Safer Surgeries Through Laser-Induced Acoustic Imaging #ASA190

Photoacoustic imaging can reveal subsurface features and guide surgeons for fewer complications.

PHILADELPHIA, May 11, 2026 — Surgery is a complicated endeavor. Even a successful surgery can lead to complications, and even the best surgeons sometimes have unsuccessful surgeries. A surgeon must rely on visual cues and their own experience to avoid hitting a nerve or a blood vessel, mistakes that can turn a simple surgery into a much more challenging one.

Unfortunately, many of these potential hazards lurk beneath the surface of the tissue, hidden from the surgeon unless a modern imaging technique reveals them.

Haichong (Kai) Zhang, an associate professor at Worcester Polytechnic Institute, will present his work integrating photoacoustic (PA) imaging into robot-assisted surgeries Monday, May 11, at 8:40 a.m. ET as part of the 190th Meeting of the Acoustical Society of America, running May 11-15.

Close-up of a robotic arm gripping a small white cube with a grid pattern, positioned near intersecting red and green rods on a pink surface.

An illustration of the probe design and how it would scan blood vessels. Credit: Kai Zhang

Robot-assisted laparoscopic surgeries are abdominal or pelvic surgeries that use a small camera, called a laparoscope, inserted through a small incision. Small incisions mean reduced pain and shorter recovery times for patients, and robot assistance means more control and precision for surgeons. Unfortunately, the danger of damaging anatomical structures under the surface remains.

“Accidentally severing a hidden blood vessel during robot-assisted laparoscopy occurred in 1%-2% of cases depending on the procedure,” said Zhang. “Furthermore, such incidents can result in a range of complications, including hemorrhage, paralysis, and, in the worst cases, fatal outcomes.”

One emerging solution is PA imaging. This technique directs lasers deep into the tissue, which absorbs the light and produces sound waves. These sound waves can be picked up by ultrasensitive microphones and used to pinpoint subsurface structures like blood vessels and nerve bundles.

“This capability enables visualization of embedded anatomical structures and their depth locations, which is highly valuable for surgical planning and intraoperative monitoring,” said Zhang.

Zhang incorporated PA imaging into a laparoscopic surgery workflow to help guide surgeons during operations. He analyzed data from the PA probe and used it to create 3D representations of neurovascular bundles, which are clusters of nerves and blood vessels surgeons desperately want to avoid. Then, these representations were overlaid on video from the laparoscopic camera, providing a real-time augmented reality video feed.

Zhang tested this technique during radical prostatectomies — a surgery to remove prostate cancer — but PA imaging has applications broader than this one surgery.

“We anticipate that this imaging instrumentation will be readily translatable to not only other laparoscopic procedures but also other image-guided procedures,” said Zhang.

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More Press Releases

Medical imaging in a wearable form: monitoring health on the go

Katherine Brown – katherine.brown@utdallas.edu

University of Texas at Dallas, Department of Bioengineering, Richardson, TX, 75080, United States

Rouzbeh M. Imenabadi
Dinesh Bhatia

Popular version of 4pBAb2 – Towards a wearable ultrasound bladder monitoring system
Presented at the 190th ASA Meeting
Read the abstract at https://eppro01.ativ.me/web/planner.php?id=ASASPRING2026

–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–

Today we schedule a medical imaging scan in a clinic, doctor’s office, or at a hospital. What if we could self-monitor with a wearable unit?

We are working towards enabling practical wearable units and have taken two key steps to making this a reality.

First, in this work we show a method to shrink the electronics needed for an ultrasound machine to fit your body. It uses the strength of AI computer vision to “see” with a sensor that is stripped down in capability and missing bits of information; AI fills in the missing information. This allows us to implement a wider field of view, about 4 times wider what has been previously achieved.

Illustration of a woman using a wearable ultrasound device on her abdomen while looking at a smartphone showing a live scan of bladder and intestines.Figure 1: Wearable ultrasound unit placed on the abdomen and images displayed on a smartphone (Image by Google Gemini 4/2026)

Second, it uses a new type of ultrasound sensor that is based on the same technology of high-volume commercial semiconductors, so it can be made cheaply, and with high accuracy. With less expensive sensors, we can implement larger arrays at a still reasonable cost. In our work we show a 2D pattern of elements which give us a 3D view into the body.

