Intra-fraction motion prediction in MRI-guided radiation therapy using Markov processes

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Authors
Mirzapour, Azam
Mazur, Thomas R.
Sharp, Gregory
Salari, Ehsan
Issue Date
2019-09-23
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Article
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en_US
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Abstract

Internal organ motion during radiation delivery may lead to underdosing of cancer cells or overdosing of normal tissue, potentially causing treatment failure or normal-tissue toxicity. Organ motion is of particular concern in the treatment of lung and abdominal cancers, where breathing induces large tumor displacement and organ deformation. A new generation of radiotherapy devices is equipped with on-board MRI scanners to acquire a real-time movie of the patient's anatomy during radiation delivery. The goal of this research is to develop, calibrate, and test motion predictive models that employ real-time MRI images to provide the short-term trajectory of respiration-induced anatomical motion during radiation delivery. A semi-Markov model predicts transitions between the phases of a respiratory cycle, and a Markov model predicts transitions to future respiratory cycles, leading to accurate motion forecasting over longer-term horizons. The intended application for this work is real-time tracking and re-optimization of intensity-modulated radiation delivery.

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Mirzapour, Azam; Mazur, Thomas R.; Sharp, Gregory; Salari, Ehsan. 2019. Intra-fraction motion prediction in MRI-guided radiation therapy using Markov processes. Physics in Medicine & Biology, vol. 64:no. 19:p. 195006
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NLM (Medline)
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1361-6560
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