Clinical trial NCT06317181: Assessment of Liver Diseases Using a Deep-Learning Approach Based on Ultrasound RF-Data
Official title: 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
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Artificial Intelligence
Ultrasonography
Elasticity Imaging Techniques
Liver Diseases
Metastasis to Liver
Keywords: Quantitative Ultrasound
Radiofrequency Data
Lead sponsor: Technische Universität Dresden
Sponsor class: OTHER
Collaborators: name: University Hospital Dresden
name: University of Leipzig
First posted: 2024-03-19
Enrollment: 200
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Data is collected in a defined group of patients (all patients listed for elastography or for ultrasonic investigation due to a focal lesion in participating departments). Afterwards performances of algorithms are compared based on this group.
Primary purpose: DIAGNOSTIC

Brief summary: 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


Eligibility criteria: Inclusion Criteria:

* scheduled for an ultrasound investigation by an independent physician
* signed declaration of consent

Exclusion Criteria:

* smaller interventions in the same liver during the last 2 Week (for example liver biopsy)
* contrast enhanced ultrasound less than a day ago
* major intervention at the liver (for example partial resection)

Primary outcomes:
measure: Performance analysis of the trained model
timeFrame: After study completion, estimated 1 year
Secondary outcomes:
Other outcomes:
Locations:
city: Dresden
country: Germany
facility: University Hospital
city: Dresden
country: Germany
facility: Diakonissen Hospital Dresden
city: Halle (Saale)
country: Germany
facility: University Hospital Halle (Saale)
city: Leipzig
country: Germany
facility: University Hospital Leipzig
Study officials:
affiliation: University Hospital Dresden
name: Moritz Herzog, MD
role: PRINCIPAL_INVESTIGATOR
References: