DOI: 10.1148/radiol.2413051535
(Radiology 2006;241:663-683.)
© RSNA, 2006
Recent Advances in Chest Radiography1
H. Page McAdams, MD,
Ehsan Samei, PhD,
James Dobbins, III, PhD,
Georgia D. Tourassi, PhD and
Carl E. Ravin, MD
1 From the Department of Radiology, Duke Advanced Imaging Laboratories, Duke University Medical Center, Box 3808, Durham, NC 27710. Received September 14, 2005; revision requested October 24; revision received November 15; accepted January 2, 2006; final version accepted January 6. Supported by National Institutes of Health grant R01 CA80490 and a research agreement with from GE Healthcare.
Address correspondence to H.P.M. (e-mail: Page.mcadams{at}duke.edu).
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ABSTRACT
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There have been many remarkable advances in conventional thoracic imaging over the past decade. Perhaps the most remarkable is the rapid conversion from film-based to digital radiographic systems. Computed radiography is now the preferred imaging modality for bedside chest imaging. Direct radiography is rapidly replacing film-based chest units for in-department posteroanterior and lateral examinations. An exciting aspect of the conversion to digital radiography is the ability to enhance the diagnostic capabilities and influence of chest radiography. Opportunities for direct computer-aided detection of various lesions may enhance the radiologist's accuracy and improve efficiency. Newer techniques such as dual-energy and temporal subtraction radiography show promise for improved detection of subtle and often obscured or overlooked lung lesions. Digital tomosynthesis is a particularly promising technique that allows reconstruction of multisection images from a short acquisition at very low patient dose. Preliminary data suggest that, compared with conventional radiography, tomosynthesis may also improve detection of subtle lung lesions. The ultimate influence of these new technologies will, of course, depend on the outcome of rigorous scientific validation.
© RSNA, 2006
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INTRODUCTION
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Despite recent advances in cross-sectional imaging of the thorax, chest radiography remains the mainstay for diagnosis of many pulmonary diseases. In most instances, it is the first—and frequently the only—diagnostic imaging test performed in patients known to have or suspected of having a thoracic abnormality. In the United States, and very likely in the world, chest radiography remains the most commonly performed diagnostic imaging test overall.
In the more than 100 years since the discovery of the x-ray, technologic advances have resulted in many improvements in chest radiography (1). Progress in film-based imaging led to the development of excellent screen-film systems designed specifically for chest radiography (1). More recently, advances in electronics and computer technology have resulted in rapid development in digital image receptors and displays. Further, rapid development of image-processing techniques and of advanced applications such as dual-energy and temporal subtraction radiography, digital tomosynthesis, and computer-aided detection (CAD) and diagnosis (CADx) promise to substantially improve the way chest radiography is practiced in the future.
In this article, we will discuss the inherent challenges of chest radiography and the specific advances made to address these challenges, including new digital detector and image display technologies, developments in image-processing techniques and CAD and CADx applications for chest radiography, advanced applications such as dual-energy and temporal subtraction radiography, and chest tomosynthesis.
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CHALLENGES
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To better appreciate the recent advances in chest radiography, we must first review some of the inherent challenges of the technique, because these challenges have been the prime motivators behind most of the developments. These challenges include but are not limited to issues related to image area and patient body habitus, latitude and dynamic range of x-ray transmission through the chest, scattered radiation, overlap of anatomic structures, and perceptual limitations.
Image Area and Body Habitus
The chest is one of largest and thickest body parts that is imaged on a routine basis. The typical imaging field in an adult readily exceeds 40-cm, particularly for patients with a large body habitus. This large field of view imposes challenging constraints on the size of the image receptor, given that the receptor must also provide consistent and uniform response over the entire field. This large field of view also increases the contribution of scattered radiation to the image, degrading the image's inherent quality. Given the marked increase in obesity in the United States over the past 20 years (2) among both children and adults, these issues will continue to pose considerable challenges to chest radiography in the future (Fig 1). For example, the authors of a recent study (3) found that the number of chest radiographs that were considered limited because of body habitus had more than doubled during a 14-year period at one hospital.
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Figure 1a: Chest radiographs obtained with computed radiography (CR) technique and grid in morbidly obese patient with signs and symptoms of pulmonary edema. (a) Anteroposterior image is limited by body habitus and was interpreted as showing possible edema. (b) Posteroanterior image obtained 30 minutes later shows no evidence of edema.
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Figure 1b: Chest radiographs obtained with computed radiography (CR) technique and grid in morbidly obese patient with signs and symptoms of pulmonary edema. (a) Anteroposterior image is limited by body habitus and was interpreted as showing possible edema. (b) Posteroanterior image obtained 30 minutes later shows no evidence of edema.
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Latitude and Dynamic Range
The wide latitude of x-ray transmission through the thorax imposes a fundamental limit on the visualization of subtle abnormalities on conventional chest radiographs. For a typical x-ray beam used in chest radiography, the regional variations in transmission through the thorax can extend over two orders of magnitude (4) (Fig 2). Ideally, an imaging system should have enough latitude to capture and effectively display this wide range, or at least the diagnostically meaningful part, of the x-ray transmission. However, coverage of such wide latitude can limit depiction of minute differences associated with subtle low-contrast lesions. Maintaining wide latitude while preserving visualization of low-contrast features in the image is a particular challenge for chest radiography (1). This large variation in x-ray opacity of anatomic structures is the primary reason that the modality uses the highest range of x-ray energy settings (typically 100–150 kVp) of all diagnostic imaging procedures, at the cost of increased scatter and reduced inherent contrast.
