European Journal of Radiology

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1 European Journal of Radiology 72 (2009) Contents lists available at ScienceDirect European Journal of Radiology journal homepage: Review Dose and perceived image quality in chest radiography Wouter J.H. Veldkamp, Lucia J.M. Kroft, Jacob Geleijns Department of Radiology, C2S, Leiden University Medical Center, Albinusreef 2, 2333 ZA Leiden, The Netherlands article info abstract Article history: Received 15 February 2009 Received in revised form 22 May 2009 Accepted 22 May 2009 Keywords: Chest radiography Dose Image quality Chest radiography is the most commonly performed diagnostic X-ray examination. The radiation dose to the patient for this examination is relatively low but because of its frequent use, the contribution to the collective dose is considerable. Consequently, optimization of dose and image quality offers a challenging area of research. In this article studies on dose reduction, different detector technologies, optimization of image acquisition and new technical developments in image acquisition and post processing will be reviewed. Studies indicate that dose reduction in PA chest images to at least 50% of commonly applied dose levels does not affect diagnosis in the lung fields; however, dose reduction in the mediastinum, upper abdomen and retrocardiac areas appears to directly deteriorate diagnosis. In addition to patient dose, also the design of the various digital detectors seems to have an effect on image quality. With respect to image acquisition, studies showed that using a lower tube voltage improves visibility of anatomical structures and lesions in digital chest radiographs but also increases the disturbing appearance of ribs. New techniques that are currently being evaluated are dual energy, tomosynthesis, temporal subtraction and rib suppression. These technologies may improve diagnostic chest X-ray further. They may for example reduce the negative influence of over projection of ribs, referred to as anatomic noise. In chest X-ray this type of noise may be the dominating factor in the detection of nodules. In conclusion, optimization and new developments will enlarge the value of chest X-ray as a mainstay in the diagnosis of chest diseases Elsevier Ireland Ltd. All rights reserved. 1. Introduction Chest radiography is the most frequently performed diagnostic X-ray examination; it is of value for solving a wide range of clinical problems. X-ray images of the chest provide important information for deciding upon further steps in the establishment of a diagnosis, treatment and follow-up procedure. Chest radiography remains the mainstay for diagnosis of many pulmonary diseases, even despite recent developments in cross sectional imaging of the thorax, particularly computed tomography (CT). Advantages of chest radiography over cross sectional imaging are lower cost, lower dose and speed of acquisition and diagnosis. In a European Directive, the need for optimization of acquisition techniques for X-ray imaging and limitation of patient dose is established [1]. The effective dose related to a posterior anterior (PA) radiographic chest image is about 0.02 msv [2]. For comparison, this is about 0.5% of a CT scan of the chest. The effective dose related to the lateral chest image is approximately a two times higher compared to the dose of a PA projection [2]. Although individual patient dose in chest radiography is relatively low, its contribution to the collective dose is significant due to the frequent use of this examination. In the Netherlands, about a third of all diagnostic X-ray examinations are a chest X-ray [2]. The associated estimated contribution to the collective dose is about 18% [2]. Similar figures are reported in other western countries [3,4]. Chest radiography may be implemented also in screening programmes in some countries, this would have a substantial impact on the collective dose from chest X-rays. The frequent use and diagnostic importance of chest X-ray make that optimization of image quality and patient dose is an important area of research. Therefore, the relation between these aspects is herewith discussed. Studies that investigated dose reduction and perceived image quality will also be discussed. The digital chest X-ray acquisition technique will be reviewed and recent chest radiography technologies will be assessed, both with respect to diagnostic accuracy and radiation dose to the patient. Corresponding author at: Department of Radiology, C2S, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands. Tel.: ; fax: address: w.j.h.veldkamp@lumc.nl (W.J.H. Veldkamp). 2. Dose and image quality in digital radiography Dose in digital chest radiography mainly affects the noise in the images. Noise in radiography can be defined as uncertainty or X/$ see front matter 2009 Elsevier Ireland Ltd. All rights reserved. doi: /j.ejrad

