Non-invasive MRI Subclassification of Heptocellular Carcinoma - HepCaSt-Study

NCT ID: NCT05202015

Last Updated: 2022-01-21

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

150 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-01-01

Study Completion Date

2024-07-01

Brief Summary

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Non-invasive MRI subclassification of Heptocellular Carcinoma - HepCaSt-Study

Detailed Description

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Hepatocellular carcinomas (HCCs) are a heterogeneous group of tumor subtypes with a different response behavior and prognosis. As a reaction, the World Health Organization (WHO) in its 5th version (updated in 2019) classifies no more two but eight subtypes, each with a different tumor biology and outcome. The new classification may serve as a key factor optimizing a more personalized therapeutic approach and therefore, especially diagnostic disciplines have to implement these new subtypes as soon as possible into their daily clinical routine algorithms.

Imaging does play a key role in this situation. Newer and advanced MRI techniques allow a precise tissue characterization. Furthermore, with the help of latest generation hepatobiliary contrast agents like the usage of Gd-EOB (Primovist) it is possible to quantify and measure the organ function and specific uptake behavior of focal liver lesions. Another approach that hold promise for advancing the characterization of HCCs heterogeneity is the use and development of artificial intelligence (AI)-based image postprocessing algorithms including radiomics analysis.

To date there aren't any established imaging features correlating with any of the new WHO HCC-subtypes. The goal of our project is to identify imaging biomarkers correlating with the new HCC-subtypes, helping to classify them noninvasively. As a next step with the help of our collaborators we will facilitate a radiological-pathological reference database. In a third step and with the help of the data we curated we will try to identify morphologic imaging characteristics by the use of AI-based post-processing algorithms to classify the subtypes noninvasively and to predict / estimate patients individual therapy response and prognosis. The last challenge will be to implement these algorithms into daily clinical routine, we therefore have to identify interface dilemmas and present smart solutions to solve them.

We are convinced that by implementing the updated WHO-criteria into clinical workflows current believes and guidelines in the diagnosis and therapy of HCC will change. MRI HCC imaging with Primovist will play a key role in this project. The results of our project may provide the knowledge to represent as a cornerstone in imaging and therapy assessment of HCC to improve a personalized therapy approach.

Conditions

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HCC Hepatocellular Carcinoma MRI

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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MRI using a hepatobiliary phase contrast agent (Gd-EOB-DPTA)

MRI of the liver accoring to our institutional daily routine protocol

Intervention Type DRUG

Eligibility Criteria

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Inclusion Criteria

Patients with hisopathologically confirmed HCC and MRI in domo with the standard high-end MRI Primovist study protocol.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Bayer

INDUSTRY

Sponsor Role collaborator

Charite University, Berlin, Germany

OTHER

Sponsor Role lead

Responsible Party

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Timo A. Auer

Dr. med. Timo Alexander Auer

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Charité - University Medicine Berlin

Berlin, , Germany

Site Status RECRUITING

Countries

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Germany

Facility Contacts

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Timo Alexander Auer, M.D.

Role: primary

+4930450657078

Dominik Geisel, PD M.D.

Role: backup

+4930450657319

Other Identifiers

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EA1/323/20

Identifier Type: -

Identifier Source: org_study_id

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