Mapping myocardial perfusion with an intravascular MR contrast agent: robustness of deconvolution methods at various blood flows
| Autor: | Marc Janier, Didier Revel, Cendrine Casali, Emmanuelle P. Canet Soulas, Bruno Neyran |
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| Rok vydání: | 2002 |
| Předmět: |
Computer science
Swine Hemodynamics Contrast Media Blood volume In Vitro Techniques Coronary circulation Robustness (computer science) Coronary Circulation medicine Animals Radiology Nuclear Medicine and imaging Blood Volume business.industry Experimental data Pattern recognition Blood flow Models Theoretical Magnetic Resonance Imaging medicine.anatomical_structure Injections Intravenous Deconvolution Artificial intelligence Nuclear medicine business Perfusion Mathematics |
| Zdroj: | Magnetic resonance in medicine. 48(1) |
| ISSN: | 0740-3194 |
| Popis: | Evaluation of quantitative parameters such as regional myocardial blood flow (rMBF), blood volume (rMBV), and mean transit time (rMTT) by MRI is gaining acceptance for clinical applications, but still lacks robust postprocessing methods for map generation. Moreover, robustness should be preserved over the full range of myocardial flows and volumes. Using experimental data from an isolated pig heart preparation, synthetic MR kinetics were generated and four deconvolution approaches were evaluated. These methods were then applied to the first-pass T(1) images of the isolated pig heart using an intravascular contrast agent and rMBF, rMBV and rMTT maps were generated. In both synthetic and experimental data, the fit between calculated and original data reached equally good results with the four techniques. rMBV was the only parameter estimated correctly in numerical experiments. Moreover, using the algebraic method ARMA, abnormal regions were well delineated on rMBV maps. At high flows, rMBF was underestimated at the experimental noise level. Finally, rMTT maps appeared noisy and highly unreliable, especially at high flows. In conclusion, over the myocardial flow range, i.e., 0-400 ml/min/100g, rMBF identification was biased in presence of noise, whereas rMBV was correctly identified. Thus, rMBV mapping could be a fast and robust way to detect abnormal myocardial regions. |
| Databáze: | OpenAIRE |
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