Flowmotion Monitored by Flow Mediated Skin Fluorescence (FMSF): A Tool for Characterization of Microcirculatory Status

Abstract

Oscillations in the microcirculation, known as flowmotion, are a well-recognized characteristic of cutaneous blood flow. Since flowmotion reflects the microcirculatory status of the vascular system, which is very often impaired in many diseases and disorders, a quantitative assessment of skin flowmotion could potentially be used to screen for early symptoms of such conditions. In this study, skin flowmotion was monitored using the Flow Mediated Skin Fluorescence (FMSF) technique. The flowmotion parameter was used for quantitative assessment of basal flowmotion both at rest (FM) and during reperfusion [FM(R)] following the post-occlusive reactive hyperemia (PORH). The study population was composed of healthy volunteers between the ages of 30 and 72 (n = 75). The FM parameter showed an inverse dependence relative to age, while the FM(R) parameter was inversely correlated to blood pressure. The FM(R) parameter reflects the strong effect of hypoxia on flowmotion, which is mainly due to increased myogenic activity in the vessels. The FMSF technique appears to be uniquely suited for the analysis of basal flowmotion and the hypoxia response, and may be used for the characterization of microcirculatory status.

Keywords: FMSF technique; NADH fluorescence; microcirculation; response to hypoxia; skin flowmotion.

FIGURE 1

Exemplary FMSF trace recorded for a healthy volunteer (male, age 35 years). Black lines – second order polynomial baselines (see detailed explanation in the text).

FIGURE 2

Correlation between power spectra density (PSD × 10⁶) value and FM parameter.

FIGURE 3

(A) Exemplary FMSF signal trace observed for a healthy volunteer (male, age 72 years). Power spectrum density (PSD), calculated a mean squared amplitude of the FFT of the signal. Pie chart shows the presence of three components in flowmotion: endothelial (endo), neurogenic (neuro) and myogenic (myo). (B) Heartbeat oscillations seen in the FMSF signal, over a 25 s period of time.

FIGURE 4

Correlation between the basal flowmotion parameter FM and age (protocol 1, females – circles and males – triangles). Code 043 denotes a result FM = 165 above the upper prediction band (female, age 39 years).

FIGURE 5

Exemplary FMSF traces recorded for: (A) a patient with high flowmotion response to hypoxia (male, age 30 years), (B) a patient with low flowmotion response to hypoxia (male, age 34 years). Calculated flowmotion parameters and contribution of different frequency activities to flowmotion are shown below the traces.

FIGURE 6

(A) Comparison of the flowmotion parameters at rest FM and at reperfusion stage FM(R). (B) Contribution of the myogenic component to FM parameter (myo) and FM(R) parameter (myo(R)) (p-values were calculated using the paired-sample Wilcoxon signed rank test).

FIGURE 7

Correlation between the flowmotion parameter at reperfusion stage FM(R) and the basal flowmotion parameter FM (females – circles and males – triangles). Squares denote the individuals with disturbed flowmotion response to hypoxia (shown in Table 2). Code 110 denotes a result FM(R) = 269 above the upper prediction band (female, age 30 years).

FIGURE 8

Correlation between the flowmotion parameter at reperfusion stage FM(R) and myogenic component myo(R) (protocol 2, females – circles and males – triangles). Squares denote the individuals with disturbed flowmotion response to hypoxia (shown in Table 2).

FIGURE 9

Correlation between the flowmotion parameter at reperfusion stage FM(R) and systolic (A) and diastolic (B) blood pressure (protocol 2, females – circles and males – triangles). Squares denote the individuals with disturbed flowmotion response to hypoxia (shown in Table 2). Code 110 denotes a result FM(R) = 269 above the upper prediction band (female, age 30 years)