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Review
Research progress in the application of cardiac magnetic resonance imaging in dilated cardiomyopathy
ZHANG Linxin  CHEN Ying  QI Haicheng  XING Yan 

Cite this article as: ZHANG L X, CHEN Y, QI H C, et al. Research progress in the application of cardiac magnetic resonance imaging in dilated cardiomyopathy[J]. Chin J Magn Reson Imaging, 2025, 16(3): 150-155. DOI:10.12015/issn.1674-8034.2025.03.025.


[Abstract] Dilated cardiomyopathy (DCM), a leading cause of heart failure and sudden cardiac death, exhibits a 10-year survival rate below 60%, underscoring the critical need for precise assessment of myocardial injury and risk stratification to improve prognosis. Cardiac magnetic resonance (CMR), leveraging its multimodal tissue characterization capabilities, has emerged as the gold standard for evaluating cardiac structure and function. Although artificial intelligence has significantly enhanced CMR by optimizing image quality, analytical efficiency, and diagnostic accuracy, current research lacks robust multimodal data integration and systematic clinical validation, limiting its comprehensive application in DCM precision management. This review systematically examines representative advancements in CMR technology and its clinical applications in DCM, aiming to provide timely and evidence-based insights for clinical practice and future research.
[Keywords] dilated cardiomyopathy;cardiac magnetic resonance;artificial intelligence;cine;late gadolinium enhancement;tissue characterization imaging

ZHANG Linxin   CHEN Ying   QI Haicheng   XING Yan*  

Imaging Center, First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, China

Corresponding author: XING Y, E-mail: xingyanzwb@sina.com

Conflicts of interest   None.

Received  2025-01-09
Accepted  2025-03-10
DOI: 10.12015/issn.1674-8034.2025.03.025
Cite this article as: ZHANG L X, CHEN Y, QI H C, et al. Research progress in the application of cardiac magnetic resonance imaging in dilated cardiomyopathy[J]. Chin J Magn Reson Imaging, 2025, 16(3): 150-155. DOI:10.12015/issn.1674-8034.2025.03.025.

