Visualizing and quantifying cutaneous microvascular reactivity in humans by use of optical coherence tomography:...

The pathophysiology and time course of impairment in cutaneous microcirculatory function and structure remain poorly understood in people with diabetes, partly due to the lack of investigational tools capable of directly imaging and quantifying the microvasculature in vivo. We applied a new optical coherence tomography (OCT) technique, at rest and during reactive hyperemia (RH), to assess the skin microvasculature in people with diabetes with foot ulcers (DFU, n = 13), those with diabetes without ulcers (DNU, n = 9), and matched healthy controls (CON, n = 13). OCT images were obtained from the dorsal part of the foot at rest and following 5 min of local ischemia induced by inflating a cuff around the thigh at suprasystolic level (220 mmHg). One-way ANOVA was used to compare the OCT-derived parameters (diameter, speed, flow rate, and density) at rest and in response to RH, with repeated-measures two-way ANOVA performed to analyze main and interaction effects between groups. Data are means ± SD. At rest, microvascular diameter in the DFU (84.89 ± 14.84 µm) group was higher than CON (71.25 ± 7.6 µm, P = 0.012) and DNU (71.33 ± 12.04 µm, P = 0.019) group. Speed in DFU (65.56 ± 4.80 µm/s, P = 0.002) and DNU (63.22 ± 4.35 µm/s, P = 0.050) were higher than CON (59.58 ± 3.02 µm/s). Microvascular density in DFU (22.23 ± 13.8%) was higher than in CON (9.83 ± 2.94%, P = 0.008), but not than in the DNU group (14.8 ± 10.98%, P = 0.119). All OCT-derived parameters were significantly increased in response to RH in the CON group (all P < 0.01) and DNU group (all P < 0.05). Significant increase in the DFU group was observed in speed (P = 0.031) and density (P = 0.018). The change in density was lowest in the DFU group (44 ± 34.1%) compared with CON (199.2 ± 117.5%, P = 0.005) and DNU (148.1 ± 98.4, P = 0.054). This study proves that noninvasive OCT microvascular imaging is feasible in people with diabetes, provides powerful new physiological insights, and can distinguish between healthy individuals and patients with diabetes with distinct disease severity.