A patient-specific respiratory model of anatomical motion for radiation treatment planning
Qinghui Zhang, Alex Pevsner, Agung Hertanto, Yu-Chi Hu, Kenneth E., Rosenzweig, C. Clifton Ling, Gig S Mageras

TL;DR
This paper presents a patient-specific respiratory motion model for thoracic organs that does not assume repeatable breath cycles, improving the accuracy of radiotherapy dose calculations.
Contribution
The study introduces a novel model based on diaphragm motion and principal component analysis, capturing organ motion without assuming cyclic respiration.
Findings
First two principal components suffice to describe organ motion
Model reduces artifacts in RCCT images
Successful validation on data from multiple days
Abstract
Modeling of respiratory motion is important for a more accurate understanding and accounting of its effect on dose to cancers in the thorax and abdomen by radiotherapy. We have developed a model of respiration-induced organ motion in the thorax, without the commonly adopted assumption of repeatable breath cycles. The model describes the motion of a volume of interest within the patient, based on a reference 3-dimensional image (at end-expiration), and the diaphragm positions at different time points. The input data are respiration-correlated CT images of patients treated for nonsmall cell lung cancer, consisting of 3D images, including the diaphragm positions, at 10 phases of the respiratory cycle. A deformable image registration algorithm calculates the deformation field that maps each 3D image to the reference 3D image. A principle component analysis is performed to parameterize the…
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Taxonomy
TopicsAdvanced Radiotherapy Techniques · Lung Cancer Diagnosis and Treatment · Medical Imaging Techniques and Applications