[1]
LIU M B, HE X Y, YANG X H, et al. Interpretation of report on cardiovascular health and diseases in China 2023[J]. Chin Gen Pract, 2025, 28(1): 20-38. DOI: 10.12114/j.issn.1007-9572.2024.0293.
[2]
ARBELO E, PROTONOTARIOS A, GIMENO J R, et al. 2023 ESC guidelines for the management of cardiomyopathies[J]. Eur Heart J, 2023, 44(37): 3503-3626. DOI: 10.1093/eurheartj/ehad194.
[3]
HARDING D, CHONG M H A, LAHOTI N, et al. Dilated cardiomyopathy and chronic cardiac inflammation: Pathogenesis, diagnosis and therapy[J]. J Intern Med, 2023, 293(1): 23-47. DOI: 10.1111/joim.13556.
[4]
MBBS A S, MD J A, et al. Quantitative cardiac MRI[J]. J Magn Reson Imag, 2020, 51(3): 693-711. DOI: 10.1002/jmri.26789.
[5]
MCDONAGH T A, METRA M, ADAMO M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure[J]. Eur Heart J, 2021, 42(36): 3599-3726. DOI: 10.1093/eurheartj/ehab368.
[6]
PETRYKA-MAZURKIEWICZ J, KRYCZKA K, MAZURKIEWICZ Ł, et al. Cardiovascular magnetic resonance in peripartum cardiomyopathy: comparison with idiopathic dilated cardiomyopathy[J/OL]. Diagnostics, 2021, 11(10): 1752 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/34679449/. DOI: 10.3390/diagnostics11101752.
[7]
DENG J, ZHOU L T, LI Y Y, et al. Integration of cine-cardiac magnetic resonance radiomics and machine learning for differentiating ischemic and dilated cardiomyopathy[J]. Acad Radiol, 2024, 31(7): 2704-2714. DOI: 10.1016/j.acra.2024.03.032.
[8]
LI X, XU Y W, CHEN X Y, et al. Prognostic value of enhanced cine cardiac MRI-based radiomics in dilated cardiomyopathy[J/OL]. Int J Cardiol, 2025, 418: 132617 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/39370047/. DOI: 10.1016/j.ijcard.2024.132617.
[9]
RAJIAH P S, FRANÇOIS C J, LEINER T. Cardiac MRI: state of the art[J/OL]. Radiology, 2023, 307(3): e223008 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/37039684/. DOI: 10.1148/radiol.223008.
[10]
HU H F, PAN N, FRANGI A F. Fully Automatic initialization and segmentation of left and right ventricles for large-scale cardiac MRI using a deeply supervised network and 3D-ASM[J/OL]. Comput Methods Programs Biomed, 2023, 240: 107679 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/37364366/. DOI: 10.1016/j.cmpb.2023.107679.
[11]
CURTIS A D, CHENG H M. Primer and historical review on rapid cardiac CINE MRI[J]. J Magn Reson Imaging, 2022, 55(2): 373-388. DOI: 10.1002/jmri.27436.
[12]
HAUPTMANN A, ARRIDGE S, LUCKA F, et al. Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease[J]. Magn Reson Med, 2019, 81(2): 1143-1156. DOI: 10.1002/mrm.27480.
[13]
HAJI-VALIZADEH H, GUO R, KUCUKSEYMEN S, et al. Highly accelerated free-breathing real-time phase contrast cardiovascular MRI via complex-difference deep learning[J]. Magn Reson Med, 2021, 86(2): 804-819. DOI: 10.1002/mrm.28750.
[14]
YANG Q, FENG C J. New technology of cardiac MRI and its application progress[J]. Int J Med Radiol, 2023, 46(6): 629-633. DOI: 10.19300/j.2023.s21103.
[15]
EDALATI M, ZHENG Y, WATKINS M P, et al. Implementation and prospective clinical validation of AI-based planning and shimming techniques in cardiac MRI[J]. Med Phys, 2022, 49(1): 129-143. DOI: 10.1002/mp.15327.
[16]
MORALES M A, CIRILLO J, NAKATA K, et al. Comparison of DeepStrain and feature tracking for cardiac MRI strain analysis[J]. J Magn Reson Imaging, 2023, 57(5): 1507-1515. DOI: 10.1002/jmri.28374.
[17]
SMISETH O A, RIDER O, CVIJIC M, et al. Myocardial strain imaging[J]. JACC Cardiovasc Imag, 2025, 18(3): 340-381. DOI: 10.1016/j.jcmg.2024.07.011.
[18]
LIAN X Q, ZHANG H Y, ZHAO S H, et al. From medical image to clinical diagnosis and treatment: Advances in cardiovascular magnetic resonance in 2023[J]. Chin J Magn Reson Imag, 2024, 15(7): 184-190, 215. DOI: 10.12015/issn.1674-8034.2024.07.031.
[19]
AZUMA M, KATO S, KODAMA S, et al. Relationship between cardiac magnetic resonance derived extracellular volume fraction and myocardial strain in patients with non-ischemic dilated cardiomyopathy[J]. Eur Heart J, 2020, 41(Supplement_2): ehaa946.0239. DOI: 10.1093/ehjci/ehaa946.0239.
