Image Quality The capacity to define, measure, and assess image quality is a primarily responsibility of a CT Technologist.

IMAGE QUALITY TESTS The one comprehensive  CT image quality characteristic is visibility.  That is the visibility of anatomical structures, various tissues, and signs of pathology.  However, visibility depends on a somewhat complex combination of the five (5) more specific image characteristics shown here.  Contrast Sensitivity Visibility of Detail, as affected by blurring (Sometimes called spatial resolution) Visual Noise Artifacts Spatial or geometric characteristics of the image/body relationship Each of these can have an effect on the visibility of specific anatomical or pathologic objects within the body.

Scan Parameters Many factors affect the quality of the image produced. Those that can be controlled by the operator are: Milliampere level (mA) Scan time Field of view Reconstruction algorithm Kilovolt-peak (kVp) Pitch (when helical mode is used)

Milliamperes and Scan Time Referred to as mAs The total x-ray beam exposure Together they define the quantity of the x-ray energy Higher mA settings allow shorter scan times to be used A short scan time is critical in avoiding image degradation as a result of patient motion

Tube Voltage or Kilovolt Peak Commonly referred to as kVp Defines the quality (average energy) of the x-ray beam In CT, kVp does not change contrast as directly as it does in film-screen radiography Compared with mA selection, choices of kVp are more limited

Impact of mAs and kVp on Radiation Dose The appropriate selection of mAs and kVp is critical to optimize radiation dose and image quality It is more common to manipulate the mAs, rather than the kVp, when modifying the radiation dose, because The choice of mA is more flexible The effect of mA on image quality is more straight-forward and predictable

The Uncoupling Effect Using digital technology, the image quality is not directly linked to the dose, so even when an mA or kVp setting that is too high is used, a good image results Makes CT physics somewhat different from that of film-screen radiography

Automatic Tube Current Modulation Software that automatically adjusts the mAs to fit the specific anatomic region Results in a 15% to 40% reduction in dose, without degrading image quality

Slice Thickness and Field of View In discussion of image quality we are primarily interested in the slice thickness (how the data were acquired) rather than image thickness (how the data are reconstructed) Scan field of view (SFOV) determines the area, within the gantry, for which raw data are acquired Display field of view (DFOV) determines how much, and what section, of the collected raw data are used to create an image

Reconstruction Algorithm and Pitch By choosing a specific algorithm, the operator selects how the data are filtered in the reconstruction process Can only be applied to raw data Pitch The relationship between slice thickness and table travel per rotation during a helical scan acquisition

Scan Geometry Tube arc during the acquisition for each slice Full scan (360°) is most common Partial scan (180° + degree of arc of the fan angle) Also referred to as half-scans Overscans (400°) Used mainly in fourth-generation scanners to reduce motion artifact

Image Quality Defined Applies to all types of images The comparison of the image to the actual object In many regards “quality” is a subjective notion and is dependent on the purpose for which the image was acquired In CT, the image quality is directly related to its usefulness in providing an accurate diagnosis This section deals primarily with the more objective measures of image quality

Image Quality Two main features are used to measure image quality or visibility of detail - Spatial resolution: the ability to resolve (as separate objects) small, high-contrast objects Contrast resolution: the ability to differentiate between objects with very similar densities as their background

Spatial Resolution Also called detail resolution (units of line pairs per centimeter lp/cm) Measured using two methods Directly, using a line pairs phantom Or by data analysis known as the modulation transfer function (MTF) MTF is often used to graphically represent a system’s performance – is an objective measurement.

Spatial Resolution (cont’d) Can be described in two dimensions In-plane resolution: resolution in the x,y direction Longitudinal resolution: resolution in the z direction

In-plane resolution Is the accuracy with which the object being imaged is represented. When x-rays are detected, a signal is generated. This signal has a specific frequency that relates to the size and density of the object being imaged. Larger objects of uniform density are represented by low spatial frequency signal Smaller dense objects and sharp borders by high spatial frequency signal. The relationship of this signal to the object detail (lp/mm) is the MTF. Where MTF can be used to compare scanner performance. If Scanner A has 5.2 lp/mm at 0.1 MTF compared with 3.5 lp/cm at 0.1 MTF for scanner B, then it means scanner A has better spatial resolution.

In-Plane Resolution Measurements Can be measured by evaluating the point spread function (PSF). Is used to quantify amount of blurring that occurs within an image of an object. To measure the PSF, a phantom with small wire is scanned. Alternatively can measure resolution with a patter of bars or the smallest range of closely spaced holes that can be discerned.

ACR PHANTOM – SPATIAL RESOLUTION

Factors Affecting In-Plane Spatial Resolution Focal spot size Detector Size Reconstruction algorithm Pixel size Matrix size Display field of view Sampling Frequency Pitch Patient motion

Focal spot and detector size Small FS size improves In-plane resolution. Large FS size increases geometric unsharpness – penumbra Selection of FS size tied to mA. Each CT system has an mA cutoff point, where the FS switches from small to large. Why? Smaller, more closely spaced detectors improve spatial resolution. Aka detector aperture or detector spacing. More detector means more signal may be recorded, so sensitivity to wide range of signals is improved.

