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Motion-Map Constrained Image Reconstruction for 4DCBCT Reconstruction in IGRT

C Park

C Park1*, J Kim2, B Song3, W Song4, (1) University of California, La Jolla, San Diego, CA, (2) Samsung Medical Center, Seoul, ,(3) University of California, San Diego, La Jolla, CA, (4) University of California, San Diego, La Jolla, CA

TH-C-103-1 Thursday 10:30AM - 12:30PM Room: 103

Purpose: We developed a novel low-dose 4DCBCT reconstruction algorithm, named Motion-Map Constrained Image Reconstruction (MCIR), that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose as well as the X-ray projections used in a standard free-breathing 3DCBCT (FB-3DCBCT) scan.

Methods: The unknown 4DCBCT volume at each phase was mathematically modeled as combination of FB-3DCBCT and motion-map matrix with phase-specific update vector. The motion-map matrix, which is the key innovation of MCIR algorithm, was defined as the matrix that distinguishes voxels between ones that are moving and stationary. This 4DCBCT model was then reconstructed with compressed sensing (CS) reconstruction framework such that the voxels with high motion would be aggressively updated by the input phase information and the voxels with less motion would be minimally updated to preserve the FB-3DCBCT. To evaluate the performance of our proposed MCIR algorithm, we have tested on both numerical phantoms and lung cancer patient CBCT scans. The results were then compared with the 1) clinical FB-3DCBCT reconstructed using FDK, 2) 4DCBCT reconstructed using FDK, and 3) 4DCBCT reconstructed using the best-known algorithm to date: PICCS.

Results: Examination of the MCIR algorithm showed that high phase resolution 4DCBCT with sets up to 20 phases using typical patient FB-3DCBCT scan could be reconstructed without compromising the image quality. Moreover, both in numerical as well as in real patient data sets, the MCIR algorithm outperformed the other algorithms. This is achieved without using any a priori data, such as the planning CT.

Conclusion: This work demonstrates the potential for providing high-quality 4DCBCT information during on-line IGRT and ART environment, without sacrificing imaging dose. Proposed algorithm is also entirely compatible to GPU programming, which could sufficiently speed up the process to achieve within clinically usable time-frame (<30 sec).

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