Integrated AI-supported quality and dose management for radiology

Integrated AI-supported quality and dose management for radiology - IQUADORA

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00039484

Enrollment

20000

Registered

2026-03-11

Start date

2026-04-01

Completion date

Unknown

Last updated

2026-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Dose Management in Diagnostic Radiology

Interventions

Group 1: Retrospective analysis of dose values from radiological examinations

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: CT examination at UKB

Exclusion criteria

Exclusion criteria: None

Design outcomes

Primary

Measure	Time frame
The central methodological element of our research is the creation of models (predominantly AI-based models) that describe the relationship between examination- and patient-specific factors and the radiation dose applied in CT examinations. The hypothesis is that a multiparametric model can identify deviations between the actual radiation dose administered and the appropriate radiation dose significantly better than the current dose reference value-based method, which does not take into account patient-specific characteristics or aspects of image quality. To this end, we compare the number of relevant and unnecessary warnings between a model-based approach and the currently used reference value-based method in dose management. In addition, we quantify the number of relevant deviations from optimal examination procedures newly discovered by the model.	—

Measure

Time frame

The central methodological element of our research is the creation of models (predominantly AI-based models) that describe the relationship between examination- and patient-specific factors and the radiation dose applied in CT examinations. The hypothesis is that a multiparametric model can identify deviations between the actual radiation dose administered and the appropriate radiation dose significantly better than the current dose reference value-based method, which does not take into account patient-specific characteristics or aspects of image quality. To this end, we compare the number of relevant and unnecessary warnings between a model-based approach and the currently used reference value-based method in dose management. In addition, we quantify the number of relevant deviations from optimal examination procedures newly discovered by the model.

—

Countries

Germany

Contacts

Public ContactAlois Martin Sprinkart

Universitätsklinik Bonn

Alois.Sprinkart@ukbonn.de+49 228 287 25670

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Jun 11, 2026