PTC17-0355: A New Algorithm for Motion Adapted Cone Beam CT Reconstruction Using an Advanced Motion Model

Yair Censor, F. Sherwood Rowland, Tai Dou, Daniel Abraham Low, Reinhard W. Schulte

Research output: Contribution to journalMeeting Abstractpeer-review


Purpose: To describe a novel algorithm for motion adapted cone beam CT (CBCT) reconstruction useful for 4D radiation therapy of lung tumors.
Materials and Methods: The presence of internal motion during CBCT acquisition is a challenge to CBCT reconstruction. We report on a novel algorithm that adapts to the presence of lung motion by using a free-breathing acquisition of CBCT ray sums, a surrogate breathing signal, and an advanced motion model1. The new algorithm solves the reconstruction problem as a feasibility problem with an iterative projection method. We are testing and optimizing the algorithm with a modification of the 4D FORBILD thorax phantom 2 and the simulation package jSNARK3.
Results: We simulated 25 helical scans of the 4D phantom and a motion described by 5 cosine terms. For helical-CT reconstruction, we used the Katsevich algorithm4. The deformable image registration toolbox Elastix was used to register the image from the first helical scan to the remaining 24 images establishing the motion model parameters1. We are currently simulating a CBCT acquisition of the 4D phantom and will use it to reconstruct the reference-breathing image of the phantom with the new algorithm.
Conclusion: A novel CBCT motion-adapted reconstruction algorithm in combination with advanced breathing motion model has been developed for applications in particle therapy.
Original languageEnglish
Pages (from-to)173
Number of pages1
JournalInternational Journal of Particle Therapy
Issue number2
StatePublished - 28 Dec 2017

Bibliographical note

In: Additional Proceedings to the 56th Annual Meeting of the Particle Therapy Cooperative Group (PTCOG), 8-13 May 2017.

References: [1] Thomas D, et al. Int J Radiat Oncol Biol Phys. 89:191-8, 2014. [2] [3] [4] A. Katsevich. Advances in Applied Mathematics, 32:681–697, 2004.


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