Literature DB >> 21695484

Three-dimensional analysis of interventricular septal curvature from cardiac magnetic resonance images for the evaluation of patients with pulmonary hypertension.

M Agustina Sciancalepore1, Francesco Maffessanti, Amit R Patel, Mardi Gomberg-Maitland, Sonal Chandra, Benjamin H Freed, Enrico G Caiani, Roberto M Lang, Victor Mor-Avi.   

Abstract

Although abnormal septal motion is a well-known sign of increased pulmonary arterial pressures, it is not routinely used to quantify the severity of pulmonary hypertension (PH). This determination relies on invasive measurements or Doppler echocardiographic estimation of right ventricular (RV) pressures, which is not always feasible or accurate in patients with PH. We hypothesized that dynamic 3D analysis of septal curvature from cardiac magnetic resonance (CMR) images may reveal differences between patients with different degrees of PH. Forty-four patients (14 controls; 30 PH patients who underwent right heart catheterization) were studied using CMR and echocardiography. CMR imaging was performed using Philips 1.5T scanner with a phased-array cardiac coil, in a retrospectively gated steady-state free precession cine mode at 30 frames per cardiac cycle. Patients were divided into 3 subgroups according to pulmonary arterial pressure. CMR images were used to reconstruct dynamic 3D left ventricular endocardial surfaces, which were analyzed to calculate septal curvature throughout the cardiac cycle. 3D curvature analysis was feasible in 88% patients. Septal curvature showed different temporal patterns in different groups. Curvature values progressively decreased with increasing severity of PH, and correlated well with invasive pressures (r-values 0.78-0.79), pulmonary vascular resistance (r = 0.83) and Doppler-derived RV peak-systolic pressure (r = 0.75). 3D analysis of septal curvature from CMR images may become a useful component in the CMR examination in patients with known or suspected PH.

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Year:  2011        PMID: 21695484     DOI: 10.1007/s10554-011-9913-3

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.357


  39 in total

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Authors:  Benjamin H Freed; Amit R Patel; Roberto M Lang
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2.  Machine learning based automated dynamic quantification of left heart chamber volumes.

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Journal:  Int J Cardiovasc Imaging       Date:  2013-04       Impact factor: 2.357

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Authors:  Marius Berman; Deepa Gopalan; Linda Sharples; Nick Screaton; Caroline Maccan; Karen Sheares; Joanna Pepke-Zaba; John Dunning; Steven Tsui; David P Jenkins
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7.  Regional shape, global function and mechanics in right ventricular volume and pressure overload conditions: a three-dimensional echocardiography study.

Authors:  Jurate Bidviene; Denisa Muraru; Francesco Maffessanti; Egle Ereminiene; Attila Kovács; Bálint Lakatos; Jolanta-Justina Vaskelyte; Remigijus Zaliunas; Elena Surkova; Gianfranco Parati; Luigi P Badano
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Authors:  Akane Matsumura; Ayako Shigeta; Hajime Kasai; Hajime Yokota; Jiro Terada; Keiko Yamamoto; Toshihiko Sugiura; Takuma Matsumura; Seiichiro Sakao; Nobuhiro Tanabe; Koichiro Tatsumi
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9.  [Characteristics of Ventricular Function in Pulmonary Hypertension Patients 
with Different Shape of Interventricular Septum:
Preliminary Study with Cardiac Magnetic Resonance Imaging].

Authors:  Dan Wang; Zhang Zhang; Fan Yang; Le Zhang; Zhenwen Yang; Wen Ren; Tielian Yu; Dong Li
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Authors:  Paul J Critser; Nara S Higano; Sean M Lang; Paul S Kingma; Robert J Fleck; Russel Hirsch; Michael D Taylor; Jason C Woods
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  10 in total

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