A novel respiratory motion perturbation model adaptable to patient breathing irregularities

Publication date: Available online 3 September 2016
Source:International Journal of Radiation Oncology*Biology*Physics
Author(s): Amy Yuan, Jie Wei, Carl P. Gaebler, Hailiang Huang, Devin Olek, Guang Li
PurposeTo develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities.Methods and MaterialsA novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained two terms: initial tumor motion trajectory (MT) measured from four-dimensional computed tomography (4DCT) and motion perturbation (ΔMT), calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The ΔMT was derived from patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied and two amplitude-binned 4DCT images for each patient were acquired within two weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate TV and BP as functions of the breathing phase. The motion was predicted from 4DCTsim to 4DCTtxt, and vice versa, resulting in a total of 800 predictions. As comparisons, non-corrected (NC) motion differences and the predictions from a published 5D model were used.ResultsThe average motion range in the superior-inferior direction was 9.4±4.4mm, while an average ΔTV ranged 10-248 mm³ (-26–61%), and ΔBP ranged 0-0.2 (-71-333%) between two 4DCT. The mean NC motion difference was 2.0±2.8mm between two 4DCT MTs. After applying the RMP model, the mean motion difference was reduced significantly to 1.2±1.8 mm (p=0.0018), a 40% improvement, similar to 1.2±1.8 mm (p=0.72) predicted with the 5D model.ConclusionA novel physical RMP model was developed with average accuracy of 1.2±1.8 mm for interfractional motion prediction, similar to that of a published lung motion model. This physical RMP is analytically derived and able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.

Teaser

ovel physics-law-based respiratory motion perturbation model is developed to predict tumor motion under breathing irregularities. This adaptive model predicts motion variations using tidal-volume and breathing-pattern updates and is validated using two 4DCT sets from ten patients. Forty motion trajectories of 40 bifurcation points per 4DCT are tracked and 800 4DCT1↔4DCT2 predictions are evaluated with known ground truth. Average accuracy (1.2±1.8mm) is achieved, similar to an established model while significantly improved from raw motion differences.


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