title: A direct PCA-based approach for real-time description of physiological organ deformations.
abstract: Dynamic magnetic resonance (MR)-imaging can provide functional and positional information in real-time, which can be conveniently used online to control a cancer therapy, e.g., using high intensity focused ultrasound or radio therapy. However, a precise real-time correction for motion is fundamental in abdominal organs to ensure an optimal treatment dose associated with a limited toxicity in nearby organs at risk. This paper proposes a real-time direct principal component analysis (PCA)-based technique which offers a robust approach for motion estimation of abdominal organs and allows correcting motion related artifacts. The PCA was used to detect spatio-temporal coherences of the periodic organ motion in a learning step. During the interventional procedure, physiological contributions were characterized quantitatively using a small set of parameters. A coarse-to-fine resolution scheme is proposed to improve the stability of the algorithm and afford a predictable constant latency of 80 ms. The technique was evaluated on 12 free-breathing volunteers and provided an improved real-time description of motion related to both breathing and cardiac cycles. A reduced learning step of 10 s was sufficient without any need for patient-specific control parameters, rendering the method suitable for clinical use.
authors.forename: Baudouin
authors.initials: B
authors.lastname: Denis de Senneville
authors.forename: Abdallah
authors.initials: A
authors.lastname: El Hamidi
authors.forename: Chrit
authors.initials: C
authors.lastname: Moonen
mesh_terms: D000465:Algorithms; D006321:Heart / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007668:Kidney / Q000502:physiology; D008168:Lung / Q000502:physiology; D000069550:Machine Learning; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement / Q000502:physiology; D025341:Principal Component Analysis