Deep tissue flowmetry using diffuse speckle contrast analysis

Inventors

Lee, Kijoon • Bi, Renzhe • Dong, Jing

Assignees

Pedra Technology Pte Ltd

Abstract

Blood flow rates can be calculated using diffuse speckle contrast analysis in spatial and time domains. In the spatial domain analysis, a multi-pixel image sensor can be used to detect a spatial distribution of speckles in a sample caused by diffusion of light from a coherent light source that is blurred due to the movement of scatterers within the sample (e.g., red blood cells moving within a tissue sample). Statistical analysis of the spatial distribution can be used to calculate blood flow. In the time domain analysis, a slow counter can be used to obtain time-series fluctuations in light intensity in a sample caused by diffusion of light in the sample that is smoothened due to the movement of scatterers. Statistical analysis of the time-series data can be used to calculate blood flow.

Core Innovation

The invention determines blood flow characteristics in deep tissue in a patient by directing coherent light from a laser light source through an input optical fiber positioned directly onto a first location on a skin surface. A second location of the skin surface is imaged, where a portion of the coherent light is scattered diffusively by blood flow at a depth of penetration between 5 mm and 50 mm beneath the skin surface and is at least partially detectable at the second location. Image data from the second location are sent to a software or hardware processor for analysis.

Blood flow characteristics are calculated from the image data by statistically analyzing a probability distribution of intensity fluctuations of the scattered light to determine a speckle contrast ratio and associated values, including a temporal speckle contrast ratio (Kt) and 1/Kt2 values. The processor correlates the 1/Kt2 values with blood flow using statistical analysis without having to rely on autocorrelation analysis on fast time-series data. The calculated blood flow characteristics are signaled to an operator in real time using audible, visual, or tactile indicia.

In one form, a spatial domain speckle contrast analysis (sDSCA) system statistically analyzes a probability distribution of speckle intensity fluctuations of the image data to determine a spatial speckle contrast ratio (Ks) and 1/Ks2 values, and correlates the 1/Ks2 values with blood flow. In a related system implementation, coherent laser light is applied to tissue, a multi-pixel image sensor captures diffusively scattered optical information at penetration depths between 5 mm and 50 mm, and a hardware or software processor analyzes the captured optical information using Ks and 1/Ks2 with statistical analysis without autocorrelation on fast time-series data, with the processor output provided to a display.

Claims Coverage

The document provides three independent claims (method claim 1, method claim 6, and system claim 9) covering both temporal and spatial speckle contrast analysis pathways and an associated system architecture. Across the independent claims, the inventive features focus on deep-tissue coherent-light imaging with fiber-delivered illumination, multi-pixel detection, statistical speckle-contrast computation using intensity-fluctuation probability distributions, correlation of 1/K-squared values with blood flow, and operator signaling without autocorrelation on fast time-series data.

Overall, the independent claims cover deep-tissue blood flow assessment using coherent laser light delivered via an input optical fiber, multi-location skin imaging with a multi-pixel sensor, and statistical speckle-contrast computation from intensity fluctuations to generate Ks/Kt and corresponding 1/K-squared values that are correlated with blood flow without relying on autocorrelation analysis on fast time-series data, with operator signaling or display output.

Stated Advantages

Documented Applications