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Projects / Programmes source: ARIS

Zagotavljanje kakovosti v nuklearni kardiologiji (Slovene)

Research activity

Code Science Field Subfield
3.06.00  Medical sciences  Cardiovascular system   

Code Science Field
B145  Biomedical sciences  Nuclear medicine, radiobiology 
B725  Biomedical sciences  Diagnostics 
Keywords
Nuclear cardiology, perfusion scintigraphy of myocardium, quality control of radiopharmaceuticals, quality control of nuclear medicine detectors, quality assurance, artificial inteligence
Evaluation (rules)
source: COBISS
Researchers (10)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  17679  Jožica Arko    Researcher  1999 - 2001 
2.  09790  PhD Jurij Fettich  Cardiovascular system  Head  1996 - 2001  297 
3.  09791  PhD Valentin Fidler  Cardiovascular system  Researcher  1996 - 2001  118 
4.  15706  PhD Tanja Gmeiner  Pharmacy  Researcher  1999 - 2001  147 
5.  06769  PhD Ciril Grošelj  Cardiovascular system  Researcher  1996 - 2001  85 
6.  17680  Olga Ivančič    Researcher  1996 - 2001 
7.  17681  Albina Pečarič    Researcher  1996 - 2001 
8.  17682  Mira Pompe    Researcher  1996 - 2001 
9.  05366  Milan Prepadnik  Cardiovascular system  Researcher  1998 - 2001  51 
10.  17683  Ivan Slodnjak    Researcher  1999 - 2001  42 
Organisations (1)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0312  University Medical Centre Ljubljana  Ljubljana  5057272000  77,904 
Abstract
The purpose of the research project is to increase the quality and reproducubility of the myocardial perfusion scintigraphy for the diagnosis of iscaemic heart disease. For this purpose we have standarised acquisition protocols of the procedure. Quality control of the nuclear medicine equipment, software as well as hardware was carried out in the framework of interlaboratory colaboration coordinated by European Community''s COST B2 project and COST B3 project for quality control of the radiopharmaceuticals. The aim of the study is to determine whether it is possible to increase the accuracy of interpretation of results of myocardial perfusion scintigraphy by applying methods of artificial intelligence, which can simultaneously evaluate all available clinical data (history, stress test, ECG, and scintigraphy). We intend to test this hypothesis on results of scintigraphy of patients with angiographically confirmed or excluded coronary artery disease.
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