[20]
LI G X, ZHANG Z, GAO Y Y, et al. Age- and sex-specific reference values of biventricular strain and strain rate derived from a large cohort of healthy Chinese adults: a cardiovascular magnetic resonance feature tracking study[J/OL]. J Cardiovasc Magn Reson, 2022, 24(1): 63 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/36404299/. DOI: 10.1186/s12968-022-00881-1.
[21]
KAMMERLANDER A A, DONÀ C, NITSCHE C, et al. Feature tracking of global longitudinal strain by using cardiovascular MRI improves risk stratification in heart failure with preserved ejection fraction[J]. Radiology, 2020, 296(2): 290-298. DOI: 10.1148/radiol.2020200195.
[22]
ROMANO S, JUDD R M, KIM R J, et al. Feature-tracking global longitudinal strain predicts death in a multicenter population of patients with ischemic and nonischemic dilated cardiomyopathy incremental to ejection fraction and late gadolinium enhancement[J]. JACC Cardiovasc Imaging, 2018, 11(10): 1419-1429. DOI: 10.1016/j.jcmg.2017.10.024.
[23]
LIU T, GAO Y F, WANG H, et al. Association between right ventricular strain and outcomes in patients with dilated cardiomyopathy[J]. Heart, 2021, 107(15): 1233-1239. DOI: 10.1136/heartjnl-2020-317949.
[24]
XIANG X R, SONG Y Y, ZHAO K K, et al. Incremental prognostic value of left atrial and biventricular feature tracking in dilated cardiomyopathy: a long-term study[J/OL]. J Cardiovasc Magn Reson, 2023, 25(1): 76 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/38057892/. DOI: 10.1186/s12968-023-00967-4.
[25]
GAO Y Y, PU C L, LI Q, et al. Assessment of right atrial function measured with cardiac MRI feature tracking for predicting outcomes in patients with dilated cardiomyopathy[J/OL]. Radiology, 2024, 310(3): e232388 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/38470238/. DOI: 10.1148/radiol.232388.
[26]
LI Y J, XU Y W, TANG S Q, et al. Left atrial function predicts outcome in dilated cardiomyopathy: fast long-axis strain analysis derived from MRI[J]. Radiology, 2022, 302(1): 72-81. DOI: 10.1148/radiol.2021210801.
[27]
RAAFS A G, VOS J L, HENKENS M T H M, et al. Left atrial strain has superior prognostic value to ventricular function and delayed-enhancement in dilated cardiomyopathy[J]. JACC Cardiovasc Imaging, 2022, 15(6): 1015-1026. DOI: 10.1016/j.jcmg.2022.01.016.
[28]
CAU R, PISU F, PINTUS A, et al. Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach[J]. Eur Radiol, 2024, 34(9): 5691-5704. DOI: 10.1007/s00330-024-10640-8.
[29]
PUJADAS E R, RAISI-ESTABRAGH Z, SZABO L, et al. Prediction of incident cardiovascular events using machine learning and CMR radiomics[J]. Eur Radiol, 2023, 33(5): 3488-3500. DOI: 10.1007/s00330-022-09323-z.
[30]
WANG Y J, YANG K, WEN Y, et al. Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging[J]. Nat Med, 2024, 30(5): 1471-1480. DOI: 10.1038/s41591-024-02971-2.
[31]
CHENG T, CHEN K, WANG Y J, et al. Progress of late gadolinium enhancement cardiac of magnetic resonance imaging[J]. Int J Med Radiol, 2022, 45(6): 686-689. DOI: 10.19300/j.2022.Z19740.
[32]
KIM H W, REHWALD W G, JENISTA E R, et al. Dark-blood delayed enhancement cardiac magnetic resonance of myocardial infarction[J]. JACC Cardiovasc Imaging, 2018, 11(12): 1758-1769. DOI: 10.1016/j.jcmg.2017.09.021.
[33]
SI D Y, WU Y F, XIAO J J, et al. Three-dimensional high-resolution dark-blood late gadolinium enhancement imaging for improved atrial scar evaluation[J/OL]. Radiology, 2023, 307(5): e222032 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/37278633/. DOI: 10.1148/radiol.222032.
[34]
WENDELL D, JENISTA E, KIM H W, et al. Assessment of papillary muscle infarction with dark-blood delayed enhancement cardiac MRI in canines and humans[J]. Radiology, 2022, 305(2): 329-338. DOI: 10.1148/radiol.220251.
[35]
XIE C, ZHANG R, MENSINK S, et al. Automated inversion time selection for late gadolinium–enhanced cardiac magnetic resonance imaging[J]. Eur Radiol, 2024, 34(9): 5816-5828. DOI: 10.1007/s00330-024-10630-w.
