Suitability of the muscle O₂ resaturation parameters most used for assessing reactive hyperemia: a near-infrared spectroscopy study

Adequação de parâmetros de ressaturação muscular de O₂ mais utilizados na avaliação da hiperemia reativa: um estudo por espectroscopia no infravermelho próximo

Abstract

Background

There is a spectrum of possibilities for analyzing muscle O₂ resaturation parameters for measurement of reactive hyperemia in microvasculature. However, there is no consensus with respect to the responsiveness of these O₂ resaturation parameters for assessing reactive hyperemia.

Objectives

This study investigates the responsiveness of the most utilized muscle O₂ resaturation parameters to assess reactive hyperemia in the microvasculature of a clinical group known to exhibit impairments of tissue O₂ saturation (StO₂).

Methods

Twenty-three healthy young adults, twenty-nine healthy older adults, and thirty-five older adults at risk of cardiovascular disease (CVD) were recruited. Near-infrared spectroscopy (NIRS) was used to assess StO₂ after a 5-min arterial occlusion challenge and the following parameters were analyzed: StO_{2slope_10s}, StO_{2slope_30s}, and StO_{2slope_until_baseline} (upslope of StO₂ over 10s and 30s and until StO₂ reaches the baseline value); time to StO_2baseline and time to StO_2max (time taken for StO₂ to reach baseline and peak values, respectively); ∆StO_2reperfusion (the difference between minimum and maximum StO₂ values); total area under the curve (StO_2AUCt); and AUC above the baseline value (StO_{2AUC_above_base}).

Results

Only StO_{2slope_10s} was significantly slower in older adults at risk for CVD compared to healthy young individuals (p < 0.001) and to healthy older adults (p < 0.001). Conversely, time to StO_2max was significantly longer in healthy young individuals than in older adult at CVD risk.

Conclusions

Our findings suggest that StO_{2slope_10s} may be a measure of reactive hyperemia, which provides clinical insight into microvascular function assessment.

Keywords:
cardiovascular physiology; capillary endothelial cells; vascular disease; hypertension; aging

Resumo

Contexto

Existe um espectro de possibilidades na análise dos parâmetros de ressaturação de O₂ muscular como uma medida de hiperemia reativa na microvasculatura. No entanto, não há consenso com relação à responsividade desses parâmetros de ressaturação de O₂ para avaliação de hiperemia reativa.

Objetivos

Este estudo investigou a capacidade de resposta dos parâmetros de ressaturação muscular de O₂ mais utilizados para avaliar a hiperemia reativa na microvasculatura de um grupo clínico conhecido por apresentar comprometimento da saturação de O₂ (StO₂).

Métodos

Foram recrutados 23 jovens saudáveis, 29 idosos saudáveis e 35 idosos com risco para doença cardiovascular. A espectroscopia no infravermelho próximo foi usada para avaliar a StO₂ após um teste de oclusão arterial de 5 minutos, no qual os seguintes parâmetros foram analisados: StO_{2slope_10s}, StO_{2slope_30s} e StO2_{slope_until_baseline} (inclinação da StO₂ em 10 s, 30 s e até StO₂ atingir valores basais); tempo para StO_2baseline e tempo para StO_2máx (o tempo necessário para StO₂ atingir os valores da linha de base e o máximo, respectivamente); ∆StO_2reperfusão (a diferença entre o valor de StO_2mínimo e StO_2máximo); área total sob a curva (StO_2AUCt); e área sob a curva acima do valor da linha de base (StO_{2AUC_above_base}).

Resultados

Apenas StO_{2slope_10s} foi significativamente mais lento em idosos em risco de doença cardiovascular comparados com indivíduos jovens saudáveis (p < 0,001) e idosos saudáveis (p < 0,001). Por outro lado, o tempo para StO_2max foi significativamente maior em indivíduos jovens saudáveis do que em idosos em risco de doença cardiovascular.

Conclusões

Nossos achados sugerem que StO_{2slope_10s} pode ser uma medida de hiperemia reativa, que fornece informações clínicas sobre a avaliação da função microvascular.

Palavras-chave:
fisiologia cardiovascular; células endoteliais capilares; doenças vasculares; hipertensão arterial; envelhecimento

INTRODUCTION

Endothelial dysfunction is an abnormality of the vascular system that predicts a cardiovascular event.^1,2 Assessment of reactive hyperemia in microcirculation has been used as a measure of microvascular function.³ Microvascular dysfunction may lead to rarefaction of downstream vessels and consequent reduction in the number of capillaries, contributing to hypertension and cardiovascular events.⁴ Moreover, downstream arterial disease may reduce muscle blood supply, leading to fatigue, cramp, discomfort, or pain in limbs during daily activities.⁵ Therefore, measuring microvascular function may be important for identification of pathophysiologic mechanisms that impair adequate tissue blood perfusion.

