Predictive cardiac motion modeling and correction with partial least squares regression.
Respiratory-induced cardiac deformation is a major problem for high-resolution cardiac imaging. This paper presents a new technique for predictive cardiac motion modeling and correction, which uses partial least squares regression to extract intrinsic relationships between three-dimensional (3-D) cardiac deformation due to respiration and multiple one-dimensional real-time measurable surface intensity traces at chest or abdomen. Despite the fact that these surface intensity traces can be strongly coupled with each other but poorly correlated with respiratory-induced cardiac deformation, we demonstrate how they can be used to accurately predict cardiac motion through the extraction of latent variables of both the input and output of the model. The proposed method allows cross-modality reconstruction of patient specific models for dense motion field prediction, which after initial modeling can be used for real-time prospective motion tracking or correction. Detailed numerical issues related to the technique are discussed and the effectiveness of the motion and deformation modeling is validated with 3-D magnetic resonance data sets acquired from ten asymptomatic subjects covering the entire respiratory range.
Ablitt
Nicholas A
NA
Royal Society/Wolfson Foundation Medical Image Computing Laboratory, Department of Computing, Imperial College London, London SW7 2BZ, U.K.
Gao
Jianxin
J
Keegan
Jennifer
J
Stegger
Lars
L
Firmin
David N
DN
Yang
Guang-Zhong
GZ
D000465:Algorithms; D003198:Computer Simulation; D006321:Heart / Q000033:anatomy & histology* / Q000502:physiology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008955:Models, Cardiovascular; D009068:Movement / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique