
92.
93.
94.
95.
96.
Hoad C, Palaniyappan N, Kaye P et al. (2015) A study of T1 relaxation time as a measure of liver fibrosis and the influence of confounding histological factors. NMR Biomed 28 (6): 706–714.PubMedCrossRef
97.
Floyd RA, Yoshida T, Leigh JS (1975) Changes of tissue water proton relaxation rates during early phases of chemical carcinogenesis. Proceedings of the National Academy of Sciences 72 (1): 56 LP – 58.CrossRef
98.
99.
100.
Tunnicliffe EM, Rajarshi B, Pavlides M et al. (2016) A model for hepatic fibrosis: the competing effects of cell loss and iron on shortened modified Look‐Locker inversion recovery T1 (shMOLLI‐T1) in the liver. Journal of Magnetic Resonance Imaging 45 (2): 450–462. https://​doi.​org/​10.​1002/​jmri.​25392CrossRefPubMed
101.
101. Brunt EM, Janney CG, Di Bisceglie AM et al. (1999) Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. American Journal of Gastroenterology 94 2467.CrossRefPubMed
102.
103.
104.
105.
106.
107.
108.
Petersen RJ, Nielsen NS, Johannesen HH et al. (2019) PET/DW-MRI for evaluating treatment in chronic hepatitis C patients. American Journal of Nuclear Medicine and Molecular Imaging 9 (1): 84–92.PubMedPubMedCentral
109.
110.
Taouli B, Chouli M, Martin A et al. (2008) Chronic hepatitis: role of diffusion-weighted imaging and diffusion tensor imaging for the diagnosis of liver fibrosis and inflammation. Journal Magnetic Resonance Imaging 28 (1): 89–95.CrossRef
111.
Liu Y, Dong JH, An WM et al. (2017) Quantitative Comparison of Diffusion Weighted Image in Liver at Two Field Strengths for Chronic Hepatitis. Zhonghua Yi Xue Za Zhi 97 (21): 1638–1642.PubMed
112.
Kocakoc E, Bakan AA, Poyrazoglu OK et al. (2015) Assessment of Liver Fibrosis with Diffusion-Weighted Magnetic Resonance Imaging Using Different b-values in Chronic Viral Hepatitis. Medical principles and practice : international journal of the Kuwait University, Health Science Centre 24 (6): 522–526https://​doi.​org/​10.​1159/​000434682CrossRef
113.
Xiong, H., & Zeng YL (2016) Standard-b-value versus low-b-Value diffusion-weighted Imaging in hepatic lesion discrimination: a meta-analysis. Journal of Computer Assisted Tomography 40 (3): 498–504.PubMedCrossRef
114.
Tavakoli A, Attenberger UI, Budjan J et al. (2019) Improved liver diffusion-weighted imaging at 3 T using respiratory triggering in combination with simultaneous multislice acceleration. Investigative Radiology 54 (12): 744–751.PubMedCrossRef
115.
Ichikawa S, Motosugi U, Morisaka H et al. (2014) MRI‐based staging of hepatic fibrosis: comparison of intravoxel incoherent motion diffusion‐weighted imaging with magnetic resonance elastography. Journal Magnetic Resonance Imaging 42 (1): 204–210.CrossRef
116.
117.
118.
119.
120.
121.
122.
123.
124.
Chitturi S, Weltman M, Farrell G et al. (2002) HFE mutations, hepatic iron, and fibrosis: ethnic-specific association of NASH with C282Y but not with fibrotic severity. Hepatology 36 142–149.PubMedCrossRef
125.
126.
127.
128.
Terada T, Nakanuma Y (1989) Survey of iron-accumulative macroregenerative nodules in cirrhotic livers. Hepatology 10 (5): 851–854.PubMedCrossRef
129.
130.
131.
132.
133.
Mojtahed A, Kelly C, Herlihy A et al. (2019) Reference range of liver corrected T1 values in a population at low risk for fatty liver disease-a UK Biobank sub-study, with an appendix of interesting cases. Abdomimal Radiology (NY) 44 (1): 72–84.CrossRef
134.
Thomaides-Brears, HB Shumbayawonda E, Mouchti S, Castelo-Branco M et al. (2019) Characterization of MR derived biomarkers of liver health in a European cohort with metabolic syndrome and NAFLD in comparison to healthy controls: Preliminary analysis of an ongoing prospective trial (RADIcAL1). AASLD, Liver Meet. Boston, 10–12 November.
135.
136.
Müller A, Hochrath K, Stroeder J et al. (2017) Effects of liver fibrosis progression on tissue relaxation times in different mouse models assessed by ultrahigh field magnetic resonance imaging. BioMed Research International 2017 (8720367): 10.
137.
