Prospective Prediction of Thin-Cap Fibroatheromas from Baseline Virtual Histology Intravascular Ultrasound Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F15%3A10314395" target="_blank" >RIV/00216208:11110/15:10314395 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00064165:_____/15:10314395

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-24571-3_72" target="_blank" >http://dx.doi.org/10.1007/978-3-319-24571-3_72</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-24571-3_72" target="_blank" >10.1007/978-3-319-24571-3_72</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prospective Prediction of Thin-Cap Fibroatheromas from Baseline Virtual Histology Intravascular Ultrasound Data

Popis výsledku v původním jazyce

Thin-cap fibroatheroma (TCFA) is particularly prone to rupture, which may result in myocardial infarction and death. Virtual histology intravascular ultrasound (VH-IVUS) provides quantitative information about plaque composition and enables TCFA identification. However, prospective prediction of future development of TCFA has not been previously possible. The aim of our study was to determine whether subsequent development of TCFA can be predicted from baseline VH-IVUS data. Corresponding VH-IVUS imagesof baseline and follow-up examinations were identified by a highly automated approach to register IVUS pullback pairs from 24 patients (2,331 image pairs). Next, 20 location-specific VH-based and IVUS-based features including plaque phenotype and morphology, and 15 systemic patient-specific features were extracted and ranked using a support vector machine recursive feature elimination (SVM RFE) technique. SVM was applied to assess the prediction power of different feature sets, by addin

Název v anglickém jazyce

Prospective Prediction of Thin-Cap Fibroatheromas from Baseline Virtual Histology Intravascular Ultrasound Data

Popis výsledku anglicky

Thin-cap fibroatheroma (TCFA) is particularly prone to rupture, which may result in myocardial infarction and death. Virtual histology intravascular ultrasound (VH-IVUS) provides quantitative information about plaque composition and enables TCFA identification. However, prospective prediction of future development of TCFA has not been previously possible. The aim of our study was to determine whether subsequent development of TCFA can be predicted from baseline VH-IVUS data. Corresponding VH-IVUS imagesof baseline and follow-up examinations were identified by a highly automated approach to register IVUS pullback pairs from 24 patients (2,331 image pairs). Next, 20 location-specific VH-based and IVUS-based features including plaque phenotype and morphology, and 15 systemic patient-specific features were extracted and ranked using a support vector machine recursive feature elimination (SVM RFE) technique. SVM was applied to assess the prediction power of different feature sets, by addin

Druh

D - Stať ve sborníku

CEP obor

FA - Kardiovaskulární nemoci včetně kardiochirurgie

OECD FORD obor

—

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015

ISBN

978-3-319-24570-6

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

8

Strana od-do

603-610

Název nakladatele

Springer International Publishing

Místo vydání

Cham

Místo konání akce

Munich

Datum konání akce

5. 10. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000366206800072