When a neurosurgeon clips a cerebral aneurysm or excises a tumor, whether the patient recovers fully or sustains permanent injury can hinge on knowing, in real time, which vessels are perfused and which are not. That information has remained frustratingly incomplete for most surgical teams — not because the underlying optical physics was unsolvable, but because solving it required hardware that operating rooms do not carry. A technique published last month in the Proceedings of the National Academy of Sciences by researchers at the University of Texas at Austin has now removed that hardware barrier, and the story of how they did it is a lesson in engineering a problem differently rather than spending more.
The method is called sinusoidal intensity modulation speckle imaging, or SIMSI. Developed in the Functional Optical Imaging Laboratory led by biomedical engineering professor Andrew Dunn, SIMSI delivers continuous, wide-field, quantitative maps of blood flow across an entire surgical field using nothing more exotic than a standard camera — the same class of sensor already present in surgical microscopes.
Standard Cameras Reveal What High-Speed Hardware Could Not
To understand what SIMSI has accomplished, it helps to understand what stopped its predecessors. The dominant technique in intraoperative blood-flow imaging is laser speckle contrast imaging, or LSCI, which works by projecting laser light onto tissue and watching how the resulting granular interference pattern — the "speckle" — blurs as red blood cells move beneath the surface. Faster-moving cells blur the speckle pattern more. A camera captures the blur; software converts it into a flow map. The approach is contact-free, requires no injected dyes, and covers the entire surgical field simultaneously.
There is, however, a structural limitation that no amount of software improvement has been able to fix. The optical fluctuations that encode how fast blood is moving flicker at frequencies too high for a standard camera to sample directly. A conventional camera's shutter stays open long enough that the fast temporal information averages out, leaving only a record of relative change — whether flow went up or down — rather than a physically meaningful flow rate. To capture the fast dynamics directly, researchers have had to use high-speed, high-sensitivity cameras that cost far more than standard sensors and are not part of typical OR equipment.
"Blood flow can change over many timescales, but the optical fluctuations that reveal how fast blood is moving are often too fast for standard cameras to sample directly," said Hengfa Lu, a postdoctoral fellow in Dunn's lab and the lead developer of the SIMSI framework, in remarks published by UT Austin.
How SIMSI Encodes Fast Blood Flow Into Long Exposures
SIMSI's solution is to stop trying to make the camera faster and instead engineer the light source to do the temporal work. During each camera exposure, the laser illumination is not steady — it is varied in a precise sinusoidal wave at a controlled frequency. This modulation pattern encodes information about fast blood flow dynamics directly into the speckle image, even though the camera's shutter is open far too long to sample those dynamics directly.
By sweeping the modulation frequency across successive exposures — changing the rate at which the light oscillates from one image to the next — SIMSI systematically maps what physicists call the power spectral density of the intensity fluctuations. The power spectral density is the frequency-domain fingerprint of how fast things are moving beneath the laser. Once that spectrum is mapped, a physics-based model fits the measured data and extracts a spectral cutoff frequency, which serves as a rigorous, physically meaningful flow index.
The validation is as important as the concept. In controlled microfluidic phantom experiments — miniature flow channels designed to simulate vessel geometry — the SIMSI-derived spectral cutoff frequency tracked the imposed flow velocity linearly, and the team's power spectral density estimates agreed with reference measurements taken simultaneously by a coaligned high-speed detector. In live mouse cortex, SIMSI-derived flow maps clearly distinguished vascular compartments with different spectral signatures, and the technique tracked the spatiotemporal evolution of cortical blood flow changes for ten days following induced ischemic stroke. Code and representative processed data are publicly available via the Functional Optical Imaging Laboratory.
This advance is technically distinct from SIMSI's immediate predecessor, a technique called multi-exposure speckle imaging, or MESI, which Dunn's group had developed earlier. MESI improved on basic LSCI by recording images at multiple exposure times and fitting the resulting speckle statistics to a model — an approach that extracted more information but still could not access the very fast frequency components that encode rapid blood flow dynamics. SIMSI works in the frequency domain rather than the time domain, which is why it can reach faster dynamics while retaining the signal-to-noise advantages of a long camera exposure.
"SIMSI gives us a way to get quantitative, physically meaningful numbers from a technique that is already fast and practical enough to use in the clinic," said Andrew Dunn, professor in the Cockrell School of Engineering's Department of Biomedical Engineering, in the university's press release.
Quantitative vs. Relative Measurements: Why Surgeons Need Both Numbers
The distinction between relative and absolute measurements is the clinical heart of the SIMSI story. Conventional LSCI tells a surgical team that flow in a vessel changed — it rose 30%, it dropped by half — relative to a baseline measured earlier in the procedure. That information is useful but incomplete. Knowing that perfusion in a specific cortical region has fallen below a threshold associated with ischemic damage is something different: it is an actionable number tied to a known physiological consequence.