[36]
MUSCOGIURI G, MARTINI C, GATTI M, et al. Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm[J/OL]. Int J Cardiol, 2021, 343: 164-170 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/34517017/. DOI: 10.1016/j.ijcard.2021.09.012.
[37]
ZHANG Q, BURRAGE M K, LUKASCHUK E, et al. Toward replacing late gadolinium enhancement with artificial intelligence virtual native enhancement for gadolinium-free cardiovascular magnetic resonance tissue characterization in hypertrophic cardiomyopathy[J]. Circulation, 2021, 144(8): 589-599. DOI: 10.1161/CIRCULATIONAHA.121.054432.
[38]
QI H K, QIAN P F, TANG L L, et al. Predicting late gadolinium enhancement of acute myocardial infarction in contrast-free cardiac cine MRI using deep generative learning[J/OL]. Circ Cardiovasc Imaging, 2024, 17(9): e016786 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/39253820/. DOI: 10.1161/CIRCIMAGING.124.016786.
[39]
ZHANG Y C, MENG Y D, ZHENG Y L. Automatically segment the left atrium and scars from LGE-MRIs using a boundary-focused nnU-net[EB/OL]. 2023: 2304.14071. https://arxiv.org/abs/2304.14071v1.
[40]
CHA M J, HONG Y J, PARK C H, et al. Utilities and limitations of cardiac magnetic resonance imaging in dilated cardiomyopathy[J]. Korean J Radiol, 2023, 24(12): 1200-1220. DOI: 10.3348/kjr.2023.0531.
[41]
RAMAN S V, MARKL M, PATEL A R, et al. 30-minute CMR for common clinical indications: a Society for Cardiovascular Magnetic Resonance white paper[J/OL]. J Cardiovasc Magn Reson, 2022, 24(1): 13 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/35232470/. DOI: 10.1186/s12968-022-00844-6.
[42]
HEYMANS S, LAKDAWALA N K, TSCHÖPE C, et al. Dilated cardiomyopathy: causes, mechanisms, and current and future treatment approaches[J]. Lancet, 2023, 402(10406): 998-1011. DOI: 10.1016/S0140-6736(23)01241-2.
[43]
HALLIDAY B P, JOHN BAKSI A, GULATI A, et al. Outcome in dilated cardiomyopathy related to the extent, location, and pattern of late gadolinium enhancement[J]. JACC Cardiovasc Imaging, 2019, 12(8Pt 2): 1645-1655. DOI: 10.1016/j.jcmg.2018.07.015.
[44]
EICHHORN C, KOECKERLING D, REDDY R K, et al. Risk stratification in nonischemic dilated cardiomyopathy using CMR imaging: a systematic review and meta-analysis[J]. JAMA, 2024, 332(18): 1535-1550. DOI: 10.1001/jama.2024.13946.
[45]
BEHERA D R, V K A K, K K N N, et al. Prognostic value of late gadolinium enhancement in cardiac MRI of non-ischemic dilated cardiomyopathy patients[J]. Indian Heart J, 2020, 72(5): 362-368. DOI: 10.1016/j.ihj.2020.06.011.
[46]
DI MARCO A, BROWN P F, BRADLEY J, et al. Improved risk stratification for ventricular arrhythmias and sudden death in patients with nonischemic dilated cardiomyopathy[J]. J Am Coll Cardiol, 2021, 77(23): 2890-2905. DOI: 10.1016/j.jacc.2021.04.030.
[47]
GUO R, WEINGÄRTNER S, ŠIURYTĖ P, et al. Emerging techniques in cardiac magnetic resonance imaging[J]. J Magn Reson Imaging, 2022, 55(4): 1043-1059. DOI: 10.1002/jmri.27848.
[48]
HUANG C Y, SUN L W, LIANG D, et al. RS-MOCO: a deep learning-based topology-preserving image registration method for cardiac T1 mapping[J/OL]. Comput Biol Med, 2025, 184: 109442 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/39608033/. DOI: 10.1016/j.compbiomed.2024.109442.
[49]
CHEN W S, DOEBLIN P, AL-TABATABAEE S, et al. Synthetic extracellular volume in cardiac magnetic resonance without blood sampling: a reliable tool to replace conventional extracellular volume[J/OL]. Circ Cardiovasc Imaging, 2022, 15(4): e013745 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/35360924/. DOI: 10.1161/CIRCIMAGING.121.013745.
[50]
ABASIJIANG·ADILI, LI S, QI H C, et al. Application and research progress of magnetic resonance parameter quantitative technique in myocardial involvement diseases[J]. Chin J Magn Reson Imag, 2023, 14(2):179-185. DOI: 10.12015/issn.1674-8034.2023.02.032.
[51]
