Previous dosimetric studies during photodynamic therapy (PDT) of superficial lesions within a cavity such as the nasopharynx, demonstrated significant intra‐ and interpatient variations in fluence rate build‐up as a result of tissue surface re‐emitted and reflected photons, which depends on the optical properties. This scattering effect affects the response to PDT. Recently, a meta‐tetra(hydroxyphenyl)chlorin‐mediated PDT study of malignancies in the paranasal sinuses after salvage surgery was initiated. These geometries are complex in shape, with spatially varying optical properties. Therefore, preplanning and in vivo dosimetry is required to ensure an effective fluence delivered to the tumor. For this purpose, two 3D light distribution models were developed: first, a simple empirical model that directly calculates the fluence rate at the cavity surface using a simple linear function that includes the scatter contribution as function of the light source to surface distance. And second, an analytical model based on Lambert’s cosine law assuming a global diffuse reflectance constant. The models were evaluated by means of three 3D printed optical phantoms and one porcine tissue phantom. Predictive fluence rate distributions of both models are within ± 20% accurate and have the potential to determine the optimal source location and light source output power settings.
Background: Photodynamic therapy (PDT) is a promising treatment option for recurrent sinonasal malignancies. However, light administration in this area is challenging given the complex geometry, varying tissue optical properties and difficult accessibility. The goal of this study was to estimate the temporal and spatial variation in fluence and fluence rate during sinonasal mTHPC-mediated PDT. It was investigated whether the predetermined aim to illuminate with a fluence of 20 J⋅cm − 2 and fluence rate of 100 mW⋅cm − 2 was achieved. Methods: In eleven patients the fluence and fluence rates were measured using in vivo light dosimetry at the target location during real-time sinonasal PDT. There was a variance in sinonasal target location and type of light diffuser used. In four patients two isotropic detectors were used within the same cavity. Results: All measurements showed major fluence rate fluctuations within each single isotropic detector probe over time, as well as between probes within the same cavity. The largest fluence rate range measured was 328 mW⋅cm − 2 . Only one probe showed a mean fluence rate of ~100 mW⋅cm − 2 . Taken all probes together, a fluence rate above 80 mW⋅cm − 2 was measured in 31 % of the total light exposure; in 22 % it was less than 20 mW⋅cm − 2 . Thirty-three percent showed a fluence of at least 20 J⋅cm − 2 . Conclusions: The current dosimetry approach for sinonasal intra-cavity PDT shows major temporal and spatial variations in fluence rate and a large variance in light exposure time. The results emphasize the need for improvement of in vivo light dosimetry and dosimetry planning.
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