An interventional study of Collection of elastography data and Collection of ultrasonic raw data in Artificial Intelligence, Ultrasonography and Elasticity Imaging Techniques, sponsored by Technische Universität Dresden. Recruiting at 4 sites in Germany. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-08-20.
Sponsored by Technische Universität Dresden · Not applicable, Interventional, and Diagnostic
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:
To answer these questions participants with a clinically indicated fibroscan will undergo:
2,081 studies on the registry are indexed under Liver Diseases; 390 are open to participants now.
This study's planned enrollment of 200 is above the median of 50 across 1,323 interventional studies indexed under Liver Diseases.
Browse Liver Diseases studies →Technische Universität Dresden is the lead sponsor of 237 studies on the registry; 45 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Collection of ultrasound data and elastography data from patients who were clinically planned for elastography
Device: Collection of elastography data
Collection of ultrasound data of the suspected lesion and a definitive diagnosis based on either normal ultrasound investigation or if not sufficient additional investigations like CEUS, Biopsy, MRI or CT. This further investigation should be in accordance to normal clinical routine of the centers to differentiate focal lesions.
Device: Collection of ultrasonic raw data
patients who are scheduled for an elastography for clinical reasons usually receive an ultrasound scan in which the b-mode images of the liver tissue are collected. In this study additional radiofrequency data is collected through a software access.
Patients who are transferred to the ultrasound departement due to suspicious focal lesions receive an ultrasonic investigation including the acquisition of raw data and extracting a definitive diagnose from the following clinical routine investigation, depending on the standards of the participating center
Performance analysis of the trained model
Analysis of the concordance of a Deep Learning-based analysis of RF data with established clinical measures. In case of diffuse disease the stiffness of the tissue and in case of the focal lesions the underlying disease as diagnosed by the local physicians are the measures. Performance is evaluated by the area under the receiver operating characteristic curve and a correlation coefficient.
Time frame: After study completion, estimated 1 year
Documents are hosted by the registry — open the source record to download them.
Plan to share: Yes — After the publication of data the anonymized IPD will be provided.
Supporting information: Study protocol, Sap, Icf, Csr
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Technische Universität Dresden