Share：
Share this content in WeChat
X
[Chinese][PDF]7713
• Special Focus •
Heterogeneous parameters of non-contrast enhanced CMR T1/T2 mapping in detecting cardiac involvement in neuromuscular diseases
HUANG Lu  ZHAO Peijun  TANG Dazhong  RAN Lingping  XIA Liming 

Cite this article as: Huang L, Zhao PJ, Tang DZ, et al. Heterogeneous parameters of non-contrast enhanced CMR T1/T2 mapping in detecting cardiac involvement in neuromuscular diseases[J]. Chin J Magn Reson Imaging, 2022, 13(12): 6-12. DOI:10.12015/issn.1674-8034.2022.12.002.


[Abstract] Objective To investigate the diagnostic value of cardiac magnetic resonance (CMR) native T1/T2 mapping parameters to detect cardiac involvement in neuromuscular diseases (NMDs).Materials and Methods This study retrospectively analyzed 60 cases of NMD patients, while 20 age and gender-matched healthy controls were enrolled in this study. NMDs patients with abnormal electrocardiograph (ECG) or positive late gadolinium enhancement (LGE) or reduced left ventricle ejection fraction (LVEF)/right ventricle ejection fraction (RVEF) were categorized as the cardiac involvement subgroup. All subjects underwent a CMR exam on a 3.0 T MR scanner, including short-axis steady-state free precession (SSFP) cine, native T1/T2 mapping and LGE sequences, covering the whole heart. Histogram obtained by T1/T2 mapping and six parameters were calculated, including mean, median, standard deviation (SD), minimum, maximum and entropy were calculated from the T1/T2 mapping. All quantitative data were compared by analysis of variance (ANOVA) or Kruskal-Wallis test among three groups. Multivariate logistics regression analysis was used to establish a CMR multi-parametric model, and receiver operator characteristic (ROC) curve was used to evaluate the diagnostic performance of quantitative parameters as well as multi-parametric model of CMR T1/T2 mapping in detecting NMD cardiac involvement.Results Forty-one NMDs patients were categorized as the cardiac involvement subgroup, and the remaining 19 were categorized as the non-involvement subgroup. Compared to the controls, T1 mean, median, SD, maximum and entropy, as well as T2 mean, median, maximum and entropy of the cardiac involvement subgroup all elevated significantly (P＜0.05 for all), while in the non-involvement subgroup, only native T1 mean and median increased (P＜0.05 for both). The native T1/T2 SD and entropy as well as T1 maximum, were all significantly higher in the cardiac involvement subgroup compared to then non-involvement subgroup (P＜0.05 for all). A multi-variate regression model including all heterogeneous parameters exhibited a diagnostic accuracy of 83.0% (area under ROC curve: 0.81, 95% confidence interval: 0.72-0.94) to detect cardiac involvement in NMDs patients.Conclusions Heterogeneous parameters of non-contrast enhanced CMR T1/T2 mapping can detect cardiac involvement in patients with NMD, and the multi-parameter model had the highest diagnostic efficiency. The multi-heterogeneity parameter model provides a new method for the detection of cardiac involvement in patients with NMD. It has great potential in early screening of cardiac involvement in patients with NMD and has a wide clinical application prospect.
[Keywords] neuromuscular diseases；cardiac involvement；magnetic resonance imaging；cardiac magnetic resonance；longitudinal relaxation time；transverse relaxation time；heterogeneity

HUANG Lu   ZHAO Peijun   TANG Dazhong   RAN Lingping   XIA Liming*  

Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

Xia LM, E-mail: lmxia@tjh.tjmu.edu.cn

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81873889); Hubei Provincial Science and Technology Program Youth Fund (No. 2021CFB060).
Received  2022-08-02
Accepted  2022-11-28
DOI: 10.12015/issn.1674-8034.2022.12.002
Cite this article as: Huang L, Zhao PJ, Tang DZ, et al. Heterogeneous parameters of non-contrast enhanced CMR T1/T2 mapping in detecting cardiac involvement in neuromuscular diseases[J]. Chin J Magn Reson Imaging, 2022, 13(12): 6-12. DOI:10.12015/issn.1674-8034.2022.12.002.

