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Comparison of methods of attenuation correction in myocardial scintigraphy with algorithms based on a based on a Convolutional Neural Network for attenuation correction

Comparison of methods of attenuation correction in myocardial scintigraphy with algorithms based on a based on a Convolutional Neural Network for attenuation correction - MYO-SCAC

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00033102
Enrollment
59
Registered
2023-12-19
Start date
2023-08-07
Completion date
Unknown
Last updated
2025-04-07

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

Conditions

Coronary heart disease

Interventions

Group 1: Myocardial scintigraphy SPECT/CT

Sponsors

Universitätsklinikum Augsburg, Klinik für Nuklearmedizin
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: Patients who are suspected of having chronic CHD after appropriate basic cardiological diagnostics and who have a corresponding pre-test probability. The range of indications for cardiac imaging diagnostics is considered to be a pre-test probability of CHD between 15 and 85% (average pre-test probability). The patient must be 18 years of age at the time of inclusion. Pregnancy is excluded by standard laboratory chemistry prior to the examination.

Exclusion criteria

Exclusion criteria: - Refusal of the clinical examination or participation in the study - Intolerance of the examination position due to other illnesses - Minors ( 200 mmHg syst., > 110 mmHg diast.) - Tachyarrhythmia or bradyarrhythmia - Hypertrophic cardiomyopathy and other forms of outflow tract obstruction - Severe AV blockages - Physical and/or psychological impairments - Ventricular pacemaker rhythm - Haemodynamically unstable patients or patients with acute myocardial infarction (ST segment elevation, Creatinine kinase or MB isoenzyme eleva

Design outcomes

Primary

MeasureTime frame
The aim of the study is to determine whether the CNN-based procedures for attenuation correction methods with the classical attenuation correction methods used in routine attenuation correction methods used in routine lead to methodological differences in the image data and ultimately also in the findings.

Secondary

MeasureTime frame
Furthermore, possible strengths and weaknesses of the individual strengths and weaknesses of the individual methods in order to determine whether one method is superior to the other. In addition, possible pitfalls in the diagnosis can be can be identified in order to further reduce the occurrence of false-positive or false-negative findings in the future.

Countries

Germany

Contacts

Public ContactConstantin Lapa

Universitätsklinikum Augsburg, Klinik für Nuklearmedizin

Nuk.Studien@uk-augsburg.de+498214002050

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026