Over the past decades, near-infrared spectroscopy (NIRS) combined with a vascular occlusion test (VOT) has been used for assessment of tissue O₂ saturation (StO₂). Since NIRS detects changes in oxygenated and deoxygenated hemoglobin in the tissues using absorption of near-infrared light at a specific wavelength,^6,7 oxygenation kinetics in the microcirculation (i.e., arterioles, venules, and capillaries) can be noninvasively assessed and used to measure reactive hyperemia in microcirculation.^6,8

Performing a VOT with an NIRS device fitted to the limb of interest, the StO₂ signal follows a downward path during the cuff inflation phase and then StO₂ goes rapidly upward immediately after cuff deflation (reperfusion phase).^8-10 The sudden increase in the StO₂ signal during reperfusion enables various StO₂ parameters to be calculated, which, in general, are interpreted as measures of microvascular function.³ The majority of StO₂ parameters adopted in previous studies include reperfusion rate (i.e., upslope of the StO₂ signal during the initial 10 s and 30 s, and until the StO₂ signal reaches baseline values),^11-13 magnitude of reperfusion (i.e., total area under the curve [AUC] of StO₂ and the difference between the lowest and highest StO₂ value),^4,13-17 and others (e.g., time to StO₂ baseline, time to StO₂ maximum, and AUC above the baseline).^13,15,18,19

Despite a range of possibilities for interpretation of muscle O₂ resaturation parameters, the lack of standardization of which NIRS parameters are used during the reperfusion phase makes comparisons between studies difficult and/or may even lead to misinterpretation of results. For example, since the time to maximum StO₂ parameter is calculated as the time elapsed from release of the cuff to the maximum StO₂ value during reperfusion, individuals with higher O₂ extraction capacity (i.e., healthy young individuals) might exhibit a longer time to maximum StO₂. In other words, in individuals with higher O₂ extraction, the distance between the lowest StO₂ value reached during cuff inflation and the highest StO₂ reached during the cuff deflation is longer, thereby influencing calculation of some NIRS parameters, such as time to StO₂ maximum and even area under the reperfusion curve. Therefore, the present study investigates the usefulness of the muscle O₂ resaturation parameters most utilized to assess reactive hyperemia in a clinical group known to exhibit impairments in muscle StO₂. It was hypothesized that some NIRS parameters might be more sensitive than others (mainly those influenced by muscle O₂ extraction) for detecting abnormal reactive hyperemia in a clinical sample.

METHODS

Participants

Twenty-three healthy young individuals, 29 healthy older adults, and 35 older adults at risk of CVD were recruited to participate in the study. For the younger group, inclusion criteria were being healthy (not presenting CVD risk factors) and age < 35 years. For the healthy older adult group, individuals had to be healthy and ≥ 60 years of age. The inclusion criteria for older adults at high risk for CVD were age ≥ 60 years and possessing at least four CVD risk factors, according to a previous study demonstrating that presence of three or more CVD risk factors is related to microvascular dysfunction.^10,20 The following CVD risk factors were used as inclusion criteria: triglycerides ≥ 150 mg/dL; total-cholesterol ≥ 200 mg/dL; LDL-cholesterol ≥ 150 mg/dL, HDL-cholesterol ≤ 40 mg/dL for men and ≤ 50 mg/dL for women; high-blood glucose ≥ 120 mg/dL and/or taking oral hypoglycemic medications; and high systolic blood pressure (SBP) ≥ 135 mm Hg, and/or high diastolic blood pressure (DBP) ≥ 90 mm Hg, and/or taking anti-hypertensive medications. The exclusion criteria included human immunodeficiency virus (HIV); cancer; rheumatoid arthritis; smoking; and chronic obstructive pulmonary disease; as well as participants not being engaged in any exercise program. All experimental procedures were performed after explaining the nature of the study and obtaining written consent from participants. The study was conducted in accordance with declaration of Helsinki ethical standards and approved by the institutional ethics committee at the Universidade Federal do Rio de Janeiro (UFRJ), Macaé, RJ, Brasil. (N^o. 1.489.668).

Experimental protocol

After 12 h fasting, the participants arrived at the laboratory, where they underwent anthropometric measurement (weight, height, and forearm skin-fold) before blood samples were taken. Blood samples were collected only at baseline in order to determine the CVD risk factors (i.e., fasting blood glucose, triglycerides, cholesterol, etc.) of the participants enrolled on the study. Afterwards, participants rested for 10 min in the supine position on an examination table, followed by assessment of the NIRS parameters for level of muscle oxygen saturation. The experimental procedures were conducted between 8:00 and 10:00 a.m. and participants were recommended to avoid caffeine and foods rich in nitrates and nitrites for 24 h before the laboratory visit.

