Friday, August 21, 2026

New guide could help scientists see deeper into the human body using light and sound

University of Birmingham

Scientists have published the most comprehensive analysis to date of ultrasound detectors underpinning photoacoustic tomography (PAT) - a fast-emerging medical imaging technology capable of revealing blood vessels, tumours, and tissue function deep inside the body.

Published in Nature Reviews Methods Primers, researchers at the University of Birmingham and UCL reveal that large ceramic detectors are currently best for deep imaging, while optical ultrasound sensors may be the future for high-resolution imaging of tiny structures.

The authors reviewed published data on 82 ultrasound detectors used in photoacoustic imaging, establishing the first standardised ‘noise-equivalent pressure’ (NEP) landscape – a performance map showing which detectors can hear the faintest biological signals across four main types:

Ceramic piezoelectric detectors;
Polymer piezoelectric detectors;
CMUTs (capacitive ultrasound detectors); and
Optical ultrasound sensors that detect sound using light rather than electricity.

PAT works by shining short pulses of laser light into tissue. When tissues absorb the light, they produce tiny ultrasound waves which researchers can detect – using them to create images of blood vessels, tumours, and other structures inside the body. However, sound waves originating from deep tissues are extremely weak - the deeper the target, the weaker the signal.

The researchers found that:

Large ceramic detectors are the most sensitive to low frequency ultrasound waves that arrive head-on, making them well-suited to deep-tissue imaging, such as breast cancer imaging;
Optical sensors excel when detectors need to be tiny – these detectors can be made extremely small, often under 100 micrometres across, while remaining highly sensitive;
Polymer detectors provide broader frequency coverage – this can help capture more image detail, particularly for superficial structures; and
CMUT detectors showed sensitivity comparable to some of the best technologies, but published measurements lacked detail, making it difficult to assess true performance.

Lead author Dr James Guggenheim, from the University of Birmingham, said: “There is no single ‘best’ ultrasound detector for all photoacoustic imaging applications. Deep tissue imaging, such as breast cancer detection, currently benefits from very sensitive ceramic detectors. However, optical ultrasound sensors which are already best for high-resolution imaging of tiny blood vessels might one day come to dominate even in deep tissue imaging as their sensitivity increases.”

“Our study provides researchers and manufacturers with a practical guide to selecting the right detector technology for specific clinical challenges now. It also highlights where future innovation is needed, for example, to develop dense, small-element detector arrays capable of delivering both deep-tissue and high-resolution imaging.”

Until now, comparing detector technologies has been difficult because researchers used inconsistent definitions and measurement approaches. The study concludes that future improvements in photoacoustic imaging will depend on creating more sensitive detectors. There also needs to be improvement in detector arrays, standardisation of how performance is measured, and development of practical high-channel-count systems for clinical use.

‘Noise-equivalent pressures of ultrasound detectors used in photoacoustic tomography’ - James A. Guggenheim, Dylan M. Marques, Thomas J. Allen, Olumide O. Ogunlade, and Paul C. Beard is published by Nature Reviews Methods Primers.

Notes for editors

The University of Birmingham is ranked amongst the world’s top 100 institutions. Its work brings people from across the world to Birmingham, including researchers, teachers and more than 40,000 students from over 150 countries.
England’s first civic university, the University of Birmingham is proud to be rooted in one of the most dynamic and diverse cities in the country. A member of the Russell Group and a founding member of the Universitas 21 global network of research universities, the University of Birmingham has been changing the way the world works for more than a century.

Journal

Nature Reviews Methods Primers

Method of Research

Data/statistical analysis

Subject of Research

Not applicable

Article Title

Noise-equivalent pressures of ultrasound detectors used in photoacoustic tomography

Article Publication Date

6-Aug-2026

After 30 years of research, Penn State startup reinvents the putting green

PennPoa, the brainchild of David Huff, a professor at the department of plant science, is helping the golf industry use a coveted strain of grass seed that delivers professional putting surfaces at a fraction of the cost

Penn State

image:
Spring Lake Golf Club in Spring Lake Heights, New Jersey, is one of a number of courses throughout the country that are now using a type of grass that was once considered a weed on their putting greens. PennPoa, a startup based on Penn State research, is playing a critical role in making the grass the go-to seed for luxury courses.
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Credit: Tom Havelka

UNIVERSITY PARK, Pa. — While they are on opposite sides of the country, Shinnecock Hills Golf Club in New York and California’s Pebble Beach Golf Club have at least two things in common. They are both hosting the U.S. Open Golf tournament and they both now seed their greens with a weed that most of the nation’s golf clubs spent decades eradicating.

With professional golf season in full swing, David Huff, professor of turfgrass breeding and genetics at Penn State, says that seven out of the top 10 courses are using Poa, a type of grass that was once considered a weed — and his startup, PennPoa, is playing a critical role in making the grass the go-to seed for luxury courses.

So, Huff added, there’s a reason he won the “Crazy as a Loon” award at the 2001 International Turfgrass Conference in Toronto.

