High-Density Speckle Contrast Optical Tomography (HD-SCOT) is an optical technique with the potential to address the limitations of current techniques for imaging Cerebral Blood Flow (CBF). To evaluate HD-SCOT’s performance, we developed an anatomical-head-based simulation to obtain HD-SCOT measurements and reconstructed images. We observed that including longer source-detector distances can reduce localization errors. Even though speckle contrast decreases with increased exposure times, the System-to-Noise Ratio (SNR) can increase dramatically. For instrumentation, we evaluated statistics of speckles through a multi-mode fiber (MMF) bundle and demonstrated the feasibility of tracking pulsatile blood flow in a human subject using MMFs.
High-density speckle contrast optical tomography (HD-SCOT) is a potentially attractive technique for bedside imaging of cerebral blood flow (CBF). To evaluate the performance of HD-SCOT, we built a pipeline with an anatomical head model for simulating measurements and reconstructed images. We observed that the cortical region is well represented by measurements with source-detector distance at least 29 mm. Including larger source-detector distances can reduce localization errors but with reduced signal-to-noise ratio (SNR). Imaging performance is highly dependent on the exposure time, with optimal exposure time dependent on the noise model. Future HD-SCOT systems will be designed using these results.
A variety of diffuse optical methods use laser speckle contrast and its statistics to non-invasively determine blood flow. In most cases, this implies very low detected count-rates which leads to systematic errors in determining the correct speckle statistics. We have developed a comprehensive method for simulating realistic speckle contrast resultant from light propagation in tissue taking into account experimental and fundamental sources of noise. Results of the simulation are used to determine the relationship of these parameters on the precision and accuracy of the speckle contrast signal.
We present a method for simulating speckle contrast signal, noise, and signal offset in speckle contrast optical spectroscopy and tomography. The simulations provide a realistic model by simulating custom system and tissue properties.
We present a computationally fast algorithm for estimating the optical property distribution of turbid media using diffuse optics principles without the inversion of Jacobian matrix. The algorithm is validated by simulations and experimental studies.
Speckle contrast optical spectroscopy/tomography (SCOS/SCOT) is a low-cost, non-invasive, and real-time optical imaging modality for measuring cerebral blood flow with increased signal-to-noise ratio relative to diffuse correlation spectroscopy. However, the recent camera-based detector system is not ideal for imaging a large area of the human brain because of the limited area of focus over the contour of the head and hair occluding the field of view. Here we demonstrated the feasibility of using inexpensive multi-mode fiber bundles to build a SCOS system for mapping the flow of fluids, and we showed a statistical method for distinguishing noise and speckle signals.
High-density speckle contrast optical tomography (HD-SCOT) is attractive for imaging cerebral blood flow (CBF), with desirable cost and signal-to-noise ratio (SNR). Previous studies showed feasibility of HD-SCOT in rodent models using lab instruments. To investigate potential performance for a dedicated HD-SCOT instrument, we simulated HD-SCOT imaging for an anatomical head model. We evaluated potential imaging performance versus depth for varying exposure times and measurement availability. Results showed that an HD-SCOT system could have image resolution of 13 mm full-width-half-maximum at 12 mm depth, with instrument parameters affecting localization error and SNR. These results will guide design of future research instruments
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