[1]
Morrison BM. Neuromuscular diseases[J]. Semin Neurol, 2016, 36(5): 409-418. DOI: 10.1055/s-0036-1586263.
[2]
Dangouloff T, Boemer F, Servais L. Newborn screening of neuromuscular diseases[J]. Neuromuscul Disord, 2021, 31(10): 1070-1080. DOI: 10.1016/j.nmd.2021.07.008.
[3]
Thompson R, Spendiff S, Roos A, et al. Advances in the diagnosis of inherited neuromuscular diseases and implications for therapy development[J]. Lancet Neurol, 2020, 19(6): 522-532. DOI: 10.1016/S1474-4422(20)30028-4.
[4]
Megarbane A, Bizzari S, Deepthi A, et al. A 20-year Clinical and Genetic Neuromuscular Cohort Analysis in Lebanon: An International Effort[J]. J Neuromuscul Dis, 2022, 9(1): 193-210. DOI: 10.3233/JND-210652.
[5]
Feingold B, Mahle WT, Auerbach S, et al. Management of Cardiac Involvement Associated With Neuromuscular Diseases: A Scientific Statement From the American Heart Association[J/OL]. Circulation, 2017, 136(13): e200-e231 [2022-07-30]. https://www.ahajournals.org/doi/10.1161/CIR.0000000000000526?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed. DOI: 10.1161/CIR.0000000000000526.
[6]
Schmid J, Beer M, Berghold A, et al. Cardiac involvement in a cross-sectional cohort of myotonic dystrophies and other skeletal myopathies[J]. ESC Heart Fail, 2020, 7(4): 1900-1908. DOI: 10.1002/ehf2.12763.
[7]
Leiner T, Bogaert J, Friedrich MG, et al. SCMR Position Paper (2020) on clinical indications for cardiovascular magnetic resonance[J/OL]. J Cardiovasc Magn Reson, 2020, 22(1): 76 [2022-07-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649060/. DOI: 10.1186/s12968-020-00682-4.
[8]
Diederichsen LP. Cardiovascular involvement in myositis[J]. Curr Opin Rheumatol, 2017, 29(6): 598-603. DOI: 10.1097/BOR.0000000000000442.
[9]
Opinc AH, Makowski MA, Łukasik ZM, et al. Cardiovascular complications in patients with idiopathic inflammatory myopathies: does heart matter in idiopathic inflammatory myopathies?[J]. Heart Fail Rev, 2021, 26(1): 111-125. DOI: 10.1007/s10741-019-09909-8.
[10]
Blaszczyk E, Gröschel J, Schulz-Menger J. Role of CMR Imaging in Diagnostics and Evaluation of Cardiac Involvement in Muscle Dystrophies[J]. Curr Heart Fail Rep, 2021, 18(4): 211-224. DOI: 10.1007/s11897-021-00521-2.
[11]
Khoo T, Stokes MB, Teo K, et al. Cardiac Involvement in Idiopathic Inflammatory Myopathy Detected By Cardiac Magnetic Resonance Imaging[J]. Clin Rheumatol, 2019, 38(12): 3471-3476. DOI: 10.1007/s10067-019-04678-z.
[12]
Feng C, Liu W, Sun X, et al. Myocardial involvement characteristics by cardiac MR imaging in patients with polymyositis and dermatomyositis[J]. Rheumatology (Oxford) , 2022, 61(2): 572-580. DOI: 10.1093/rheumatology/keab271.
[13]
Yu L, Sun J, Sun J, et al. Early detection of myocardial involvement by T 1 mapping of cardiac MRI in idiopathic inflammatory myopathy[J]. J Magn Reson Imaging, 2018, 48(2): 415-422. DOI: 10.1002/jmri.25945.
[14]
Xu Y, Sun J, Wan K, et al. Multiparametric cardiovascular magnetic resonance characteristics and dynamic changes in myocardial and skeletal muscles in idiopathic inflammatory cardiomyopathy[J/OL]. J Cardiovasc Magn Reson, 2020, 22(1): 22 [2022-07-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7147024/. DOI: 10.1186/s12968-020-00616-0.
[15]
He J, Zhao SH, Lu MJ. Cardiac magnetic resonance feature tracking technique and its progress[J]. Chin J Magn Reson Imaging, 2020, 11(6): 469-473. DOI: 10.12015/issn.1674-8034.2020.06.018.
[16]
Baessler B, Luecke C, Lurz J, et al. Cardiac MRI and Texture Analysis of Myocardial T1 and T2 Maps in Myocarditis with Acute versus Chronic Symptoms of Heart Failure[J]. Radiology, 2019, 292(3): 608-607. DOI: 10.1148/radiol.2019190101.
