Photodynamic therapy for glioblastoma: A preliminary approach for practical application of light propagation models

Abstract : 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.
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Contributeur : Maximilien Vermandel <>
Soumis le : mercredi 20 septembre 2017 - 11:02:39
Dernière modification le : mercredi 20 septembre 2017 - 15:38:21


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Clément Dupont, Anne-Sophie Vignion-Dewalle, Serge Mordon, Nicolas Reyns, Maximilien Vermandel. Photodynamic therapy for glioblastoma: A preliminary approach for practical application of light propagation models. Lasers in Surgery and Medicine, Wiley, 2017, Epub ahead of print. 〈〉. 〈10.1002/lsm.22739〉. 〈inserm-01590765〉



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