Laser speckle imaging (LSI) is a wide-field, noninvasive optical technique that allows researchers and clinicians to quantify blood flow in a variety of applications. However, traditional LSI devices are cart or tripod based mounted systems that are bulky and potentially difficult to maneuver in a clinical setting. We previously showed that the use of a handheld LSI device with the use of a fiducial marker (FM) to account for motion artifact is a viable alternative to mounted systems. Here we incorporated a handheld gimbal stabilizer (HGS) to produce a motion stabilized LSI (msLSI) device to further improve the quality of data acquired in handheld configurations. We evaluated the msLSI device in vitro using flow phantom experiments and in vivo using a dorsal window chamber model. For in vitro experiments, we quantified the speckle contrast of the FM (K FM ) using the mounted data set and tested 80% and 85% of K FM as thresholds for useable images (K FM,Mounted,80% and K FM,Mounted,85% ). Handheld data sets using the msLSI device (stabilized handheld) and handheld data sets without the HGS (handheld) were collected. Using K FM,Mounted,80% and K FM,Mounted,85% as the threshold, the number of images above the threshold for stabilized handheld (38 ± 7 and 10 ± 2) was significantly greater (p = 0.031) than for handheld operation (16 ± 2 and 4 ± 1). We quantified a region of interest within the flow region (K FLOW ), which led to a percent difference of 8.5% ± 2.9% and 7.8% ± 3.1% between stabilized handheld and handheld configurations at each threshold. For in vivo experiments, we quantified the speckle contrast of the window chamber (K WC ) using the mounted data set and tested 80% of K WC (K WC,Mounted,80% ). Stabilized handheld operation provided 53 ± 24 images above K WC,Mounted,80% , while handheld operation provided only 23 ± 13 images. We quantified the speckle flow index (SFI) of the vessels and the background to calculate a signal-to-background ratio (SBR) of the window chamber. Stabilized handheld operation provided a greater SBR (2.32 ± 0.29) compared to handheld operation (1.83 ± 0.21). Both the number of images above threshold and SBR were statistically significantly greater in the stabilized handheld data sets (p = 0.0312). These results display the improved usability of handheld data acquired with an msLSI device.

Noncontact photoplethysmography (PPG) is limited by a poor signal-to-noise ratio (SNR). A solution to this limitation is the use of alternate sources of optical contrast to generate a complementary pulsatile waveform. One such source is laser speckle contrast, which is modulated in biological tissues by the flow rate of red blood cells. Averaging a region of interest from a speckle contrast image over time allows for the calculation of a speckleplethysmogram (SPG). Similar to PPG, SPG enables monitoring of heart rate and respiratory rate. A gap in the knowledge base exists as to the precise spatiotemporal relationship between PPG and SPG signals. We have developed an eight-layer tissue model to simulate both PPG and SPG signals in a reflectance geometry via Monte Carlo methods. We modeled PPG by compression of the upper and lower blood nets due to expansion of the larger arterial layer below. The in silico PPG peak-to-peak amplitude percent was greater at 532 nm than at 860 nm (5.6% vs. 3.0%, respectively), which matches trends from the literature. We modeled SPG by changing flow speeds of red blood cells in both the capillaries and arterioles over the cardiac cycle. The in silico SPG peak-to-peak amplitude percent was 24% at 532 nm and 40% at 860 nm. In silico results are similar to in vivo results measured with a two-camera set up for simultaneous imaging of PPG and SPG. Both in silico and in vivo data suggest SPG has a much larger SNR than PPG, which may prove beneficial for noncontact, wide-field optical monitoring of cardiovascular health.

We have previously demonstrated that the use of a commercially-available immersion-based optical clearing agent (OCA) enables, within 3–6 hours, three-dimensional visualization of subsurface exogenous fluorescent and absorbing markers of vascular architecture and neurodegenerative disease in thick (0.5–1.0mm) mouse brain sections. Nonetheless, the relative performance of immersion-based OCAs has remained unknown. Here, we show that immersion of brain sections in specific OCAs (FocusClear, RIMS, sRIMS, or Sca l eSQ) affects both their transparency and volume; the optical clearing effect occurs over the entire visible spectrum and is reversible; and that Sca l eSQ had the highest optical clearing potential and increase in imaging depth of the four evaluated OCAs, albeit with the largest change in sample volume and a concomitant decrease in apparent microvascular density of the sample. These results suggest a rational, quantitative framework for screening and characterization of the impact of optical clearing, to streamline experimental design and enable a cost-benefit assessment.

. Significance: To explore brain architecture and pathology, a consistent and reliable methodology to visualize the three-dimensional cerebral microvasculature is beneficial. Perfusion-based vascular labeling is quick and easily deliverable. However, the quality of vascular labeling can vary with perfusion-based labels due to aggregate formation, leakage, rapid photobleaching, and incomplete perfusion. Aim: We describe a simple, two-day protocol combining perfusion-based labeling with a two-day clearing step that facilitates whole-brain, three-dimensional microvascular imaging and characterization. Approach: The combination of retro-orbital injection of Lectin-Dylight-649 to label the vasculature, the clearing process of a modified iDISCO+ protocol, and light-sheet imaging collectively enables a comprehensive view of the cerebrovasculature. Results: We observed increase in contrast-to-background ratio of Lectin-Dylight-649 vascular labeling over endogenous green fluorescent protein fluorescence from a transgenic mouse model. With light-sheet microscopy, we demonstrate sharp visualization of cerebral microvasculature throughout the intact mouse brain. Conclusions: Our tissue preparation protocol requires fairly routine processing steps and is compatible with multiple types of optical microscopy.