In the last 20 years, near-infrared diffuse correlation spectroscopy (DCS) has been developed for providing a noninvasive estimate of microvascular blood flow (BF) as a BF index (BFi) in the human skin, muscle, breast, brain and other tissue types. In this study, we proposed a new motion correction algorithm for DCS-derived BFi able to remove motion artifacts occurring during dynamic muscle exercises. We tested this algorithm on DCS data collected during cycling exercise, and demonstrated that DCS can be used to quantify muscle BFi during dynamic high-intensity exercise. In addition, we measured tissue regional oxygen metabolic rate (MRO2i) by combining frequency-domain multi-distance near-infrared spectroscopy (FDNIRS) oximetry with DCS flow measures. Twelve recreationally active subjects (31 ± 8 yr, 183 ± 4 cm, 79 ± 10 kg) pedaled at 80-100 rpm until volitional fatigue with a work rate increase of 30 W every 4 min. Exercise intensity was normalized in each subject to the cycling power peak (Wpeak). Both rectus femoris BFi and MRO2i increased from 15% up to 75% Wpeak and then plateaued to the end of the exercise. During the recovery at 30 W cycling power, BFi remained almost constant while MRO2i started to decrease. The BFi /MRO2i plateau was associated with the rising of the lactate concentration indicating the progressive involvement of the anaerobic metabolism. These findings further highlight the utility of DCS and FDNIRS oximetry as an effective, reproducible, and noninvasive technique to assess muscle BFi and MRO2i in real-time during a dynamic exercise such as cycling.

Diffuse correlation spectroscopy and frequency-domain near-infrared spectroscopy for measuring microvascular blood flow in dynamically exercising human muscles

Quaresima, Valentina
;
Ferrari, Marco;
2019-01-01

Abstract

In the last 20 years, near-infrared diffuse correlation spectroscopy (DCS) has been developed for providing a noninvasive estimate of microvascular blood flow (BF) as a BF index (BFi) in the human skin, muscle, breast, brain and other tissue types. In this study, we proposed a new motion correction algorithm for DCS-derived BFi able to remove motion artifacts occurring during dynamic muscle exercises. We tested this algorithm on DCS data collected during cycling exercise, and demonstrated that DCS can be used to quantify muscle BFi during dynamic high-intensity exercise. In addition, we measured tissue regional oxygen metabolic rate (MRO2i) by combining frequency-domain multi-distance near-infrared spectroscopy (FDNIRS) oximetry with DCS flow measures. Twelve recreationally active subjects (31 ± 8 yr, 183 ± 4 cm, 79 ± 10 kg) pedaled at 80-100 rpm until volitional fatigue with a work rate increase of 30 W every 4 min. Exercise intensity was normalized in each subject to the cycling power peak (Wpeak). Both rectus femoris BFi and MRO2i increased from 15% up to 75% Wpeak and then plateaued to the end of the exercise. During the recovery at 30 W cycling power, BFi remained almost constant while MRO2i started to decrease. The BFi /MRO2i plateau was associated with the rising of the lactate concentration indicating the progressive involvement of the anaerobic metabolism. These findings further highlight the utility of DCS and FDNIRS oximetry as an effective, reproducible, and noninvasive technique to assess muscle BFi and MRO2i in real-time during a dynamic exercise such as cycling.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/138136
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