Share：
Share this content in WeChat
X
[Chinese] [PDF] 5 1
• Review •
Progress in non-invasive elastography techniques for the diagnosis and assessment of metabolic dysfunction-associated steatotic liver disease
MIAO Miao  ZHAO Jian 

DOI:10.12015/issn.1674-8034.2025.11.034.


[Abstract] In recent years, the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) has been steadily increasing, making it a leading cause of end-stage liver disease. Early detection and accurate staging of liver fibrosis are crucial for preventing MASLD progression and its complications. However, liver biopsy, the current gold standard, has significant limitations, highlighting the importance of non-invasive diagnostic techniques as essential alternatives. Existing reviews often focus solely on a single imaging modality or, while covering multiple imaging techniques, fail to include artificial intelligence applications. Moreover, most are based on the outdated NAFLD nomenclature, making it difficult to comprehensively reflect current research progress. Based on the MASLD nomenclature and clinical guidelines, this article systematically reviews the latest advances in magnetic resonance elastography (MRE), shear-wave elastography (SWE), and vibration-controlled transient elastography (VCTE) for MASLD assessment, while also exploring the potential of artificial intelligence in improving diagnostic efficiency. The aim is to enhance early detection of liver fibrosis and provide more precise imaging support for MASLD diagnosis and treatment.
[Keywords] magnetic resonance elastography；metabolic dysfunction-associated steatotic liver disease；liver fibrosis；non-invasive tests；artificial intelligence

MIAO Miao   ZHAO Jian*  

Department of Radiology, Hebei Medical University Third Hospital, Shijiazhuang 050051, China

Corresponding author: ZHAO J, E-mail: 37400408@hebmu.edu.cn

Conflicts of interest   None.

Received  2025-07-04
Accepted  2025-11-10
DOI: 10.12015/issn.1674-8034.2025.11.034
DOI:10.12015/issn.1674-8034.2025.11.034.

[1]
RINELLA M E, LAZARUS J V, RATZIU V, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature[J]. Hepatology, 2023, 78(6): 1966-1986. DOI: 10.1097/HEP.0000000000000520.
[2]
CHEW N W S, NG C H, TAN D J H, et al. The global burden of metabolic disease: Data from 2000 to 2019[J/OL]. Cell Metab, 2023, 35(3): 414-428.e3 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/36889281/. DOI: 10.1016/j.cmet.2023.02.003.
[3]
YOUNOSSI Z M, GOLABI P, PAIK J M, et al. The global epidemiology of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH): a systematic review[J]. Hepatology, 2023, 77(4): 1335-1347. DOI: 10.1097/HEP.0000000000000004.
[4]
LE M H, LE D M, BAEZ T C, et al. Global incidence of non-alcoholic fatty liver disease: A systematic review and meta-analysis of 63 studies and 1, 201, 807 persons[J]. J Hepatol, 2023, 79(2): 287-295. DOI: 10.1016/j.jhep.2023.03.040.
[5]
ZHANG J, WANG H W, WANG Q B, et al. EEF1A2 identified as a hub gene associated with the severity of metabolic dysfunction-associated steatotic liver disease[J]. Mamm Genome, 2025, 36(1): 93-105. DOI: 10.1007/s00335-024-10078-9.
[6]
DAWOD S, BROWN K. Non-invasive testing in metabolic dysfunction-associated steatotic liver disease[J]. Front Med (Lausanne), 2024, 11: 1499013 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/39606621/. DOI: 10.3389/fmed.2024.1499013.
[7]
KOUVARI M, VALENZUELA-VALLEJO L, GUATIBONZA-GARCIA V, et al. Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive steatotic liver disease indexes: Results from a large multi-center study[J/OL]. Metabolism, 2023, 147: 155666 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/37527759/. DOI: 10.1016/j.metabol.2023.155666.