After all, he is dedicated to the widespread distribution of a grass that the golf industry long considered a problem. Huff wanted golf course developers to adopt Poa annua, also known as annual bluegrass, over the industry’s darling, creeping bent grass.

At first glance, the early industry-wide skepticism about Poa annua seemed warranted. The annual version that comes in as a weed is “big and ugly and doesn’t tolerate extreme temperatures or disease so it dies out real fast,” Huff said.

Huff’s love for Poa annua though, wasn’t just for the sake of being a contrarian, he said. He had noticed that, while the rest of the industry had been treating it as a weed, seven of the top 10 golf courses in the country had it on their putting greens. What did these elite institutions know about the grass that the rest of the industry had staked entire careers trying to eliminate?

The trick, it turns out, lies in letting the weed be.

After years — often decades — that same ugly weed grows back as a “beautiful, high shoot-density, perennial grass that serves as a premier putting surface,” Huff explained. The elite golf courses had simply let the Poa annua thrive and reaped its rich rewards after decades.

Sure, Poa annua in its perennial avatar is hardy and drought- and disease-resistant, but its much sought-after trait is its ability to deliver championship playing surfaces.

“Poa annua has very upright growth; it’s dense like bristles on a brush, and you can mow it extremely short to less than a tenth of an inch,” Huff said. It’s this dynamite combination that leads to greens with a very fast putting surface, the kind of challenge professional golfers love.

The rest of the country’s nearly 16,000 golf course developers might want in on the action but don’t have the luxury of waiting 50 years for the perennial version of Poa annua to grow. To short-circuit the process, Huff said, he went to work to develop a strain that would exhibit all the desirable characteristics and do so over a shorter weeks-long time period.

That’s when Huff encountered a significant obstacle: the loss of dwarfism, the valuable trait that allowed grass to be mowed short without losing its plushness. Even if golf course developers might want dwarfism, successive strains of Poa annua in the lab didn’t deliver. After decades of additional lab research, Huff said, he came up with the "Goldilocks" strain of Poa annua, with all the desirable characteristics, including dwarfism. In addition, once established, a process which usually takes 8-12 weeks, the new strain of seed can be immediately used as a putting surface.

Cole Thompson, director of research, Green Section, at the U.S. Golf Association (USGA), said he has been impressed by Huff’s tenacity in understanding the breeding mechanics at play. The USGA funded a grant that helped Huff resolve the frustrating issue.

“Dr. Huff has stuck with it and done some really interesting science along the way in resolving the issue,” Thompson said. After extensive tinkering and production, when the product was ready for its time in the sun, Huff said, he wasn’t sure how to make the leap to industry distribution.

It was the Office of Technology Transfer, along with the Office for Research Protections, at Penn State that helped him establish a startup, PennPoa, in 2024 and sell the seed to professional golf course developers. The Small Business Development Center at Penn State assisted with sorting out business details. In addition, the Penn State Startup Leadership Network encouraged Huff to set up a board of advisers for his fledgling company.

“They have been helpful in giving me so much insight and turning me into a business person, which I wasn’t before,” Huff said with a laugh.

Finding farmland to grow PennPoa has been another challenge, which Huff has solved so far by leasing acres at the Russell E. Larson Agricultural Research Center, a part of Penn State College of Agricultural Sciences. Penn State owns and operates the land. Huff said that demand for PennPoa is far outpacing supply — the startup has completed its 2026 harvest and filled nearly all of its domestic customers’ preorders and will have to invest in farmland very soon.

For now, Huff said, he is focused on delivering high-quality turfgrass — with the help of Penn State’s technology transfer and business development institutions.

“OTT was critical because they gave me the first push to start my own company and later it was the College of Ag that helped me with the land problem; I am very grateful,” Huff said.

PennPoa’s success doesn’t surprise Thompson.

“We always know we’re going to get good work from Dr. Huff and from Penn State, one of the original turfgrass research institutions in the U.S.,” he said.

As for Huff, despite his success with PennPoa, he admitted his golf handicap is not very impressive, but he’s happy to leave that to the pros, he said.

Method of Research

Experimental study

Demand for PennPoa is far outpacing supply — the startup has completed its 2026 harvest and filled nearly all of its domestic customers’ preorders and will have to invest in farmland very soon.

Credit

David Huff / Penn State

MIT engineers design a better controller for operating construction diggers

The new, more intuitive system could speed up the training process for excavator operators.

Massachusetts Institute of Technology

Anyone who’s ever wrestled with a claw machine at an arcade can appreciate the difficulty in pulling and pushing on joysticks, in just the right way, to get a mechanical arm to scoop up that one special toy. Coordinating the joysticks and connecting their movement to the claw’s motion is a type of “mental mapping” that is not immediately intuitive. (And it’s what arcade owners depend on to bring players back, again and again).

In fact, the mechanics of a claw machine are broadly similar to driving an excavator: An operator uses joysticks to control the digger’s boom, arm, and bucket, and the direction of its cab. But an excavator’s maneuvers are far more complex than anything an arcade claw can do. Operators must learn more complicated mental maps to direct a digger to move rocks, grade soil, clear debris, and dig foundations, among other essential on-site jobs. Indeed, it can often take years for operators to build up expertise in maneuvering the heavy machines.