Tissue O₂ saturation measurement

Tissue O₂ saturation (%StO₂) was assessed using an NIRS system (PortaMon, Artinis, Medical Systems) connected to a personal computer via Bluetooth for data acquisition (10 Hz). Analogue‐to‐digital conversion and subsequent analysis of the raw data (i.e., no filter was used) was conducted using native software (Oxysoft version 2.1.6; Artinis Medical Systems), as previously described by Oliveira et al.^7,10 In brief, the NIRS device was placed on the forearm flexor muscle (flexor carpi radialis), 2 cm below the medial epicondyle of the humerus, and muscle %StO₂ was recorded continuously throughout the VOT (30 s at baseline, 5 min of occlusion, and 2 min of reperfusion). The cuff was placed over the arm, 2 cm above the medial epicondyle of the humerus and a cuff pressure of 250 mm Hg was used during the occlusion period (Figure 1). To evaluate muscle StO₂ during ischemia and reperfusion, the following NIRS parameters were used in the statistical analysis: (i) StO₂ during baseline (StO_2base, %) was calculated as the average over the 30 s before cuff occlusion; (ii) the lowest StO₂ value reached during cuff inflation (StO_2min) and the highest StO₂ value reached following cuff deflation (StO_2max); (iii) time for the StO₂ signal to reach its peak after cuff release (time to StO_2max); (iv) time for the StO₂ signal to reach the pre-occlusion baseline value after cuff release (time to StO_2base); (v) difference between StO_2min and the StO_2max after cuff deflation (ΔStO_2reperfusion); (vi) the area under the reperfusion curve (AUC) above the baseline (StO_{2AUCabove_base}); (vii) the total AUC over 2 minutes of reperfusion (StO_2AUCt); (viii) upslope of StO₂ signal over a 10 s reperfusion window immediately following cuff deflation (StO_{2slope_10s}); (ix) upslope of StO₂ signal over a 30 s reperfusion window immediately following cuff deflation (StO_{2slope_30s}); and (x) upslope of StO₂ signal over the time elapsed between StO_2min and reaching pre-occlusion baseline StO₂ values (Figure 2).

Figure 1
Cuff and near-infrared spectroscopy (NIRS) probe on skin overlying forearm flexor muscles. Note that in the picture the NIRS probe is shown without the black vinyl sheet and the elastic tensor band that cover it, for the purposes of illustrating the probe location in the image.

Figure 2
Near-infrared spectroscopy (NIRS)-derived tissue O₂ saturation (StO₂) signal analysis during cuff deflation phase (reperfusion). (A) The lowest StO₂ value reached during cuff inflation (StO_2min) and the highest StO₂ value reached following cuff deflation (StO_2max); (B) time for the StO₂ signal to reach the peak after cuff release (time to StO_2max); (C) time for the StO₂ signal to reach the pre-occlusion baseline values after cuff release (time to StO_2base); (D) difference between the StO_2min and StO_2max after cuff deflation (ΔStO_2reperfusion); (E) area under the reperfusion curve (AUC) above the baseline (StO_{2AUCabove_base}); (F) the total AUC over 2 minutes of reperfusion (StO_2AUCt); (G) upslope of StO₂ signal over a 10 s reperfusion window immediately following cuff deflation (StO_{2slope_10s}); (H) upslope of StO₂ signal over a 30 s reperfusion window immediately following cuff deflation (StO_{2slope_30s}); and (I) upslope of StO₂ signal over the time elapsed between StO_2min and pre-occlusion baseline StO₂ values.

Statistical analysis

One-way ANOVA was used to identify significant differences between the characteristics of the participants at baseline and tissue StO₂ parameters during the VOT. An a priori power analysis was conducted (G*Power v. 3.0.1) for a specific test (ANOVA: Fixed effects, omnibus, one-way). Based on a statistical power (1 – β) of 0.80, an effect size of 0.46, and an overall significance level of 0.05, 51 participants would be needed to detect a statistical difference. The effect size was based on a previous study that found d=0.93 (or f=0.46; d=2f) when assessing reperfusion rates in older individuals and young participants.¹⁷ The present study enrolled 87 participants. Additional post hoc tests with Bonferroni adjustment were performed when appropriate. Statistical significance was set at a P value ≤ 0.05 and the results were expressed as mean ± standard deviation (SD). A commercially available statistical package (IBM SPSS Statistics version 22 for Mac, Armonk, N.Y., USA) was used for statistical analysis. The figure was designed using GraphPad Prism 5.0.

RESULTS

Baseline characteristics of the participants and medications used are shown in Table 1. Healthy young individuals exhibited significant lower body mass index than healthy older adults (P = 0.029) and than older adults at risk for CVD (P = 0.016). Blood glucose (P < 0.001), total cholesterol (P = 0.004), triglycerides (P = 0.049), and systolic blood pressure (P = 0.001) were significantly higher in older adults at risk for CVD than in healthy young individuals. Moreover, blood glucose (P < 0.001), triglycerides (P = 0.026), and systolic blood pressure (P = 0.012) were significantly higher than in healthy older adults.

Table 1
Baseline characteristics of the participants.

