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Proceedings Paper

Early photosensitizer uptake kinetics predict optimum drug-light interval for photodynamic therapy
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Paper Abstract

Photodynamic therapy (PDT) has shown promising results in targeted treatment of cancerous cells by developing localized toxicity with the help of light induced generation of reactive molecular species. The efficiency of this therapy depends on the product of the intensity of light dose and the concentration of photosensitizer (PS) in the region of interest (ROI). On account of this, the dynamic and variable nature of PS delivery and retention depends on many physiological factors that are known to be heterogeneous within and amongst tumors (e.g., blood flow, blood volume, vascular permeability, and lymph drainage rate). This presents a major challenge with respect to how the optimal time and interval of light delivery is chosen, which ideally would be when the concentration of PS molecule is at its maximum in the ROI. In this paper, a predictive algorithm is developed that takes into consideration the variability and dynamic nature of PS distribution in the body on a region-by-region basis and provides an estimate of the optimum time when the PS concentration will be maximum in the ROI. The advantage of the algorithm lies in the fact that it predicts the time in advance as it takes only a sample of initial data points (~12 min) as input. The optimum time calculated using the algorithm estimated a maximum dose that was only 0.58 ± 1.92% under the true maximum dose compared to a mean dose error of 39.85 ± 6.45% if a 1 h optimal light deliver time was assumed for patients with different efflux rate constants of the PS, assuming they have the same plasma function. Therefore, if the uptake values of PS for the blood and the ROI is known for only first 12 minutes, the entire curve along with the optimum time of light radiation can be predicted with the help of this algorithm.

Paper Details

Date Published: 2 March 2015
PDF: 8 pages
Proc. SPIE 9308, Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXIV, 930811 (2 March 2015); doi: 10.1117/12.2077842
Show Author Affiliations
Lagnojita Sinha, Illinois Institute of Technology (United States)
Jonathan T. Elliott, Thayer School of Engineering Dartmouth College (United States)
Tayyaba Hasan, Wellman Ctr. for Photomedicine, Harvard Medical School, Massachusetts General Hospital (United States)
Brian W. Pogue, Thayer School of Engineering at Dartmouth (United States)
Kimberley S. Samkoe, Thayer School of Engineering at Dartmouth (United States)
Kenneth M. Tichauer, Illinois Institute of Technology (United States)

Published in SPIE Proceedings Vol. 9308:
Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXIV
David H. Kessel; Tayyaba Hasan, Editor(s)

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