[8]
TINCOPA M A, LOOMBA R. Non-invasive diagnosis and monitoring of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis[J]. Lancet Gastroenterol Hepatol, 2023, 8(7): 660-670. DOI: 10.1016/S2468-1253(23)00066-3.
[9]
HUDSON D, AFZAAL T, BUALBANAT H, et al. Modernizing metabolic dysfunction-associated steatotic liver disease diagnostics: the progressive shift from liver biopsy to noninvasive techniques[J/OL]. Therap Adv Gastroenterol, 2024, 17: 17562848241276334 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/39553445/. DOI: 10.1177/17562848241276334.
[10]
TACKE F, HORN P, WONG V W, et al. EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD)[J]. J Hepatol, 2024, 81(3): 492-542. DOI: 10.1016/j.jhep.2024.04.031.
[11]
STERLING R K, PATEL K, DUARTE-ROJO A, et al. AASLD Practice Guideline on blood-based noninvasive liver disease assessment of hepatic fibrosis and steatosis[J]. Hepatology, 2025, 81(1): 321-357. DOI: 10.1097/HEP.0000000000000845.
[12]
STERLING R K, DUARTE-ROJO A, PATEL K, et al. AASLD Practice Guideline on imaging-based noninvasive liver disease assessment of hepatic fibrosis and steatosis[J]. Hepatology, 2025, 81(2): 672-724. DOI: 10.1097/HEP.0000000000000843.
[13]
INDRE M G, LEUCUTA D C, LUPSOR-PLATON M, et al. Diagnostic accuracy of 2D-SWE ultrasound for liver fibrosis assessment in MASLD: a multilevel random effects model meta-analysis[J]. Hepatology, 2025, 82(2): 454-469. DOI: 10.1097/HEP.0000000000001190.
[14]
SCHAAPMAN J J, TUSHUIZEN M E, COENRAAD M J, et al. Multiparametric MRI in patients with nonalcoholic fatty liver disease[J]. J Magn Reson Imaging, 2021, 53(6): 1623-1631. DOI: 10.1002/jmri.27292.
[15]
ABDELHAMEED F, KITE C, LAGOJDA L, et al. Non-invasive scores and serum biomarkers for fatty liver in the era of metabolic dysfunction-associated steatotic liver disease (MASLD): A comprehensive review from NAFLD to MAFLD and MASLD[J]. Curr Obes Rep, 2024, 13(3): 510-531. DOI: 10.1007/s13679-024-00574-z.
[16]
BUZZETTI E, PINZANI M, TSOCHATZIS E A. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD)[J]. Metabolism, 2016, 65(8): 1038-1048. DOI: 10.1016/j.metabol.2015.12.012.
[17]
VIDAL-CEVALLOS P, SORROZA-MARTÍNEZ A P, CHÁVEZ-TAPIA N C, et al. The relationship between pathogenesis and possible treatments for the MASLD-cirrhosis spectrum[J/OL]. Int J Mol Sci, 2024, 25(8): 4397 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/38673981/. DOI: 10.3390/ijms25084397.
[18]
BANSAL S K, BANSAL M B. Pathogenesis of MASLD and MASH–role of insulin resistance and lipotoxicity[J]. Aliment Pharmacol Ther, 2024, 59(S1): S10-S22. DOI: 10.1111/apt.17930.
[19]
XU G X, WEI S, YU C, et al. Activation of kupffer cells in NAFLD and NASH: mechanisms and therapeutic interventions[J/OL]. Front Cell Dev Biol, 2023, 11: 1199519 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/37261074/. DOI: 10.3389/fcell.2023.1199519.
[20]
HORN P, TACKE F. Metabolic reprogramming in liver fibrosis[J]. Cell Metab, 2024, 36(7): 1439-1455. DOI: 10.1016/j.cmet.2024.05.003.