Scattered Radiation
The combined use of high x-ray photon energy in conjunction with a thick body part and a large field of view results in a large amount of scattered radiation in chest radiography compared with that in other x-ray imaging modalities. Scattered x-rays can account for 95% of the detected x-ray flux in the mediastinum and up to 70% in the lung in radiographs acquired without a grid (Fig 3) (6,7). Scattered radiation has the deleterious effects of degrading contrast and increasing image noise. While this reduction in contrast can be remedied with postprocessing, at least in digital radiography, the contribution of scattered radiation to image noise may not be readily correctable. Further, increased obesity in the U.S. population, as noted earlier, has had a notable effect on the increased level of scattered radiation in chest radiography.
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Figure 3: Graph shows scatter fractions in lung, mediastinum, and diaphragm regions without a grid (black bars), with a grid (white bars), and with a slot-scan device (gray bars). Note marked reduction in scatter with slot-scan device.
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Overlay of Anatomic Structures
In its conventional form, chest radiography involves the projection of a three-dimensional structure onto a two-dimensional image. In this process, anatomic features such as ribs, lung vessels, heart, mediastinum, and diaphragm overlay each other in a pattern that can be referred to as anatomic noise (8). Anatomic noise can have a detrimental effect on the ability of the observer to detect abnormalities of concern. The projection of ribs is of particular concern for detection of lung nodules, because the ribs overlay about 75% of the area of the lungs (9). Furthermore, a substantial portion of the lungs is projected over the heart and diaphragm regions of the image (1), affecting the contrast of potential lung lesions on the image.
The appearance of lung nodules on chest radiographs is of particular concern. The similarity of a lesion's appearance to that of the background anatomy in which it is located causes the conspicuity of the lesion to be poor. This phenomenon can result in up to 30% of pulmonary nodules being missed on initial chest radiographs (10), even though the nodules could be observed retrospectively. Purely on the basis of inherent contrast, a nodule as small as 3 mm in diameter should be visible on chest radiographs, even in the presence of scattered radiation; however, it is rare to detect nodules smaller than about 8 mm on chest radiographs, owing to the influence of anatomic noise. A great deal of work has been performed on the effect of anatomic noise on nodule detectability, beginning with the work of Kundel and colleagues (11,12) several decades ago. More recently, Samei et al (13) demonstrated that anatomic background is far more important than quantum noise in limiting the detectability of lung nodules (Fig 4).
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Figure 4a: Images in middle-aged woman with history of right partial mastectomy for breast cancer who presented for routine follow-up. (a) Posteroanterior chest radiograph was interpreted as normal. (b) Transverse computed tomographic (CT) scan shows 8-mm nodule (arrowhead) in right lower lobe that was obscured by overlying breast implant, diaphragm, and rib shadows on a.
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Figure 4b: Images in middle-aged woman with history of right partial mastectomy for breast cancer who presented for routine follow-up. (a) Posteroanterior chest radiograph was interpreted as normal. (b) Transverse computed tomographic (CT) scan shows 8-mm nodule (arrowhead) in right lower lobe that was obscured by overlying breast implant, diaphragm, and rib shadows on a.
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Perceptual Limitations
Medical images are generally of little value until an expert reader interprets them. Thus, the perceptual and cognitive processes involved in reading a medical image have a direct bearing on its clinical utility and effectiveness. These processes are of particular importance in chest radiography because of the complexity of the tasks and the confounding effect of anatomic noise, as noted earlier in this article (14). Anatomic noise can hinder detection through two processes: (a) local influence, or "camouflaging," and (b) global influence, or "confusion" (15). The local effect obscures the definition of an abnormality by means of patterns immediately surrounding or overlaying it. For the global effect, however, the detectability of an abnormality (eg, a nodule) is influenced by the degree of its distinctiveness from similar structures created by the global noise characteristics of the background.
Perceptual errors can occur at both the visual and the cognitive level. Incompleteness of the search task may lead to about 55% of the missed lesions. These errors occur when the observer fails to look at the territory of the lesion (30%) (11,16) or when he or she does not fix his or her eyes on the territory for a dwell time of at least 0.3 second (25%) (17). Cognitive errors (accounting for 45% of missed lesions) can occur when the fixation time on an abnormality candidate exceeds the above limit (eg, a nodule is recognized), but the observer commits a decision-making error by calling the case negative (11).
Results of prior studies suggest that perceptual errors can be reduced by providing radiologists with fixation feedback (18) and by using systematic search strategies, coning devices, and double reading of chest radiographs (19). CAD (further discussed later), with its ability to offer a complete search of the image data, has the potential to reduce certain types of perceptual error. The most effective method by far, however, is the reduction or elimination of anatomic noise, which has been shown to be the main factor limiting the detection of subtle lung nodules (13).
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DETECTOR DEVELOPMENTS
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The imaging receptor (or detector) is a key component of chest radiography. In the past few decades, changes in receptor technology have brought about one of the most important advances in chest radiography, leading to improved image quality and new image acquisition techniques. This section will summarize the most important developments in this area. Because most advances have been focused on digital technologies, they will be the main focus of this section. The Table provides a summary of the current commercially available digital receptor technologies for chest radiography.
Analog Chest Radiography
Chest radiography is conventionally performed with analog screen-film receptors. In the most common implementation, these receptors are made of double-emulsion light-sensitive film sandwiched between two layers of phosphor screens. The screens serve as the primary medium to convert x-ray photons to light photons, which are subsequently detected by the film emulsion, where the ionic silver of the emulsion is converted to metallic silver. Subsequent chemical processing washes the desensitized chemicals away, leaving the residual metallic silver behind to form the x-ray image (20).
