TY - GEN
T1 - A framework combining multi-sequence MRI for fully automated quantitative analysis of cardiac global and regional functions
AU - Zhuang, Xiahai
AU - Shi, Wenzhe
AU - Duckett, Simon
AU - Wang, Haiyan
AU - Razavi, Reza
AU - Hawkes, David
AU - Rueckert, Daniel
AU - Ourselin, Sebastien
PY - 2011
Y1 - 2011
N2 - In current clinical settings, there are several technological challenges to perform automated functional analysis from cardiac MRI. In this work, we present a framework to automatically segment the heart anatomy, define segments of the left ventricle, and extract myocardial motions for quantitative analysis of cardiac global and regional functions. This framework makes use of the cardiac MRI sequences that are widely available in clinical practice, and improves the performance of the automated processing by combining information from multiple MRI sequences. We employed 20 pathological datasets to evaluate the proposed framework where the automatic analysis was compared with the manual intervention assisted analysis. The results showed high correlation between the two methods for the global function analysis (volume: R2>0.8, ejection fraction:R2=0.88), and for the regional dyssynchrony analysis (wall motion: R2=0.89; thickening:R2=0.81). We also found that the automated method could fully include apical and basal volume, resulting in consistent overestimation of the left ventricle volume (∼40mL, P<0.05) and small underestimation of ejection fraction (-0.024, P<0.001).
AB - In current clinical settings, there are several technological challenges to perform automated functional analysis from cardiac MRI. In this work, we present a framework to automatically segment the heart anatomy, define segments of the left ventricle, and extract myocardial motions for quantitative analysis of cardiac global and regional functions. This framework makes use of the cardiac MRI sequences that are widely available in clinical practice, and improves the performance of the automated processing by combining information from multiple MRI sequences. We employed 20 pathological datasets to evaluate the proposed framework where the automatic analysis was compared with the manual intervention assisted analysis. The results showed high correlation between the two methods for the global function analysis (volume: R2>0.8, ejection fraction:R2=0.88), and for the regional dyssynchrony analysis (wall motion: R2=0.89; thickening:R2=0.81). We also found that the automated method could fully include apical and basal volume, resulting in consistent overestimation of the left ventricle volume (∼40mL, P<0.05) and small underestimation of ejection fraction (-0.024, P<0.001).
UR - http://www.scopus.com/inward/record.url?scp=79957654683&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21028-0_47
DO - 10.1007/978-3-642-21028-0_47
M3 - Conference contribution
AN - SCOPUS:79957654683
SN - 9783642210273
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 367
EP - 374
BT - Functional Imaging and Modeling of the Heart - 6th International Conference, FIMH 2011, Proceedings
T2 - 6th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2011
Y2 - 25 May 2011 through 27 May 2011
ER -