[21]
CAPUTO V, TARANTINO G, SANTINI S J, et al. The role of epigenetic control of mitochondrial (dys)function in MASLD onset and progression[J/OL]. Nutrients, 2023, 15(22): 4757 [2025-05-05].https://pubmed.ncbi.nlm.nih.gov/38004151/. DOI: 10.3390/nu15224757.
[22]
PORTINCASA P, KHALIL M, MAHDI L, et al. Metabolic dysfunction-associated steatotic liver disease: from pathogenesis to current therapeutic options[J/OL]. Int J Mol Sci, 2024, 25(11): 5640 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/38891828/. DOI: 10.3390/ijms25115640.
[23]
KAYLAN K B, PAUL S. NAFLD No more: a review of current guidelines in the diagnosis and evaluation of metabolic dysfunction-associated steatotic liver disease (MASLD)[J/OL]. Curr Diab Rep, 2024, 25(1): 5 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/39535566/. DOI: 10.1007/s11892-024-01558-y.
[24]
SIGRIST R M S, LIAU J, KAFFAS A EL, et al. Ultrasound elastography: review of techniques and clinical applications[J]. Theranostics, 2017, 7(5): 1303-1329. DOI: 10.7150/thno.18650.
[25]
ZONCAPÈ M, LIGUORI A, TSOCHATZIS E A. Non-invasive testing and risk-stratification in patients with MASLD[J]. Eur J Intern Med, 2024, 122: 11-19. DOI: 10.1016/j.ejim.2024.01.013.
[26]
KOBAYASHI T, NAKATSUKA T, SATO M, et al. Diagnostic performance of two-dimensional shear wave elastography and attenuation imaging for fibrosis and steatosis assessment in chronic liver disease[J]. J Med Ultrason (2001), 2025, 52(1): 95-103. DOI: 10.1007/s10396-024-01473-5.
[27]
JIANG H, QIN C, XU Y M. Feasibility of shear wave elastography for assessing steatosis in early-stage non-alcoholic fatty liver disease[J/OL]. PLoS One, 2025, 20(5): e0324637 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/40440252/. DOI: 10.1371/journal.pone.0324637.
[28]
OH H. A non-invasive test that enables longitudinal monitoring of chronic liver disease: VCTE versus 2D-SWE[J]. Korean J Intern Med, 2022, 37(2): 281-282. DOI: 10.3904/kjim.2022.065.
[29]
BIRIS A I, KARAMATZANIS I, BIRI D, et al. Non-invasive ultrasound diagnostic techniques for steatotic liver disease and focal liver lesions: 2D, Dopplercolour, 3D, two-dimensional shear wave elastography (2D-SWE), and ultrasound-guided attenuation parameter (UGAP)[J/OL]. Cureus, 2024, 16(10): e72087 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/39440161/. DOI: 10.7759/cureus.72087.
[30]
KIM M N. Noninvasive imaging test to assess liver fibrosis: vibration-controlled transient elastography[J]. Korean J Gastroenterol, 2024, 84(5): 201-205. DOI: 10.4166/kjg.2024.120.
[31]
SHEN M, LEE A N, LEFKOWITCH J H, et al. Vibration-controlled transient elastography for assessment of liver fibrosis at a USA academic medical center[J]. J Clin Transl Hepatol, 2022, 10(2): 197-206. DOI: 10.14218/JCTH.2021.00188.
[32]
CHON Y E, JIN Y J, AN J, et al. Optimal cut-offs of vibration-controlled transient elastography and magnetic resonance elastography in diagnosing advanced liver fibrosis in patients with nonalcoholic fatty liver disease: A systematic review and meta-analysis[J]. Clin Mol Hepatol, 2024, 30(Suppl): S117-S133. DOI: 10.3350/cmh.2024.0392.
[33]
SHARPTON S R, TAMAKI N, BETTENCOURT R, et al. Diagnostic accuracy of two-dimensional shear wave elastography and transient elastography in nonalcoholic fatty liver disease[J/OL]. Therap Adv Gastroenterol, 2021, 14: 17562848211050436 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/34646360/. DOI: 10.1177/17562848211050436.
