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Функциональное ультразвуковое исследование×Кинетическое моделирование ПЭТ×
ОбластьМедицинская визуализацияМедицинская визуализация
СемействоProcess / pipelineProcess / pipeline
Год появления20111983
Автор методаMickael TanterChristoph Patlak
ТипHigh-framerate doppler imaging for hemodynamicsMathematical framework for tracer kinetics in PET imaging
Основополагающий источникMacé, E., Montaldo, G., Trenholm, S., et al. (2011). Functional ultrasound imaging of the brain. Nature Methods, 8(8), 662-664. DOI ↗Patlak, C. S., Blasberg, R. G., Fenstermacher, J. D. (1983). Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Journal of Cerebral Blood Flow & Metabolism, 3(1), 1-7. DOI ↗
Другие названияfUS, doppler ultrasound, ultrafast ultrasoundPET pharmacokinetics, Dynamic PET, PET compartmental modeling
Связанные55
СводкаFunctional Ultrasound (fUS) is a high-framerate Doppler ultrasound technique that dynamically maps blood flow and hemodynamic changes in vivo with millisecond temporal resolution. Pioneered by Tanter, Macé, and colleagues in the 2010s, fUS enables real-time imaging of microvascular perfusion in the brain and other organs. By combining ultrafast acquisition (1000-5000 frames per second) with Doppler processing, fUS reveals functional activity (hemodynamic changes during stimulation or behavior) and vascular networks with unprecedented spatiotemporal detail.PET kinetic modeling is a quantitative analysis technique that tracks the temporal behavior of radioactive tracers in tissue to extract physiological parameters such as blood flow, metabolic rate, and receptor density. Established by Patlak, Logan, and Gunn in the 1980s and 1990s, kinetic modeling transforms raw PET time-activity curves into interpretable biological measures. It is widely used in neurology, oncology, and cardiology to assess disease severity, treatment response, and regional tissue function.
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ScholarGateСравнение методов: Functional Ultrasound · PET Kinetic Modeling. Получено 2026-06-19 из https://scholargate.app/ru/compare