Demographics	Young healthy	Older healthy	Older, at risk of CVD
N	23	29	35
Male/female	14/9	13/16	14/21
Age (years)	28.4 ± 5.9	67.6 ± 5.8	68.4 ± 8.2
Weight (kg)	74.8 ± 9.3	77.9 ± 13.8	72.6 ± 11.2
Height (cm)	171.8 ± 0.1	168.4 ± 0.8	169.5 ± 0.6
Body mass index (kg/m2)	25.2 ± 1.8	30.1 ± 4.1*	30.1 ± 8.8*
Forearm skin fold thickness (mm)	2.1 ± 0.4	2.3 ± 0.6	2.3 ± 0.8
Biochemistry
Blood glucose (mg/dL)	87.91 ± 6.9	90.2 ± 13.4	123.9 ± 41.8*†
Total cholesterol (mg/dL)	157.3 ± 30.1	170.8 ± 30.1	190.3 ± 44.3*
LDL-cholesterol (mg/dL)	121.9 ± 33.1	110.2 ± 31.6	125.0 ± 42.2
HDL-cholesterol (mg/dL)	39.7 ± 8.9	44.7 ± 10.9	37.9 ± 13.4
Triglycerides (mg/dL)	121.2 ± 33.7	112.3 ± 29.4	146.5 ± 64.9*†
Clinical
SBP (mm Hg)	122.1 ± 10.1	125.8 ± 4.4	136.8 ± 20.6*†
DBP (mm Hg)	80.3 ± 5.2	80.8 ± 9.1	81.6 ± 9.2
Medications used	n	n	n
ACE-i/ARB	-	-	22
Diuretic	-	-	17
α-blocker	-	-	1
β-blocker	-	-	10
CCB	-	-	6
Antiplatelet drugs	-	-	5
Statins	-	-	12

• N = number; CVD = cardiovascular disease; SBP = systolic blood pressure; DBP = diastolic blood pressure; ACE-I = angiotensin converting enzyme inhibitors; ARB = angiotensin receptor blockers; CCB = calcium channel blockers.
• ^*
  Significantly different from healthy young group;
• ^†
  Significantly different from healthy older adults. Statistical significance was set at the 0.05 level of confidence. Values were expressed as means ± standard deviation.

Muscle StO₂ saturation parameters are shown in Table 2. Significantly slower StO_2slope__10s (P < 0.001), and StO_2slope__30s (P < 0.001), and blunted ΔStO_2reperfusion (P < 0.001), StO_{2AUCabove_base} (P < 0.001), StO_2AUCt (P < 0.001), StO_2max (P = 0.035), and StO_{2 min} (P < 0.001) were observed in older adults at CVD risk compared to healthy young individuals. Additionally, StO_2slope__10s was significantly slower (P < 0.001) in older adults at risk for CVD compared to their healthy counterparts. Time to StO_2max was significantly slower (P = 0.047) in healthy young individuals than older adults at risk of CVD.

Table 2
Muscle O₂ saturation parameters in healthy young individuals and older adults with cardiovascular disease (CVD) risk factors.

Variables	Young healthy	Older healthy	Older, at risk of CVD
StO2base (%)	69.39 ± 5.10	70.91 ± 3.45	70.28 ± 3.52
StO2slope_10s (%.s-1)	1.36 ± 0.48	1.02 ± 0.34*	0.48 ± 0.44*†
StO2slope_30s (%.s-1)	1.21 ± 0.35	0.90 ± 0.31*	0.75 ± 0.27*
StO2slope_until_base (%.s-1)	1.24 ± 0.41	1.09 ± 0.37	0.98 ± 0.40
Time to StO2base (s)	22.39 ± 11.53	20.34 ± 6.21	19.00 ± 6.55
Time to StO2max (s)	54.17 ± 19.58	46.82 ± 16.64	44.68 ± 14.76*
ΔStO2reperfusion (%)	36.04 ± 9.91	26.30 ± 8.24*	22.79 ± 7.46*
StO2AUCabove_base (%. s)	1137.77 ± 321.99	860.31 ± 310.43*	699.62 ± 309.78*
StO2AUCt (%. s)	3578.34 ± 1046.77	2663.58 ± 765.86*	2348.91 ± 739.57*
StO2max (%)	79.98 ± 5.11	78.73 ± 3.49	77.24 ± 3.41*
StO2min (%)	44.00 ± 10.39	52.33 ± 7.40*	54.44 ± 8.11*

• ^*
  Significantly different from young group;
• ^†
  Significantly different from healthy older adults. Statistical significance was set at the 0.05 level of confidence. Values were expressed as means ± SD. Base = baseline; AUC = area under the curve; StO₂ = tissue O₂ saturation

Significant slower StO_{2slope_30s} (P = 0.003) and blunted ΔStO_2reperfusion (P < 0.001), StO_{2AUCabove_base} (P = 0.006), StO_2AUCt (P = 0.001), and StO_{2 min} (P = 0.002) were found in healthy older adults compared to healthy young people. No significant differences in StO_2base, time to StO_2base, or StO_{2slope_until_base} were found between groups (P > 0.05).

