Módszerek összehasonlítása
Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.
| Képalkotási tömegcitometria× | PET kinetikai modellezés× | |
|---|---|---|
| Tudományterület | Orvosi képalkotás | Orvosi képalkotás |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 2014 | 1983 |
| Megalkotó≠ | Bernd Bodenmiller | Christoph Patlak |
| Típus≠ | Multiplexed single-cell imaging by mass spectrometry | Mathematical framework for tracer kinetics in PET imaging |
| Alapmű≠ | Giesen, C., Wang, H. A., Schapiro, D., et al. (2014). Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nature Methods, 11(4), 417-422. 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 ↗ |
| Alternatív nevek≠ | IMC, mass cytometry, multiplex ion beam imaging, MIBI | PET pharmacokinetics, Dynamic PET, PET compartmental modeling |
| Kapcsolódó | 5 | 5 |
| Összefoglaló≠ | Imaging Mass Cytometry (IMC) is a multiplexed proteomics technique that maps the subcellular localization of up to 40-50 proteins in tissue sections simultaneously using mass spectrometry detection. Developed by Bodenmiller and colleagues in 2014, IMC combines the single-cell imaging power of immunofluorescence with the multiplexing capacity of mass cytometry, enabling comprehensive analysis of cell types, states, and spatial interactions within tissue microenvironments. IMC has emerged as a powerful tool in immuno-oncology, immunobiology, and tissue biology for dissecting cellular heterogeneity and spatial organization. | 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. |
| ScholarGateAdatkészlet ↗ |
|
|