2 210 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) imprecision of the recording of an image, i.e. unwanted stochastic fluctuations in the image. The most disturbing effect on image quality (and thereby on diagnosis) is that noise can cover or reduce the visibility of certain structures. The loss of visibility is especially significant for low contrast objects. An important source of noise in X-ray images is related to the random manner in which the photons are distributed within the image. In a uniform digital image, pixel values (that are associated to the individual detector elements) will vary around their expected value. This type of noise is known as quantum noise. The degree of the fluctuations is related to the exposure level: quantum noise in a detector element is proportional to the square root of the exposure level (noise expressed by the standard deviation of the signal). Here it should be noted that the signal in the detector element is proportional to the number of photons imparting on it [5]. Therefore signal-to-noise ratio (SNR) and thereby image quality will improve with higher exposure levels. For example, improving the SNR by a factor 2 can only be obtained by increasing the dose by a factor 4 (assuming that quantum noise is the predominant source of noise). The resulting improvement of image quality will obviously have to be assessed clinically against the increased dose absorbed by the patient. Apart from quantum noise other additional noise sources must be considered in digital radiography, i.e. detector noise (for instance electronic noise) and anatomical noise [6 8]. Detector noise becomes more significant at low exposure levels whereas for higher exposure levels quantum noise and anatomic noise will dominate in medical radiographs. Anatomic noise can be referred to as overlaying anatomic features such as ribs, lung vessels, heart, mediastinum, and diaphragm in a chest radiograph. This occurs since chest radiography involves the projection of a three-dimensional structure onto a twodimensional image [3]. It has been shown that anatomic noise can have an important negative effect on observer performance in detecting abnormalities especially in chest radiography [3,7,8] Detector technology With the former film-screen systems, the range of patient dose in clinical practice was inherently limited by its sensitivity (speed class). Because of the small dynamic range, film-screen radiography images appear underexposed at low dose and overexposed at higher dose. With digital radiography underexposure or overexposure is less likely to occur. This can be explained by wide dynamic range of these detectors [9] (Fig. 1). However, as explained above, the selected dose level used will influence the quantum noise level in the image and thereby the diagnostic potential. Low exposures will still create images with clear appearance of gross anatomical structures but increased quantum noise will possibly hamper visualization of subtle anatomic and pathologic structures. This aspect of digital radiographic systems forms an extra challenge and opportunity for optimizing patient dose and (perceived) image quality. An additional aspect of digital radiography is that differences in digital detector technology lead to differences in image quality and dose. In the past decade in most western European hospitals radiological film-screen (FS) radiography has been replaced by digital radiography systems. Already in the early eighties, computed radiography (CR) with phosphor plate systems was introduced. The radiation level received at each point of X-ray photons reaching the storage phosphor screen, is stored in the local electron configuration by elevating the energy level of electrons (excitation) in the phosphor. After exposure, the photon energy stored in the phosphor plate is read out by a laser scanner and a digital image is obtained. At first, the quality of these systems was moderate and the dose needed for recording chest images was higher compared to the FS systems. Over the last 20 years the CR systems improved in both dose requirements as in image quality. Recent advances in CR are more efficient collection of light by reading both sides of the screen (dual-sided read CR) which results in an increased signalto-noise ratio, line scan read out yields improved speed and the use of needle-like phosphor allows for improved X-ray absorption efficiency (a thicker phosphor) without loss of spatial resolution [10]. In the nineties, so-called direct radiography (DR) digital systems with a flat-panel detector (FPD) became available for chest radiography. In a short period, different digital radiography chest systems were introduced for clinical use. In FPD s the conversion of the latent X-ray image into a measurable signal most often occurs in a layer of Cesium Iodide (CsI-FPD), Gadolinium Oxisulphide (GOS- Fig. 1. Digital versus conventional chest radiography. For film-screen systems, the optical density is directly related to the dose (see upper row of images). This is not the case with digital techniques (lower row of images). Due to the better dynamic range at very low and very high doses, a clear image is shown. Or, in other words, irrespective of the dose, digital images are presented in similar gray values. However, increased quantum noise at low doses possibly hamperes visualization of subtle anatomic and pathologic structures.

