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Updated: Jun 14, 2025
In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Characterization of myocardial perfusion imaging systems - an extension of quality metrics
Dea Dundara Debeljuh1, Roberta Matheoud2, Orazio Zoccarato3
1Medical Physics and Radiation Protection Department, University Hospital Rijeka, Croatia; Radiology Department, General Hospital Pula, Pula, Croatia; Department of Medical Physics and Biophysics, Faculty of Medicine, University of Rijeka, Croatia.
Purpose:
The aim of this study was to evaluate the performance of myocardial perfusion imaging (MPI) systems in detecting perfusion defects (PDs). The defect perfusion index (DPI) was introduced to extend and further advance the current MPI quality metrics.
Methods:
An anthropomorphic phantom simulating normal and pathological myocardial perfusion conditions was imaged by various NaI-crystal detector systems with and without corrections for scatter (SC) and attenuation (AC) (Symbia, Symbia + SC, Symbia IQ + SCAC, Symbia IQ), and cadmium-zinc-telluride detector systems without corrections (DSPECT, D530c). The extent of PD and the summed score (SS) were obtained by comparing polar maps with ad hoc normal databases created for each MPI system by using phantom polar maps with normal perfusion. The segmental uptake (SU) and the global uniformity (GU) were evaluated. The DPI was calculated on segments included in the PD to minimize attenuation artifacts outside the PD. The 17 segmental model was used.
Results:
The highest level of uniformity of polar map was obtained for Symbia IQ + SCAC. D530c showed the highest extent of PD and dependence of the extent on the PD position. It showed in general the lowest SU values and the highest GU due to attenuation artifacts. Nevertheless, D530c outperforms other MPI systems in terms of PD detection, showing the highest DPI value. DSPECT system showed the lowest SS value, and DPI values comparable to NaI-crystal detector systems.
Conclusion:
The DPI can be evaluated to investigate the intrinsic ability of MPI systems to detect PDs, whatever the quantitative post-processing software used.
