2021
DOI: 10.1364/boe.431310
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Machine learning for real-time optical property recovery in interstitial photodynamic therapy: a stimulation-based study

Abstract: With the continued development of non-toxic photosensitizer drugs, interstitial photodynamic therapy (iPDT) is showing more favorable outcomes in recent clinical trials. IPDT planning is crucial to further increase the treatment efficacy. However, it remains a major challenge to generate a high-quality, patient-specific plan due to uncertainty in tissue optical properties (OPs), µ a … Show more

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Cited by 13 publications
(10 citation statements)
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“…These results highlight the importance of careful patient-specific treatment planning for PDT. This has been thoroughly investigated for PDT of cancer, for which multiple investigators have reported treatment planning for sites including head and neck, 33 , 38 , 39 brain, 40 42 and prostate 43 46 tumors. Largely in the context of interstitial applications, these previous treatment plans focused on determination of the optimal type and number of source optical fibers, as well as the placement and optical power delivered by these fibers.…”
Section: Discussionmentioning
confidence: 99%
“…These results highlight the importance of careful patient-specific treatment planning for PDT. This has been thoroughly investigated for PDT of cancer, for which multiple investigators have reported treatment planning for sites including head and neck, 33 , 38 , 39 brain, 40 42 and prostate 43 46 tumors. Largely in the context of interstitial applications, these previous treatment plans focused on determination of the optimal type and number of source optical fibers, as well as the placement and optical power delivered by these fibers.…”
Section: Discussionmentioning
confidence: 99%
“…The pig lung mesh executes slowly as photons frequently cross tetrahedral boundaries, requiring lookup of optical properties in the entered tetrahedron, and frequently cross tissue regions, requiring additional reflection and refraction calculations. Table 4 shows the relative performance of PDT plan optimization via PDT-SPACE using the Colin27 brain atlas and two different tumor cases, one small ( and three light sources) and one large ( and 19 light sources), which are cases T7 and T2 from Yassine et al., 50 respectively. Note that PDT-SPACE currently supports only CPU-based implementations.…”
Section: Fullmontewebmentioning
confidence: 99%
“…For the case of light dose deposited in tissue, this is largely determined by the tissue optical properties: absorption and scattering. Multiple studies have shown the importance of patient-specific measures of tissue optical properties for PDT treatment planning purposes [7][8][9], as these can vary widely between individuals [10]. This is particularly true for abscesses, as morphology can be quite distinct between subjects and the integrating sphere effect can result in fluence rates much different than those predicted purely by geometry or diffusion of light [11].…”
Section: Introductionmentioning
confidence: 99%