3 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) Fig. 2. A radiograph of an anthropomorphic phantom (left image). Different lesions are simulated and attached on the phantom. (A) simulated interstitial linear disease; (B) simulated nodule; (C) simulated nodule. In the observer study the radiologist identified the lesions and indicated the location of the detected lesions. FPD) or Selenium (Se-FPD) in combination with a matrix of thin film transistors (TFTs) from which the light (CsI, GOS) or electrical charge (Se), provoked in the layer, is read out and transformed into a digital image. Detectors that use a scintillator that converts X-ray into light, are called indirect conversion systems. The light is actually transformed by photodiodes in the TFT-layer into an electrical signal. The detector material in direct conversion systems directly converts X-ray photons into an electrical charge. A selenium layer is used for this purpose. A different technique uses charge-coupled devices (CCD) in combination with a scintillation layer. The chest is much larger than currently available CCD chips. Solutions for projecting the chest on a CCD chip are the use of lenses or tapered optical fibers, at the cost of reduced dose efficiency and degraded image quality. A better solution is the uses of the so-called slot-scan technique. This technique uses a linear array of small CCD detectors in combination with a narrow X-ray beam that scans the chest. Several studies have shown the advantages of digital systems compared to FS [11 13], for instance the improved visibility of the mediastinal areas in the image. One of these studies used an anthropomorphic phantom with simulated lesions to investigate detection of lesions in the chest for a digital CCD slot-scan system (Fig. 2). It was found that with the digital system, the number of lesions observed in the mediastinum was almost twice the number found with the FS system. For the lung lesions no significant difference was found. The dose levels were roughly comparable between the digital and the FS system (speed class 400). In another study the diagnostic performance was compared for eight different digital radiography chest systems [14]. The systems were assessed for detection of simulated chest disease under clinical conditions. The following systems were regarded: four different flat-panel detector systems, two different charge-coupled device systems, one selenium-coated drum, and one storage phosphor system. Differences in diagnostic performance were found among the eight different digital chest systems in the configurations under which they were routinely applied in clinical practice. Interestingly, differences in detection rates could not be explained by dose (Fig. 3). The differences in detector design were given as explanation here. The DR systems significantly outperformed the single-sided read CR system with respect to image quality whereas the dose levels used with the DR systems were lower. Furthermore, the results suggested that the scanning CCD or slot-scan technique gave best detection results. Due to the superior anti scatter properties of the small scanning detector (most scattered photons will go along it) a grid can be omitted, therefore this technique is associated with excellent image quality at relatively low doses [13,15]. Several other researchers investigated or compared different digital systems. Better performance at low spatial frequencies for CsI-FPD systems compared to Se-FPD systems is found by studies that use physical parameters to investigate image quality as a function of spatial frequency. This is explained by the high atomic number and high density of CsI resulting in good capture of the latent X-ray image. On the contrary, at the higher spatial frequencies the Se-based systems show better performance since these systems show less blurring of the image signal [16,17]. For indirect conversion detectors, apart from to the high atomic number and high density, the needle-like structure of CsI reduces the spreading of light in the scintillator that allows the use of a thicker layer with higher efficiency compared with unstructured scintillators like GOS and regular CR systems [16 18]. An extensive overview of studies that investigated dose requirements and image quality of various digital systems for chest radiography is given in a recent publication [19]. Fig. 4 givesanover-

4 212 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) all impression of the results found in literature as partly discussed above. Common systems are given as a function of dose and image quality in clinical practice. The circles represent the uncertainty in the results: the acquisition technique may vary in practice, different research methods are used in literature (each giving inherent limited results), differences found between systems are not necessary unequivocal and finally, differences between manufacturers may exist per detector type Diagnostic perception Fig. 3. Different digital systems with respect to dose and lesion detection were compared in a phantom study (Fig. 2). Dose for various digital systems varies (upper bar plot). Differences in lesion detection (lower bar plot) cannot be explained by differences in dose but by detector design. Quantum noise and detector noise hamper detection of objects with low contrast. Detectability of objects on a uniform background is a function of object contrast and object size (detail). Detectability of objects can be improved by increasing radiation dose. It was demonstrated however that in radiographic chest images for detection of lung nodules with sizes in the order of 10 mm, the projected anatomy (anatomic noise) is far more disturbing than quantum noise and system noise [8]. Anatomic noise can hinder detection through two processes: local influence, or camouflaging, and global influence, or confusion [6]. Local influence is for instance a rib that is projected over a small nodule while global influence describes lesions that fit very well in the global pattern of certain anatomical structures. Confusion is for instance a small nodule that may be interpreted as a tangentially projected vessel. Anatomical noise by the projection of ribs is of particular concern for detection of lung nodules (i.e., potential malignancies), because the ribs overlay about 75% of the area of the lungs [3]. It was estimated that 50% of nodules measuring 6 10 mm are missed owing to superimposition of anatomy like ribs, heart, and mediastinal structures [20]. Interestingly, purely on the basis of inherent contrast, a nodule as small as 3 mm in diameter should be visible on chest radiographs when anatomic noise is not taken into account [3]. In general, it appears that many overlooked lung nodules in chest radiographs are visible in retrospect [21,22]. 