[34]
LEE H W, LEE J S, KIM M N, et al. Risk stratification by noninvasive tests in patients with metabolic dysfunction-associated steatotic liver disease[J]. Clin Mol Hepatol, 2025, 31(3): 1018-1031. DOI: 10.3350/cmh.2024.1183.
[35]
GAWRIEH S, VILAR-GOMEZ E, WILSON L A, et al. Increases and decreases in liver stiffness measurement are independently associated with the risk of liver-related events in NAFLD[J]. J Hepatol, 2024, 81(4): 600-608. DOI: 10.1016/j.jhep.2024.05.008.
[36]
IMAJO K, HONDA Y, KOBAYASHI T, et al. Direct comparison of US and MR elastography for staging liver fibrosis in patients with nonalcoholic fatty liver disease[J/OL]. Clin Gastroenterol Hepatol, 2022, 20(4): 908-917.e11 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/33340780/. DOI: 10.1016/j.cgh.2020.12.016.
[37]
LIN H P, LEE H W, YIP T C, et al. Vibration-controlled transient elastography scores to predict liver-related events in steatotic liver disease[J]. JAMA, 2024, 331(15): 1287-1297. DOI: 10.1001/jama.2024.1447.
[38]
MOURA CUNHA G, FAN B, NAVIN P J, et al. Interpretation, reporting, and clinical applications of liver MR elastography[J/OL]. Radiology, 2024, 310(3): e231220 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/38470236/. DOI: 10.1148/radiol.231220.
[39]
MEYER T, CASTELEIN J, SCHATTENFROH J, et al. Magnetic resonance elastography in a nutshell: tomographic imaging of soft tissue viscoelasticity for detecting and staging disease with a focus on inflammation[J]. Prog Nucl Magn Reson Spectrosc, 2024, 144/145: 1-14. DOI: 10.1016/j.pnmrs.2024.05.002.
[40]
REN H, YANG D W, XU H, et al. The staging of nonalcoholic fatty liver disease fibrosis: A comparative study of MR elastography and the quantitative DCE-MRI exchange model[J/OL]. Heliyon, 2024, 10(2): e24558 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/38312594/. DOI: 10.1016/j.heliyon.2024.e24558.
[41]
JANG W, JO S, SONG J S, et al. Comparison of diffusion-weighted imaging and MR elastography in staging liver fibrosis: a meta-analysis[J]. Abdom Radiol (NY), 2021, 46(8): 3889-3907. DOI: 10.1007/s00261-021-03055-2.
[42]
LIANG Y Z, LI D W. Magnetic resonance elastography in staging liver fibrosis in non-alcoholic fatty liver disease: a pooled analysis of the diagnostic accuracy[J/OL]. BMC Gastroenterol, 2020, 20(1): 89 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/32252641/. DOI: 10.1186/s12876-020-01234-x.
[43]
WEI X D, QI S, WEI X H, et al. Inflammation activity affects liver stiffness measurement by magnetic resonance elastography in MASLD[J]. Dig Liver Dis, 2024, 56(10): 1715-1720. DOI: 10.1016/j.dld.2024.04.031.
[44]
LIANG J X, AMPUERO J, NIU H, et al. An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography[J]. J Hepatol, 2023, 79(3): 592-604. DOI: 10.1016/j.jhep.2023.04.025.
[45]
LARA ROMERO C, LIANG J-X, FERNÁNDEZ LIZARANZAZU I, et al. Liver stiffness accuracy by MR elastography in histologically proven non-alcoholic fatty liver disease patients: a Spanish cohort[J/OL]. Rev Esp Enferm Dig, 2023, 115(4): 162-167. DOI: 10.17235/reed.2022.8777/2022
[46]
GIDENER T, YIN M, DIERKHISING R A, et al. Magnetic resonance elastography for prediction of long-term progression and outcome in chronic liver disease: A retrospective study[J]. Hepatology, 2022, 75(2): 379-390. DOI: 10.1002/hep.32151.