Putting together these two concepts we demonstrate a wearable imaging system a bit larger than a deck of playing cards. It has a wide field of view and can continuously scan the body in the course of daily activities using ultrasound. There are many potential applications of the technology demonstrated in this unit – abdominal imaging monitoring for bladder volume or fluid in the lungs, heart imaging for ejection fraction, large vessel imaging to sense oxygenation levels, and many more.

Using Deep Learning to Enhance Photoacoustic Brain Images

Matthew Olmstead – mjo5585@psu.edu

Instagram: @mattomatty707
Graduate Program in Acoustics, The Pennsylvania State University, University Park, PA, 16802, United States

Hyungjoo Park – hpp5133@psu.edu
MD Rizwanul Kabir – rizwanulkabir@vt.edu
Aiguo Han – aiguohan@vt.edu
Yun Jing – yqj5201@psu.edu

Popular version of 1aBAa7 – Improving Photoacoustic Imaging through the Skull using Deep Learning: Considering 3D Effects
Presented at the 190th ASA Meeting
Read the abstract at https://eppro01.ativ.me/web/page.php?page=Session&project=ASASPRING2026&id=4082496&nohistory&nohistory=true

–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–

Did you know that there’s potentially a better way than ultrasound to image your brain? Say hello to photoacoustics, which combines the benefits of optics and sound, giving us the “best of both worlds.” Instead of an acoustic signal, we’re sending a laser signal into the brain, then receiving an acoustic signal back thanks to the phenomenon of the photoacoustic effect! When we’re dealing with a mixed medium like human tissue, the ultrasound signal often gets distorted by the time it’s picked up by the receiving probe. Thankfully in photoacoustics, the acoustic signal only travels one way, so compared to what happens in traditional ultrasound imaging, it goes through less distortion by the time it reaches the ultrasound probe. One example of a mixed medium is the skull, which has a very porous layer in the middle (see Figure 1).

Diagram showing pulse laser and ultrasound array detecting blood vessels inside a human skull.

Figure 1. Schematic of the photoacoustic imaging process. Image courtesy of Hyeonu Heo.

Over the past several years, it has been a challenge trying to get a good acoustic signal when imaging through the skull. However, as you’re probably aware, AI has lately become popular in enhancing different applications, and the biomedical field is no exception to that. This project proposes using a deep learning model to improve photoacoustic images distorted by the skull, by training it on these images and comparing them to their “ground truth” counterparts. By the time the model is finished training, it will be able to improve the quality of images that it has never seen before! The model we’re working with is called U-Net, named after its literal shape of a U. The two main parts of U-Net are the encoder on the left side and the decoder on the right side (see Video 1). The encoder takes an image, lowers its resolution, and extracts important features out of it to learn from. Later, the decoder restores the image’s resolution and is able to pinpoint down to each pixel which parts of the image are what (for example, a blood vessel or background).

Video 1. Basic overview of U-Net model.

So far in our research, we’ve noticed how the types of images that we feed the model are very important. For instance, if we train it on images that only consider 2D wave effects, it isn’t going to perform as well when tested on images with more realistic 3D wave effects. It is crucial that the training data for the model is as realistic as possible, before it gets deployed out into the real world to be used in clinical settings. Fortunately, our U-Net model has proven to be very robust, and the results that we’ve obtained thus far have pointed us toward ways to further improve it. The future in this field is exciting, since several categories of photoacoustic imaging tasks can benefit from deep learning enhancements, such as monitoring stroke diseases.

Is it possible to break kidney stones with acoustic vortices?