HAMILTON J I, JIANG Y, MA D, et al. Investigating and reducing the effects of confounding factors for robust T1 and T2 mapping with cardiac MR fingerprinting[J/OL]. Magn Reson Imag, 2018, 53: 40-51 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/29964183/. DOI: 10.1016/j.mri.2018.06.018.
[52]
MA L, WU Y, DUAN L, et al. Normal values of T1, T2, and ECV in 1.5T cardiovascular magnetic resonance scanning in health adults[J]. Chin J Gen Pract, 2024, 22(6): 1022-1027. DOI: 10.16766/j.cnki.issn.1674-4152.003558.
[53]
XU Z Q, LI W H, WANG J Q, et al. Reference ranges of myocardial T1 and T2 mapping in healthy Chinese adults: a multicenter 3T cardiovascular magnetic resonance study[J/OL]. J Cardiovasc Magn Reson, 2023, 25(1): 64 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/37968645/. DOI: 10.1186/s12968-023-00974-5.
[54]
PU C L, HU X, LV S Y, et al. Identification of fibrosis in hypertrophic cardiomyopathy: a radiomic study on cardiac magnetic resonance cine imaging[J]. Eur Radiol, 2023, 33(4): 2301-2311. DOI: 10.1007/s00330-022-09217-0.
[55]
THAVENDIRANATHAN P, ZHANG L L, ZAFAR A, et al. Myocardial T1 and T2 mapping by magnetic resonance in patients with immune checkpoint inhibitor-associated myocarditis[J]. J Am Coll Cardiol, 2021, 77(12): 1503-1516. DOI: 10.1016/j.jacc.2021.01.050.
[56]
ANTONOPOULOS A S, XINTARAKOU A, PROTONOTARIOS A, et al. Imagenetics for precision medicine in dilated cardiomyopathy[J/OL]. Circ Genom Precis Med, 2024, 17(2): e004301 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/38415367/. DOI: 10.1161/CIRCGEN.123.004301.
[57]
XU Y W, LI Y J, WANG S Q, et al. Prognostic value of mid-term cardiovascular magnetic resonance follow-up in patients with non-ischemic dilated cardiomyopathy: a prospective cohort study[J/OL]. J Cardiovasc Magn Reson, 2024, 26(1): 101002 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/38237899/. DOI: 10.1016/j.jocmr.2024.101002.
[58]
LI Y J, XU Y W, LI W H, et al. Cardiac MRI to predict sudden cardiac death risk in dilated cardiomyopathy[J/OL]. Radiology, 2023, 307(3): e222552 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/36916890/. DOI: 10.1148/radiol.222552.
[59]
ZHANG J, XU Y W, LI W H, et al. The predictive value of myocardial native T1 mapping radiomics in dilated cardiomyopathy: a study in a Chinese population[J]. J Magn Reson Imaging, 2023, 58(3): 772-779. DOI: 10.1002/jmri.28527.
[60]
FENT G J, GARG P, FOLEY J R J, et al. Synthetic myocardial extracellular volume fraction[J]. JACC Cardiovasc Imaging, 2017, 10(11): 1402-1404. DOI: 10.1016/j.jcmg.2016.12.007.
[61]
YOUN J C, HONG Y J, LEE H J, et al. Contrast-enhanced T1 mapping-based extracellular volume fraction independently predicts clinical outcome in patients with non-ischemic dilated cardiomyopathy: a prospective cohort study[J]. Eur Radiol, 2017, 27(9): 3924-3933. DOI: 10.1007/s00330-017-4817-9.
[62]
ZHUANG B Y, SIRAJUDDIN A, WANG S L, et al. Prognostic value of T1 mapping and extracellular volume fraction in cardiovascular disease: a systematic review and meta-analysis[J]. Heart Fail Rev, 2018, 23(5): 723-731. DOI: 10.1007/s10741-018-9718-8.
[63]
GAO Y, WANG H P, LIU M X, et al. Early detection of myocardial fibrosis in cardiomyopathy in the absence of late enhancement: role of T1 mapping and extracellular volume analysis[J]. Eur Radiol, 2023, 33(3): 1982-1991. DOI: 10.1007/s00330-022-09147-x.
[64]
FEHRMANN A, TREUTLEIN M, RUDOLPH T, et al. Myocardial T1 and T2 mapping in severe aortic stenosis: Potential novel insights into the pathophysiology of myocardial remodelling[J/OL]. Eur J Radiol, 2018, 107: 76-83 [2025-01-08]. https://pubmed.ncbi.nlm.nih.gov/30292277/. DOI: 10.1016/j.ejrad.2018.08.016.
[65]
WARNICA W, AL-ARNAWOOT A, STANIMIROVIC A, et al. Clinical impact of cardiac MRI T1 and T2 parametric mapping in patients with suspected cardiomyopathy[J]. Radiology, 2022, 305(2): 319-326. DOI: 10.1148/radiol.220067.

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