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Tissue Contrast

Tissue Contrast. intrinsic factors relative quantity of protons tissue proton density relaxation properties of tissues T1 & T2 relaxation secondary factors flow contrast agents. Contrast. the ability to discriminate different tissues based on their relative brightness. Basic Principle.

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Tissue Contrast

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  1. Tissue Contrast • intrinsic factors • relative quantity of protons • tissue proton density • relaxation properties of tissues • T1 & T2 relaxation • secondary factors • flow • contrast agents

  2. Contrast • the ability to discriminate different tissues based on their relative brightness

  3. Basic Principle • relatively intermediate intensity structures look bright on a dark background • important to remember with fatsat • relatively intermediate intensity structures look dark on a light background

  4. Caveat • windowing affects the relative contrast of tissues • intensity values of pixels are relative to one another, unlike CT • windowing can make a solid tumor look like a “cyst”

  5. “CYST” T2 FSE T1 SE

  6. CYST? T2 FSE T1 SE

  7. CYST? T2 FSE T2 FSE

  8. Summary • need visible differences in intensity to discriminate tissues • surrounding tissues can make an intermediate signal tissue appear dark or bright • windowing affects image and tissue contrast

  9. Noise • constant at a given machine setup • reduces the ability to visualize low contrast structures • adds to or subtracts from the average signal intensity of a given pixel

  10. Noise • increasing the available signal will reduce the relative effects of noise • machine parameters must be chosen to maximize signal without significantly extending exam times • S/N is a relative measure allowing for comparison in a variety of circumstances

  11. high signal high SNR low signal low SNR SI SI frequency frequency Signal versus Noise

  12. Image Contrast 100% noise

  13. Image Contrast 80% noise

  14. Image Contrast 60% noise

  15. Image Contrast 40% noise

  16. Image Contrast 20% noise

  17. Image Contrast 0% noise

  18. Factors Affecting SNR • strength of main magnet • coil selection • voxel size • phase encoding • number of averages • receiver bandwidth • pulse sequence parameters

  19. SNR

  20. Factors INCREASING SNR • stronger main magnet • proper imaging coil • larger voxel size • decreased phase encoding • increased number of averages • decreased receiver bandwidth • (pulse sequence parameters)

  21. linear increase less T1 weighting at high fields increased chemical shift effects in RO direction Stronger Main MagnetS/N effect Downside

  22. Coil SelectionS/N effect Downside • increase in signal with surface coils • quadrature provides 40% increase S/N over linear • phased array increased over quadrature • limited coverage with surface coils • more complex coils are more expensive

  23. Larger Voxel SizeS/N effect Downside • linear increase in either RO or PE direction • linear increase with increased slice thickness • decreased resolution

  24. Decreased Phase EncodingsS/N effect Downside • square root increase in signal to noise • linear decrease in scan time • decreased resolution in PE direction • Gibb’s phenomenon in PE direction

  25. Increased Signal AveragesS/N effect Downside • square root increase in signal to noise • linear increase in scan time

  26. Decreased Receiver BWS/N effect Downside • square root increase in signal to noise • increase in chemical shift artifact in RO direction

  27. Pulse Sequence Parameters • SE imaging • increased TR provides nonlinear increase in SNR with linear increase in scan time • decreased TE provides nonlinear increase in SNR with no effect on scan time and less T2 weighting

  28. Pulse Sequence Parameters • GE imaging • complex effects • maximum SNR typically between 30 and 60 degrees • long TR sequences (2D) • increase SNR with increased flip angle • short TR sequences (TOF & 3D) • decreased SNR with increased flip angle

  29. SNR Application • pituitary imaging • baseline: • 16 cm FOV, 3 mm slice thickness, 192 phase encodes, 4 NEX • new goal: • reduced scan time, same SNR

  30. SNR Example

  31. Fat Suppression and SNR • non fat-suppressed image • each image pixel comprised of signal from water and fat in the imaging voxel • fat-suppression • reduces total signal by suppression of fat from the voxel • reduces SNR

  32. without fat suppresion high SNR with fat suppression lower SNR SI SI frequency frequency Fat Suppression water plus fat water only

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