Modeling and simulation of right ventricular volume measurement system during right heart catheterization

Toumpaniaris, P; Skalkidis, I; Nikolakopoulos, I; Kelekis, N; Filippatos, G; Koutsouris, D

dc.contributor.author	Toumpaniaris, P	en
dc.contributor.author	Skalkidis, I	en
dc.contributor.author	Nikolakopoulos, I	en
dc.contributor.author	Kelekis, N	en
dc.contributor.author	Filippatos, G	en
dc.contributor.author	Koutsouris, D	en
dc.date.accessioned	2014-03-01T02:11:27Z
dc.date.available	2014-03-01T02:11:27Z
dc.date.issued	2012	en
dc.identifier.issn	01485598	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/29903
dc.subject	Neural network	en
dc.subject	Right catheterization	en
dc.subject	Right ventricular volume	en
dc.subject.other	article	en
dc.subject.other	artificial neural network	en
dc.subject.other	cardiovascular magnetic resonance	en
dc.subject.other	computer program	en
dc.subject.other	critically ill patient	en
dc.subject.other	diastole	en
dc.subject.other	geometry	en
dc.subject.other	heart catheter	en
dc.subject.other	heart catheterization	en
dc.subject.other	heart cycle	en
dc.subject.other	heart right ventricle	en
dc.subject.other	heart right ventricle enddiastolic volume	en
dc.subject.other	heart right ventricle endsystolic volume	en
dc.subject.other	heart right ventricle volume	en
dc.subject.other	hemodynamic monitoring	en
dc.subject.other	human	en
dc.subject.other	measurement	en
dc.subject.other	model	en
dc.subject.other	nuclear magnetic resonance imaging	en
dc.subject.other	nuclear magnetic resonance scanner	en
dc.subject.other	pulmonary artery catheter	en
dc.subject.other	sensor	en
dc.subject.other	systole	en
dc.subject.other	ultrasound	en
dc.subject.other	ultrasound transducer	en
dc.subject.other	biological model	en
dc.subject.other	computer simulation	en
dc.subject.other	heart right ventricle function	en
dc.subject.other	heart stroke volume	en
dc.subject.other	physiology	en
dc.subject.other	reproducibility	en
dc.subject.other	Swan Ganz catheter	en
dc.subject.other	Catheterization, Swan-Ganz	en
dc.subject.other	Computer Simulation	en
dc.subject.other	Humans	en
dc.subject.other	Models, Cardiovascular	en
dc.subject.other	Neural Networks (Computer)	en
dc.subject.other	Reproducibility of Results	en
dc.subject.other	Stroke Volume	en
dc.subject.other	Ventricular Function, Right	en
dc.title	Modeling and simulation of right ventricular volume measurement system during right heart catheterization	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s10916-010-9525-9	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s10916-010-9525-9	en
heal.publicationDate	2012	en
heal.abstract	Haemodynamic monitoring is necessary for the effective management of critically ill cardiac patients. Pulmonary artery catheterization has been used for monitoring the circulation, for measurement of intracardiac pressures and to estimate preload and afterload. However, pressures may not be accurate reflection of the circulation and simultaneous measurement of volumes would improve patient treatment. However, measurement of cardiac volumes especially of the right ventricle is difficult in everyday clinical practice In this work we propose the use of pulmonary artery catheter (PAC) with ultrasonic sensors built on it, to calculate the right ventricular end-diastolic (RVEDV) and end-systolic volume (RVESV). This is achieved by using the Ultrasonic (US) beam, to measure the distances between the transducers on the catheter and the RV walls. These distances, will be used as an input to a Volume calculating algorithm, which finally provides the RVEDV and RVESV, using a Neural Network (NN). For that reason, we have used cardiac Magnetic Resonance Imaging (MRI) and have modeled the catheter and the US transducers, to get as input the distances to the surface of the cavity. With these distances, and the known cardiac volumes (calculated using MR images) we trained and validated a NN for volume calculation. The results show that the algorithm accurately calculates the RVEDV. For the RVESV, greater deviations are observed between values calculated with our algorithm and cardiac MRI. © Springer Science+Business Media, LLC 2010.	en
heal.journalName	Journal of Medical Systems	en
dc.identifier.doi	10.1007/s10916-010-9525-9	en
dc.identifier.volume	36	en
dc.identifier.issue	2	en
dc.identifier.spage	615	en
dc.identifier.epage	620	en