Sergio Maldonado-Ortega – smalort@upv.es
Instagram: @i3m_upvcsic

Instituto de Instrumentación para Imagen Molecular (i3M), Universitat Politècnica de València (UPV) – Consejo Superior de Investigaciones Científicas (CSIC), València, València, 46022, Spain

Enrique González-Mateo
Alejandro Cebrecos
Brenda Morant-Ferrando
César D. Vera-Donoso
Alicia Carrión
Francisco Camarena
Noé Jiménez

Popular version of 3aBAa5 – Preliminary results of kidney stone comminution using acoustic vortices
Presented at the 190th ASA Meeting
Read the abstract at https://eppro01.ativ.me/web/index.php?page=Session&project=ASASPRING2026&id=531062

–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–

Kidney stones are a painful reality for millions of people worldwide. When these small, hard mineral deposits get too big to pass naturally, doctors often turn to non-invasive treatments that use ultrasound waves to break them into tiny pieces from outside the body. The current gold standard, extracorporeal shock wave lithotripsy (ESWL), works, but it can sometimes be slow or less effective on particularly stubborn stones. In recent years burst wave lithotripsy (BWL) has emerged as a new and promising alternative. If ESWL was a big hammer hitting the stones to break them, BWL would be a tiny hammer hitting them with lower pressure but much faster.

We’ve got a new technique for breaking kidney stones that’s both efficient and effective. It uses something called acoustic vortices.

The Efficacy of the Vortices
Standard ultrasound treatments work like a hammer, hitting the stone with pulses of pressure until it cracks. But our research brings a new approach to the table. By shaping the sound waves into a vortex — kind of like a whirlpool or a tornado — we can do more than just “hit” the stone; we can also twist it. The twisting motion of an acoustic vortex creates unique stresses that pull and twist the stone’s structure at the same time. This “rotational stress” makes the fragmentation process much more efficient, tearing the stone apart from the inside out in ways that standard pulses cannot.

Testing the Technology
To test this theory, we developed a functional portable prototype shown in Fig. 1, featuring a robotic arm equipped with two specialized ultrasound transducers. One therapeutic transducer of 1.1 MHz and 128 elements, which acts as the “breaker,” sending out the vortex waves. One imaging probe with 128 elements, basically an “eye” that let us see the stone and keep an eye on how it is breaking down in real-time.

Left side shows a white autonomous robot with a robotic arm and a monitor on top, positioned in a glass-walled corridor. And a inset illustration of human skeleton.

Figure 1: Here you can see our portable prototype, with all the equipment mentioned previously, such as the robotic arm and the transducers attached to it (a). Schematic explaining how this technique would work in a real scenario (b).

We put our vortices to test by comparing them against the best emerging ultrasound technique (conventional BWL) under the same conditions. We tested them on two types of targets:

  • Artificial stones: Lab-made models of BegoStone designed to mimic the properties of different human stones.
  • Real stones: Challenging samples donated by patients that were so tough they had already survived previous conventional hospital treatments without breaking. We tested different types of stones, like uric acid, brushite, apatite, and calcium oxalate monohydrate (COM).

Twice as Fast, Twice as Effective
The results were clear. When using acoustic vortices, the artificial stones broke twice as fast as they did with conventional BWL. Video 1 illustrate the fragmentation speed difference between both techniques in experiments conducted with artificial stones.

Video 1: Real time comparison of the fragmentation of artificial stones using conventional and vortex approach.

We conducted a total of 16 experiments for this type of artificial stone. Figure 2 illustrates the average fragmentation speed across all these experiments, comparing both techniques. More importantly, the success carried over to real-world cases. The human stones we tested were “unbreakable” by current techniques, yet our vortex technology successfully crumbled them, as Fig. 2 shows.

Graph comparing kidney stone fragmentation over time using conventional BWL and vortex methods, showing faster fragmentation for artificial stones with vortex.

Figure 2: Average fragmentation process of artificial stones with conventional BWL and Vortex (a). Average fragmentation process of real kidney stones with conventional BWL and Vortex (b).

Why It Matters
This breakthrough could lead to faster medical procedures, meaning less time on the operating table for patients and a higher success rate for treating those stubborn stones that current technology struggles to crack. By adding a “twist” to traditional physics, we are opening the door to a more efficient and potentially safer non-invasive future for kidney stone treatment.