While screen-film receptors have been in continual use for many years, their inherent characteristics have imposed certain limitations on the practice of chest radiography. Owing to the limited light range sensitivity of film, represented by the Hurter and Driffield response of the receptor (Fig 5), the range of x-ray exposures that can be recorded by a screen-film detector is limited. Only a narrow range of exposures can be reliably represented on the film with acceptable contrast; exposures above or below this range will be represented suboptimally. Given the large variability in radiopacity of organs in the thoracic cavity, this characteristic leads to two limitations of analog chest radiography: (a) suboptimal contrast renditions at the extremes of the attenuation range of the thorax and (b) susceptibility to suboptimal image acquisition due to under- or overexposure.
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Figure 5: Hurter and Driffield curves of analog screen-film (InSight; Eastman Kodak) and digital (CR) systems. Detector signal is optical density for screen-film system and relative digital value for the digital system.
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In recent years, most technical developments have focused on digital technologies (discussed later). The latest development in analog chest radiographic receptors, now over 13 years old, is an improvement on traditional screen-film chest techniques; this development involves combining two different emulsions and screens with an anticrossover layer that is opaque until the film is developed. This asymmetric screen-film technology, developed and marketed by Eastman Kodak (Rochester, NY), improves the contrast of fine-detail anatomy by using a thin front screen while maintaining good overall image noise through improved x-ray detection in a thick rear screen (4,21). The overall receptor has a markedly wider acceptable exposure window and contrast sensitivity that provide a better balance between contrast sensitivity and latitude while maintaining good quantum mottle properties.
Figure 5 shows the Hurter and Driffield curves for a typical chest radiography screen-film system in comparison with a typical digital detector.
Digital Chest Radiography
While screen-film receptors have been the main technology for acquiring chest radiographs until recently, the use of digital radiography has been on the rise and is expected to replace analog technology in the near future. Digital radiography has also enabled the implementation of picture archiving and communication systems, which have their own associated advantages. There have been six main forces driving the transition to digital:
1. Decoupling of acquisition and display functions of the acquisition device in digital radiography makes it possible to optimize either of those functions independently—for example, by optimizing display contrast independently of the exposure level.
2. Availability of the image data in an electronic form makes it possible to postprocess the image for optimal display and to display the images on the more flexible soft-copy viewing workstations.
3. Availability of the image data in an electronic form makes it possible to archive the data electronically, which uses less space and requires less labor for storage.
4. Availability of the image data in an electronic form makes it possible to distribute images widely and to make copies of images available concurrently to multiple users.
5. Most digital radiography systems have integrated acquisition and processing units in the same physical system, eliminating the need to handle the cassettes and thus improving the workflow for image acquisition in the department.
6. Most digital radiography systems are able to acquire multiple images in a rapid sequence, enabling new advanced imaging applications that require the acquisition of multiple images from the chest, as will be discussed in a later section of this article.
Because of these advantages, digital radiography has been a main focus of new developments in chest radiography. Differing technologies have been the basis of the development of various commercial products, which are summarized below.
In comparing various chest radiography systems, a common metric, detective quantum efficiency, has been used as a basis of comparison. Detective quantum efficiency describes the inherent signal-to-noise performance of an imaging system per unit incident exposure to the detector (22). Most commonly reduced to its value at zero spatial frequency, various chest radiography systems offer a detective quantum efficiency in the range of 20%–70% (23,24). These values are reflective of the system performance in the absence of scattered radiation. Most recently, a new metric, termed effective detective quantum efficiency, has been introduced that further accounts for the presence of scattered radiation (25), reflecting the inherent signal-to-noise performance of an imaging system in actual clinical use.
CR Systems
CR was the first commercial digital imaging modality widely used in chest imaging (26) and currently is still the most common technology for acquiring digital chest radiographs, especially for bedside applications. The technology is based on photostimulable properties of barium halide phosphors. With a cassette similar to that used in screen-film radiography, the phosphor screen is exposed to x-rays. After exposure, the cassette is transported to a computed radiography reader device, which subjects the screen to a scanning laser beam. The laser releases the energy locally deposited by x-rays on the screen, causing the screen to fluoresce. The released light is used to form the image after it is collected by a light guide, digitized, and associated with the geometric location of the laser beam at the time of stimulation. The digital image data are then processed for presentation.
Since its commercial introduction more than 2 decades ago, CR has been under continuous improvement. The most recent advances include the collection of photostimulated light from both sides of the screen, leading to improved detective quantum efficiency (currently available only for mammography) (27), the use of line scanning and light collection technology for improved speed (28), and the use of structured phosphor for improved detection efficiency without associated loss in resolution (29).
In the most common implementation, CR devices produce image quality that tends to be lower than that for other digital radiography systems (23), but CR systems possess certain operational and economic advantages that cause them to remain competitive with other digital modalities. Those advantages can be summarized as follows: (a) In the most common implementation, CR cassettes are identical in size to screen-film cassettes, making it possible to retrofit existing analog radiography rooms; (b) the fact that the CR reader and cassettes are separate entities makes the technology extremely convenient for bedside applications; and (c) the separation of CR reader and cassette makes it further possible to have one (higher-cost) CR reader used in reading multiple (lower-cost) CR cassettes, which allows one CR reader to serve multiple radiography rooms and reduces the up-front cost of the transition to digital radiography.
Flat-Panel Detectors
While CR technology currently has the largest number of installations in the digital radiography market, with its notable advantages in terms of cost and utility for bedside applications, its disadvantages in terms of image quality per unit dose and suboptimal workflow (owing to the physical separation of the acquisition and processing functions) provide opportunities for another noteworthy technology, the flat-panel detector.
Made possible by advances in the fabrication of flat-panel displays for the computer industry, flat-panel detectors are made of thin layers of amorphous silicon thin-film transistors (TFTs) deposited on a piece of glass. The TFT layer is coupled with an x-ray absorptive layer. Depending on the material, there are two types of flat-panel detector. Indirect flat-panel detectors use a phosphor screen, most commonly cesium iodide, to convert the x-rays to light photons, which are subsequently detected by the photodiode array associated with the TFT layer and are converted to charge deposited in the capacitors associated with each TFT (24,30). Direct flat-panel detectors use instead a photoconductor layer, most commonly amorphous selenium that converts the x-ray energy directly to charge, which is subsequently directed to the collecting TFT-capacitor array through the application of a strong electric field (31,32). After exposure, the charge on the capacitors is collected line by line and pixel by pixel by using the associated gate and data lines, forming the raw digital image data for processing and display.
Flat-panel detectors are relatively new, and there continue to be a number of new developments in the technology. Most noteworthy are the use of x-ray capture materials with higher inherent absorption efficiency, improvement in the electronics to increase the frame rate and bit-depth resolution of the images, and use of flexible substrates in place of glass to enable more rugged and damage-resistant detectors, which can perhaps make these detectors practical for bedside applications (33).
Flat-panel detectors have three noteworthy advantages compared with other digital radiographic technologies. These advantages can be summarized as follows:
1. With the use of structured phosphor in indirect detectors and the application of an electric potential in direct detectors, the x-ray–sensitive layer of these detectors can be notably thicker than that of competing technologies. This makes it possible to have increased x-ray detection efficiency with minimal loss of resolution. Consequently, patient dose can be reduced without degradation of image quality (34).
2. Flat-panel detectors can acquire multiple images in a short time. Current frame rates of 30 frames per second are available in the most recent models. This makes it possible to acquire multiple images of the patient with different techniques or from different directions with minimal motion blur. This feature facilitates the use of these detectors for a host of advanced applications such as tomosynthesis and dual-energy imaging.
3. With integration of the acquisition and processing units, flat-panel detectors offer improved workflow compared with that of CR.
CCD- and CMOS-based Detectors
In the past few years, CCD and CMOS cameras have provided an alternative technology for the acquisition of digital chest radiographs. With these detectors, the x-ray energy is first converted to light within a phosphor layer. The light is then directed to a single or a multitude of CCD or CMOS cameras that detect the light image and form the radiograph (35). An important component of these detectors is the coupling of the phosphor layer and the camera. Since most CCD and CMOS sensors are limited in size, it is necessary to demagnify the original light image generated on the phosphor screen so that it can be entirely captured by the camera. This is accomplished by using either a fiberoptic coupler or a lens system. In either case there is a loss of efficiency, since only a small fraction of the light photons generated by the phosphor are detected by the camera(s). Consequently, the inherent efficiency of these detectors is limited (34).
New developments in these types of detectors have been focused on more efficient coupling between the phosphor and the camera, the use of larger sensors to minimize demagnification, and improvements in phosphor efficiency. These advances have led to the development of detectors with detection efficiencies notably higher than those of previous-generation CCD or CMOS devices. These detectors are generally less expensive than other digital technologies.
Slot-Scan Technology
As noted earlier, scattered radiation is of notable concern in chest radiography. Over the years, various techniques have been developed to reduce the contribution of scattered photons to the x-ray image, including the use of antiscatter grids (36,37), which are used in most current chest radiography systems, and air gaps (38). While these techniques can reduce scatter substantially (36), they also lead to increased patient dose, as well as a reduced field of view in cases of an air gap. These fundamental limitations can be overcome with the use of scanning beam and slit devices (37,39–42).
A recent commercial product has taken advantage of slot-scan technology to reduce the amount of scattered radiation on digital chest radiographs (43). The detector consists of a cesium iodide scintillation layer fiberoptically coupled to a series of linear CCDs. With no antiscatter grid in place, a narrow-fan x-ray beam synchronized with the movement of the detector assembly scans the patient. The image data are continuously read from the CCDs as the patient is scanned by using the time-integration method (44,45). After scanning, the image data are processed for optimal display.
The main advantage of this technology is superior scatter rejection with little effect on the detection of primary radiation. This can notably enhance the effective detection efficiency of the imaging system. Results from a recent study (25) show that this enhancement can more than compensate for the inherent efficiency limitation of CCD-based detectors, leading to improved image quality at reduced dose.
The technologies described in the preceding paragraphs represent the bulk of commercial offerings for digital chest radiography. There are a number of other technologies that are currently under development, however, including those related to new sensor materials and new detector designs such as photon-counting devices. Commercial implementation of these technologies awaits further development.
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IMAGE-PROCESSING DEVELOPMENTS
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Image data acquired with radiographic detectors cannot be viewed without additional processing and proper display. In the case of screen-film images, the film must be chemically processed and is eventually displayed on a light box. In the case of digital images, digital processing is required before a clinician can view the images. Since most of the recent developments in chest radiography have focused on digital modalities, this section will outline the current state of digital image-processing methods for optimal presentation of digital images, as well as hardware components of soft-copy display devices. Readers interested in the current state of film-processing techniques are advised to consult two publications focused on that topic (20,46).
