Artif Intell Med - An intelligent classifier for prognosis of cardiac resynchronization therapy based on speckle-tracking echocardiograms.

Tópicos

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Resumo

RPOSE: Predicting response after cardiac resynchronization therapy (CRT) has been a challenge of cardiologists. About 30% of selected patients based on the standard selection criteria for CRT do not show response after receiving the treatment. This study is aimed to build an intelligent classifier to assist in identifying potential CRT responders by speckle-tracking radial strain based on echocardiograms.METHODS AND MATERIALS: The echocardiograms analyzed were acquired before CRT from 26 patients who have received CRT. Sequential forward selection was performed on the parameters obtained by peak-strain timing and phase space reconstruction on speckle-tracking radial strain to find an optimal set of features for creating intelligent classifiers. Support vector machine (SVM) with a linear, quadratic, and polynominal kernel were tested to build classifiers to identify potential responders and non-responders for CRT by selected features.RESULTS: Based on random sub-sampling validation, the best classification performance is correct rate about 95% with 96-97% sensitivity and 93-94% specificity achieved by applying SVM with a quadratic kernel on a set of 3 parameters. The selected 3 parameters contain both indexes extracted by peak-strain timing and phase space reconstruction.CONCLUSIONS: An intelligent classifier with an averaged correct rate, sensitivity and specificity above 90% for assisting in identifying CRT responders is built by speckle-tracking radial strain. The classifier can be applied to provide objective suggestion for patient selection of CRT.

Resumo Limpo

rpose predict respons cardiac resynchron therapi crt challeng cardiologist select patient base standard select criteria crt show respons receiv treatment studi aim build intellig classifi assist identifi potenti crt respond speckletrack radial strain base echocardiogramsmethod materi echocardiogram analyz acquir crt patient receiv crt sequenti forward select perform paramet obtain peakstrain time phase space reconstruct speckletrack radial strain find optim set featur creat intellig classifi support vector machin svm linear quadrat polynomin kernel test build classifi identifi potenti respond nonrespond crt select featuresresult base random subsampl valid best classif perform correct rate sensit specif achiev appli svm quadrat kernel set paramet select paramet contain index extract peakstrain time phase space reconstructionconclus intellig classifi averag correct rate sensit specif assist identifi crt respond built speckletrack radial strain classifi can appli provid object suggest patient select crt

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