DISCUSSION

Given the widespread utilization of NIRS devices and the spectrum of possibilities for analyzing muscle O₂ resaturation parameters as a measurement of reactive hyperemia in the microvasculature of different populations, the present study investigated the effectiveness of the O₂ resaturation parameters most frequently used for evaluating reactive hyperemia in healthy older adults or older adults with CVD risk factors. It was hypothesized that analyzing the effectiveness of the most widespread NIRS parameters for detecting aging and CVD risk factors might help with development of criteria for establishing an appropriate set of muscle StO₂ parameters in order to facilitate the choice between different methodologies of NIRS analysis.

Muscle O₂ resaturation rate parameters (StO_2slope__10s, StO_2slope__30s, and StO_2slope__{until_base}) are largely adopted to assess reactive hyperemia in hypertensive individuals,⁴ gestational diabetic women,¹⁴ and older adults at risk for CVD disease,^7,10,17 among other clinical groups.^13,18 Our findings demonstrated that only StO_2slope__10s was significantly slower in older adults with CVD risk factors compared to healthy older adults and to healthy young individuals, suggesting that StO_{2slope_10s} may be a more sensitive NIRS parameter for assessing reactive hyperemia. The StO_2slope__10s has typically been adopted to assess O₂ resaturation rate, since previous studies have reported that this parameter is correlated with reactive hyperemia measured in the brachial artery²⁰ and with FMD response.^8,11 It has been postulated that the StO_2slope__10s may be a stimulus for FMD response given that FMD is evoked by increasing blood flow after cuff release.^8,20,21 In addition, utilizing the StO_{2slope_10s} may be considered an appropriate way to analyze O₂ reperfusion rate given the linearity of the StO₂ signal over the initial 10 s after cuff release.²²

Time to StO_2max may be mainly affected by the degree of muscle O₂ extraction (StO_2min), since this recovery time parameter measures the time interval between the StO_2min (the lowest StO₂ value reached during cuff inflation) and StO_2max (the highest StO₂ value reached during cuff deflation). Therefore, individuals with higher muscle O₂ extraction capacity (mitochondrial function) will reach a lower StO₂ value during the cuff inflation phase (StO_2min), which makes the time to StO_2max longer for those individuals with higher O₂ extraction capacity.^17,23 In support of this observation, a significantly longer time to StO_2max was found in healthy individuals compared to older adults at CVD risk, which may have been the result of a lower StO₂ value reached during cuff inflation (StO_2min), combined with the higher StO₂ value reached during the cuff deflation phase (StO_2max).

Previous studies have failed to show significant differences in time to StO_2max in individuals with metabolic syndrome²⁴ and older adults at risk for CVD.¹⁰ However, Kragelj et al.¹⁸ found a significantly longer time to StO_2max in individuals with peripheral vascular disease (a clinical population) compared to healthy participants. Interestingly, the groups investigated in their study¹⁸ did not exhibit a significant difference in O₂ extraction parameters, which may explain the expected longer time to StO_2max in individuals with peripheral vascular disease. Therefore, adoption of the recovery time parameters (i.e., time to StO_2max) should be recommended when the clinical population evaluated is not assumed to exhibit impairment in muscle O₂ extraction; otherwise, data interpretation and comparison may be rendered incorrect.

The current study also demonstrated a significant reduction in ΔStO_2reperfusion and StO_2AUCt in healthy older adults and those with CVD risk factors, compared to healthy young individuals. However, no significant difference was observed in these parameters in healthy older adults compared to older adults at risk for CVD, suggesting that ΔStO_2reperfusion and StO_2AUCt are not sensitive parameters for detecting the effect of CVD risk factors on reactive hyperemia. The ΔStO_2reperfusion and StO_2AUCt parameters can be interpreted as measures of the magnitude of O₂ resaturation, since the lowest and highest StO₂ value (amplitude) within the reperfusion phase (cuff deflation) are considered for calculating these parameters. However, it is important to note that, in common with time to StO_2max, these parameters may also be affected by parameters of muscle O₂ extraction during cuff deflation (i.e. StO_2min).

Corroborating this idea, Rosenberry et al.¹⁷ demonstrated that the impaired StO_2AUCt observed in older adults at CVD risk in comparison to healthy young individuals was eliminated when the level of muscle O₂ extraction (StO_2min) was standardized by varying occlusion times (3-, 4-, and 5-min cuff occlusion) across the two age groups. It is likely that differences between ΔStO_2reperfusion and StO_2AUCt parameters do not only necessarily reflect impairment in O₂ resaturation magnitude (reactive hyperemia), but also in muscle O₂ extraction during occlusion (mitochondrial dysfunction).^7,17 In light of these findings, since NIRS continuously monitors muscle O₂ saturation throughout the VOT, assessment of ΔStO_2reperfusion and StO_2AUCt could be performed controlling the level of tissue ischemia (varying the occlusion times),¹⁷ which would be crucial to better interpret ΔStO_2reperfusion and StO_2AUCt. Alternatively, AUC_{above_base} is not affected by muscle StO_2min and its utilization might be recommendable.

