Computational Optimization of Irradiance and Fluence for Interstitial Photodynamic Therapy Treatment of Patients with Malignant Central Airway Obstruction

Emily Oakley; Evgueni Parilov; Karl Beeson; Mary Potasek; Nathaniel Ivanick; Lawrence Tworek; Alan Hutson; Gal Shafirstein

doi:10.3390/cancers15092636

Computational Optimization of Irradiance and Fluence for Interstitial Photodynamic Therapy Treatment of Patients with Malignant Central Airway Obstruction

Cancers (Basel). 2023 May 6;15(9):2636. doi: 10.3390/cancers15092636.

Authors

Emily Oakley¹, Evgueni Parilov², Karl Beeson², Mary Potasek², Nathaniel Ivanick³, Lawrence Tworek¹, Alan Hutson⁴, Gal Shafirstein¹

Affiliations

¹ Department of Cell Stress Biology, Photodynamic Therapy Center, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.
² Simphotek, Inc., 211 Warren St., Newark, NJ 07103, USA.
³ Department of Thoracic Surgery, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.
⁴ Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.

Abstract

There are no effective treatments for patients with extrinsic malignant central airway obstruction (MCAO). In a recent clinical study, we demonstrated that interstitial photodynamic therapy (I-PDT) is a safe and potentially effective treatment for patients with extrinsic MCAO. In previous preclinical studies, we reported that a minimum light irradiance and fluence should be maintained within a significant volume of the target tumor to obtain an effective PDT response. In this paper, we present a computational approach to personalized treatment planning of light delivery in I-PDT that simultaneously optimizes the delivered irradiance and fluence using finite element method (FEM) solvers of either Comsol Multiphysics^® or Dosie™ for light propagation. The FEM simulations were validated with light dosimetry measurements in a solid phantom with tissue-like optical properties. The agreement between the treatment plans generated by two FEMs was tested using typical imaging data from four patients with extrinsic MCAO treated with I-PDT. The concordance correlation coefficient (CCC) and its 95% confidence interval (95% CI) were used to test the agreement between the simulation results and measurements, and between the two FEMs treatment plans. Dosie with CCC = 0.994 (95% CI, 0.953-0.996) and Comsol with CCC = 0.999 (95% CI, 0.985-0.999) showed excellent agreement with light measurements in the phantom. The CCC analysis showed very good agreement between Comsol and Dosie treatment plans for irradiance (95% CI, CCC: 0.996-0.999) and fluence (95% CI, CCC: 0.916-0.987) in using patients' data. In previous preclinical work, we demonstrated that effective I-PDT is associated with a computed light dose of ≥45 J/cm² when the irradiance is ≥8.6 mW/cm² (i.e., the effective rate-based light dose). In this paper, we show how to use Comsol and Dosie packages to optimize rate-based light dose, and we present Dosie's newly developed domination sub-maps method to improve the planning of the delivery of the effective rate-based light dose. We conclude that image-based treatment planning using Comsol or Dosie FEM-solvers is a valid approach to guide the light dosimetry in I-PDT of patients with MCAO.

Keywords: I-PDT; MCAO; computational optimization; fluence; interstitial photodynamic therapy; irradiance; malignant central airway obstruction; rate-based light dose; treatment planning.

Abstract

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