Assessment of Liver Diseases Using a Deep-Learning Approach Based on Ultrasound RF-Data
Key facts
- Where
- Dresden, Halle, and Leipzig, GermanySee the 4 sites
Where in Germany
- Diakonissen Hospital DresdenDresden, GermanyContact: Matthias Ziesch, MDTaking people
- University HospitalDresden, GermanyContact: Moritz Herzog, MDTaking people
- University Hospital Halle/SaaleHalle, GermanyContact: Valentin Blank, MDTaking people
- University Hospital LeipzigLeipzig, GermanyContact: Thomas Karlas, MDTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- Technische Universität Dresden
- Trial code
- NCT06317181
- Record updated
- 20 August 2025
- Original description
The goal of this clinical trial is to test the performance of neuronal networks trained on ultrasonic raw Data (=radiofrequency data) for the assessment of liver diseases in patients undergoing a clinical ultrasound examination. The general feasibility is currently evaluated in a retrospective cohort.Read full original descriptionShow less
Acquisition and Frequency Spectroscopic Evaluation of Broadband Clinical Ultrasound Raw Data for Liver Cirrhosis and Focal Pathologies Using Neural Networks for Tissue and Pathology Differentiation
The goal of this clinical trial is to test the performance of neuronal networks trained on ultrasonic raw Data (=radiofrequency data) for the assessment of liver diseases in patients undergoing a clinical ultrasound examination. The general feasibility is currently evaluated in a retrospective cohort.
The main questions the study aims to answer are:
* Can a neuronal network trained on RF Data perform equally good as elastography in the assessment of diffuse liver diseases? * Can a neuronal network trained on RF Data perform better than a neuronal network trained on b-mode images in the assessment of diffuse liver diseases? * Can a neuronal network trained on RF Data distinguish focal pathologies in the liver from healthy tissue?
To answer these questions participants with a clinically indicated fibroscan will undergo:
* a clinical elastography in Case ob suspected diffuse liver disease * a reliable ground truth (if normal ultrasound is not sufficient e.g. contrast enhanced ultrasound, biopsy, MRI or CT) in case of focal liver diseases, depending on the standard routine of the participating center * a clinical ultrasound examination during which b-mode images and the corresponding RF-Data sets are captured
Inclusion: scheduled for an ultrasound investigation by an independent physician; signed declaration of consent.
Exclusion: major intervention at the liver (for example partial resection); smaller interventions in the same liver during the last 2 Week (for example liver biopsy); contrast enhanced ultrasound less than a day ago.