Breaking the Skull Barrier: “Listening” to Ultrasound Therapy Inside the Brain

Pradosh Pritam Dash – ppdash@gatech.edu

Instagram: @pra.dosh.dash
George W. Woodruff School of Mechanical Engineering
Georgia Institute of Technology
Atlanta, GA, 30318
United States

Costas D. Arvanitis
Georgia Institute of Technology and Emory University

Popular version of 3pBAa7 – Breaking the Skull Barrier: Parametric Array Enable Non-Invasive Monitoring of Transcranial Focused Ultrasound
Presented at the 189th ASA Meeting
Read the abstract at https://doi.org/10.1121/10.0040891

–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–

The Challenge of Treating the Brain
Focused Ultrasound (FUS) is a revolutionary, incision-free technology that promises to treat brain disorders, such as tumors and Parkinson’s disease. It works by concentrating high-frequency sound waves to a precise point deep within the brain, much like a magnifying glass focuses sunlight. However, this promising therapy faces a major obstacle: the human skull. The skull is a thick, bony barrier that scrambles, reflects, and weakens these high-frequency waves. This makes it incredibly difficult for doctors to monitor the treatment in real-time and confirm that the energy is actually reaching the intended target. This uncertainty limits the safety and effectiveness of FUS brain therapies.

Figure 1: a - Conceptual illustration of the technique. A transmitter (bottom) sends high-frequency (1 MHz) therapeutic ultrasound waves through the skull. Where these waves interact at the focus, they generate a 50kHz low frequency "parametric Array" signal that easily passes through the skull to a receiver (top). The HASPA framework uses this detected signal to map the therapy. b- The reconstructed (first order) 1 MHz high-frequency and 100 kHz low frequency parametric field using HASPA framework with 3,6, and 9 dB contours.

Figure 1: a – Conceptual illustration of the technique. A transmitter (bottom) sends high-frequency (1 MHz) therapeutic ultrasound waves through the skull. Where these waves interact at the focus, they generate a 50kHz low frequency “parametric Array” signal that easily passes through the skull to a receiver (top). The HASPA framework uses this detected signal to map the therapy. b- The reconstructed (first order) 1 MHz high-frequency and 100 kHz low frequency parametric field using HASPA framework with 3,6, and 9 dB contours.

The skull is a thick, bony barrier that scrambles, reflects, and weakens these high-frequency waves. This makes it incredibly difficult for doctors to monitor the treatment in real-time and confirm that the energy is actually reaching the intended target. This uncertainty limits the safety and effectiveness of FUS brain therapies.d

An Acoustic “Trick” to Overcome the Barrier
Researchers at Georgia Tech and Emory University have developed a new computational framework called HASPA (Heterogeneous Angular Spectrum Parametric Array) that exploits a nonlinear acoustic “trick” known as the “parametric array effect.” When two high-frequency ultrasound beams around 1 MHz beams used for therapy meet at the target inside the brain, they interact nonlinearly and mix. This interaction generates a brand-new sound wave at a much lower difference frequency (around 50-100 kHz).

Think of it this way: High-frequency sounds, like a faint whistle, are easily blocked by a thick wall (the skull). However, low-frequency sounds, like the thumping bass from a neighbor’s stereo, travel through walls easily. In this new approach, the therapeutic “whistles” create a localized “bass” beat exactly where the treatment is happening. This low-frequency signal acts as a messenger, traveling cleanly back out through the skull to be detected by external sensors.

Decoding the Message: The HASPA Framework
The challenge is translating this low-frequency message back into a high-resolution picture of the high-frequency treatment zone inside the brain.

To achieve this, the team developed a novel computational framework called HASPA (Heterogeneous Angular Spectrum Parametric Array) and an associated inverse algorithm (iHASPA).

iHASPA analyzes the low-frequency signal measured outside the skull and mathematically reconstructs a map of the original therapy beams deep inside the brain. Crucially, the framework accounts for the complex ways sound travels through the specific properties of the patient’s skull and brain tissue, correcting for distortions.

Impact and Future
By leveraging this nonlinear acoustic effect, the HASPA framework allows us to “see” through the skull using sound. This new technique enables real-time, non-invasive monitoring of ultrasound beams inside the brain, paving the way for safer, more precise, and more effective focused ultrasound therapies for debilitating neurological disorders.

