title: Robust semi-automated quantification of cardiac MR perfusion using level set: Application to hypertrophic cardiomyopathy patient data.
abstract: BACKGROUND
  Recently there have been several clinical MR perfusion studies in patients with hypertrophic cardiomyopathy (HCM) who may suffer from myocardial ischemia due to coronary microvascular dysfunction. In these studies, data analysis relied on a manual procedure of tracing epicardial and endocardial borders. The goal of this work is to develop and validate a robust semi-automated analysis method for myocardial perfusion quantification in clinical HCM data.
  
  
  METHODS
  Dynamic multi-slice stress perfusion MRI data were acquired from 18 HCM patients. The proposed semi-automated method required user input of two landmark selections: LV center point and RV insertion point. Automated segmentations of the endocardial and epicardial borders were performed in three short-axis slices using distance regularized level set evolution on RV, LV, and myocardial enhancement frames.
  
  
  RESULTS
  The proposed automated epicardial border detection method resulted in average radial distance errors of 7.5%, 9.5%, and 11.6% in basal, mid, and apical slices, respectively, when compared to manual tracing of the borders as a reference. In linear regression analysis, the highest correlation of myocardial upslope measurements was observed between the manual method and the proposed method in the anterolateral section (r=0.964), and the lowest correlation was observed in the inferoseptal section (r=0.866).
  
  
  CONCLUSIONS
  The proposed semi-automated method for myocardial MR perfusion quantification is feasible in HCM patients who typically show (1) irregular myocardial shape and (2) low image contrast between the myocardium and its surrounding regions due to coronary microvascular disease.
authors.affiliation: Clinical Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Yoon-Chul
authors.initials: YC
authors.lastname: Kim
authors.affiliation: Department of Radiology and HVSI Imaging Center, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Sung Mok
authors.initials: SM
authors.lastname: Kim
authors.affiliation: Department of Radiology and HVSI Imaging Center, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. Electronic address: yhchoe@skku.edu.
authors.forename: Yeon Hyeon
authors.initials: YH
authors.lastname: Choe
mesh_terms: D000328:Adult; D000368:Aged; D002312:Cardiomyopathy, Hypertrophic / Q000000981:diagnostic imaging*; D016208:Databases, Factual; D005260:Female; D006352:Heart Ventricles / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D009206:Myocardium
keywords: Dynamic contrast enhanced imaging; Image segmentation; MRI; Myocardial perfusion