A novel inverse algorithm to solve IPO-IMPT of proton FLASH therapy with sparse filters
Nathan Harrison, Minglei Kang, Ruirui Liu, Serdar Charyyev, Niklas, Wahl, Wei Liu, Jun Zhou, Kristin A. Higgins, Charles Simone, Jeffrey Bradley,, William S. Dynan, Liyong Lin

TL;DR
This paper introduces SIEMAC, an inverse algorithm for IPO-IMPT in proton FLASH therapy that optimizes dose, dose rate, and LET with sparse filters, improving treatment precision and reducing biological dose to organs.
Contribution
The novel inverse algorithm enables simultaneous optimization of sparse filters and proton intensity, addressing computational challenges in IPO-IMPT for clinical and preclinical applications.
Findings
Significant increase in dose rate coverage in lung and heart tissues.
Reduction of LET coverage in critical organs, indicating safer dose distributions.
Decreased uncertainty in dose, dose rate, and LET distributions in preclinical models.
Abstract
Purpose:The recently proposed IPO-IMPT framework allows simultaneous optimization of dose, dose rate, and LET for FLASH treatment planning. Finding solutions to IPO-IMPT is difficult due to computational intensiveness. Nevertheless, an inverse solution that simultaneously specifies the geometry of a sparse filter and weights of a proton intensity map is desirable for both clinical and preclinical applications. Such solutions can reduce effective biological dose to organs at risk in cancer patients as well as reduce the number of animal irradiations needed to derive extra biological dose models in preclinical studies. Methods:Unlike our initial forward heuristic, this inverse IPO-IMPT solution includes simultaneous optimization of sparse range compensation, sparse range modulation, and spot intensity. The daunting computational tasks vital to this endeavor were resolved iteratively…
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Taxonomy
TopicsRadiation Therapy and Dosimetry · Radiation Detection and Scintillator Technologies · Advanced Radiotherapy Techniques