Experimental considerations

Of note, the NIRS system is a relevant tool that can be easily used during vascular surgery, as it continuously assesses muscle O₂ saturation. For example, a previous study conducted at our laboratory showed that prolonged occlusion of limb blood flow (i.e., tourniquet application during limb surgery) causes transient microvascular dysfunction that can be assessed by NIRS‐derived reperfusion upslope.²⁵ Additionally, this study also demonstrated that using a local nitric oxide donor (transdermal nitroglycerin) administered during prolonged forearm cuff occlusion protected against this microvascular dysfunction,²⁵ which is relevant for the field of vascular surgery. Moreover, NIRS systems have been widely utilized to detect impaired microvascular reactivity in many clinical populations, such as hypertension, older adults at risk for CVD, and patients with metabolic syndrome.^4,10,24

Although NIRS systems are largely utilized to assess oxygenation of the forearm muscles, one limitation of this technique is the discrete volume of a specific muscle (2 to 6 cm) and the superficial area of skeletal muscle that NIRS examines.²⁶ Furthermore, another important factor that should be considered is that adipose tissue thickness can affect NIR light penetration into the muscle of interest and, consequently, the muscle oxygenation levels measured. However, it is important to point out that no significant differences were observed in skin fold thickness between groups, ensuring that the depth of light penetration (~18 mm) sufficiently interrogates the forearm flexor muscles.^26,27 Additionally, it is noteworthy that all participants in this study did not undergo a clinical examination by a clinician prior to muscle oxygenation measurements. Although we are aware that it would be important for all participants to undergo clinical examination, the main purpose of this study was to investigate the effectiveness of tissue oxygenation parameters in detecting impaired reactive hyperemia in the microvasculature of a population previously known to have microvascular damage.^3,4,7,9 Therefore, the absence of clinical examination does not compromise the results of this study.

In conclusion, the findings of this study suggest that StO_{2slope_10s} was the most sensitive NIRS parameter for assessing reactive hyperemia. Additionally, the magnitude of reperfusion (i.e., StO_2AUCt) and recovery time (i.e., time to StO_2max) parameters should be interpreted with caution when assessing clinical populations, since muscle O₂ extraction may affect those parameters. The results of the present study will be helpful for future studies that investigate the effect of an external factor (disease, means of treatment, etc.) on muscle O₂ resaturation parameters.

ACKNOWLEDGMENTS

Gustavo Oliveira and Mônica Volino Souza acknowledge the financial support provided by the Fundação Carlos Chagas de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) (E-26/200.021/2020) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), respectively. Dr. Thiago S. Alvares was supported by Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) – Jovem Cientista do Nosso Estado Grant Program (E-26/202.905/2019) – and by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) – research productivity fellow (304189/2020-0).

• How to cite: Oliveira GV, Volino-Souza M, Leitão R, Pinheiro V, Conte-Júnior CA, Alvares TS. Suitability of the muscle O2 resaturation parameters most used for assessing reactive hyperemia: a near-infrared spectroscopy study. J Vasc Bras. 2021;20:e20200143. https://doi.org/10.1590/1677-5449.200143
• Financial support: Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brasil.
• The study was carried out at Universidade Federal do Rio de Janeiro (UFRJ), Macaé, RJ, Brazil.