Sound-Activated Gels to Treat Back Pain

Veerle Brans – veerle.brans@eng.ox.ac.uk

Instagram: @itsdranddr
University of Oxford – Botnar Research Centre, Old Rd, Oxford, Oxfordshire, OX3 7LD, United Kingdom

Complete author list:
[Veerle A. Brans*], Anna P. Constantinou*, Matthew J. Kibble, Valeria Nele, Daniel Reumann, Luca Bau, Sebastien J. P. Callens, James P. K. Armstrong, Nicolas Newell, Constantin Coussios, Molly M. Stevens, Michael D. Gray
* These authors contributed equally to this work

Popular version of 2pBAa5 – Quantitative cavitation monitoring for automated ultrasound-controlled hydrogel formation in spinal disc repair
Presented at the 189th ASA Meeting
Read the abstract at https://doi.org/10.1121/10.0040491

–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–

Back pain affects over 600 million people worldwide and is the leading cause of disability. Most back pain is linked to the breakdown of the intervertebral disc, which is the soft, elastic cushion between the bones of the spine that absorbs shocks and keeps us moving comfortably (Figure 1.a). When these discs wear down with age or injury, bones rub together, causing pain.

Figure 1: a) The main parts of a spinal disc: the tough outer ring (annulus fibrosus), the soft, jellylike centre (nucleus pulposus), and the thin cartilage endplates that separate each disc from the bones above and below. b) How our injectable material works: a liquid is injected into the damaged disc and, when exposed to focused ultrasound, it gently warms and solidifies into a soft gel that restores the disc’s function. Adapted from Brans et al. (2025). Advanced Healthcare Materials. [accepted].

Current treatments are limited: physiotherapy manages symptoms but rarely fixes the problem, while surgery is invasive, costly, and not always successful. Scientists are therefore exploring minimally invasive materials that can be injected as liquids and then solidify (‘gel’) inside the body, restoring cushioning to damaged discs. The challenge is how to control where and when this solidification happens.

For this, we propose to use ultrasound – sound waves beyond human hearing – not just for imaging but for therapy. Focused ultrasound can safely heat deep tissues, much like a magnifying glass focuses light to start a fire. Our team at the University of Oxford and Imperial College London developed an injectable liquid implant that solidifies into a gel when warmed to just over 41°C, a temperature reached locally and non-invasively using ultrasound (Figure 1.b). The material consists of three components: 1) a polysaccharide (sugar) solution, 2) glass spheres to accelerate heating of the material, and 3) lipid vesicles, tiny fluid-filled spheres that release calcium when heated. This released calcium links the sugar molecules into a network, turning the liquid into a gel (Figure 2.b).

To test this, we designed treatment algorithms that precisely control heating while also ‘listening’ to the behaviour of tiny bubbles inside the liquid (Figure 2.a). These bubbles form and move in response to the changing pressure of the ultrasound waves, a process known as cavitation. You can imagine it like opening a bottle of sparkling water: bubbles suddenly appear and grow as the pressure drops, and then collapse.

Figure 2: Testing ultrasound-triggered gel formation. (a) Custom setup for heating and ‘listening’ to the material with focused sound waves. (b) Heating curve and photo of the soft gel formed after ultrasound exposure. (c) Testing the approach in cow spinal segments held in a custom rig. (d) Treated discs regained some biomechanical function, with the gel well integrated into the damaged centre after testing. Adapted from Brans et al. (2025). Advanced Healthcare Materials. [accepted].

In our material, this bubble activity generates sound that changes as the liquid turns into a gel: starting off loud then fading as the material stiffens and the bubbles can no longer move freely (compared to a liquid control, see audiofiles). By tracking these sound changes, we can monitor gelation and thus the treatment’s success in real time.

Audiofiles: ‘Control‘ and ‘Gel‘

In our most recent experiments using cow spines (which are anatomically similar to human), we successfully injected the liquid material into degenerated disc tissue and used focused ultrasound to trigger gelation at the correct location (Figure 2.c). Mechanical testing showed that the treatment partially restored the disc’s natural cushioning ability (Figure 2.d), and the material stayed in place without leaking and blended well with the surrounding tissue.

These early results show real promise for using sound-activated gels to repair worn spinal discs, with ongoing improvements in the material and ultrasound technique aiming to make the treatment even more effective in the future, helping millions stand tall again.

Want to find out more? Check out this TED-style talk (https://www.youtube.com/watch?v=_phNGuTyWCQ) by Dr Veerle Brans.