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CT Image Quality
Wil Reddinger, M.Sc., R.T.(R)(CT)copyright April 1998
OutSource, Inc. (all rights reserved)
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CT IMAGE QUALITY
Wil Reddinger, M.Sc., R.T.(R)(CT)copyright April 1998
One of the most important functions of a computed
tomography (CT) system is to reproduce a three-
dimensional structure and represent that structure as an
accurate two-dimensional cross-section on a television
monitor. There are several characteristics that effect how
well a CT system performs this task. Spatial resolution,
contrast resolution, linearity, noise and artifacts are the
primary characteristics that effect image quality in CT.Enhancing or suppressing any of these characteristics
depends upon the imaging interests and the region of the
body being scanned. It is important that to realize that
changing CT parameters such as section thickness,
algorithms and field of view have a profound effect on
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the overall quality of the CT image. CT image quality is
dependant upon balancing these characteristics andparameters to produce the best possible image for the
anatomical region being scanned. Image noise and
artifacts are the two biggest enemies of CT image
quality. CT parameters can be manipulated to either
decrease or eliminate the adverse effects of these imagequality characteristics. Generally, there is a trade-off
when CT parameters are manipulated. For example, if a
bone reconstruction algorithm is utilized to increase
spatial resolution, image noise increases which degrades
contrast or soft tissue resolution. Increasing technical
factors such as mAs or kVp decreases image noise but an
increase in patient dose occurs. The CT technologist's
goal is to manipulate CT parameters according the
imaging interest or situation.
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Spatial resolution is the CT system's ability to
differentiate small objects that are adjacent to oneanother. The CT scanner's resolving power relies on how
well small objects that are close together but have very
different attenuation values or CT numbers are imaged.
The point between two small objects with very different
densities is considered to be a region of high frequencyor high contrast. An inherent problem with any CT
system is that the edges or boarders of these high
frequencies are blurred to a certain degree. Therefore,
instead of imaging these two small structures as separate
entities, the CT system "sees" them as one structure. A
CT system that can image high frequency regions
without blur results in smaller objects being resolved.
Spatial resolution in conventional radiography is superior
compared to the spatial resolution of computed
tomography. For example, when evaluating a radiograph
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of the facial bones, it is easy to see that blurring does not
occur between the maxillae and the maxillary sinuscavity. The area where the edge of the bone meets the
sinus is not blurred unless the patient moved during the
exposure. A CT section of the same region reveals a
"fuzzy" or "hazy" appearance around the edges of the
bones. There are parameters that a CT technologist canmanipulate to increase the spatial resolution when
scanning high frequency regions. Utilizing a bone, sharp,
high frequency or high pass algorithm during
reconstruction mathematically enhances the edges of
structures by diminishing structural blurring. However,
the added algorithm produces statistical interference,
which results in an increase in image noise. The increase
in image noise decreases contrast or soft tissue
resolution. Generally, this is an expected outcome
because the scan involved visualizing the bone and the
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soft tissue demonstrated is sacrificed. Utilizing a bone
window, a wide window width and a high window level,is necessary to visually enhance the edges of a structure
(Figure 1).
Decreasing section thickness narrows the collimated
beam that concentrates the photons on to a smaller area,
which increases spatial resolution. Zooming or targeting
requires the operator to manipulate the displayed field of
view. Zooming or targeting takes a selected region and
spreads it over the entire matrix that is used to create and
display the CT image. A 512 X 512 matrix yields 262,
144 pixels or "little squares" that the image is displayed
upon. If an image an entire abdomen is imaged the
matrix contains all of the abdominal structures which fill
the 262,144 pixels. If the CT technologist wants to
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Figure 1 shows the effect of window width and level
on image noise.
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increase the spatial resolution of an individual vertebra,
the vertebra is "Zoomed" or "Targeted". The result isthat the vertebra fills the 262,144 pixels thereby
increasing the imaging accuracy of the structure.
