Radiomic analysis of native T1 mapping images discriminates between MYH7 and MYBPC3-related hypertrophic cardiomyopathy

Research output: Contribution to journalArticlepeer-review


  • Fuyao Yang
  • Wentao Liu
  • Jiayu Sun
  • Yuchi Han
  • Dong Li
  • Yanjie Zhu
  • Yucheng Chen

Colleges, School and Institutes

External organisations

  • School of Manufacturing Science and Engineering, Sichuan University, Sichuan 610065
  • Department of Geosciences; Pennsylvania State University; University Park Pennsylvania USA
  • Emory University School of Medicine
  • MRC Health Data Research UK
  • Chinese Academy of Sciences


BACKGROUND: The phenotype via conventional cardiac MRI analysis of MYH7 (β-myosin heavy chain)- and MYBPC3 (β-myosin-binding protein C)-associated hypertrophic cardiomyopathy (HCM) groups is similar. Few studies exist on the genotypic-phenotypic association as assessed by machine learning in HCM patients.

PURPOSE: To explore the phenotypic differences based on radiomics analysis of T1 mapping images between MYH7 and MYBPC3-associated HCM subgroups.

STUDY TYPE: Prospective observational study.

SUBJECTS: In all, 102 HCM patients with pathogenic, or likely pathogenic mutation, in MYH7 (n = 68) or MYBPC3 (n = 34) genes.

FIELD STRENGTH/SEQUENCE: Cardiac MRI was performed at 3.0T with balanced steady-state free precession (bSSFP), phase-sensitive inversion recovery (PSIR) late gadolinium enhancement (LGE), and modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences.

ASSESSMENT: All patients underwent next-generation sequencing and Sanger genetic sequencing. Left ventricular native T1 and LGE were analyzed. One hundred and fifty-seven radiomic features were extracted and modeled using a support vector machine (SVM) combined with principal component analysis (PCA). Each subgroup was randomly split 4:1 (feature selection / test validation).

STATISTICAL TESTS: Mann-Whitney U-tests and Student's t-tests were performed to assess differences between subgroups. A receiver operating characteristic (ROC) curve was used to assess the model's ability to stratify patients based on radiomic features.

RESULTS: There were no significant differences between MYH7- and MYBPC3-associated HCM subgroups based on traditional native T1 values (global, basal, and middle short-axis slice native T1 ; P = 0.760, 0.914, and 0.178, respectively). However, the SVM model combined with PCA achieved an accuracy and area under the curve (AUC) of 92.0% and 0.968 (95% confidence interval [CI]: 0.968-0.971), respectively. For the test validation dataset, the accuracy and AUC were 85.5% and 0.886 (95% CI: 0.881-0.901), respectively.

DATA CONCLUSION: Radiomic analysis of native T1 mapping images may be able to discriminate between MYH7- and MYBPC3-associated HCM patients, exceeding the performance of conventional native T1 values.



Bibliographic note

© 2020 International Society for Magnetic Resonance in Medicine.


Original languageEnglish
JournalJournal of Magnetic Resonance Imaging
Early online date11 Jun 2020
Publication statusE-pub ahead of print - 11 Jun 2020


  • magnetic resonance imaging, cardiomyopathy, hypertrophic, machine learning, support vector machine, human genetics