[47]
KOBAYASHI T, IWAKI M, NOGAMI A, et al. Prediction of outcomes in patients with metabolic dysfunction-associated steatotic liver disease based on initial measurements and subsequent changes in magnetic resonance elastography[J]. J Gastroenterol, 2024, 59(1): 56-65. DOI: 10.1007/s00535-023-02049-9.
[48]
HAN M A T, VIPANI A, NOUREDDIN N, et al. MR elastography-based liver fibrosis correlates with liver events in nonalcoholic fatty liver patients: A multicenter study[J]. Liver Int, 2020, 40(9): 2242-2251. DOI: 10.1111/liv.14593.
[49]
GIDENER T, AHMED O T, LARSON J J, et al. Liver stiffness by magnetic resonance elastography predicts future cirrhosis, decompensation, and death in NAFLD[J/OL]. Clin Gastroenterol Hepatol, 2021, 19(9): 1915-1924.e6 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/33010409/. DOI: 10.1016/j.cgh.2020.09.044.
[50]
NIIKURA T, IMAJO K, OZAKI A, et al. Coronary artery disease is more severe in patients with non-alcoholic steatohepatitis than fatty liver[J/OL]. Diagnostics (Basel), 2020, 10(3): 129 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/32111021/. DOI: 10.3390/diagnostics10030129.
[51]
HENSON J B, SIMON T G, KAPLAN A, et al. Advanced fibrosis is associated with incident cardiovascular disease in patients with non-alcoholic fatty liver disease[J]. Aliment Pharmacol Ther, 2020, 51(7): 728-736. DOI: 10.1111/apt.15660.
[52]
TAMAKI N, KUROSAKI M, TAKAHASHI Y, et al. Liver fibrosis and fatty liver as independent risk factors for cardiovascular disease[J]. J Gastroenterol Hepatol, 2021, 36(10): 2960-2966. DOI: 10.1111/jgh.15589.
[53]
HIGUCHI M, TAMAKI N, KUROSAKI M, et al. Longitudinal association of magnetic resonance elastography-associated liver stiffness with complications and mortality[J]. Aliment Pharmacol Ther, 2022, 55(3): 292-301. DOI: 10.1111/apt.16745.
[54]
ZERUNIAN M, MASCI B, CARUSO D, et al. Liver magnetic resonance elastography: focus on methodology, technique, and feasibility[J/OL]. Diagnostics (Basel), 2024, 14(4): 379 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/38396418/. DOI: 10.3390/diagnostics14040379.
[55]
KIM D W, KIM S Y, YOON H M, et al. Comparison of technical failure of MR elastography for measuring liver stiffness between gradient-recalled echo and spin-echo echo-planar imaging: a systematic review and meta-analysis[J]. J Magn Reson Imaging, 2020, 51(4): 1086-1102. DOI: 10.1002/jmri.26918.
[56]
GILL H E, LISANTI C J, SCHWOPE R B, et al. Technical success rate of MR elastography in a population without known liver disease[J]. Abdom Radiol (NY), 2021, 46(2): 590-596. DOI: 10.1007/s00261-020-02652-x.
[57]
SGIER D, STOCKER D, JÜNGST C, et al. Feasibility and performance of spin-echo EPI MR elastography at 3 Tesla for staging hepatic fibrosis in the presence of hepatic iron overload[J]. Abdom Radiol (NY), 2024, 49(11): 3871-3882. DOI: 10.1007/s00261-023-04160-0.
[58]
BHUIYAN E H, OZKAYA E, KENNEDY P, et al. Magnetic resonance elastography for noninvasive detection of liver fibrosis: is there an added value of 3D acquisition [J]. Abdom Radiol (NY), 2023, 48(11): 3420-3429. DOI: 10.1007/s00261-023-04036-3.