Primarily, zooming or targeting decreases partial volume
averaging of a region which increases the accuracy of the
CT numbers in a region of interest measurement. Thereare 262,144 pixels used to display the image but zooming
or targeting decreases their overall size, which decreases
the possibility of many tissues occupying a single pixel.
Zooming or Targeting is not the same as image
magnification. Image magnification is usually achieved
by turning a dial or trackball, which results in pixel
stretching. Although, this technique may be visually
appealing it does not change the amount of tissue
occupying a single pixel. The ultimate situation would
be to fill each individual pixel with one tissue type.
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However, computer and display matrices are limited in
size so it is not likely to happen. Other factors thatinfluence spatial resolution include pixel size, which is
influenced by the chosen, scanned field of view and
matrix size, width of the detector, spacing between
detectors, number of projections or views obtained and
focal spot size.
Several methods that quantify or measure spatial
resolution include the point-spread function (PSF), line
spread function (LSF), edge response function (ERF) and
the modular transfer function (MTF). The MTF is the
most commonly used method to measure the spatial
resolution capabilities of a CT system, which is
graphically depicted. The MTF demonstrates the
frequency components of a structure in line pairs per
centimeter (lp/cm). A line pair phantom consists of lead
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strips that are placed at different widths apart. The more
lines that can be visualized separate from one another,the better the systems spatial resolution. Spatial
resolution depends upon imaging high frequency
structures located a very small distance apart. In figure
** an MTF value of 1.0 represents a complete, without
blurring, transfer of an object through the CT system to amonitor. An MTF value of 1.0 corresponds to imaging
large structures that can very easily be imaged accurately
by most CT systems. Therefore, the value of 0.1, which
represents small, high frequency or density structures, is
used to evaluate the spatial resolution capabilities of a CT
system. It is known that a CT system does not have
problems faithfully imaging large structures such as the
liver or brain. Because of the inherent blurring of small,
high density structures like IAC's it is important that
individual's purchasing CT systems should inquire how
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Figure 2: Modulation Transfer Function (MTF) Graph
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CT scanner to image these slight differences is known as
low contrast delectability, which is used to describecontrast resolution in computed tomography. Essentially,
contrast resolution describes the CT systems ability to
discriminate between two or more anatomical structures
that attenuate "nearly" the same amount x-ray photons.
CT is superior compared to conventional radiography indiscriminating the absorption differences between
structures that have similar but slightly different
absorption characteristics. The liver, kidneys and psoas
muscles are large structures that have different densities
and atomic numbers but the absorption characteristics ofthe structures are not very different. Conventional
radiography of the abdomen reveals the image structures
as primarily "gray shaded" shadows and are some are
superimposed. The position of the structures can be
determined but the actual attenuation values cannot be
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distinguished from one another. Computed tomography
not only eliminates the superimposition of structures but
absorption differences can be determined. Absorption
properties of any tissue are represented by linear
attenuation coefficients, which are numbers that describe
the absorption characteristics of the tissues imaged. It is
important to remember that the linear attenuationcoefficient is an absorption measurement and it is
dependant on thickness of a material, density of a
material, atomic number and photon energy. A kVp
change results in a change of a structures linear
attenuation coefficient even if the same structure is beingimaged. This is critical because the CT computer
eventually assigns each pixel that contains a linear
attenuation coefficient a number known as a Hounsfield
Unit (HU) or a CT number. A CT operator can utilize a
region of interest (ROI) measurement to visually display
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Figure 3: Region of Interest (ROI) measurements
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section thickness is reduced the lead jaws of the
collimator aperture closes which reduces the number of
photons reaching the detector. The finely collimated
beam is also filtered before it goes through the patient.
These special filters called bow-tie filters absorb weaker
energy photons, which reduce the possibility of scattered
photons being detected by the CT detectors. An x-raybeam consists of polychromatic photons or photons
having different energies. The bow-tie filters serve to
absorb lower energy photons primarily to "lessen" the
effects from the polychromatic nature of an x-ray beam.
If the x-ray beam was not heavily filtered the accuracy ofCT numbers would be sacrificed because less desirable
photon energies would probably scatter and be included
in the attenuation value of the tissue scanned. The ideal
situation would be to have monochromatic x-ray photon
energies pass through the patient and into the detectors.
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This is a virtually impossible thing to do but heavy
filtration and thin collimation of the x-ray beam makes
the situation better. When section thickness is reduced
the number of photons concentrated on the area of
interest is reduced. Decreasing the number of photons
results in the image becoming more "grainy". The
"grainy" appearance of the section is due to image noise.For example, During a CT scan of the abdomen a
technologist may be required to begin the procedure
utilizing a 10 millimeter (mm) section thickness. The
abdomen protocol may require the technologist to reduce
the section thickness to 5mm if the pancreas is a specificarea of interest. When comparing the 10 mm and 5 mm
sections, note that the 5 mm sections appear to be
grainier in appearance than the 10 mm sections. This
results from limiting the number of photons used to
create the 5 mm sections compared to the 10 mm
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sections. Increasing the number of photons to the 5 mm
sections may be accomplished by increasing mAs or
kVp. However, the increase in technical factors
increases patient dose.
A soft tissue, standard or smooth algorithm is used
during the reconstruction process to enhance soft tissueand contrast resolution. Soft tissue, standard or smooth
algorithms are low-frequency or low pass algorithms.
Low-frequency or low pass algorithms mathematically
accentuate the soft tissues or where there are subtle
attenuation differences between the tissues being imaged.
The use of these algorithms requires a narrow window
width and a low window level to properly be visualize on
a television monitor. Detector systems must be sensitive
to all the possible interactions between photons and
imaged tissues. The number of levels of information that
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a detector can detect is called the dynamic range of a
detector. The higher the dynamic range the better the
detector will be able to see and discriminate between
small differences in attenuation.
Morgan (1983) defines linearity as " Property of a
detector characterized by an output electrical current thatis exactly linearly proportional to the input radiation
incident on the detector." Linearity is utilized to describe
the performance of the CT system. Linearity describes
the accuracy between the linear attenuation coefficient
and the computer assigned CT number. The CT number
scale assigns the linear attenuation coefficient of water
the CT number zero. Bushong (1997) describes that the
phantom utilized for the quality assurance of linearity of
a CT system utilizes several materials placed in different
positions throughout a water phantom. These materials
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contains no information. Noise is characterized by a
grainy appearance of the image. Many authors describe
noise as a salt and pepper pattern on the CT image. If a
quality assurance phantom is comprised of a known
material like water, when the phantom is used to evaluate
the quality of the image, it is expected that every portion
of that phantom would have the CT number zero. Due tothe statistical fluctuation in every scan it is impossible for
this to occur. In the case of too little radiation, too few
photons reach the detectors. As a result, the variance of
CT numbers pixel to pixel is quite large. When a ROI is
selected and the average CT number is displayed, thestandard deviation is quite large. The level of noise in an
image is recorded as the standard deviation in an ROI
measurement. The larger the standard deviation, the less
accurate the average CT number of the ROI. An analogy
would be that of asalary survey. If only 5 people were
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interviewed and their annual salary recorded, an average
salary could be calculated. The variance, or deviation,
between each salary listed would in all likelihood be
quite large and the less the average would reflect any one
of the five. On the other hand, if 100 people were
interviewed, the deviation between each salary listed
would not be as great as it was with just 5 people. Theaverage salary calculated would more accurately reflect
the salary of the group(Figure 4).
