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Estimation of 3D Fluoroscopic Treatment Images Using a Single Cine EPID Image

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P Mishra

P Mishra1*, R Li2, C Williams1, R Berbeco1, J Lewis1, (1) Brigham and Women's Hospital, Dana-Farber Cancer Center, Harvard Medical School, Boston, MA, (2) Stanford University, Stanford, CA

WE-C-WAB-10 Wednesday 10:30AM - 12:30PM Room: Wabash Ballroom

Purpose: A novel algorithm for volumetric time-varying image estimation and 3D tumor localization from a single cine EPID image.
Methods: Generating a volumetric fluoroscopic (time-varying) image from a single EPID image is a two-step process. In the first step a patient-specific motion model is constructed and in the second step the motion model is updated according to the information in the EPID image. The patient-specific motion model is a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration of a reference 4DCT image (typically peak-exhale) to the 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through Principal Component Analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen coefficients are updated via cost function optimization based on DRRs and projection images. The updated eigen-coefficients are then used to obtain updated DVFs that in turn give the volumetric image corresponding to the EPID image.
Results: The algorithm was tested on 1) XCAT digital phantom data based on 8 irregular patient breathing patterns; and 2) patient cine EPID images acquired during SBRT. The root-mean-squared vector tumor localization error is (0.73 ± 0.63) mm for the XCAT data and (1.9 ± 1.6) mm for the patient data.
Conclusions: We introduced a novel method of estimating volumetric time-varying images from a single cine EPID image. This is the first method to estimate volumetric time-varying images from MV cine EPID, and has the potential to provide 3D information with no additional imaging dose to the patient.

Funding Support, Disclosures, and Conflict of Interest: The project described was supported, in part, by an RSNA Research Scholar Grant and Award Number R21CA156068 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the RSNA, National Cancer Institute or the National Institutes of Health.

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