[59]
LI J H, OBRZUT M, CHEN J, et al. Free-breathing hepatic 2D magnetic resonance elastography[J]. Magn Reson Med, 2025, 93(6): 2434-2443. DOI: 10.1002/mrm.30483.
[60]
ONAR M A, NURAL M S, DEVECI A, et al. Evaluation of liver fibrosis using diffusion-weighted virtual magnetic resonance elastography and ultrasound elastography[J/OL]. Abdom Radiol (NY), 2025 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/40500481/. DOI: 10.1007/s00261-025-05043-2.
[61]
WANG X Y, LIU B, WU C L, et al. Shear wave trajectory detection in ultra-fast M-mode images for liver fibrosis assessment: a deep learning-based line detection approach[J/OL]. Ultrasonics, 2024, 142: 107358 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/38901149/. DOI: 10.1016/j.ultras.2024.107358.
[62]
HUANG X Z, LI Y H, YUAN S S, et al. Shear wave elastography-based deep learning model for prognosis of patients with acutely decompensated cirrhosis[J]. J Clin Ultrasound, 2023, 51(9): 1568-1578. DOI: 10.1002/jcu.23577.
[63]
XUE L Y, JIANG Z Y, FU T T, et al. Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis[J]. Eur Radiol, 2020, 30(5): 2973-2983. DOI: 10.1007/s00330-019-06595-w.
[64]
WANG K, LU X, ZHOU H, et al. Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study[J]. Gut, 2019, 68(4): 729-741. DOI: 10.1136/gutjnl-2018-316204.
[65]
OZKAYA E, NIEVES-VAZQUEZ H A, YUCE M, et al. Automated liver magnetic resonance elastography quality control and liver stiffness measurement using deep learning[J]. Abdom Radiol (NY), 2025, 50(9): 4100-4109. DOI: 10.1007/s00261-025-04883-2.
[66]
CUNHA G M, DELGADO T I, MIDDLETON M S, et al. Automated CNN-based analysis versus manual analysis for MR elastography in nonalcoholic fatty liver disease: intermethod agreement and fibrosis stage discriminative performance[J]. AJR Am J Roentgenol, 2022, 219(2): 224-232. DOI: 10.2214/AJR.21.27135.
[67]
JAITNER N, LUDWIG J, MEYER T, et al. Automated liver and spleen segmentation for MR elastography maps using U-Nets[J/OL]. Sci Rep, 2025, 15(1): 10762 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/40155744/. DOI: 10.1038/s41598-025-95157-w.
[68]
NIEVES-VAZQUEZ H A, OZKAYA E, MEINHOLD W, et al. Deep learning-enabled automated quality control for liver MR elastography: initial results[J]. J Magn Reson Imag, 2025, 61(2): 985-994. DOI: 10.1002/jmri.29490.
[69]
SIM K C, KIM M J, CHO Y, et al. Diagnostic feasibility of magnetic resonance elastography radiomics analysis for the assessment of hepatic fibrosis in patients with nonalcoholic fatty liver disease[J]. J Comput Assist Tomogr, 2022, 46(4): 505-513. DOI: 10.1097/RCT.0000000000001308.
[70]
GOTTA J, GRUENEWALD L D, RESCHKE P, et al. Noninvasive grading of liver fibrosis based on texture analysis from MRI-derived radiomics[J/OL]. NMR Biomed, 2025, 38(1): e5301 [2025-05-05]. https://pubmed.ncbi.nlm.nih.gov/39702901/. DOI: 10.1002/nbm.5301.
[71]
HECTORS S J, KENNEDY P, HUANG K H, et al. Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI[J]. Eur Radiol, 2021, 31(6): 3805-3814. DOI: 10.1007/s00330-020-07475-4.

PREV Advances in precision medicine for dilated cardiomyopathy: Focusing on genetics and cardiac magnetic resonance imaging
NEXT Research progress in the application of diffusion-weighted imaging in hematological malignancies
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn