Seeram Chapter 11: Image Quality CT Seeram Chapter 11: Image Quality

CT Image Quality Parameters Spatial Resolution Contrast Resolution Image Noise Artifacts

Factors Influencing CT Image Quality Beam Characteristics Subject Transmissivity Dose Slice Thickness Scatter Display Resolution Reconstruction Algorithm

Spatial Resolution Quantifies image blurring “Ability to discriminate objects of varying density a small distance apart against a uniform background” Minimum separation required between two high contrast objects for them to be resolved as two objects

Spatial Resolution

Resolvable Object Size & Limiting Resolution Smallest resolvable high contrast object Often expressed as line pairs / cm “Pair” is one object + one space One Pair

Resolvable Object Size: Limiting Resolution Smallest resolvable high contrast object is half the reciprocal of spatial frequency Example: Limited resolution = 15 line pairs per cm Pair is 1/15th cm Object is half of pair 1/15th / 2 1/30th cm .033 cm 0.33 mm 1/15th cm 1/30th cm

Geometric Factors affecting Spatial Resolution Focal spot size detector aperture width slice thickness or collimation Less variation likely for thinner slices attenuation variations within a voxel are averaged partial volume effect

Geometric Factors affecting Spatial Resolution Finite focal spot size focal spot - detector distance focal spot - isocenter distance

Geometric Unsharpness & CT Decreased spatial resolution if object blurred over several detectors Detector aperture size must be < object for object to be resolved Focal Spot Small Object to be Imaged Detectors

Non-geometric Factors affecting Spatial Resolution # of projections Display matrix size 512 X 512 pixels standard Reconstruction algorithms smoothing or enhancing of edges

Reconstruction Algorithm & Spatial Resolution Back projecting blurs image Algorithms may be anatomically specific Special algorithms edge enhancement noise reduction smoothing soft tissue or bone emphasis

Hi-Resolution CT Technique Very small slice thicknesses 1-2 mm High spatial frequency algorithms increases resolution increases noise Noise can be offset by using higher doses Optimized window / level settings Small field of view (FOV) Known as “targeting”

Contrast Resolution Ability of an imaging system to demonstrate small changes in tissue contrast The difference in contrast necessary to resolve 2 large areas in image as separate structures

CT Contrast Resolution Significantly better than radiography CT can demonstrate very small differences in density and atomic # This’ll be on your test. I guarantee it. Contrast Resolution Radiography 10% CT <1%

CT Contrast Resolution Depends Upon reconstruction algorithm low spatial frequency algorithm smooths image Loss of spatial resolution Reduces noise enhances perceptibility of low contrast lesions image display

CT Contrast Resolution Depends on Noise

CT Contrast Resolution Contrast depends on noise Noise depends on # photons detected # photons detected depends on …

# of Photons Detected Depends Upon photon flux (x-ray technique) slice thickness patient size Detector efficiency Note: Good contrast resolution requires that detector sensitivity be capable of discriminating small differences in intensity

Small Contrast Difference Harder to Identify in Presence of Noise

CT Image Noise Fluctuation of CT #’s in an image of uniform material (water) Usually described as standard deviation of pixel values

CT Image Noise Standard deviation of pixel values S(xi - xmean)2 Xi = individual pixel value Xmean = average of all pixel values in ROI n =total # pixels in ROI

Noise Level Units CT numbers (HU’s) or % contrast

Noise Measurement in CT Scan water phantom Select regions of interest (ROI) Take mean & standard deviation in each region Standard deviation measures noise in ROI

CT Noise Levels Depend Upon # detected photons quantum noise matrix size (pixel size) slice thickness algorithm electronic noise scattered radiation object size Photon flux to detectors…

Photon Flux to Detectors Tube output flux (intensity) depends upon kVp mAs beam filtration Flux is combination of beam quality & quantity Flux to detectors modified by patient Larger patient = less photons to detector

Slice Thickness Thinner slices mean less scatter better contrast less active detector area less photons detected More noise To achieve equivalent noise with thinner slices, dose (technique factors) must be increased

Noise Levels in CT: Increasing slice width = less noise BUT Increasing slice width degrades spatial resolution less uniformity inside a larger pixel partial volume effect

CT Image Quality in Equation Form s2(m) = kT/(td3R) Where s is variance resulting from noise k is a conversion factor (constant) T is transmissivity (inverse of attenuation) t is slice thickness d is pixel size R is dose

Noise Levels in CT: When dose increases, noise decreases dose increases # detected photons Doubling spatial resolution (2X lp/mm) requires an 8X increase in dose for equivalent noise Smaller voxels mean less radiation per voxel

CT Image Quality Trade-off s2(m) = kT/(td3R) To hold noise constant If slice thickness goes down by 2 Dose must go up by 2

Measurements of Image Quality PSF = Point Spread Function LSF = Line Spread Function CTF = Contrast Transfer Function MTF = Modulation Traffic Function

Point Spread Function PSF “Point” object imaged as circle due to blurring Causes finite focal spot size finite detector size finite matrix size Finite separation between object and detector Ideally zero Finite distance to focal spot Ideally infinite

Quantifying Blurring Object point becomes image circle Difficult to quantify total image circle size difficult to identify beginning & end of object Intensity ?