3. Study designs for investigating the effect of dose reduction on image quality Fig. 4. Common systems are given as a function of dose and image quality in clinical practice according to literature. The circles represent the uncertainty in the results: the acquisition technique may vary in practice, the research methods differ in literature and give an inherent limited view and finally, differences between manufacturers may exist per detector type. A number of methods for investigating the relationship between dose and image quality have been developed. Objective measurements of physical characteristics, such as modulation-transfer function, detective quantum efficiency or contrast-to-noise-ratio, and contrast-detail studies are often used. Alternatively, anthropomorphic phantom studies and clinical studies can be used for subjective (quality rating) and objective (lesion detection) observer performance studies. The detective Quantum Efficiency (DQE) is a measure of the combined effect of the noise and contrast performance of an imaging system, it is expressed as a function of object detail. Noise can be expressed by the signal-to-noise ratio (SNR), contrast-to-noiseratio (CNR) or by the noise power spectrum (NPS). An imaging system s ability to render the contrast of an object as a function of object detail is traditionally expressed as its modulation-transfer function (MTF). The combination of the functions NPS and MTF determines the above mentioned DQE. These objectives physical measurements describe the systems technical imaging performance but it is still difficult to translate the outcome to the clinical situation that is far more complex than these measurements can describe. Contrast-detail studies can be used to determine dose levels that are related to a desired contrast-detail performance or can be used to compare different systems or acquisition techniques. An advantage of contrast-detail studies over objective physical

5 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) Fig. 5. Zoomed detail of a mm pixel size matrix showing simulated low contrast nodular lesions located in a uniform object. Details of actual images are shown at the left, whereas details of simulated images are shown at the right. The images correspond to 54 mas (A) and 25 mas(b) acquired with a scanning CCD chest system. Visually, the actual and simulated images appear quite similar. For 25 mas the NPS for an actual dose and corresponding simulated dose image is shown at the right. The NPS of the simulated reduced dose images are at the same level as their corresponding actual dose images, although these NPS do not precisely fit as the simulated images show slightly higher noise levels for higher spatial frequencies and slightly lower noise levels for lower spatial frequencies. measurements is that contrast-detail performance includes the performance of human observers. A limitation with both contrastdetail performance and physical measurements is that the anatomic background is not taken into account. Anthropomorphic phantoms better approximate the clinical reality with respect to anatomic background. Some studies use these phantoms in combination with artificial lesions that provide for a standard of reference in evaluating observer detection performance. Unfortunately it is impossible to simulate appearance of the whole spectrum of diseases with artificial lesions. An alternative is performing clinical dose experiments through computer simulation of the effect of dose reduction on image quality (note that most often it is assumed unethical to perform clinical low dose studies with real patients). A number of researchers reported on methods for simulating reduced dose images. Such techniques have been applied in digital radiography [23,24] and computed tomography [25 27]. A well-established method for reduced dose simulation that has been previously described uses DQE and NPS at the original and simulated dose levels to create an image containing filtered noise. The method provides for simulated images containing noise that, in terms of frequency content, agree very well with original images at the same dose levels [23]. Another study described and validated a pragmatic technique for simulating reduced dose digital chest images, similar to noise simulation techniques used for CT. This model includes using the raw pixel standard deviation as a measure of noise. Gaussian noise with certain standard deviation is added to the original image to obtain a simulated reduced dose image with the desired pixel standard deviation for each pixel [28]. After addition of noise the raw image was post processed in the standard way. Nodular lesions were simulated in this study in combination with the low dose simulation (Fig. 5). Then, detection performance of simulated lesions in simulated and in real low dose images was investigated using this method by performing an observer model study [28]. The purpose of one low dose simulation study was to investigate whether radiologists can rank the image quality of digital radiographic images that correspond to different dose levels [29]. Fig. 6 gives an impression of the appearance of different dose images by showing details. In this observer study, chest radiographs of 20 patients (both PA and lateral images) with a variety of chest pathologies were used to simulate reduced dose levels corresponding to 50%, 25% and 12% of the original dose. For each patient the images were displayed as hard copies on the film-viewing box in random order. Four radiologists ranked the quality of the corresponding images and rated diagnostic quality. The 100% reference dose was not recognized as the best quality image in nearly half of the cases (Fig. 7). Larger dose reductions to 25% and 12% were usually recognized as third and fourth best quality. The preliminary 4. Dose reduction in chest radiography (how low can we go?) A number of studies have been performed to investigate the possible clinical effects of dose reduction in chest radiography using methods described above. Fig. 6. Detail images of the same patient with respect to 100%, 50%, 25% and 12% of the standard dose (respectively A D). In the observer study, the entire images were presented in a random order concerning the dose levels.