REFERENCES

• ¹
  Martin BJ, Anderson TJ. Risk prediction in cardiovascular disease: the prognostic significance of endothelial dysfunction. Can J Cardiol. 2009;25(Suppl A):15A-20A. http://dx.doi.org/10.1016/S0828-282X(09)71049-9 PMid:19521569.
  » http://dx.doi.org/10.1016/S0828-282X(09)71049-9
• ²
  Thijssen DHJ, Bruno RM, van Mil ACCM, et al. Expert consensus and evidence-based recommendations for the assessment of flow-mediated dilation in humans. Eur Heart J. 2019;40(30):2534-47. http://dx.doi.org/10.1093/eurheartj/ehz350 PMid:31211361.
  » http://dx.doi.org/10.1093/eurheartj/ehz350
• ³
  Rosenberry R, Nelson MD. Reactive hyperemia: a review of methods, mechanisms, and considerations. Am J Physiol Regul Integr Comp Physiol. 2020;318(3):R605-18. http://dx.doi.org/10.1152/ajpregu.00339.2019 PMid:32022580.
  » http://dx.doi.org/10.1152/ajpregu.00339.2019
• ⁴
  Dipla K, Triantafyllou A, Koletsos N, et al. Impaired Muscle Oxygenation and Elevated Exercise Blood Pressure in Hypertensive Patients: Links With Vascular Stiffness. Hypertension. 2017;70(2):444-51. http://dx.doi.org/10.1161/HYPERTENSIONAHA.117.09558 PMid:28607132.
  » http://dx.doi.org/10.1161/HYPERTENSIONAHA.117.09558
• ⁵
  Parmenter BJ, Mavros Y, Ritti Dias R, King S, Fiatarone Singh M. Resistance training as a treatment for older persons with peripheral artery disease: a systematic review and meta-analysis. Br J Sports Med. 2020;54(8):452-61. PMid:30979698.
• ⁶
  Ferrari M, Mottola L, Quaresima V. Principles, techniques, and limitations of near infrared spectroscopy. Can J Appl Physiol. 2004;29(4):463-87. http://dx.doi.org/10.1139/h04-031 PMid:15328595.
  » http://dx.doi.org/10.1139/h04-031
• ⁷
  de Oliveira GV, Volino-Souza M, Leitão R, Pinheiro V, Alvares TS. Is flow-mediated dilatation associated with near-infrared spectroscopy-derived magnitude of muscle O₂ desaturation in healthy young and individuals at risk for cardiovascular disease? Microvasc Res. 2020;129:103967. http://dx.doi.org/10.1016/j.mvr.2019.103967 PMid:31837305.
  » http://dx.doi.org/10.1016/j.mvr.2019.103967
• ⁸
  McLay KM, Fontana FY, Nederveen JP, et al. Vascular responsiveness determined by near-infrared spectroscopy measures of oxygen saturation. Exp Physiol. 2016;101(1):34-40. http://dx.doi.org/10.1113/EP085406 PMid:26498127.
  » http://dx.doi.org/10.1113/EP085406
• ⁹
  Oliveira GV, Soares RN, Volino-Souza M, Murias JM, Alvares TS. The association between near-infrared spectroscopy assessment of microvascular reactivity and flow-mediated dilation is disrupted in individuals at high risk for cardiovascular disease. Microcirculation. 2019;26(7):e12556. http://dx.doi.org/10.1111/micc.12556 PMid:31077636.
  » http://dx.doi.org/10.1111/micc.12556
• ¹⁰
  de Oliveira GV, Soares RN, Volino-Souza M, Leitão R, Murias JM, Alvares TS. The effects of aging and cardiovascular risk factors on microvascular function assessed by near-infrared spectroscopy. Microvasc Res. 2019;126:103911. http://dx.doi.org/10.1016/j.mvr.2019.103911 PMid:31425692.
  » http://dx.doi.org/10.1016/j.mvr.2019.103911
• ¹¹
  Soares RN, Somani YB, Proctor DN, Murias JM. The association between near-infrared spectroscopy-derived and flow-mediated dilation assessment of vascular responsiveness in the arm. Microvasc Res. 2019;122:41-4. http://dx.doi.org/10.1016/j.mvr.2018.11.005 PMid:30445134.
  » http://dx.doi.org/10.1016/j.mvr.2018.11.005
• ¹²
  Papadopoulos S, Dipla K, Triantafyllou A, et al. Beetroot increases muscle performance and oxygenation during sustained isometric exercise, but does not alter muscle oxidative efficiency and microvascular reactivity at rest. J Am Coll Nutr. 2018;37(5):361-72. http://dx.doi.org/10.1080/07315724.2017.1401497 PMid:29425473.
  » http://dx.doi.org/10.1080/07315724.2017.1401497
• ¹³
  Townsend DK, Deysher DM, Wu EE, Barstow TJ. Reduced insulin sensitivity in young, normoglycaemic subjects alters microvascular tissue oxygenation during postocclusive reactive hyperaemia. Exp Physiol. 2019;104(6):967-74. http://dx.doi.org/10.1113/EP087216 PMid:31020733.
  » http://dx.doi.org/10.1113/EP087216
• ¹⁴
  Dipla K, Triantafyllou A, Grigoriadou I, et al. Impairments in microvascular function and skeletal muscle oxygenation in women with gestational diabetes mellitus: links to cardiovascular disease risk factors. Diabetologia. 2017;60(1):192-201. http://dx.doi.org/10.1007/s00125-016-4129-7 PMid:27722775.
