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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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