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A Novel Markerless 4D CBCT Projection Phase Sorting Technique Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study

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L Zhang

L Zhang*, Y Zhang , F Yin , W Harris , J Cai , L Ren , Duke University Medical Center, Durham, NC


TH-EF-BRA-2 (Thursday, August 4, 2016) 1:00 PM - 2:50 PM Room: Ballroom A

Purpose: To investigate the feasibility of a novel marker-less motion-modeling based method for automatic 4D-CBCT projection phase sorting.

Methods: Patient on-board image volume at any instant is considered as a deformation of one phase of the prior planning 4D-CT. The deformation field map(DFM) is represented as a linear combination of three major deformation patterns extracted from the planning 4D-CT using principle-component-analysis(PCA). The PCA coefficients are solved for each single projection based on data fidelity constraint, and are used as motion information for phase sorting. Projections at the valleys of the Z direction coefficient are sorted as phase 0/100% and projection phases in between are linearly interpolated. 4D-digital-extended-cardiac-torso(XCAT) phantoms and 3 patient cases were used for evaluation. XCAT phantoms simulated different patient respiratory and anatomical changes from prior 4D-CT to on-board image volume, including changes of tumor size, locations, motion amplitudes and motion directions. Three patient cases include 2 full-fan slow-rotation and one half-fan normal-rotation case. Manual phase sorting based on visual inspection was used as the gold standard. The average absolute phase difference, and the pass rate (percentage of projections sorted within 10% phase error) were used to evaluate sorting accuracy.

Results: The amplitude of PCA coefficient motion curve correlated with the actual motion amplitude. The algorithm was robust against respiratory and anatomical changes from prior to on-board imaging. For all XCAT cases, the average phase errors were lower than 1.43%, and the pass rate was 100%. The patient data set showed average phase error of 2.47%, 1.90% for full fan slow rotation case and 2.78% for half fan normal rotation case, respectively. The corresponding pass rates were 99.4%, 98.5% and 99.5% , respectively.

Conclusion: Preliminary results demonstrated the robustness and high accuracy of the marker-less PCA based phase sorting algorithm for different patient scenarios and 4D-CBCT scanning protocols.

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