title: Support vector analysis of color-Doppler images: a new approach for estimating indices of left ventricular function.
abstract: Reliable noninvasive estimators of global left ventricular (LV) chamber function remain unavailable. We have previously demonstrated a potential relationship between color-Doppler M-mode (CDMM) images and two basic indices of LV function: peak-systolic elastance (Emax) and the time-constant of LV relaxation (tau). Thus, we hypothesized that these two indices could be estimated noninvasively by adequate postprocessing of CDMM recordings. A semiparametric regression (SR) version of support vector machine (SVM) is here proposed for building a blind model, capable of analyzing CDMM images automatically, as well as complementary clinical information. Simultaneous invasive and Doppler tracings were obtained in nine mini-pigs in a high-fidelity experimental setup. The model was developed using a test and validation leave-one-out design. Reasonably acceptable prediction accuracy was obtained for both Emax (intraclass correlation coefficient Ric, = 0.81) and tau (Ric, = 0.61). For the first time, a quantitative, noninvasive estimation of cardiovascular indices is addressed by processing Doppler-echocardiography recordings using a learning-from-samples method.
authors.affiliation: Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Spain.
authors.forename: J L
authors.initials: JL
authors.lastname: Rojo-Alvarez
authors.forename: J
authors.initials: J
authors.lastname: Bermejo
authors.forename: V M
authors.initials: VM
authors.lastname: Juárez-Caballero
authors.forename: R
authors.initials: R
authors.lastname: Yotti
authors.forename: C
authors.initials: C
authors.lastname: Cortina
authors.forename: M A
authors.initials: MA
authors.lastname: García-Fernández
authors.forename: J C
authors.initials: JC
authors.lastname: Antoranz
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D018618:Echocardiography, Doppler, Color / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D017202:Myocardial Ischemia / Q000150:complications / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013318:Stroke Volume; D013552:Swine; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging* / Q000209:etiology