Limitations to X-ray Image Quality Flashcards
What are the three main limitations to x-ray image quality?
- Unsharpness.
- Scatter.
- Noise.
What does low unsharpness mean? What factors affect the unsharpness in an image?
Low unsharpness corresponds to the ability to be able to distinguish smaller objects. Objects should also appear sharper.
The following factors affect unsharpness:
- Focal spot size.
- Imaging geometry (e.g. focus-object and object-detector distance).
- Imaging receptor design (e.g. pixel size).
- Patient movement.
How does focal spot size affect unsharpness?
- For a larger focal spot, the amount of penumbra increases. This increases the unsharpness in the image.
- The focal spot size also varies across the image. It will be smaller towards the anode side of the image due to the projection of the actual focal spot from the angled anode target resulting in less unsharpness/blur at this side.
How does source-image distance (SID) distance affect unsharpness?
A shorter SID will result in a more magnified image and increased penumbra and unsharpness.
How does focus-object distance affect unsharpness?
A smaller focus-object distance will produce a magnified image with increased penumbra and unsharpness.
How are the unsharpness effects associated with reduced focus-object distance avoided in magnification mammography acquisitions? What are the issues with this?
- The fine focus is selected on the system.
- Tube loading effects mean a longer exposure time is required increasing the likelihood of movement blur.
How does compression in mammography affect unsharpness?
Compression causes the focus-breast distance to increase and the breast moves closer to the detector. This will decrease unsharpness, thus improving resolution.
State the equation for blurring b for an object at a distance x from a focal spot of size f and a distance y from a detector. How is this corrected to determine the geometric unsharpness (U_g) in object plane? What does this equation suggest is required to minimise U_g.
By considering geometry of the similar triangles created by this setup, we know that:
y/x = b/f
=> b = yf/x
M = SID/SOD = (x + y)/x
=> b = f(M-1)
U_g = f(M-1)/M
=> U_g = yf/(x + y)
=> U_g is minimised with a small focal spot (f), a large focus-object distance (x) and a small object-detector distance (y).
What factors determine receptor unsharpness (U_r) for DR and CR detectors? What is the equation?
- Unsharpness in DR detectors will be limited pixel size.
- Unsharpness in CR detectors will be limited by laser spot size.
- This can be calculated as U_r = F/M where F is the intrinsic receptor unsharpness (typically the pixel size for a DR detector).
How are geometric and receptor unsharpness combined?
Defining the unsharpness as the FWHM of each contribution, the total unsharpness can be determined by adding the geometric and receptor unsharpness in quadrature.
How can motion unsharpness be minimised?
- Use an exposure time that is as short as possible. There are limits on this, however, due to the size of the focal spot and anode heating effects.
- Increasing focus-detector distance and reducing object-detector distance will reduce motion effects.
- Compression can immobilise the breast in mammography.
How does scatter affect image quality?
Scattered photons contain no positional information regarding the distribution of x-ray attenuation coefficients in the material. This degrades image quality by reducing contrast.
What are the equations for contrast in the absence of scatter and with scatter included?
In the absence of scatter, contrast is defined as:
C = 1 - e^(x(mu_1 - mu_2))
where x is the thickness of the object and mu_1 and mu_2 are the attenuation coefficients of the object and the background, respectively.
With scatter included, this becomes:
C = (1 - e^(x(mu_1 - mu_2))/(1+R)
where R is the scatter-to-primary ratio (typically around 1 or above) and 1/(1+R) is the contrast degradation factor.
For a signal trace, this can be calculated as the difference in signal between an object and background as a proportion of the background signal.
How does an anti-scatter grid reduce scatter?
The grid consists of strips of high-attenuation material (e.g. Pb) separated by low attenuation material. Primary photons will pass through the low attenuation regions of the grid (assuming they are parallel). Scattered photons will be incident at a different angle and, therefore, will be preferentially attenuated by the high-attenuation regions. It should be noted that some primary photons will be attenuated and some scattered photons will still pass through the grid unattenuated.
Explain and give equations for the grid ratio and lines per mm for an anti-scatter grid. How to these factors affect scatter reduction?
- Grid ratio r = h/D where h is the length of the Pb bars and D is the width of the low-attenuation material. An increased grid ratio will make the likelihood of a scattered photon reaching the detector low as the acceptance angle will be small.
- Line-pairs per mm N = 1/(D+d) where d is the Pb bar thickness. Increased line-pairs will reduce the amount of scattered photons reaching the detector.
How does the divergence of an x-ray beam cause issues for a parallel anti-scatter grid? What is a solution to this?
- An increased amount of primary photons will be attenuated by the grid at the periphery of the image due to beam divergence.
- A focussed grid can be used get around this issue. The Pb strips are angled to match the divergence of the beam. This means they are only useable over a small range of focus-to-grid distances.
What issues are associated with the use of an anti-scatter grid?
- Total air kerma at the detector is reduced (primary transmission ~ 0.6). This means an increase in patient dose is required to maintain SNR, despite the effects of reduced scatter. This is known as the bucky factor.
- Grid artefacts associated with the grid attenuating primary photons. Normally, a moving grid design is employed to blur grid artefacts.
How does an air gap minimise scatter in magnification mammography? What are the issues associated with this?
- As the object is some distance from the detector (i.e. there is an air gap), scattered photons are more likely to be attenuated before reaching the detector or they are more likely to scatter outside of the detector area and not be detected.
- Geometric unsharpness will increase due to the increased magnification unless a smaller focal spot is used.
List and explain some techniques other than an anti-scatter grid or air gap that can be used to reduce scatter.
- Collimation will reduce the volume of exposed tissue and, therefore, the amount of scatter.
- Using a lower kV will increase the probability of photoelectric interaction (where this is approximately proportional to Z^3/E^3). This will mean photons are absorbed rather than scattered. However, this will correspond to an increase in patient dose.
- Compression in mammography will reduce the volume of tissue exposed and, therefore, reduce the amount of scatter.
What are the typical noise components apparent in an x-ray image?
- Quantum noise.
- Fixed pattern noise.
- Electronic noise.
- Anatomical noise.
- Film noise (granularity) in screen-film.
What is quantum noise? Provide an equation.
Quantum noise arises due to the random nature of photon interaction processes. They are described by Poisson statistics. The standard deviation gives a measure of quantum noise:
rho = sqrt(N) where N is the number of photons detected.
Provide an equation for signal-to-noise ratio (SNR) and explain. What is the effect of increasing the number of photons at the detector?
- SNR = sqrt(N) as signal is proportional to N and noise is proportional to sqrt(N) => N/sqrt(N) = sqrt(N).
- SNR will increase. Both signal and noise will increase but as the signal will increase more rapidly, the appearance of noise in the image will be reduced. This will mean an increase in contrast.
Why should x-ray systems be quantum noise limited?
Quantum noise limited systems can be optimised by varying dose to alter image quality to a level that is adequate for diagnostic purposes.
What causes fixed pattern noise? How does it vary with dose? How can it be reduced in DR systems?
- Fixed pattern noise results from variations in pixel sensitivity, filter thickness, tabletop attenuation etc.
- Its magnitude is dose dependent where it can be thought of as a signal (i.e. increased signal corresponds to increased fixed pattern noise).
- It can be reduced in DR systems with flat field corrections.