Reconstruction algorithm (aka convolution kernel) High spatial frequency algorithms, such as those used for edge or bone, emphasize high frequency signals during reconstruction. Lower spatial frequency algorithms, such as soft tissue, produce low spatial frequency information. Selection of algorithm is based on clinical application.

Pixel size Combination of large matrix and small DFOV (large zoom factor) results in a smaller pixel size and increase in the in-plane resolution. Relationship of DFOV and matrix directly controls the size of the smallest detail a CT system is able to resolve. Smaller pixels will represent tissue more accurately.

Sampling Frequency The number of view obtained by the CT system during acquisition. Aka – views per rotation. Higher sampling frequency obtained by increasing the number of detectors or sampling rate.

Longitudinal Spatial Resolution Aka cross-plane spatial resolution Described by the slice sensitivity profile (SSP). Represent the slice thickness (or thickness of tissue) in the z-direction. As pitch is increased, the SSP indicates that there is broadening of the slice thickness along the z-axis. The reason for the broadinig is partial volume averaging, which increases with helical acquisitions. Effective section width refers to the widened SSP that occurs with increased pitch. Wilting, J.E. “Technical aspects of spiral CT”

SSP Effective section width is the Full Width at Half Maximum (FWHM) of the SSPM. It is measured by examining the SSP at half of its maximum height.

Factors that affect Longitudinal Spatial Resolution Spiral interpolation algorithm – applied to helical acquisitions to reduce the SSP broadening effects. 180 LI interpolation most commonly used. 360 is also used, but is wider than the 180. Pitch – For MSCT the detector collimation along the z-axis sometimes compensates for the negative effects of pitch.

Contrast Resolution Also called low-contrast detectability or system sensitivity Is the ability of a CT system to detect an object with a small difference in linear attenuation coefficient compared with surrounding tissue. CT is superior to all other clinical modalities in its contrast resolution For comparison, in screen-film radiography, the object must have at least a 5% difference in contrast from its background to be discernible on the image. On CT images, objects with a 0.5% contrast variation can be distinguished

Contrast Resolution (cont’d) Measured using phantoms that contain objects of varying sizes and with a small difference in density (typically from 4 to 10 HU) from the background Noise plays an important role in low-contrast resolution Noise is the undesirable fluctuation of pixel values in an image of homogeneous material “salt-and-pepper” look The presence of noise on an image degrades its quality

Factors Affecting Contrast Resolution Inherent subject contrast Thickness and atomic density of object as compared to surrounding tissue Inherent contrast can be augmented with administration of IV contrast. Beam Collimation Scatter radiation reduces contrast resolution. Reconstruction algorithm Low spatial frequency algorithms, like soft tissue or standard, improve contrast resolution. Window Width and Window Level

Factors Affecting Contrast Resolution Detector Collimation Increased detector collimation results in reconstruction of thinner sections. As section width decreases, the photon flux for each pixel also decreases. **Noise** Any increase in noise results in decreased contrast resolution. CT NOISE INCREASES WITH: SMALL PIXEL SIZES THIN CT SLICES LARGE PATIENT SIZES LOW CT DOSES

Noise Any portion of signal that is unwanted. Is random (stochastic) statistical variation in signal. Appears as overall graininess. 3 types Quantum noise – results when there is an insufficient x-ray flux. Is inversely related to the amount of radiation exposed to each voxel. What determines amount of radiation?? 2. Electronic noise – signal may be lost and noise introduced by the reconstruction process. 3. Artifactual noise – artifacts may be viewed as a type of noise. Signal to Noise ratio (SNR) – describes or quantified the amount of noise in a displayed CT image. Goal is produce an image with high SNR while keeping dose and spatial resolution appropriate.

Noise Many technical factors that affect noise and resolution. The relationship can be illustrated as: D = SNR2 / (∆3t) Where D is radiation dose ∆ is pixel dimension T is section width.

Parameters that most directly affect Noise X-ray photon flux – rate at which x-ray photons pass through a given unit of tissue. Largely controlled by mA and time and kVp. Voxel Size – Larger voxel has greater photon flux and less noise. Size can be increased by increasing DFOV (decrease zoom factor), decrease matrix size, or increase section width. Pitch/Table Speed – Increase in pitch means that each voxel is exposed to less photons. Detector sensitivity Patient factors Algorithm/kernel.

Other Contrast Resolution Considerations Pixel size Slice thickness Patient size

Temporal Resolution How rapidly data are acquired Controlled by Gantry rotation speed Number of detector channels in the system Speed with which the system can record changing signals Reconstruction method Reported in milliseconds 1,000 milliseconds = 1 second

Review The appropriate technique for a given patient examination is 200 mAs. The technologist mistakenly uses 100 mAs. Which aspect of image quality will be most affected? Spatial resolution Contrast resolution Temporal resolution

Answer c. Contrast resolution Insufficient mAs will result in increased noise, which primarily affects contrast resolution.