MIT engineers are looking to shorten the learning curve for excavator operators with a new training interface. Instead of using joysticks, the team has designed a more intuitive controller, which itself resembles a miniature excavator’s arm and bucket. Trainees grasp the device and use their arm and hand to make it move the way an excavator does. A digital excavator projected on an immersive six-screen display mirrors the trainee’s movements in a virtual environment.

“This is a more intuitive way to command the machine,” says Hermano Krebs, principal research scientist in MIT’s Department of Mechanical Engineering. “With this new interface, we can eliminate a lot of the mental maps that an operator would need to build in order to operate an excavator.”

Krebs sees the interface as a faster way to train excavator operators, as well as a new way to physically operate the machines, both on-site and remotely.

“Instead of having joysticks, you might have this miniature arm on the side, where the operator would place their own arm, kind of like an exoskeleton, which would allow them to operate the excavator in the cab,” Krebs says. “If work has to be done in a difficult or unsafe environment, you could have an operator sitting off-site in a trailer and using this arm to remotely tele-operate the excavator.”

The team reports its open-access results this week in the Journal of Computing and Civil Engineering. MIT co-authors include Moises Alencastre-Miranda, Joao Buzzatto, and Eran Beeri Bamani, along with collaborators from Sumitomo Heavy Industries, an industrial machinery manufacturer based in Japan.

A machine mimic

At MIT, Krebs’ group works on human-robot interactions, with a longtime focus on physical rehabilitation. Through this work, the team has accumulated knowledge about the ways in which humans control their limbs and how they can most intuitively interact with machines.

In 2018, Krebs struck up a collaboration with researchers at Sumitomo Heavy Industries, who were looking for a faster way to train excavator operators. They noted that in Japan, the population of heavy machinery operators is aging rapidly; training their replacements takes time.

Operators typically learn by driving actual excavators on a controlled driving course. As they operate the machine, novices must learn to relate the actions of the excavator’s joysticks with the movements of the arm, bucket, and cab. Coordinating these actions to carry out actual tasks adds another level of complexity that can take months to years to master.

The team reasoned that if they could eliminate the need for this mental map, they might significantly shorten the training process. To do so, they looked for a more natural way to control the machine, as an alternative to the traditional joysticks. They soon landed on the mechanical arm design, reasoning that the physical resemblance to the digger’s own arm and bucket could enable operators to mimic and control the excavator’s movements directly, without much mental translation.

Over the next few years, the researchers worked to build the mechanical arm, along with the software to pair its movements with a virtual simulation of an excavator. The combination of the mechanical arm and the virtual simulator constitutes a new training and control platform for digger operators, which the team has named the “World-Space Interface.”

“‘World-space’ refers to everything in the world that is outside of yourself, or in this case, outside of the excavator’s cab,” Krebs explains. “Normally, operators have to build a mental map of how to manipulate things in the world-space. But now, we can just mime picking up rocks or dirt, and the computer will do that translation to the world-space for us.”

Construction on day one

For their new study, the team ran training experiments with volunteers who used the World-Space Interface (WSI) as well as a more traditional, joystick-based excavator simulator. The researchers developed virtual simulations of 15 realistic excavation environments, including construction sites, highways, forest roads, riverbanks, mining areas, and urban and rural settings. Each virtual environment was associated with various excavation tasks, such as scooping and dumping sand or gravel, digging and grading trenches, clearing debris from roads, removing tree branches from water edges, and breaking up rocks.

The team designed the experiment to resemble the tasks that an operator typically performs during a weeklong excavator driving course. For one hour each day for seven days, volunteers — both expert and novice — operated the WSI and the joystick counterpart, training on tasks with increasing difficulty.

The researchers then compared the volunteers’ performance before and after the training period. For the joystick simulator, they found that novices were consistently worse than experts, though they did improve over the training period. In comparison, the team found that with the new World-Space Interface, novices were just as good as experts from the start.

“In this case, joysticks are a non-intuitive way to control and coordinate the machine,” says study co-author and MIT postdoc Joao Buzzatto. “This is the first interface that does not require me to command the excavator with joysticks.”

The team is now working to add haptics, or feeling to the WSI’s physical arm. The idea is that, as an operator uses the arm to mime an action such as picking up a pile of rocks, the arm will generate a force in response, as if the operator can feel the heaviness of the rocks, as confirmation that the excavator is indeed picking them up.

“Haptics would make this an even more intuitive system,” says co-author and visiting engineer Solmon Jeong.

The team says the new training interface can be a more natural alternative to excavator simulators that the construction industry is currently exploring. Companies such as Caterpillar, Hyundai, and Komatsu are developing virtual simulators, both to help train operators before they go on-site, and to one day remotely control excavators from a distance. However, these simulators are largely based on traditional joystick controllers that still take time to learn.

If the team’s new arm-and-bucket controller were incorporated, as an appendage in an excavator cab, or in a virtual, teleoperational simulator, the researchers envision that even first-time operators could get to work, from day one.

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This research was supported, in part, by Sumitomo Heavy Industries.