McKay A, Dennis A, Kelly M et al. (2019) Multi-parametric MRI as a composite biomarker for NASH and NASH with fibrosis. Keystone Integr. Pathways Dis. NASH NAFLD Symp. St. Fe, New Mex. 20–24 January
138.
139.
140.
Harrison S, Roberts K, Lisanti C et al. (2019) Predicting the Severity of Hepatic Steatosis and fibrosis by Transient Elastography and MRI-based techniques in Adult Patients with Suspected NAFLD. EASL Int. Liver Congr. Vienna, 10–14 April
141.
Aslam F, Mouchti S, Dennis A et al. (2019) Non-invasive imaging modalities for assesment of fibrosis, inflammation and steatosis in a Japanese NASH population. AASLD, Liver Meet. Boston, 10–12 November
142.
143.
Friedman S, Neuschwander-Tetri B, Rinella M, Sanyal A (2018) Mechanisms of NAFLD development and therapeutic strategies. Nature Medicine 24 (7): 908–922.PubMedPubMedCentralCrossRef
144.
145.
146.
147.
148.
149.
150.
151.
Ostovaneh M, Ambale-Venkatesh B, Fuji T et al. (2018) Association of liver fibrosis with cardiovascular diseases in the general population: The Multi-Ethnic Study of Atherosclerosis (MESA). Circulation: Cardiovascular Imaging 11 e007241.
152.
153.
Jayaswal A, Pavlides M, Banerjee R et al. (2018) cT1 is accurate as biopsy at predicting outcomes in patients with chronic liver disease. AASLD, Liver Meet. San Fransisco, 9–13 November
154.
Jayaswal A, Pavlides M, Banerjee R et al. (2019) Liver cT1 predicts clinical outcomes in patients with chronic liver disease. EASL Int. Liver Congr. Vienna, 10–14 April
155.
Jayaswal AN., Barnes E, Banerjee R et al. (2020) Prognostic value of multiparametric MRI, transient elastography and serum fibrosis markers in patients with chronic liver disease. Liver International (in press)
156.
157.
Dillman J, Serai S, Trout A et al. (2019) Diagnostic performance of quantitative magnetic resonance imaging biomarkers for predicting portal hypertension in children and young adults with autoimmune liver disease. Pediatric Radiology 49 (3): 332–341.PubMedCrossRefPubMedCentral
158.
Pik-Eu Chang J, Jayaswal AN., Tim-Ee Cheng L et al. (2020) Multiparametric magnetic resonance imaging of liver and spleen is a reliable non-invasive predictor of clinically relevant hepatic venous pressure gradient thresholds and predicts failure of primary prophylaxis for variceal bleeding. Alimentary Pharmacology & Therapeutics. submitted
159.
160.
161.
162.
Thomaides-Brears H, Barragán E, de Celis Alonso B et al. (2019) Prevalence of non-alcoholic fatty liver disease in a Mexican paediatric population diagnosed non-invasively by multiparametric magnetic resonance imaging. ISMRM Work. MRI Obes. Metab. Disord. Singapore, 21–24 July 2019
163.
Halliday D, Simpson H, Borghetto A et al. (2019) Repeatability and reproducibility of multiparametric magnetic resonance imaging of the liver in children. EASL Int. Liver Congr. Vienna, 10–14 April
164.
Janowski K, Dennis A, Kin S et al. (2017) Non-invasive assessment of paediatric liver disease with multiparametric MRI. AASLD, Liver Meet. Washington, 20–24 Oct.
165.
Jayaswal A, Levick C, Collier J et al. (2020) Liver cT1 decreases following direct acting antiviral therapy in patients with chronic hepatitis C virus – a prospective observational cohort study. PLoS One submitted
166.
Zawada E, Serafin Z, Dybowska D et al. (2019) Monoexponential and biexponential fitting of diffusional magnetic resonance imaging signal analysis for prediction of liver fibrosis severity. J Comput Assist Tomogr 43 (6): 857–862.PubMedCrossRef
167.
Lee C, Peng S, Lee C et al. (2019) Transient elastography correlated with diffusion-weighted magnetic resonance imaging and cholestatic complications. J Formos Med Assoc 118 (11): 1522–1527.PubMedCrossRef
168.
169.
170.
171.
Dhaliwal H, Hoeroldt B, Dube A et al. (2015) Long-term prognostic significance of persisting histological activity despite biochemical remission in autoimmune hepatitis. American Journal Gastroenterol 110 (7): 993–999.CrossRef
172.
Tsiotsios C, Stewart R, Milanesi M et al. (2016) Multiparametric MRI could help track AIH patient response to therapy as alternate to biopsy. Panhellenic Congr. Radiol. Athens, 4–6 November
173.
