Improving Laparoscopic Techniques Using Speckle Imaging
DOI: 10.1063/10.0003381
Improving Laparoscopic Techniques Using Speckle Imaging lead image
By integrating laser speckle contrast imaging, LSCI, with laparoscopic surgical techniques, it becomes possible to visualize blood flow in tissues in a minimally invasive way. Wu et al. report an improvement on the method designed to increase accuracy and demonstrate its utility using both phantom flows in glass tubes and blood vessels in a live rabbit’s ear.
The new technique, known as multi-exposure speckle imaging, MESI, is based on the same principle as LSCI, but uses multiple camera exposures. LSCI can provide blood flow information to high spatial and temporal resolution, but the measured blood flow velocities are subject to inaccuracies from noise, uncontrolled variations in illumination, and static scattering from the tissues.
Both techniques rely on the motion of scattering particles inside the illuminated region. These cause localized fluctuations of the scattered light. The resulting blur is referred to as speckling and can be reduced to a speckle correlation time.
Flow velocity can be obtained from the inverse correlation time (ICTD) with straightforward calculations. The parameter D accounts for the multiple dynamic scattering events in a single vessel and is related to the diameter of the channel.
Measurements were carried out with fluid flowing through glass channels of varying size. Additional measurements of blood flow through a rabbit’s ear confirmed that MESI greatly increases the accuracy of blood velocity measurements.
“Our study uses multiple exposure images to extract flow-related contributions, and correct the influence of noise,” said author Jialin Liu. “Furthermore, our results confirm that the relationship between obtained ICTD and flow velocity is rescaled by a weighting term that is proportional to the vessel diameter.”
Source: “Laparoscopic multi-exposure speckle imaging for quantitative flow measurement,” by Qiong Wu, Jialin Liu, Baoteng Xu, Wei Zhou, Chi Wang, Xibin Yang, and Daxi Xiong, AIP Advances (2021) The article can be accessed at https://doi.org/10.1063/5.0033464 .