CT system manufacturers have minimum and maximum
values for allowable differences in CT numbers of a
water phantom. Generally the range of +3 to -3
difference in CT numbers is negligible. Many of the
spiral/helical scanners have a +4 to -4 allowable range
because of the mathematical process of interpolation is
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Figure 4: Noise as a result of low radiation dose
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included with the image reconstruction process. The
major types of noise include quantum noise, electronic
noise and computational noise. Quantum noise is a result
of too few photons reaching a detector after being
attenuated by the body. Any factor that limits the
number of attenuated photons at the detector will
increase image noise. Anatomical structure size,reduction of slice thickness without increasing technical
factors, decreasing pixel size and scatter radiation are all
factors that contribute to image noise. Electronic noise is
noise contained within the image that can be caused by
vibrations of any of the physical components, especiallythe rotational components or power fluctuations.
Computational noise is primarily caused by all the
statistical fluctuations that occur from the reconstruction
mathematics that are essential to produce a CT image. A
CT image involves millions of mathematical equations
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being solved at approximately the same time.
Spiral/helical CT data uses a mathematical technique
called interpolation along with a reconstruction algorithm
to produce axial image data from a volume of data. The
process of adding a mathematical technique makes the
computer work harder, which results in the CT image
suffering by becoming grainier in appearance. It may be
very difficult to actually distinguish which characteristic
is responsible for the grainy appearance of an image but
noise is always there.
"An Artifact is any distortion or error in the image that is
unrelated to the subject being studied (Morgan 1983)."
Wolbarst (1993) describes artifacts as aberrations that
arise at the interfaces of materials significantly different
from the radiologic properties of the structures being
scanned. There are many causes of artifacts that degrade
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image quality as well as hide areas of pathology.
Artifacts can appear as geometrical inconsistencies,
blurring, streaks or inaccurate CT numbers. Streak
artifacts are the most common distortions or errors that
affect the quality of CT images. Motion, metallic
objects, out-of-field, edge gradient effects, high-low
frequency interfaces, equipment malfunctions and
sampling errors are all causes of streak artifacts.
Motion artifacts occur primarily because during
reconstruction the mathematical algorithm is unable to
solve for the inconsistencies in attenuation. Imagereconstruction relies on the computer's ability to place
attenuation values onto a matrix, which is nothing more
than grid that has rows and columns of little blocks or
pixels. If motion occurs during the scan the computer is
unable to place an attenuation value at the proper
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corresponding "address" so it can only manipulate the
data it is given. The result usually appears as blurring or
streaking of the object being scanned.
Metallic objects such as dental fillings or prosthesis
cause a streaking effect on an image. The appearance
may mimic a "splashing" effect from the middle of thestructure towards the edges of the object scanned. The
primary reason that streaks occur from metal objects is
because the objects exceed the attenuation values that CT
system can faithfully image(Figure 5).
Many older CT number scales assign the number 1000 as
the top of the number scale. The number 1000 coincides
with the attenuation value of cortical bone, which is
primarily the densest structure in the human body. Many
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alloys used to make dental fillings or prosthesis have
attenuation values greater than cortical bone. Therefore,
the computer can only assign the highest value it knows.
These metallic type objects exceed the dynamic range of
the detectors in the detector array. The result is the
metallic object is unable to be faithfully image resulting
in streak artifacts. Many newer CT systems include
attenuation values higher than bone. CT number scales
have been expanded to include objects that have a CT
number as high as 4,000.
Out of field artifacts are caused by anatomy that is outside of the selected scan field of view. For example, if a
persons chest measures 54 centimeters (cm) and the
maximum scan field of view is 48cm, the CT system can
only image 48 of the 54 cm. Unfortunately, The "extra"
tissues are blocking detectors and attenuating photons.
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The CT system can only account for the 48 cm scan
circle and is unable to avoid the blocked detectors.
Streak artifacts occur throughout the entire image, which
degrades diagnostic accuracy and the overall quality of
the CT image(Figure 6).
Edge gradient and high-low frequency interface aresimilar causes of streak artifacts present on an image.
Edge gradient streak artifacts generally occur when the
edges of a "sharp" high-density object interface with a
smooth surface. A streak artifact originates from the
edges of the high frequency structure. Edge gradientartifacts frequently occur from the edges between bone
and soft tissue. For example, on a CT image of the pelvis
the ischial spines are sharp high frequency structure that
interface with adjacent muscle tissue, which is a low
frequency structure. A thin black streak artifact arises
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Figure 6: Streaking caused by tissue being outside the scan
circle (scan FOV).
