(Tuesday, 7/14/2020) 3:30 PM - 5:30 PM [Eastern Time (GMT-4)]
Room: Track 2
Purpose:
Breathing, stomach contractions and a range of physiological motions together determine abdominal dynamic configuration. A hierarchical motion model was developed to measure and combine these motion modes.
Methods:
Each temporal sample of the patient’s abdomen was acquired by a spoke from a 20-minute golden angle stack-of-stars MRI sequence. 21 breathing states were reconstructed using a previously published method, and deformations between these and the exhale state were used to remove breathing motion from the sampled spokes for subsequent motion modeling. 21 antral contraction phases were subsequently determined through PCA of rician-filtered temporal signals in the stomach. Slow configuration states were extracted via alignment of reconstructions every 17 seconds. Each spoke was assigned to appropriate breathing, contraction and configuration states.
Interpolated deformations of breathing, contraction and slow configuration states to those of a given spoke yielded composite representations of the patient for actual motion estimates at any given time. An average patient model was generated as the mean deformation across all motion models for the sampled time. Motion models were generated from 10 example scans across 6 patients. Planned (on the average state) versus model-estimated (through weighted sum of dose delivery from composite motion states according to their probability of occurrence) delivered dose distributions were compared for one example.
Results:
Motions from sources other than breathing were significant. Of a total average of 13.1mm (±3.5) motion range detected, 1.5mm (±0.9) and 6.5mm (±2.0) were contributed from antral contraction and slow configuration respectively for the stomach surface. Motion led to dose differences of up to 20.1% and 13.7% for maximum doses to 0.1cc and 0.5cc to the stomach, respectively.
Conclusion:
A hierarchical motion model is able to account for superimposed motion effects in the abdomen, with potential uses in guiding robust treatment planning, motion management strategies, and IGRT strategies.
Funding Support, Disclosures, and Conflict of Interest: Funded by NIH R01 EB016079
Keywords
Taxonomy
IM/TH- MRI in Radiation Therapy: MRI for treatment planning
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