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Photodynamic therapy for glioblastoma: A preliminary approach for practical application of light propagation models
Author(s) -
Dupont Clément,
Vignion AnneSophie,
Mordon Serge,
Reyns Nicolas,
Vermandel Maximilien
Publication year - 2018
Publication title -
lasers in surgery and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 112
eISSN - 1096-9101
pISSN - 0196-8092
DOI - 10.1002/lsm.22739
Subject(s) - monte carlo method , fluence , sensitivity (control systems) , glioblastoma , variance (accounting) , computer science , photodynamic therapy , standard deviation , radiation treatment planning , algorithm , optics , mathematics , statistics , physics , laser , radiation therapy , chemistry , medicine , electronic engineering , surgery , accounting , organic chemistry , cancer research , business , engineering
Purpose Photodynamic therapy (PDT) is a promising treatment modality to be added in the management of glioblastoma multiforme (GBM). Light distribution modeling is required for planning and optimizing PDT. Several models have been developed to predict the light propagation inside biological tissues. In the present study, two analytical methods of light propagation emitted from a cylindrical fiber source were evaluated: a discrete and a continuous method. Methods The two analytical approaches were compared according to their fluence rate results. Several cylindrical diffuse lengths were evaluated, and the relative deviation in the fluence rates was estimated. Moreover, a sensitivity analysis was conducted to compute the variance of each analytical model. Results The discrete method provided fluence rate estimations closer to the Monte‐Carlo simulations than the continuous method. The sensitivity study results did not reveal significant differences between the variance of the two analytical models. Conclusions Although the discrete model provides relevant light distribution, the heterogeneity of GBM tissues was not considered. With the improvement in parallel computing that drastically decreased the computing time, replacing the analytical model by a Monte‐Carlo GPU‐accelerated code appeared relevant to the GBM case. Nonetheless, the analytical modeling may still function in the optimization algorithms, which might be used in the Photodynamic treatment planning system. Lasers Surg. Med. 50:523–534, 2018. © 2017 Wiley Periodicals, Inc.

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