CAiM · Uppsala University · Medical ultrasound innovation

Sound speed gives ultrasound new insight

Ultrasound is already used across healthcare, but it does not always provide enough information for confident decisions. Our approach uses sound-speed imaging to extract added insight into tissue properties from the same ultrasonic waves.

Sound-speed ultrasound imaging research visual
Sound-speed imaging adds tissue-property information to conventional ultrasound.

Why it matters

Ultrasound is safe, fast, affordable, and widely used. Yet conventional ultrasound mainly shows how strongly tissue reflects sound. That is not always enough to distinguish tissues or determine whether a change is disease-related.

1

More information from the same exam

Sound-speed imaging adds tissue-property information to ultrasound, without changing the basic patient workflow.

2

Better decisions earlier

The added information can support diagnosis, triage, and follow-up in diseases where conventional ultrasound alone can be uncertain.

3

Accessible by design

The approach is being developed for existing clinical ultrasound systems, including portable and handheld settings.

How it helps

We image sound speed — how fast sound travels through tissue. Different tissues can transmit sound at different speeds. By turning this information into an image, ultrasound gains a new map of tissue content.

The aim is not to replace ultrasound, but to make it more informative: earlier diagnosis, better triage, fewer unnecessary examinations, and more equitable care.

Example sound-speed reconstruction
A sound-speed reconstruction converts ultrasound measurements into a quantitative tissue-property map.
Sound-speed ultrasound processing pipeline
From ultrasound data to sound-speed image: the research pipeline behind the added tissue information.
Clinical annotation and evaluation of ultrasound data
Clinical annotation and evaluation help connect the image information to medical decision-making.

Potential applications

The technology is being explored for clinical situations where accessible and objective tissue information could improve care pathways.

Ultrasound system used in a breast imaging context

Breast cancer and breast density

Clinical studies have shown promising results for breast cancer detection and breast density assessment, with the potential to support risk stratification and biopsy decisions.

Sound-speed imaging example related to malignancy assessment

Distinguishing tissue changes

By adding information about tissue content, sound-speed imaging can support decisions where echo images alone are uncertain.

Sound-speed imaging example for breast density assessment

Risk and follow-up

Quantitative tissue maps may support assessment of breast density and other factors relevant to risk stratification and monitoring.

Additional sound-speed ultrasound imaging applications

Broader clinical potential

Future targets include fatty liver disease, muscular disease, and settings where accessible imaging can bring diagnostics closer to patients.

From research to clinical use

The research has progressed from method development to prototype and clinical evaluation. The next step is broader validation and integration into deployable systems.

Prototype

Convert raw ultrasound data into sound-speed images.

Clinical studies

Evaluate diagnostic value with clinical partners.

Integration

Adapt the technology for existing ultrasound systems and workflows.

Adoption

Work with healthcare and medtech partners toward everyday clinical use.

Clinical ultrasound system for sound-speed imaging development
The approach is designed for integration with clinical ultrasound systems and familiar workflows.
Breast cancer study result for sound-speed imaging
Clinical evaluation links the new quantitative maps to diagnostic questions such as breast cancer assessment.

Collaboration opportunities

We seek healthcare providers, medtech companies, and innovation partners for clinical validation and product integration. The goal is to bring sound-speed imaging into practical use where it can improve diagnosis, triage, and access to care.

Team

The work is led from the Computer-assisted Applications in Medicine group at the Department of Information Technology, Uppsala University, with clinical and research collaborators.

Portrait of Orcun Göksel
Orcun Göksel, Ph.D.Professor, Uppsala University · Principal investigator
Portrait of Can Deniz Bezek
Can Deniz Bezek, M.Sc.Doctoral student, Uppsala University · Technical development and implementation
Portrait of Dieter Schweizer
Dieter Schweizer, Ph.D.Dr. · Hardware, ultrasound processing, and translation experience