  » http://dx.doi.org/10.1007/s00125-016-4129-7
• ¹⁵
  Le Roux-Mallouf T, Vibert F, Doutreleau S, Verges S. Effect of acute nitrate and citrulline supplementation on muscle microvascular response to ischemia-reperfusion in healthy humans. Appl Physiol Nutr Metab. 2017;42(9):901-8. http://dx.doi.org/10.1139/apnm-2017-0081 PMid:28460182.
  » http://dx.doi.org/10.1139/apnm-2017-0081
• ¹⁶
  Ramos Gonzalez M, Caldwell JT, Branch PA, et al. Impact of shear rate pattern on post-occlusive near-infrared spectroscopy microvascular reactivity. Microvasc Res. 2018;116:50-6. http://dx.doi.org/10.1016/j.mvr.2017.10.004 PMid:29080792.
  » http://dx.doi.org/10.1016/j.mvr.2017.10.004
• ¹⁷
  Rosenberry R, Munson M, Chung S, et al. Age-related microvascular dysfunction: novel insight from near-infrared spectroscopy. Exp Physiol. 2018;103(2):190-200. http://dx.doi.org/10.1113/EP086639 PMid:29114952.
  » http://dx.doi.org/10.1113/EP086639
• ¹⁸
  Kragelj R, Jarm T, Erjavec T, Presern-Strukelj M, Miklavcic D. Parameters of postocclusive reactive hyperemia measured by near infrared spectroscopy in patients with peripheral vascular disease and in healthy volunteers. Ann Biomed Eng. 2001;29(4):311-20. http://dx.doi.org/10.1114/1.1359451 PMid:11339328.
  » http://dx.doi.org/10.1114/1.1359451
• ¹⁹
  Mattu AT, MacInnis MJ, Doyle-Baker PK, Murias JM. Effects of the menstrual and oral contraceptive cycle phases on microvascular reperfusion. Exp Physiol. 2020;105(1):184-91. http://dx.doi.org/10.1113/EP088135 PMid:31625647.
  » http://dx.doi.org/10.1113/EP088135
• ²⁰
  Rosenberry R, Trojacek D, Chung S, Cipher DJ, Nelson MD. Interindividual differences in the ischemic stimulus and other technical considerations when assessing reactive hyperemia. Am J Physiol Regul Integr Comp Physiol. 2019;317(4):R530-8. http://dx.doi.org/10.1152/ajpregu.00157.2019 PMid:31314545.
  » http://dx.doi.org/10.1152/ajpregu.00157.2019
• ²¹
  Tremblay JC, King TJ. Near-infrared spectroscopy: can it measure endothelial function? Exp Physiol. 2016;101(11):1443-4. http://dx.doi.org/10.1113/EP085902 PMid:27620539.
  » http://dx.doi.org/10.1113/EP085902
• ²²
  Soares RN, Oliveira GV, Alvares TS, Murias JM. The effects of the analysis strategy on the correlation between the NIRS reperfusion measures and the FMD response. Microvasc Res. 2020;127:103922. http://dx.doi.org/10.1016/j.mvr.2019.103922 PMid:31479661.
  » http://dx.doi.org/10.1016/j.mvr.2019.103922
• ²³
  Ryan TE, Brophy P, Lin CT, Hickner RC, Neufer PD. Assessment of in vivo skeletal muscle mitochondrial respiratory capacity in humans by near-infrared spectroscopy: a comparison with in situ measurements. J Physiol. 2014;592(15):3231-41. http://dx.doi.org/10.1113/jphysiol.2014.274456 PMid:24951618.
  » http://dx.doi.org/10.1113/jphysiol.2014.274456
• ²⁴
  Gayda M, Juneau M, Tardif JC, Harel F, Levesque S, Nigam A. Cardiometabolic and traditional cardiovascular risk factors and their potential impact on macrovascular and microvascular function: preliminary data. Clin Hemorheol Microcirc. 2015;59(1):53-65. http://dx.doi.org/10.3233/CH-141816 PMid:24518371.
  » http://dx.doi.org/10.3233/CH-141816
• ²⁵
  Soares RN, Proctor DN, Oliveira GV, Alvares TS, Murias JM. Acute application of a transdermal nitroglycerin patch protects against prolonged forearm ischemia‐induced microvascular dysfunction. Microcirculation. 2020;27(3):e12599. http://dx.doi.org/10.1111/micc.12599 PMid:31782855.
  » http://dx.doi.org/10.1111/micc.12599
• ²⁶
  Grassi B, Quaresima V. Near-infrared spectroscopy and skeletal muscle oxidative function in vivo in health and disease: a review from an exercise physiology perspective. J Biomed Opt. 2016;21(9):091313. http://dx.doi.org/10.1117/1.JBO.21.9.091313 PMid:27443955.
  » http://dx.doi.org/10.1117/1.JBO.21.9.091313
• ²⁷
  van Beekvelt MC, Borghuis MS, van Engelen BG, Wevers RA, Colier WN. Adipose tissue thickness affects in vivo quantitative near-IR spectroscopy in human skeletal muscle. Clin Sci. 2001;101(1):21-8. http://dx.doi.org/10.1042/cs1010021 PMid:11410110.
  » http://dx.doi.org/10.1042/cs1010021

Publication Dates

• Publication in this collection
  24 May 2021
• Date of issue
  2021

History

• Received
  14 Aug 2020
• Accepted
  12 Oct 2020