In recent years, the increasingly digital nature of chest radiography, as well as advances in computer technology, have facilitated the application of computerized image analysis for improving the clinical efficacy of chest radiographs. As a general rule, computerized medical image analysis aims to reduce both the perceptual and the cognitive errors that burden the diagnostic interpretation process. Consequently, the latest image-processing developments in chest radiography fall into two general application areas: (a) techniques to improve visual presentation and soft-copy reading of radiographs and (b) techniques to automate diagnostic interpretation of such images. For the most part, these techniques are application dependent.
Prior to display, each digital image commonly undergoes a series of processing steps (Fig 6). Broadly speaking, these processes can be divided into two parts: preprocessing and postprocessing.
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Figure 6a: Effects of various (a–c) gray-scale and (d–f) equalization postprocessing schemes on appearance of a posteroanterior chest radiograph. Gray-scale processing improves contrast of image features with a corresponding reduction in latitude (ie, range of data that is properly displayed). Equalization, on the other hand, provides improved visualization of details without a corresponding reduction in latitude. (Image courtesy of M. J. Flynn, PhD, Henry Ford Hospital, Detroit, Mich.)
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Figure 6b: Effects of various (a–c) gray-scale and (d–f) equalization postprocessing schemes on appearance of a posteroanterior chest radiograph. Gray-scale processing improves contrast of image features with a corresponding reduction in latitude (ie, range of data that is properly displayed). Equalization, on the other hand, provides improved visualization of details without a corresponding reduction in latitude. (Image courtesy of M. J. Flynn, PhD, Henry Ford Hospital, Detroit, Mich.)
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Figure 6c: Effects of various (a–c) gray-scale and (d–f) equalization postprocessing schemes on appearance of a posteroanterior chest radiograph. Gray-scale processing improves contrast of image features with a corresponding reduction in latitude (ie, range of data that is properly displayed). Equalization, on the other hand, provides improved visualization of details without a corresponding reduction in latitude. (Image courtesy of M. J. Flynn, PhD, Henry Ford Hospital, Detroit, Mich.)
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Figure 6d: Effects of various (a–c) gray-scale and (d–f) equalization postprocessing schemes on appearance of a posteroanterior chest radiograph. Gray-scale processing improves contrast of image features with a corresponding reduction in latitude (ie, range of data that is properly displayed). Equalization, on the other hand, provides improved visualization of details without a corresponding reduction in latitude. (Image courtesy of M. J. Flynn, PhD, Henry Ford Hospital, Detroit, Mich.)
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Figure 6e: Effects of various (a–c) gray-scale and (d–f) equalization postprocessing schemes on appearance of a posteroanterior chest radiograph. Gray-scale processing improves contrast of image features with a corresponding reduction in latitude (ie, range of data that is properly displayed). Equalization, on the other hand, provides improved visualization of details without a corresponding reduction in latitude. (Image courtesy of M. J. Flynn, PhD, Henry Ford Hospital, Detroit, Mich.)
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Figure 6f: Effects of various (a–c) gray-scale and (d–f) equalization postprocessing schemes on appearance of a posteroanterior chest radiograph. Gray-scale processing improves contrast of image features with a corresponding reduction in latitude (ie, range of data that is properly displayed). Equalization, on the other hand, provides improved visualization of details without a corresponding reduction in latitude. (Image courtesy of M. J. Flynn, PhD, Henry Ford Hospital, Detroit, Mich.)
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Image Preprocessing
Image preprocessing consists of two components: correction and scaling (47). Necessitated by the intrinsic nonuniformity of digital detectors, the first type of processing includes image corrections for detector defects or nonuniformities often present on raw digital images. The nonuniformities include stationary patterns of the detector, thickness nonuniformities of the capture element of the detector, pixel dropouts, "dead" (inactive) pixels, dead columns and rows, and dark current variations. The corrections often require periodic flat-field calibration processes for the detector. These include one-dimensional shading corrections in the case of CR and linear CCD-based detectors and two-dimensional flat-field correction for flat-panel detectors and two-dimensional CCD- and CMOS-based systems. In either method, an averaged, normalized flat-field image (map) is used to normalize the original image to remove the patterns.
The second type of preprocessing is scaling. One of the advantages of digital radiography is the wide range of exposures within which the detector is able to provide a consistent response. This enables the acquisition of high-latitude chest radiographs with less susceptibility to over- and underexposure. However, the dynamic range of the detector is beyond the perception capability of the human visual system, and full-data presentation leads to considerable contrast reduction. Identification of the anatomically relevant range of exposures is essential for optimal display of the image.
This task is typically achieved through two steps. First, the collimated area is segmented to identify the exposed area and thus exclude unexposed areas from further analysis. Second, the anatomically relevant range of exposures in the exposed area is identified. The most common technique for this task is histogram analysis of the image data. On the basis of the expected general distribution of pixel values in the anatomic area of interest, the image system marks the range of the detector signal of interest to be used for postprocessing.
Image Postprocessing
Once the raw image data are corrected for inherent "flaws" and the useful range of image data is identified, the data undergo image postprocessing. Digital radiography has utilized various digital postprocessing algorithms for enhanced image display of chest radiographs. Broadly speaking, these algorithms can be categorized into three types: gray-scale processing, edge enhancement, and multifrequency processing (48,49).
Gray-scale processing.—This process involves the conversion of detector signal values to display values. In this process, the display intensities of an image are changed by means of either a look-up table or windowing and leveling. Most systems employ a response look-up table similar to the Hurter and Driffield response of screen-film systems, so that digital chest radiographs look similar to conventional film images.