A 2021 review of intraoperative cerebral blood flow technologies concluded that all existing monitoring approaches suffer from drawbacks including limited spatial and temporal resolution, and that no currently available technique meets all the criteria for optimal OR use — which include real-time imaging, quantitative output, non-contact operation, and integration into existing surgical workflow. SIMSI addresses each of those criteria simultaneously, though the path from bench to bedside will still require FDA clearance through the commercialization pathway.
That pathway has already been established. In November 2024, Dunn worked with UT Austin's Discovery to Impact commercialization hub to license his SpeckleView surgical imaging platform to Austin-based medical device startup Dynamic Light on an exclusive worldwide basis. Dynamic Light already deploys SpeckleView technology in neurovascular, robotic, and plastic surgery settings and was selected for the Texas Medical Center Innovation 2025 HealthTech Accelerator cohort. SIMSI represents the next-generation upgrade in that technology lineage.
What Does Real-Time Surgical Perfusion Imaging Look Like in Practice?
The practical OR picture that Dunn's group describes involves SIMSI as an add-on layer rather than a replacement system. A modulated laser source is attached to an existing surgical microscope — the team demonstrated this configuration with standard research hardware — and a software layer handles the frequency-sweep protocol and physics-model fitting in real time. No contrast dye is injected, no tissue contact is required, and the imaging continues throughout the procedure rather than providing only a snapshot at a discrete moment.
This continuous-monitoring capability matters because blood flow during neurovascular surgery is not static. Clip placement, cauterization, vessel retraction, and anesthesia all produce hemodynamic changes that can develop over seconds to minutes. A system that captures one image after the surgeon asks for a reading differs fundamentally from one that continuously streams flow data across the entire operative field. SIMSI is designed to do the latter.
Stroke Research, Heart Surgery, Dementia: Applications Beyond Neurosurgery
Dunn's team is deliberate in not overselling a clinical timeline, but the paper's applications section reaches well beyond the operating room. SIMSI's core capability — wide-field, non-contact, quantitative measurement of fast dynamics using standard cameras — maps onto any domain where blood flow is an early indicator of tissue health.
For cardiac surgery, continuous perfusion monitoring during procedures that temporarily restrict coronary flow could flag ischemic events earlier than current methods. In reconstructive surgery, SIMSI could assess tissue viability in transplanted flaps before perfusion failure becomes irreversible. In acute stroke care, rapid flow mapping could inform treatment decisions during the narrow window in which thrombolytic therapy is effective. In laboratory research on dementia and traumatic brain injury, the technique could track microvascular changes over extended time periods — the ten-day cortical stroke tracking experiment in mice is a proof-of-concept for exactly this use case.
The research was funded by the UT Austin Portugal Program and the National Institutes of Health. The paper's authors include Hengfa Lu, Qingwei Fang, Jewel A. Ashbrook, Victoria Nemchek, Michela Fracassi, and Theresa A. Jones, spanning UT Austin's departments of Biomedical Engineering, Physics, Psychology, and Neuroscience.
Frequently Asked Questions
How do surgeons currently monitor brain blood flow during operations?
The current standard for intraoperative cerebral blood flow visualization is indocyanine green angiography, which requires injecting a fluorescent dye intravenously and imaging its wash-in to determine which vessels are perfused. That approach provides only a momentary snapshot and can be performed only a limited number of times per surgery due to dye administration constraints. Laser speckle contrast imaging is a dye-free alternative already in research use, but existing versions yield only relative — not absolute — flow measurements.
What is laser speckle contrast imaging and how does it work?
Laser speckle contrast imaging works by projecting coherent laser light onto tissue and capturing the resulting speckle pattern — the granular interference pattern that forms when light bounces off moving red blood cells. Faster-moving cells blur the speckle more; software converts the blur pattern into a map of relative flow across the entire illuminated field. The technique is non-contact and requires no injected dyes, but conventional versions cannot produce absolute flow measurements because the fast optical fluctuations that encode blood speed exceed standard camera frame rates.
What makes SIMSI different from standard laser speckle imaging?
SIMSI modulates the laser illumination in a sinusoidal wave at a controlled frequency within each camera exposure, then sweeps that frequency across successive exposures to map the power spectral density of intensity fluctuations. A physics-based model fits the resulting spectral data and extracts a spectral cutoff frequency as a quantitative flow index. This approach encodes fast blood flow dynamics into standard long-exposure images, eliminating the need for expensive high-speed cameras while providing the absolute flow measurements that conventional laser speckle techniques cannot produce.
When might SIMSI become available in operating rooms?
SIMSI is currently a peer-reviewed research technique; it has been validated in microfluidic phantoms and in live mouse models but has not yet completed the clinical trials required for FDA clearance as a medical device. UT Austin licensed the SpeckleView surgical imaging platform — the commercial predecessor in this technology lineage — to Austin startup Dynamic Light in November 2024, and that company is already active in surgical markets. SIMSI would represent the next technological generation in that product line, but its specific clinical timeline has not been publicly disclosed.
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