title: Automated Classification of Severity in Cardiac Dyssynchrony Merging Clinical Data and Mechanical Descriptors.
abstract: Cardiac resynchronization therapy (CRT) improves functional classification among patients with left ventricle malfunction and ventricular electric conduction disorders. However, a high percentage of subjects under CRT (20%-30%) do not show any improvement. Nonetheless the presence of mechanical contraction dyssynchrony in ventricles has been proposed as an indicator of CRT response. This work proposes an automated classification model of severity in ventricular contraction dyssynchrony. The model includes clinical data such as left ventricular ejection fraction (LVEF), QRS and P-R intervals, and the 3 most significant factors extracted from the factor analysis of dynamic structures applied to a set of equilibrium radionuclide angiography images representing the mechanical behavior of cardiac contraction. A control group of 33 normal volunteers (28 ± 5 years, LVEF of 59.7% ± 5.8%) and a HF group of 42 subjects (53.12 ± 15.05 years, LVEF < 35%) were studied. The proposed classifiers had hit rates of 90%, 50%, and 80% to distinguish between absent, mild, and moderate-severe interventricular dyssynchrony, respectively. For intraventricular dyssynchrony, hit rates of 100%, 50%, and 90% were observed distinguishing between absent, mild, and moderate-severe, respectively. These results seem promising in using this automated method for clinical follow-up of patients undergoing CRT.
authors.affiliation: Bioengineering Department, Instituto Tecnológico y de Estudios Superiores de Monterrey, Campus Ciudad de México, Mexico City, Mexico.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Santos-Díaz
authors.affiliation: Neuroimaging Laboratory, Electrical Engineering Department, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, Mexico.
authors.forename: Raquel
authors.initials: R
authors.lastname: Valdés-Cristerna
authors.affiliation: Centro Medico ABC (American British Cowdray Hospital), Mexico City, Mexico.
authors.forename: Enrique
authors.initials: E
authors.lastname: Vallejo
authors.affiliation: Nuclear Cardiology Department, Instituto Nacional de Cardiología "Ignacio Chávez", Mexico City, Mexico.
authors.forename: Salvador
authors.initials: S
authors.lastname: Hernández
authors.affiliation: Engineering in Biomedical Systems Department, Faculty of Engineering, Universidad Nacional Autónoma de México, Mexico City, Mexico.
authors.forename: Luis
authors.identifier: 0000-0002-7390-0814
authors.initials: L
authors.lastname: Jiménez-Ángeles
mesh_terms: D000328:Adult; D000465:Algorithms; D000792:Angiography; D001145:Arrhythmias, Cardiac / Q000503:physiopathology; D002138:Calibration; D058406:Cardiac Resynchronization Therapy / Q000379:methods; D001330:Electronic Data Processing; D005260:Female; D064368:Healthy Volunteers; D006321:Heart / Q000000981:diagnostic imaging* / Q000503:physiopathology; D006329:Heart Conduction System; D006333:Heart Failure / Q000000981:diagnostic imaging* / Q000628:therapy; D006352:Heart Ventricles / Q000503:physiopathology; D006801:Humans; D008297:Male; D008490:Medical Informatics / Q000379:methods*; D009200:Myocardial Contraction; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D016896:Treatment Outcome; D018487:Ventricular Dysfunction, Left / Q000628:therapy; D016277:Ventricular Function, Left