Edge enhancement.—This process aims to enhance fine details within the image by manipulating the high-frequency content of the radiograph, most commonly by using a variant of the unsharp masking technique in which a blurred version of the image is formed, and a fraction of the resultant image is subtracted from to the original image. The process is commonly used to compensate for the lower inherent resolution performance of CR images. However, its use is often balanced against the implied enhancement of quantum mottle within the image and the unusually textured appearance of the lungs.
Multifrequency processing.—While edge enhancement offers only a simplistic modification of spatial frequencies on the radiograph, multifrequency processing involves a more flexible manipulation of multiple portions of the frequency spectrum. The image is initially decomposed into multiple frequency components. The component images are then weighted and added back together. If the processing parameters are set optimally, the resultant image can compress the overall dynamic range of the image while at the same time enhance local contrast. This is of particular utility in chest radiography, where the details of opaque regions of the image are made visible with no compromise in the contrast in the lung regions. The widely used MUSICA multiscale image-processing package offered by Agfa (Greenville, SC) is an example of this type of processing (50).
While these algorithms have enabled flexibility in the presentation quality of chest radiographs, most chest radiography systems are set up to provide digital chest radiographs that mimic the appearance of screen-film images, with varying degrees of success. While it is possible to use the appearance flexibility of digital radiographs to optimize the system in terms of diagnostic performance, that task has remained largely untackled. One reason, perhaps, has been the large number of abnormalities of interest on chest radiographs, each of which might need to be optimized independently. Furthermore, there is uncertainty as to the extent that image postprocessing algorithms can improve the presentation of subtle lesions without similar enhancement of anatomic patterns and increased false-positive rates.
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DISPLAY DEVELOPMENTS
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Once processed, the digital chest radiograph must be viewed by a radiologist. Soft-copy display is an essential element of contemporary digital chest radiography, because many advantages of digital imaging cannot be realized without soft-copy display. The conventional method to display digital radiographs has been on cathode-ray tubes, which currently still dominate the market (51). More recently, however, active-matrix liquid-crystal displays are rapidly replacing cathode-ray tubes in many facilities (52–54). The advantages of liquid-crystal displays include improved resolution, reduced weight, smaller form factor, reduced reflection, improved bit depth, and improved luminance range (55), although their disadvantages in terms of angular response and structured noise have not yet been fully addressed (56–58).
Another recent trend in soft-copy display has been the increased acceptance of color monitors, some of which have shown acceptable technical performance (59) for radiographic applications. With cathode-ray tubes, a monochrome monitor offers important advantages over a color monitor in terms of image quality due to improved brightness, reduced glare, reduced reflection, and improved resolution (55). Therefore, color cathode-ray tubes have not demonstrated adequate performance for clinical use. Current color liquid-crystal displays, however, do not have the same drawbacks as do color cathode-ray tubes, other than reduced brightness, which can be tolerated given the fact that most current liquid-crystal displays have better luminance response. The use of color monitors offers the advantage of being able to accommodate applications other than image viewing on the same device, with workflow and multitasking advantages. Color monitors would also make it possible to take advantage of color for viewing multidimensional chest images on the same display. Current commercial offerings also have enabled the luminance calibration of color displays to the gray-scale standard display function (60). It is thus expected that color liquid-crystal displays will gradually replace the monochrome monitors in clinical practice.
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APPLICATION DEVELOPMENTS
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As noted earlier, discerning subtle lesions in chest radiographs is made difficult by the confluence of anatomy that overlies the lesion. An early attempt at overcoming poor lesion conspicuity was equalization radiography (61,62). Equalization was developed to improve the visibility of lesions in dense regions of the chest such as the mediastinum and the retrocardiac and retrodiaphragmatic areas. With screen-film radiography, these areas of the chest were typically underexposed and showed poor lesion contrast owing to the shape of the Hurter and Driffield curve of the film. Equalization modulated the incident intensity onto the patient in such a way that a higher exposure was delivered to the dense regions, and a lower exposure was delivered to the unobscured lungs. This process forced all of the thoracic regions into the higher-contrast "linear" portion of the film response curve. Studies indicated significantly improved detection of lesions when equalization was used (62,63). Despite its promise, equalization has largely disappeared from clinical use because of the edge-enhanced appearance imposed on the images, which some found difficult to interpret, and also because of the more recent transition to digital imaging and away from screen-film radiography.
The advent of digital chest radiography in the 1980s enabled the development of new techniques to improve the detection of subtle lesions. These techniques included algorithms, typically coupled with methodological innovations that used some aspect of imaging physics to improve conspicuity, and/or image subtraction strategies. Three notable techniques are dual-energy imaging, temporal subtraction imaging, and digital tomosynthesis. All of these techniques are implemented by using a conventional chest radiography system coupled with a digital imaging receptor.
Dual-Energy Subtraction Imaging
Dual-energy subtraction imaging can be used to generate images of two independent tissue types, most commonly bone and soft tissue. The dual-energy technique distinguishes bone from soft tissue by using the known energy dependence of x-ray attenuation in soft tissue and in bone. Calcified structures attenuate far more heavily, by means of photoelectric absorption, than do soft-tissue structures; thus, the contrast of calcium diminishes with increases in beam energy much faster than does the contrast of soft tissue. Thus, if two images are acquired at different beam energies, the image obtained at the lower energy will show a larger fraction of contrast from bone than from soft tissue. These two images may be combined in such a way that the soft-tissue or calcium components can be exactly isolated. Typically, an image containing only calcified structures and an image containing only soft-tissue structures are generated (Fig 7). Thus, dual-energy subtraction radiography can improve lung nodule conspicuity by eliminating overlying anatomic noise from the bones. The technique can also be used to better demonstrate calcium in lesions (64–68).
