19 February 2018 Evaluation of blood flow in human exercising muscle by diffuse correlation spectroscopy: a phantom model study
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Abstract
Diffuse correlation spectroscopy (DCS) has a potential to noninvasively and quantitatively measure the blood flow in the exercising muscle that could contribute to the fields of sports physiology and medicine. However, the blood flow index (BFI) measured from skin surface by DCS reflects hemodynamic signals from both superficial tissue and muscle layer. Thus, an appropriate calibration technology is required to quantify the absolute blood flow in the muscle layer. We therefore fabricated a realistic two-layer phantom model consisted of a static silicon layer imitating superficial tissue and a dynamic flow layer imitating the muscle blood flow and investigated the relationship between the simulated blood flow rate in the muscle layer and the BFI measured from the surface of the phantom. The absorption coefficient and the reduced scattering coefficient of the forearm were measured from 25 healthy young adults using a time-resolved nearinfrared spectroscopy. The depths of the superficial and muscle layers of forearm were also determined by ultrasound tomography images from 25 healthy young adults. The phantoms were fabricated to satisfy these optical coefficients and anatomical constraints. The simulated blood flow rate were set from 0 mL/ min to 68.7 mL/ min in ten steps, which is considered to cover a physiological range of mean blood flow of the forearm between per 100g of muscle tissue at rest to heavy dynamic handgrip exercise. We found a proportional relationship between the flow rates and BFIs with significant correlation coefficient of R = 0.986. Our results suggest that the absolute exercising muscle blood flow could be estimated by DCS with optimal calibration using phantom models.
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Mikie Nakabayashi, Mikie Nakabayashi, Yumie Ono, Yumie Ono, Masashi Ichinose, Masashi Ichinose, } "Evaluation of blood flow in human exercising muscle by diffuse correlation spectroscopy: a phantom model study", Proc. SPIE 10486, Design and Quality for Biomedical Technologies XI, 1048609 (19 February 2018); doi: 10.1117/12.2288044; https://doi.org/10.1117/12.2288044
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