TY - GEN
T1 - Adapting population liver motion models for individualized online image-guided therapy
AU - Nguyen, Thao Nguyen
AU - Moseley, Joanne L.
AU - Dawson, Laura A.
AU - Jaffray, David A.
AU - Brock, Kristy K.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - Respiratory motion varies on a daily basis in abdominal cancer patients, affecting the ability to successfully deliver local therapy and requiring increased treatment margins to account for this variation. Deformable registration techniques can accurately describe respiratory motion, however, online application can be limited by long computational times and user intervention. A technique has been developed to quickly quantify patient breathing motion from respiratory-sorted volumetric images by calculating 1D shifts in image intensities between spatially corresponding regions of interest (navigator channels) on patient's images. The 1D motion at the superior, inferior, anterior, and posterior liver edges was detected and applied to adapt a population liver respiratory motion model. For validation, deformable registration was performed for each patient using a validated technique, MORFEUS, for relative validation, and vessel bifurcations, identified on patient's inhale and exhale images, for absolute validation. The accuracy of the adaptedpopulation model to describe the patient respiratory motion was (absolute mean ± SD) 0.26 ± 0.11 cm and 0.30 ± 0.21 cm in the superior-inferior (SI) and anterior-posterior (AP) directions, respectively. The accuracy of predicting the tumor COM motion was 0.30 ± 0.22 cm, and 0.34 ± 0.31, while the absolute validation, based on bifurcations was 0.26 ± 0.16 cm and 0.13 ± 0.04 cm in the SI and AP directions, respectively. This technique was developed to complement and quickly adapt a full 3D biomechanical based deformable registration technique, MORFEUS, to be applied in the online setting.
AB - Respiratory motion varies on a daily basis in abdominal cancer patients, affecting the ability to successfully deliver local therapy and requiring increased treatment margins to account for this variation. Deformable registration techniques can accurately describe respiratory motion, however, online application can be limited by long computational times and user intervention. A technique has been developed to quickly quantify patient breathing motion from respiratory-sorted volumetric images by calculating 1D shifts in image intensities between spatially corresponding regions of interest (navigator channels) on patient's images. The 1D motion at the superior, inferior, anterior, and posterior liver edges was detected and applied to adapt a population liver respiratory motion model. For validation, deformable registration was performed for each patient using a validated technique, MORFEUS, for relative validation, and vessel bifurcations, identified on patient's inhale and exhale images, for absolute validation. The accuracy of the adaptedpopulation model to describe the patient respiratory motion was (absolute mean ± SD) 0.26 ± 0.11 cm and 0.30 ± 0.21 cm in the superior-inferior (SI) and anterior-posterior (AP) directions, respectively. The accuracy of predicting the tumor COM motion was 0.30 ± 0.22 cm, and 0.34 ± 0.31, while the absolute validation, based on bifurcations was 0.26 ± 0.16 cm and 0.13 ± 0.04 cm in the SI and AP directions, respectively. This technique was developed to complement and quickly adapt a full 3D biomechanical based deformable registration technique, MORFEUS, to be applied in the online setting.
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U2 - 10.1109/iembs.2008.4650073
DO - 10.1109/iembs.2008.4650073
M3 - Conference contribution
C2 - 19163576
AN - SCOPUS:61849126311
SN - 9781424418152
T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
SP - 3945
EP - 3948
BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PB - IEEE Computer Society
T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Y2 - 20 August 2008 through 25 August 2008
ER -