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Measuring Image Quality with Digital Radiography Systems

James F. Young, DVM

Imaging

|August 2005|Peer Reviewed

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The first article in this series briefly discussed the main two modalities that comprise filmless radiography: computed radiography and indirect digital radiography, the latter represented by flat-panel detectors and charged coupled device (CCD) systems. Comparisons were made in the basic means by which the systems convert the x-ray energy into a digital image. It was also discussed that the greatest value in computed radiography and digital radiography systems lies in their ability to improve image quality without taking repeated pictures, ultimately leading to an improved level of medicine. This article explores in greater detail key elements of measuring image quality.

Measuring Image Quality
Image quality can be measured and characterized but often becomes a subjective matter. In veterinary medicine, vendors and distributors are not required to provide the objective performance values of their systems and indeed may actually "muddy the waters" by providing biases about measures that have little influence on actual performance. This is critical, especially for our profession, as no standards set for imaging systems are currently being introduced for veterinary medicine. In human medicine, clearly established guidelines exist and systems are actually regulated by the Food and Drug Administration (FDA). Systems that have not been cleared by the FDA may introduce artifacts. Some digital radiography systems being introduced to veterinarians may not be approved by the FDA and may not measure up to long-established standards in human medicine. Until veterinary standards are set, we must determine what is acceptable on an individual basis. Thus, it is very important to understand the factors that are used to evaluate digital systems. The following definitions and key determinants are used to evaluate system performance and image quality.

Image Algorithm
One of the most important considerations when evaluating a system is the algorithm used to adjust the raw image. Human algorithms work well for humans but have inherent limitations when used for images of small animals, especially cats and small- and toy-breed dogs.

Performance Parameters
Detective Quantum Efficiency. Simply stated, detective quantum efficiency (DQE) is the measure of exposure needed to produce a good digital image. Some computed radiography and digital radiography systems will automatically optimize image brightness over a range of X-ray exposures and thus do not rely on a precise X-ray technique chart. For underexposed images, the system will create an acceptable image, and overexposures are corrected as well without loss of image detail. However, suboptimal X-ray intensity results in a "noisy," grainy, lower-detailed image, and the operator has no indication of excessive
X-ray exposure unless it is indicated by the digital radiography system. The goal is to have maximum image quality with minimal X-ray exposure. Greater DQE value equals better system performance, thereby reducing X-ray exposure of patients and staff while maintaining acceptable image quality. Also, faster systems enable shorter exposure times, reducing motion artifacts.

Systems that do not operate in an automatic mode require more precise technique charts and can necessitate retakes because of improper exposure. The DQE graphs are not typically supplied by vendors, so an alternative way to evaluate exposure sensitivity is to determine the equivalent film speed of the system. Typically, computed radiography systems require twice the X-ray exposure that typical 400-speed screen film systems need to achieve similar image quality. Flat-panel detectors offer the further advantage of reducing X-ray exposure-anywhere from two to three times less than that of computed radiography systems (thus, they are faster than film systems). The CCD systems are technique-dependent, with larger patients requiring X-ray exposures higher than those used for computed radiography systems.

Modulation Transfer Function and Resolution. Vendors often indicate the number of pixels a system contains, but it is actually far more important to determine how much signal cross-talk occurs between pixels. Cross-talk blends pixels, which reduces image detail. Modulation transfer function (MTF) is the most appropriate measure of resolution with digital systems-greater MTF results in better detail. The MTF can be manipulated by reducing the field of view and must relate to the actual field of view used (e.g., 14 x 17 for small animal veterinary practice). An easier (simplified) measure and more commonly reported value of resolution is line-pair resolution. A minimum of 2.5 line pair per mm is a human standard for chest radiographs; however, veterinarians need better resolution when imaging fine detail, such as the bones of small animals or the thoraxes of cats and small dogs.

Contrast Ratio. In essence, contrast ratio is the ability to demonstrate the "dynamic range" of a system. One test of this parameter is to evaluate the unprocessed (raw) image of the lateral view of the pelvis of a large dog. The question to ask is, can I visualize the pelvis as well as the stifle joint without making any changes to the image? Better yet, can I see the soft tissue at the stifle joint?

Bit Depth. Simply put, bit depth is a measure of the different shades of color that can be displayed; in radiology, we are only concerned with gray shades. In human medicine, the minimum standard for a digital chest image is 10 bits (1025 gray shades) per pixel. Systems that create 8-bit (256 gray scale) images limit the dynamic range of the image. Conversely, vendors may list on the specification sheet that a system captures images in 14 to 16 bits, but the Digital Imaging and Communi­cation in Medicine (DICOM) storage of the image is compressed to a 12-bit (4096 gray scale) image. Systems with images greater than 12 bits do not have better image quality, unless the system can automatically optimize the gray scale level before creating a DICOM image file.

Monitor and Viewing
For human medicine, the American College of Radiology has established that interpretation of digital radiographs should only be done on gray-scale monitors. Gray-scale monitors provide excellent image quality without requiring frequent changes to contrast and latitude. The image also holds up to zooming better than in color monitors. Other features of digital systems include the ability to measure, invert, magnify, and adjust contrast as well as latitude. System-viewing software is an important feature to evaluate in comparing systems. Reliability of the software is crucial: Your practice depends on it!

Conclusion
Traditional film is still the gold standard by which to evaluate x-ray images-a "perfectly" exposed film always provides the highest-quality image. Unfortunately, the perfect film can be illusive, thus we are continually challenged with striving to achieve an optimal image while often accepting one which is "good enough." Additionally, we see that the best image for bone may not be ideal for soft tissue or even subtle changes to the bone itself, all of which can result in missed opportunities to detect abnormalities at an early stage.

Dynamic range is the key benefit of using a digital radiology system in the practice setting. The dynamic range of filmless systems provides the veterinary profession with a way to enhance image quality without the need for creating several images for the same area of interest. Digital systems that cannot provide this feature are severely limited in what they can do for your practice. Beyond dynamic range, we need to consider system performance with regard to artifacts and resolution. It is hoped that this discussion will be helpful in making an objective decision on which system will provide the best image quality for your practice.


MEASURING IMAGE QUALITY WITH DIGITAL RADIOGRAPHY SYSTEMS • James F. Young

Suggested Reading
Digital Radiology-The Available Technologies and How to Separate Hype from Reality. Hornof WJ-Minneapolis: Proc AVMA Annu Conf, 2005.
The Essential Physics of Medical Imaging, 2nd ed. Bushberg JT, Seibert JA, Leidholdt EM, Boone JM-Philadelphia: Lippincott Williams & Wilkins, 2002.

For global readers, a calculator to convert laboratory values, dosages, and other measurements to SI units can be found here.

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