Open AccessAutomatic interstitial photodynamic therapy planning via convex optimization
Author(s) -
Abdul-Amir Yassine,
William Kingsford,
Yihuan Xu,
J Cassidy,
Lothar Lilge,
Vaughn Betz
Publication year - 2018
Publication title -
biomedical optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.9.000898
Subject(s) - computer science , photodynamic therapy , concomitant , selection (genetic algorithm) , light source , power (physics) , mathematical optimization , medicine , artificial intelligence , surgery , mathematics , optics , physics , chemistry , organic chemistry , quantum mechanics
Finding a high-quality treatment plan is an essential, yet difficult, stage of Photodynamic therapy (PDT) as it will determine the therapeutic efficacy in eradicating malignant tumors. A high-quality plan is patient-specific, and provides clinicians with the number of fiber-based spherical diffusers, their powers, and their interstitial locations to deliver the required light dose to destroy the tumor while minimizing the damage to surrounding healthy tissues. In this work, we propose a general convex light source power allocation algorithm that, given light source locations, guarantees optimality of the resulting solution in minimizing the over/under-dosage of volumes of interest. Furthermore, we provide an efficient framework for source selection with concomitant power reallocation to achieve treatment plans with a clinically feasible number of sources and comparable quality. We demonstrate our algorithms on virtual test cases that model glioblastoma multiforme tumors, and evaluate the performance of four different photosensitizers with different activation wavelengths and specific tissue uptake ratios. Results show an average reduction of the damage to organs-at-risk (OAR) by 29% to 31% with comparable runtime to existing power allocation techniques.