Dependence of subject-specific parameters for a fast helical CT respiratory motion model on breathing rate: an animal study
- 1 February 2018
- journal article
- research article
- Published by IOP Publishing in Physics in Medicine & Biology
- Vol. 63 (4) , 04NT04
Abstract
To determine if the parameters relating lung tissue displacement to a breathing surrogate signal in a previously published respiratory motion model vary with the rate of breathing during image acquisition. An anesthetized pig was imaged using multiple fast helical scans to sample the breathing cycle with simultaneous surrogate monitoring. Three datasets were collected while the animal was mechanically ventilated with different respiratory rates: 12 bpm (breaths per minute), 17 bpm, and 24 bpm. Three sets of motion model parameters describing the correspondences between surrogate signals and tissue displacements were determined. The model error was calculated individually for each dataset, as well asfor pairs of parameters and surrogate signals from different experiments. The values of one model parameter, a vector field denoted α → which related tissue displacement to surrogate amplitude, determined for each experiment were compared. The mean model error of the three datasets was 1.00 ± 0.36 mm with a 95th percentile value of 1.69 mm. The mean error computed from all combinations of parameters and surrogate signals from different datasets was 1.14 ± 0.42 mm with a 95th percentile of 1.95 mm. The mean difference in α → over all pairs of experiments was 4.7% ± 5.4%, and the 95th percentile was 16.8%. The mean angle between pairs of α → was 5.0 ± 4.0 degrees, with a 95th percentile of 13.2 mm. The motion model parameters were largely unaffected by changes in the breathing rate during image acquisition. The mean error associated with mismatched sets of parameters and surrogate signals was 0.14 mm greater than the error achieved when using parameters and surrogate signals acquired with the same breathing rate, while maximum respiratory motion was 23.23 mm on average.Keywords
Funding Information
- Siemens Healthcare
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