Model-guided respiratory organ motion prediction of the liver from 2D ultrasound.
With the availability of new and more accurate tumour treatment modalities such as high-intensity focused ultrasound or proton therapy, accurate target location prediction has become a key issue. Various approaches for diverse application scenarios have been proposed over the last decade. Whereas external surrogate markers such as a breathing belt work to some extent, knowledge about the internal motion of the organs inherently provides more accurate results. In this paper, we combine a population-based statistical motion model and information from 2d ultrasound sequences in order to predict the respiratory motion of the right liver lobe. For this, the motion model is fitted to a 3d exhalation breath-hold scan of the liver acquired before prediction. Anatomical landmarks tracked in the ultrasound images together with the model are then used to reconstruct the complete organ position over time. The prediction is both spatial and temporal, can be computed in real-time and is evaluated on ground truth over long time scales (5.5 min). The method is quantitatively validated on eight volunteers where the ultrasound images are synchronously acquired with 4D-MRI, which provides ground-truth motion. With an average spatial prediction accuracy of 2.4 mm, we can predict tumour locations within clinically acceptable margins.
Medical Image Analysis Center, University of Basel, Switzerland. Electronic address: frank.preiswerk@unibas.ch.
Frank
F
Preiswerk
Computer Vision Lab, ETH Zurich, Switzerland.
Valeria
V
De Luca
Medical Image Analysis Center, University of Basel, Switzerland.
Patrik
P
Arnold
Division of Radiological Physics, University of Basel, Switzerland.
Zarko
Z
Celicanin
Faculty of Medicine, Radiology, University of Geneva, Switzerland.
Lorena
L
Petrusca
Computer Vision Lab, ETH Zurich, Switzerland.
Christine
C
Tanner
Division of Radiological Physics, University of Basel, Switzerland.
Oliver
O
Bieri
Faculty of Medicine, Radiology, University of Geneva, Switzerland; Radiology Department, University Hospitals of Geneva, Switzerland.
Rares
R
Salomir
Medical Image Analysis Center, University of Basel, Switzerland.
Philippe C
PC
Cattin
D000293:Adolescent; D000328:Adult; D000368:Aged; D059925:Anatomic Landmarks / Q000000981:diagnostic imaging; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging* / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D009068:Movement / Q000502:physiology; D015203:Reproducibility of Results; D015656:Respiratory Mechanics / Q000502:physiology*; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods*; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000379:methods*; D055815:Young Adult
4D-MRI; Respiratory motion compensation; Spatio-temporal prediction; Statistical motion model; Ultrasound