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Figure 7a: Dual-energy subtraction radiography in healthy middle-aged woman. Conventional (a) posteroanterior, (b) bone-subtracted, and (c) soft-tissue–subtracted images are normal except for scoliosis. Note improved depiction of vascular anatomy in b.
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Figure 7b: Dual-energy subtraction radiography in healthy middle-aged woman. Conventional (a) posteroanterior, (b) bone-subtracted, and (c) soft-tissue–subtracted images are normal except for scoliosis. Note improved depiction of vascular anatomy in b.
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Figure 7c: Dual-energy subtraction radiography in healthy middle-aged woman. Conventional (a) posteroanterior, (b) bone-subtracted, and (c) soft-tissue–subtracted images are normal except for scoliosis. Note improved depiction of vascular anatomy in b.
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Although the dual-energy technique was proposed as early as the 1950s (69), it was not until practical digital radiographic detectors became available in the 1980s that dual-energy imaging was clinically feasible for chest applications. There currently are two commercially available methods for accomplishing dual-energy imaging. These methods are based on different types of detectors. The first method, based on CR storage-phosphor plates, was developed in the late 1980s (70–72). It generates low- and high-energy images by exposing a sandwich of two CR plates with a copper filter between. The first plate records the standard chest image at a spectral beam energy typical of conventional chest radiography. The second plate records a higher mean spectral beam energy, due to beam hardening that occurs in the intervening copper filter; this second plate has worse image noise, however, due to the loss of beam flux from the copper filter. The low- and high-energy images are recorded simultaneously with the CR dual-energy method, with a single x-ray exposure to the patient.
The second commercially available dual-energy method uses flat-panel detectors (73). In this embodiment, a sandwich detector configuration is not practical, so two separate x-ray exposures are made of the patient. The first exposure is at a standard voltage for chest radiography (typically, 120 kV), and the second is acquired at a lower voltage (typically, 60 kV). These images are separated in time by up to several hundred milliseconds, so there is the potential for some motion of patient anatomy between exposures, thus giving rise to some potential edge artifacts in the resulting tissue and bone images. However, the image quality of the flat-panel dual-energy images is much higher than that of the CR embodiment, owing to better energy separation between the low- and high-energy beams, higher x-ray flux in the high-energy image, and better detective quantum efficiency of the flat-panel detector, relative to those of CR. Image postprocessing is accomplished with the flat-panel dual-energy images to mitigate anatomic misregistration between the low- and high-energy images, but some slight edge effects still persist (Fig 8).
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Figure 8: Soft-tissue subtracted image from dual-energy chest radiograph in patient with right aortic arch. Excess cardiac motion results in incomplete subtraction of soft-tissue components and considerable artifact (arrow) at left cardiac border.
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Considerable attention has been given to optimizing the acquisition and processing methods for dual-energy imaging. The effects of scattered radiation have been considered (71,74–76), as has the importance of accurate accounting for beam hardening in the separation of tissue and bone (77,78). It is also important to include some type of postprocessing for noise suppression, regardless of which dual-energy method is used, because of the inherent decrease in signal-to-noise ratio with dual-energy relative to the ratio with conventional chest radiography (79). Some of these processing methods have been summarized in a recent publication (80).
Dual-energy methods have been in clinical use for several years, and there are data in the literature that indicate that dual-energy imaging can improve detection and classification of pulmonary nodules. Early reports (65,67,70,81) indicated statistically significant improvements in the detection of pulmonary nodules and patterns of calcification (Fig 9). Recent studies in which a flat-panel dual-exposure system (Revolution XQ/i; GE Healthcare, Milwaukee, Wis) was used showed the clinical efficacy of dual-energy subtraction for the detection of calcified chest abnormalities (82) and noncalcified pulmonary nodules (83). For 37 calcified chest lesions, radiologists' sensitivity significantly increased from 36% to 66%, while specificity remained constant at 73% (82). Statistically significant but smaller improvements in sensitivity, specificity, and confidence were also observed for 59 noncalcified pulmonary nodules ranging from 0.2 to 2.5 cm in diameter (83).
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Figure 9a: Dual-energy subtraction radiography in a healthy middle-aged man. (a) Conventional posteroanterior radiograph shows possible lung nodule (arrow) overlying right upper lobe. (b) Bone-subtracted image shows small soft-tissue nodule (arrow) in left lung apex, not seen on a. No nodule is seen in right upper lobe. (c) Soft-tissue–subtracted image confirms that nodule seen on a represents calcification at first costochondral junction (arrow).
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Figure 9b: Dual-energy subtraction radiography in a healthy middle-aged man. (a) Conventional posteroanterior radiograph shows possible lung nodule (arrow) overlying right upper lobe. (b) Bone-subtracted image shows small soft-tissue nodule (arrow) in left lung apex, not seen on a. No nodule is seen in right upper lobe. (c) Soft-tissue–subtracted image confirms that nodule seen on a represents calcification at first costochondral junction (arrow).
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Figure 9c: Dual-energy subtraction radiography in a healthy middle-aged man. (a) Conventional posteroanterior radiograph shows possible lung nodule (arrow) overlying right upper lobe. (b) Bone-subtracted image shows small soft-tissue nodule (arrow) in left lung apex, not seen on a. No nodule is seen in right upper lobe. (c) Soft-tissue–subtracted image confirms that nodule seen on a represents calcification at first costochondral junction (arrow).
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Dual-energy imaging has also been investigated for other applications. It has been shown (84), for example, to improve detection of coronary artery and other cardiac calcifications (Fig 10). On the other hand, dual-energy imaging does not seem to improve detection of interstitial disease (85).