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from the edge of the bone. The streak emanating from a
thin biopsy needle is an example of edge gradient streak
artifacts. Streak artifacts arise from materials or
structures when a high-density material such as barium
interfaces with a low-density material such as air. This
type of streak artifact commonly occurs in the
gastrointestinal tract is filled with barium and air. The
artifact arises due to the inability of the CT system to
"transfer" the information accurately. In the previous
discussion of spatial resolution, it was explained that CT
systems inherently have problems with imaging
structures that rapidly change from high to low densities(Figure 7).
Equipment malfunctions such as tube arching, electrical
malfunctions and detector malfunctions produce streak
artifacts on a CT image. Tube arching artifacts give rise
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Figure 7: Steaks due to dense contrast material in the bowel.
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to many streaks and may appear to look like a "lightening
storm". Streak artifacts that arise from malfunctioning
detectors generally appear as straight line streaks. Edge
gradient streak artifacts are contained within the
anatomical part and are not always straight line streak
artifacts. A malfunctioning detector causes a straight
black line streak artifact on a scout image. Streak
artifacts may also arise if too few views or projections of
an object are obtained. These types of streak artifacts
have been virtually eliminated because CT scanners are
capable of producing hundreds of thousands of views or
projections. The more views, or projections, "taken" ofan object, the more accurate the image reconstruction.
Beam hardening artifacts occur when the low energy
photons are absorbed leaving the high-energy photons to
strike the detectors. When x-ray photons strike a high-
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density structure such as bone, lower energy photons are
absorbed which results in further hardening of the beam.
Hardening the beam results in a more penetrating beam.
If the photons then traverse over a region that consists of
low densities structures such as the brain, the resultant
effect is a thick streak artifact that appears across the
region. This occurs because the effective energy of the
x-ray beam is increased when it passes through the
tissues being scanned. When the energy of the beam is
changed during the scanning process, the linear
attenuation coefficients of the tissue that the "harder"
beam travels across are changed. If an ROI measurementwere taken in the area of the dark streak one would find
that the CT numbers would be lower in that region. For
example, when imaging the posterior fossa, beam-
hardening artifacts are found in the area between the
bone and soft tissue. If an ROI measurement were
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occurs due to one or several misaligned or miscalibrated
detectors in the detector array of the rotate-rotate CT
system. The tube and detector array rotate at the same
time. The tube and detectors are physically connected to
one another. If the tube shifts slightly it can cause
misalignment of the CT system. Therefore, a "bad" view
is created for every photon that the misaligned or
miscalibrated detector or detectors "sees". The result is
non-uniform information becoming a part of the image
that manifests as a series of rings. The detector or
detectors must be re-aligned or re-calibrated to eliminate
ring artifacts(Figure 9)
.
The partial volume effect or volume averaging is when
two or more different tissue types occupy the same pixel
and are averaged together. The ultimate scenario for CT
would be for one tissue type to occupy one pixel. Due to
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Figure 9: Ring artifact(s)
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the limitations of CT matrices, which determine how
many pixels, makes up a CT image this is virtually
impossible to accomplish. For example, if one pixel
contained three separate tissues that had CT numbers of
60, 80 and 200, the ROI measurement of that pixel would
be approximately 113. The tissues are averaged which
produces a number that is inconsistent with the three
tissues that were evaluated. Partial volume averaging is
always present and can never be entirely eliminated.
Utilizing smaller section thicknesses or smaller displayed
field of views may increase the accuracy of CT numbers.
CT image quality is dependant upon the balancing of
parameters relative to image resolution. Balancing image
quality by manipulating and altering CT parameters
depends upon the region or the condition being scanned
with respect for patient dose. Image quality is also
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dependant upon limiting or eliminating the image
degrading effects of noise and artifacts.
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