Quantifying Blurring Full Width at Half Maximum (FWHM) width of point spread function at half its maximum value Maximum value easy to identify Half maximum value easy to identify Easy to quantify width at half maximum Maximum Half Maximum FWHM

Line Spread Function LSF Line object image blurred Image width larger than object width Intensity ?

Contrast Response Function CTF or CRF Measures contrast response of imaging system as function of spatial frequency Lower Frequency Higher Frequency Loss of contrast between light and dark areas as bars & spaces get narrower. Bars & spaces blur into one another.

Contrast Response Function CTF or CRF Blurring causes loss of contrast darks get lighter lights get darker Lower Frequency Higher Frequency Higher Contrast Lower Contrast

CT Phantoms Measure spatial resolution noise contrast resolution Available from CT manufacturer private phantom manufacturers American Association of Physicists in Medicine AAPM Measure noise spatial resolution contrast resolution slice thickness dose

CT Spatial vs. Contrast Resolution Spatial & contrast resolution interact High contrast objects are easier to resolve Omprove one at the expense of the other Can only improve both by increasing dose Increasing object size Increasing contrast

Increasing object size Contrast & Detail Larger objects easy to see even at low contrast Increasing object size Increasing contrast

Increasing object size Contrast & Detail Small objects only visible at high contrast Increasing object size Increasing contrast

Contrast – Detail Relationship Contrast vs. object diameter less contrast means object must be larger to resolve Visibility Increasing object size Difference in CT # Object Diameter Increasing contrast

Modulation Transfer Function MTF Fraction of contrast reproduced as a function of frequency Freq. = line pairs / cm 1 MTF 50% Recorded Contrast (reduced by blur) Contrast provided to film frequency

MTF Can be derived from MTF = 1 means MTF = 0 means point spread function line spread function MTF = 1 means all contrast reproduced at this frequency MTF = 0 means no contrast reproduced at this frequency

MTF If MTF = 1 all contrast reproduced at this frequency Contrast provided to film Recorded Contrast

MTF If MTF = 0.5 half of contrast reproduced at this frequency Contrast provided to film Recorded Contrast

MTF If MTF = 0 no contrast reproduced at this frequency Contrast provided to film Recorded Contrast

CT Number Calculated from reconstructed pixel attenuation coefficient (mt - mW) CT # = 1000 X ------------ mW Where: ut = linear attenuation coefficient for tissue in pixel uW = linear attenuation coefficient for water

Linearity Linear relationship of CT #’s to object linear attenuation coefficients Checked with phantom of several known materials average CT # of each material obtained from ROI analysis Compare CT #’s with known coefficients 77 -100 325 50 -44

CatPhan

Cross-Field Uniformity Use uniform phantom (water) CT pixel values should be uniform anyplace in image Take 5 ROI 1 center ROI 4 corners ROI’s Compare standard deviation between ROI’s

CT Artifacts Distortion Areas where image not faithful to subject Sources patient image process equipment

CT Artifacts Distortion Phantoms with evenly distributed objects

Preview! CT Artifacts: Causes motion metal & high-contrast sharp edges beam hardening partial volume averaging sampling detectors

Motion Artifacts Causes streaks in image Algorithms have trouble coping because of inconsistent data

Artifacts: Abrupt High Contrast Changes Examples: prostheses dental fillings surgical clips Electrodes bone Metal absorbs all radiation in ray causes star-shaped artifact Can be reduced by software

CT Artifacts: Beam Hardening Increase in mean energy of polychromatic beam as it passes through patient Can cause broad dark bands or streaks cupping artifact Reduced by beam hardening correction algorithms

CT Artifacts: Partial Volume Effect CT #’s based on linear attenuation coefficient for tissue voxels If voxel non-uniform (contains several materials), detection process will average

Partial Volume Effect Can appear as Minimizing incorrect densities streaks bands Minimizing Use thinner slices

Image Artifacts: Ring Artifact in 3rd Generation Causes 1 or more bad detectors small offset or gain difference of 1 detector compared to neighbors detector calibration required Reason: rays measured by a given detector are all tangent to same circle

Quality Control in CT spatial resolution contrast resolution noise Performance tested at prescribed intervals Image Quality Tests spatial resolution contrast resolution noise slice width kVp waveform average & standard deviation of water phantom CT # scatter & leakage