研究目的
To validate a low-cost laser speckle contrast imaging system as a quantitative tool for assessing retinal vascular function in small animal models.
研究成果
The modified LSCI system demonstrated the ability to non-invasively quantify relative changes to retinal hemodynamics in rodent models. The system offers a cost-effective tool for studying retinal vascular diseases, though improvements in laser power and camera sensitivity are needed for better resolution and sensitivity to higher flow rates.
研究不足
The system was limited to imaging retinal vessels at exposure durations greater than 20 ms and microcapillary apparatus at exposure durations greater than 4 ms due to under-sampling at shorter exposure times. The spatial resolution was insufficient to resolve smaller capillaries and secondary blood vessels.
1：Experimental Design and Method Selection
The study involved modifying a commercial fundus camera into a laser speckle contrast imaging (LSCI) system to assess retinal vascular function in rodents. The methodology included the use of a coherent light source and a custom laser speckle contrast analysis pipeline.
2：Sample Selection and Data Sources
Age-matched male and female C57BL/6 J mice were used for in vivo retinal LSCI. Controlled microcapillary flow studies were conducted using whole blood from sheep.
3：List of Experimental Equipment and Materials
A commercial fundus camera (Micron IV, Phoenix), a 10 mW 640 nm coherent red laser diode (Edmund Optics), plano-concave and biconvex lenses, linear polarizer, syringe pump (KD Scientific), and glass microcapillary tubes.
4：Experimental Procedures and Operational Workflow
The fundus camera was modified to replace the incoherent light source with a laser diode. In vivo imaging was performed under anesthesia, and controlled flow experiments were conducted using a syringe pump to force blood through microcapillary tubes at various flow rates.
5：Data Analysis Methods
Speckle contrast was calculated using both spatial and temporal processing schemes. Data were fit to a speckle correlation model using a custom Matlab script to derive decorrelation time measurements.
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