Author: Wenhua Cao, Hadis Moazami Goudarzi, Madison Emily Grayson, Zongsheng Hu, Gino Lim, Steven Hsesheng Lin, Radhe Mohan 👨🔬
Affiliation: The University of Texas MD Anderson Cancer Center, Department of Industrial Engineering, University of Houston, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center 🌍
Purpose: Proton Arc Therapy (PAT) offers significant potential in treating complex cancer cases by delivering a continuous radiation dose as the gantry rotates. This study aims to investigate the potential of energy layer optimization (ELO) for PAT to improve dosimetric quality and reduce radiation-induced lymphopenia (RIL) risk for esophageal cancer, compared to standard intensity modulated proton therapy (IMPT).
Methods: A mini-batch semi-stochastic gradient descent algorithm with partial group coordinated descent (mS2GD-PGCD) was developed for ELO to select optimum energy layers. Two single-arc PAT plans with and without ELO and one two-field IMPT plan were generated for an esophageal cancer patient. Dose-volume histograms (DVHs) were evaluated for target and critical organs, including heart, lung, liver, spleen, esophagus, etc. Predicted risks for G4 RIL and absolute lymphocyte count (ALC) nadir were calculated for all plans using previously developed prediction models.
Results: The ELO plan demonstrated improved dose conformity in the target and reduced doses in selected normal tissues compared to the non-ELO PAT plan and the IMPT plan. Predicted G4 RIL risk was lowest for the ELO plan (12.4%), followed by the plan without ELO (13.2%), while the clinical IMPT plan had a higher predicted risk (22.2%). Similarly, the ALC nadir prediction showed the highest value for the ELO plan (413 cells/µL vs. 346 cells/µL for non-ELO and 312 cells/µL for IMPT), indicating better preservation of ALC. DVH comparisons confirmed that ELO maintains superior target coverage while reducing dose to OARs.
Conclusion: Energy layer optimization using the mS2GD-PGCD algorithm enhances the dosimetric quality of PAT for esophageal cancer. In addition to improving dose conformity and sparing critical organs, the ELO approach may reduce the risk of RIL. This study demonstrates the feasibility and advantages of integrating ELO in proton arc therapy and establishes its potential as a clinical tool.