Arndtz K, Hodson J, Eddowes P et al. (2017) Multi-parametric MRI imaging correlates with clinically meaningful surrogates of disease activity in autoimmune hepatitis. Hepatology 66 188A.
174.
Arndtz K, Shumbayawonda E, Hodson J et al. (2020) Multiparametric MRI imaging, autoimmune hepatitis, and prediction of disease activity. Hepatology. submitted
175.
Arndtz K, Hodson J, Eddowes P et al. (2018) Cross-sectional, prospective, evaluation of the utility of multi-parametric MRI imaging in predicting clinically meaningful outcomes in autoimmune hepatitis. AASLD, Liver Meet. San Fr. 9–13 November
176.
177.
Arndtz K, Hodson J, Eddowes P et al. (2018) Evaluation of multiparametric MRI in comparison with MR elastography in patients evaluated for chronic liver disease. EASL Int. Liver Congr. Paris, 11–15 April
178.
179.
180.
181.
Gomez-Castaneda, E., Janowski, K., Dennis, A., Kazimianec, A., Shumbayawonda, E., Pronicki, M., Grajkowska, W., Wozniak, M., Pawliszak, P., Jurkiewicz, E., Kelly, M., Neubauer, M., Banerjee, R., Socha P (2019) Multi-parametric liver MRI can discriminate between treatment naïve autoimmune hepatitis patients and those under treatment in the paediatric Kids 4 Life cohort. AASLD, Liver Meet. Boston, 10–12 November
182.
Janowski K, Shumbayawonda E, Dennis A et al. (2020) Multiparametric MRI as a non-invasive monitoring tool for children with autoimmune liver disease. Journal Paediatric Gastroenterology & Nutrition. submitted
183.
Janowski K, Dennis A, Kin S et al. (2019) A combined blood and MR imaging risk score for monitoring liver inflammation in paediatric auto-immune hepatitis. EASL Int. Liver Congr. Vienna, 10–14 April
184.
Janowski K, Dennis A, Kin S et al. (2018) MRI as a biomarker for Wilson’s disease in children: early observations from a larger trial into paediatric liver disease. EASL Int. Liver Congr. Paris, 11–15 April
185.
Janowski K, Dennis A, Kin S et al. (2018) MRI as a biomarker for Wilson’s Disease in children: early observations from a larger trial into paediatric liver disease. EASL Int. Liver Congr. Paris, 11–15 April 2018 ESPGHAN, Prague, 10–13 May
186.
Janowski K, Dennis A, Kin S et al. (2019) Multi-parametric MRI as a composite biomarker for classifying liver disease in paediatrics. ECR, Vienna, 27 Feb-3 March
187.
Janowski K, Dennis A, Kin S et al. (2017) Multi-parametric MRI as a biomarker for paediatric Autoimmune Hepatitis: Preliminary observations. CALD Pediatr. Autoimmune Liver Dis. Symp. Cincinatti, 8–9 Oct.
188.
189.
190.
Metadata
Title
Multiparametric MR mapping in clinical decision-making for diffuse liver disease
Authors
Helena B. Thomaides-Brears
Rita Lepe
Rajarshi Banerjee
Carlos Duncker
Publication date
01-11-2020
Publisher
Springer US
Published in
Abdominal Radiology / Issue 11/2020
Print ISSN: 2366-004X
Electronic ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-020-02684-3

Other articles of this Issue 11/2020

Abdominal Radiology 11/2020 Go to the issue

Special Section: Diffuse Liver Disease

Diffusion-weighted imaging and texture analysis: current role for diffuse liver disease

Review

Tumors presenting in both pediatric and adult patients: a case-based review of pathology and imaging features for the radiologist

Hollow Organ GI

Multiple metabolic parameters and visual assessment of 18F-FDG uptake heterogeneity of PET/CT in advanced gastric cancer and primary gastric lymphoma

Special Section: Urothelial Disorders

Commentary: Ureteral pseudodiverticulosis is diagnosable on computed tomography

Special Section: Diffuse Liver Disease

Dual-energy CT in diffuse liver disease: is there a role?

Review

Intrahepatic cholangiocarcinoma: pathogenesis, current staging, and radiological findings
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

Read more

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Pediatric Cardiology Video

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

Cardiopulmonary Comorbidity Video

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Valvular Heart Disease Video

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

Watch now

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits