Protonvda LLC

Northern Illinois University

Ethan A Dejongh

Don F Dejongh

Nicholas Karonis

Kirk Duffin

John Winans

Caesar Ordoñez

Disclosed herein are systems and methods for proton radiation therapy treatment planning that perform deformable image reconstruction and relative stopping power (RSP) maps updating using individual proton measurement data without requiring use of an entire proton radiography image. The systems and methods are capable of using protons from an arbitrary set of angles and/or positions. The iterative method optimally fits protons, while minimizing deviations from the original or deformed RSP map. The systems and methods use a covariance matrix to account for different uncertainties. Each iteration correctly accounts for in the proton data from measurement uncertainties, optimizing the overall fit of the RSP map to the proton data even though each proton does not fit perfectly due to measurement uncertainties. Different weights for the deviations from the original or deformed RSP map may be assigned to different voxels. The different weights may account for correlations in the deviations between voxels.

Updating proton stopping power maps for proton radiation therapy treatment planning

Described herein is a system for 3D proton imaging encompassing both proton radiography (pRad) and proton CT (pCT). The disclosed system can reduce range uncertainties, while providing a fast and efficient check of patient set up and integrated range along a beam's eye view just before treatment. The disclosed system provides a complete solution to the range inaccuracy problem in proton therapy, substantially reducing the uncertainties of treatment planning by directly measuring relative stopping power without being affected by image artifacts and with much lower dose to the patient than comparable x-ray images. Also described herein is a proton imaging algorithm for prompt iterative 3D pCT image reconstruction, where each iteration is fast and efficient, and the number of iterations is minimized. The method offers a unique solution that optimally fits different protons and does not depend on the starting point for the first iteration.

Iterative algorithm for proton CT image reconstruction

A computer-implemented system and method for generating a medical image is provided. In some embodiments, the medical image is generated by determining a location and an alignment for a first tracking detector with respect to a particle beam system. The direction of a beam generated from the particle beam system is determined. A first position of a first particle from a detected particle hit on the first tracking detector is also determined. A determination is made as to a first residual range of the first particle from a detected particle hit on a residual range detector. The system reconstructs a path for the first particle based on the location, the alignment, the first position, and the first residual range of the first particle. The resulting medical image that is generated by the system is based on the reconstructed path for the first particle.

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Batavia, IL, United States of America

Ethan A Dejongh