In vivo laser speckle imaging reveals microvascular remodeling and hemodynamic changes during wound healing angiogenesis

Abstract

Laser speckle contrast imaging (LSCI) is a high-resolution and high contrast optical imaging technique often used to characterize hemodynamic changes in short-term physiological experiments. In this study, we demonstrate the utility of LSCI for characterizing microvascular remodeling and hemodynamic changes during wound healing angiogenesis in vivo. A 2 mm diameter hole was made in the mouse ear and the periphery of the wound imaged in vivo using LSCI over 12 days. We were able to visualize and quantify the vascular and perfusion changes that accompanied wound healing in the microenvironment proximal to the wound, and validated these changes with histology. We found that consistent with the stages of wound healing, microvessel density increased during the initial inflammatory phase (i.e., day 0–3), stayed elevated through the tissue formation phase (i.e., until day 7) and returned to baseline during the tissue remodeling phase (i.e., by day 12). Concomitant ‘‘wide area mapping’’ of blood flow revealed that tissue perfusion in the wound periphery initially decreased, gradually increased from day 3–7, and subsided as healing completed. Interestingly, some regions exhibited a reestablishment of tissue perfusion approximately 6 days earlier than the ∼ 18 days usually reported for the long term remodeling phase. The results from this study demonstrate that LSCI is an ideal platform for elucidating in vivo changes in microvascular hemodynamics and angiogenesis, and has the potential to offer invaluable insights in a range of disease models involving abnormal hemodynamics, such as diabetes and tumors.

Quantifying the vascular response to ischemia with speckle variance optical coherence tomography

“…In addition to the importance of understanding these processes at a basic science level, the ability to quantitatively evaluate the therapeutic potential of pro-and anti-angiogenic therapies in preclinical models is necessary to improve success in clinical trials [1,7]. Characterization of vascular remodeling and screening of novel therapies are often performed in animal models of cancer [1,8,9], wounds [10,11], and cardiovascular disease [5,7,[12][13][14]. Vascular remodeling is a dynamic and complex process, so non-invasive tools that can quantify in vivo vascular remodeling over time are desirable.…”

“…Similarly, xray angiography [13,15,16] and microcomputed tomography (micro-CT) [17,18] provide vessel morphology data, but are terminal endpoints that require contrast agents. Several in vivo imaging methods have also been employed to evaluate vascular remodeling over time, including fluorescence microscopy [19,20], photoacoustic microscopy [21,22], laser speckle imaging [10,23], high frequency ultrasound [24], and magnetic resonance (MR) angiography [16,25]. These methods provide the advantage of assessing dynamic changes in the vasculature within individual animals, but there are often trade-offs between resolution, field of view, and imaging depth.…”

“…Photoacoustic microscopy somewhat improves upon the penetration depth of fluorescence microscopy with a depth of ~0.5 mm while maintaining axial resolution on the order of 10 µm [22]. Laser speckle imaging provides vascular maps with approximately 10-25 µm resolution and covers larger spatial areas than microscopy, but data are two dimensional and superficial (< 1 mm) [10,23]. While each of these methods has been successfully applied to assess vascular morphology in preclinical studies, there are trade-offs with each and the ideal methodology is application-specific.…”

Temperature Fluctuations of Leg Ulcers in Patients with Sickle Cell Anemia

“…Temperature and blood flow oscillations within each ROI were then assessed using a Fast Fourier Transform (FFT) based on the Cooley-Tukey algorithm. The power spectrum for each ROI was calculated using the following expression: (3) where is the time series of one pixel, is the number of pixels within a given ROI, and is the averaged power spectrum for said ROI. The power of oscillations within each frequency range of interest was then assessed by analyzing the power density, or area under the curve (AUC), in each specific range, given by: (4) where and denote the lower and upper limits of the frequency range of interest.…”

“…LSCI operates by illuminating tissue with a diverging near-infrared laser and imaging the reflected light with a CCD camera. The light is scattered by moving red blood cells, producing a blur in the collected images that is proportional to red blood cell flux through a given region [3]. The LSCI camera calculates flux values by performing a contrast analysis on the image via low-resolution spatial processing, which analyzes variation in intensity within small groups of pixels [4].…”