[17]
Neisius U, El-Rewaidy H, Kucukseymen S, et al. Texture signatures of native myocardial T1 as novel imaging markers for identification of hypertrophic cardiomyopathy patients without scar[J]. J Magn Reson Imaging, 2020, 52(3): 906-919. DOI: 10.1002/jmri.27048.
[18]
Parker MJS, Oldroyd A, Roberts ME, et al. The performance of the European League Against Rheumatism/American College of Rheumatology idiopathic inflammatory myopathies classification criteria in an expert-defined 10 year incident cohort[J]. Rheumatology (Oxford), 2019, 58(3): 468-475. DOI: 10.1093/rheumatology/key343.
[19]
Serrano C, Montero-Sánchez A, Escudero LM, et al. Neuromuscular disease classification system[J/OL]. J Biomed Opt, 2013, 18(6): 066017 [2022-07-30]. https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-18/issue-06/066017/Neuromuscular-disease-classification-system/10.1117/1.JBO.18.6.066017.full?SSO=1. DOI: 10.1117/1.JBO.18.6.066017.
[20]
Fairley JL, Wicks I, Peters S, et al. Defining cardiac involvement in idiopathic inflammatory myopathies: a systematic review[J]. Rheumatology (Oxford), 2022, 61(1): 103-120. DOI: 10.1093/rheumatology/keab573.
[21]
Zhong Y, Bai W, Xie Q, et al. Cardiac function in patients with polymyositis or dermatomyositis: a three-dimensional speckle-tracking echocardiography study[J]. Int J Cardiovasc Imaging, 2017, 34(5): 683-693. DOI: 10.1007/s10554-017-1278-9.
[22]
Sun J, Yin G, Xu Y, et al. Phenotyping of myocardial involvement by cardiac magnetic resonance in idiopathic inflammatory myopathies[J]. Eur Radiol, 2021, 31(7): 5077-5086. DOI: 10.1007/s00330-020-07448-7.
[23]
Wu C, Wu R, Shi R, et al. Histogram Analysis of Native T1 Mapping and Its Relationship to Left Ventricular Late Gadolinium Enhancement, Hypertrophy, and Segmental Myocardial Mechanics in Patients With Hypertrophic Cardiomyopathy[J]. J Magn Reson Imaging, 2019, 49(3): 668-677. DOI: 10.1002/jmri.26272.
[24]
Baessler B, Luecke C, Lurz J, et al. Cardiac MRI Texture Analysis of T1 and T2 Maps in Patients with Infarctlike Acute Myocarditis[J]. Radiology, 2018, 289(2): 357-365. DOI: 10.1148/radiol.2018180411.
[25]
Huang L, Tao Q, Zhao P, et al. Using multi-parametric quantitative MRI to screen for cardiac involvement in patients with idiopathic inflammatory myopathy[J/OL]. Sci Rep, 2022, 12: 9819 [2022-07-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198094/. DOI: 10.1038/s41598-022-13858-y.
[26]
Neisius U, El-Rewaidy H, Nakamori S, et al. Radiomic Analysis of Myocardial Native T1 Imaging Discriminates Between Hypertensive Heart Disease and Hypertrophic Cardiomyopathy[J]. JACC Cardiovasc Imaging, 2019, 12(10): 1946-1954. DOI: 10.1016/j.jcmg.2018.11.024.
[27]
Wu X, Tang LL, Hu YT, et al. Research progress of MRI radiomics in cardiac diseases[J]. Chin J Magn Reson Imaging, 2021, 12(11): 113-116. DOI: 10.12015/issn.1674-8034.2021.11.028.
[28]
Lilleker JB, Diederichsen ACP, Jacobsen S, et al. Using serum troponins to screen for cardiac involvement and assess disease activity in the idiopathic inflammatory myopathies[J]. Rheumatology (Oxford), 2018, 57(6): 1041-1046. DOI: 10.1093/rheumatology/key031.

PREV Development of MRI of cardiomyopathy in the last 40 years: More precise and intelligent
NEXT Characteristics of the left ventricular myocardial strain in Fabry disease and its value in differential diagnosis of hypertrophic cardiomyopathy
  


LINK


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