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Figure 10a: Dual-energy subtraction radiography in an elderly man. (a) Soft-tissue–subtracted posteroanterior image shows coronary artery calcification (arrow) not clearly identified on (b) conventional posteroanterior image. (Image courtesy of R. C. Gilkeson, MD, University Hospital, Cleveland, Ohio.)
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Figure 10b: Dual-energy subtraction radiography in an elderly man. (a) Soft-tissue–subtracted posteroanterior image shows coronary artery calcification (arrow) not clearly identified on (b) conventional posteroanterior image. (Image courtesy of R. C. Gilkeson, MD, University Hospital, Cleveland, Ohio.)
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The clinical use of dual-energy techniques in chest imaging is still evolving. Some institutions advocate dual-energy radiography for all chest examinations, precisely because one does not know, a priori, which patients will have previously undiagnosed pulmonary nodules. Other institutions, however, have applied dual-energy imaging more selectively to subsets of patients in whom nodules are more likely. Additional clinical experience will likely be necessary before a consensus is reached on the best practices for the use of dual-energy techniques in chest imaging.
Temporal Subtraction Imaging
Another way to improve the visual assessment of chest radiographs is with temporal image subtraction. Temporal subtraction techniques aim to selectively enhance areas of interval change by subtracting the patient's previous radiograph from the current one (86). The quality of the difference image strongly depends on the success of the two-dimensional registration and warping of the two radiographs so that the effect of patient positioning variation is minimized (87–89). Generally, the difference image appears uniformly gray in areas of no change. Areas that stand out in the uniform gray background indicate interval change (Fig 11). Several studies (91–98) have shown that temporal subtraction improves the visual perception of subtle abnormalities such as pulmonary nodules, infiltrative opacities, and diffuse lung disease. A 20% reduction in the average reading time when temporal subtraction is used was noted as well (91). Currently, temporal subtraction is commercially available in Japan (99).
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Figure 11a: Temporal subtraction radiography in a middle-aged patient. (a) Initial posteroanterior radiograph was interpreted as normal, even when compared with (b) that from examination performed 1 year previously. (c) Subtraction image suggests new masses in both upper lobes (arrows), confirmed on (d, e) transverse CT scans. Biopsy revealed synchronous lung cancers. (Reprinted, with permission, from reference 90.)
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Figure 11b: Temporal subtraction radiography in a middle-aged patient. (a) Initial posteroanterior radiograph was interpreted as normal, even when compared with (b) that from examination performed 1 year previously. (c) Subtraction image suggests new masses in both upper lobes (arrows), confirmed on (d, e) transverse CT scans. Biopsy revealed synchronous lung cancers. (Reprinted, with permission, from reference 90.)
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Figure 11c: Temporal subtraction radiography in a middle-aged patient. (a) Initial posteroanterior radiograph was interpreted as normal, even when compared with (b) that from examination performed 1 year previously. (c) Subtraction image suggests new masses in both upper lobes (arrows), confirmed on (d, e) transverse CT scans. Biopsy revealed synchronous lung cancers. (Reprinted, with permission, from reference 90.)
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Figure 11d: Temporal subtraction radiography in a middle-aged patient. (a) Initial posteroanterior radiograph was interpreted as normal, even when compared with (b) that from examination performed 1 year previously. (c) Subtraction image suggests new masses in both upper lobes (arrows), confirmed on (d, e) transverse CT scans. Biopsy revealed synchronous lung cancers. (Reprinted, with permission, from reference 90.)
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Figure 11e: Temporal subtraction radiography in a middle-aged patient. (a) Initial posteroanterior radiograph was interpreted as normal, even when compared with (b) that from examination performed 1 year previously. (c) Subtraction image suggests new masses in both upper lobes (arrows), confirmed on (d, e) transverse CT scans. Biopsy revealed synchronous lung cancers. (Reprinted, with permission, from reference 90.)
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Digital Tomosynthesis
Section imaging is another method for improving detection of subtle lesions such as pulmonary nodules. Traditional geometric tomography, which produces a single section image at a time, has been known since the 1930s (100). In recent years, however, with the advent of multisection CT and other three-dimensional imaging modalities, conventional geometric tomography has fallen out of favor and is used today only in limited cases of excretory urography and some skeletal imaging applications. The difficulties with conventional geometric tomography were that only a single section could be acquired at a time, and, if multiple sections were desired, considerable positioning time and patient dose were required. Digital tomosynthesis is a technique that has evolved from conventional tomography and solves many of the problems associated with the earlier technique.
Digital tomosynthesis can produce an unlimited number of section images at arbitrary depths from a single set of acquisition images. A digital detector, conventional x-ray tube, and computer-controlled apparatus to move the x-ray tube are used; during motion of the tube, a series of projection radiographs are acquired, and the anatomy at different depths in the patient changes orientation in the projection images owing to parallax. These projection images are then shifted and added to bring into focus objects in a given plane. By varying the amount of shift, different plane depths can be reconstructed. Objects outside of the focus plane are rendered with varying amounts of blur.
A variety of reconstruction approaches have been investigated for tomosynthesis, although the simple shift-and-add approach is the most common. It is important to use a deblurring algorithm to eliminate the residual blur from structures overlying the planes of interest. Various approaches for deblurring have been investigated, including matrix-inversion tomosynthesis (101–105), filtered back projection (106,107), and iterative restoration (108). These deblurring methods produce section images with excellent rendition of anatomy and effective elimination of structures outside the section of interest.
Tomosynthesis has been applied to such diverse applications as angiographic,<
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ABSTRACT
INTRODUCTION
