22 February 2017 A visible Chinese human-combined Monte Carlo simulation study on low-level light therapy of stroke
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Abstract
Stroke is a devastating disease, which is the third leading cause of death and disability worldwide. Although the incidence of stroke increases progressively with age, morbidity among young and middle-aged adults is increasing annually. Medications nevertheless remain the bulwarks of stroke. The treatment is ineffective, speculative and has a long treatment cycle. The function of acupuncture and moxibustion, which are potential therapeutic tools for stroke, is still controversial. Recently, Low-level light therapy (LLLT) has been demonstrated potent in vivo efficacy for treatment of ischemic conditions of acute myocardial infraction and stroke in multiple validated animal models. Optimum LLLT treatment has a dominant influence on therapy of stroke. While more than a thousand clinical trials have been halted, only a few trials on animals have been reported. We addressed this issue by simulating near-infrared light propagation with accurate visible Chinese human head by Monte Carlo modeling. The visible human head embody region of atherosclerotic plaques in head. Through comparing the light propagation of different light illumination, we can get a precise, optimized and straightforward treatment. Here, we developed a LLLT helmet for treating stroke depend on near-infrared light. There are more than 30 LED arrays in in multi-layered 3D printed helmet. Each LED array has independent water-cooling module and can be adjusted to touch the head of different subjects based on Electro pneumatic module. Moreover, the software provides the setup of illumination parameters and 3D distribution of light fluence rate distribution in human brain.
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Pengbo Wang, Pengbo Wang, Boan Pan, Boan Pan, Fulin Zhong, Fulin Zhong, Ting Li, Ting Li, } "A visible Chinese human-combined Monte Carlo simulation study on low-level light therapy of stroke", Proc. SPIE 10066, Energy-based Treatment of Tissue and Assessment IX, 100660C (22 February 2017); doi: 10.1117/12.2251645; https://doi.org/10.1117/12.2251645
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