6 214 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) Fig. 7. Ranking the images from 100% to the lower levels was difficult for the observers as is shown by the bar plots. The 100% reference dose was not recognized as the best quality image in nearly half of the cases for both PA and lateral images. subjective findings suggested therefore that a 50% dose reduction seems feasible in a variety of chest pathologies. However, further dose reduction (more than 50%) clearly reduced the perceived diagnostic quality. In addition to their subjective study on dose reduction, the same authors also objectively investigated to what extent dose reduction resulted in decreased detection of simulated nodules in the lungs [30]. Raw data from 20 normal clinical digital PA chest images were used in this study. Low dose images were simulated and nodules were attaches digitally. Hard copies were printed representing 100% dose and simulated patient doses of 50, 25, and 12%. These hardcopy images were reviewed by four radiologists. It was found that the decrease in radiation dose from 100% to 50, 25, or 12% had no effect on lesion detection in the lungs. However, the decrease in radiation dose had a prominent effect on lesion detection in the mediastinum. The detection performance of the four radiologists in the mediastinum deteriorated with each dose reduction step (Fig. 8). A different study by other authors evaluated the influence of different doses to the patient and peak kilovoltage settings on diagnostic performance with respect to PA radiographic chest images performed with a FPD [31]. An anthropomorphic chest phantom was used in combination with simulated lesions attached on the phantom. The acquisition technique was varied when making chest radiographs of the phantom. Four radiologists assessed all of the images. For the lung fields only, no significant loss in diagnostic performance could be demonstrated, even after a 50% reduction in radiation dose. This however did not count for the mediastinum where the diagnostic performance deteriorated at this level of dose reduction. This finding is in accordance with the conclusions by the study reported earlier Acquisition technique Diagnostic X-rays used for radiographs represent a certain energy range: the X-ray spectrum. Contrast in a radiograph is influenced by the X-ray spectrum used. In general radiography a common X-ray spectrum (of intermediate energies) usually provides the best compromise between sufficient image quality and acceptable patient radiation dose. However, in chest radiography such an intermediate X-ray spectrum would result in a very pronounced appearance of the ribs in the radiographs. Bone particularly effective attenuates X-rays at intermediate energies and the resulting bright appearance of the ribs in the radiographs would seriously hinder the evaluation of chest pathology. Historically, to overcome this problem, a compromise had to be made: chest radiography is routinely performed using a relatively high energetic X-ray spectrum. This result in relatively translucent represented ribs but also results in less contrast in the soft tissues and particularly soft tissue lesions. Some studies indicate that CR compared to FS can be used properly in high-energy radiography of the chest providing equal image quality at comparable effective dose to the patient [32]. Other studies find improved SNRs or visibility scores when using lower tube voltages under constant effective dose levels for CR and DR [33,34]. Some recent studies however indicate that lower tube voltages chest radiography have as negative side effect prominent imaging of the ribs which may disturb the radiologist in his or her detection [33,35]. Therefore in another study it is concluded that a compromise has to be made in tube voltage setting. It was demonstrated that an optimum X-ray spectrum for chest radiography with cesium iodide amorphous silicon flat-panel detectors is obtained with 120 kvp and 0.2 mm of copper filtration [36]. In addition it was concluded from an anthropomorphic phantom study with human observers that standard PA chest radiographs should be acquired with 120 kvp (also routinely used) in terms of diagnostic performance and effective dose [31]. 5. New developments in chest radiography The strong current interest in, dual energy, tomosynthesis and temporal subtraction have been made possible by the introduction of digital radiography Dual energy An effective method to improve radiologic detection performance seems reduction or elimination of ribs, which has been shown to be the main factor limiting the detection of subtle lung nodules as an early sign of lung cancer [3]. This can be achieved by dual energy chest radiography. Dual energy comprehends weighted subtraction of low and high-energy images and results in images representing bone structures or images representing soft tissue. It was found that dual energy added to standard PA chest radiography significantly improves the detection of small non-calcified pulmonary nodules and the detection of calcified chest lesions [37].

7 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) Fig. 8. Permission to reproduce these figures is given by the Radiological Society of North America (RSNA ). Original publication: Kroft LJM, Veldkamp WJH, Mertens BJA, et al. Detection of simulated nodules on clinical radiographs: dose reduction at digital posteroanterior chest radiography. Radiology 2006;241: (A D) Clinical PA digital radiographs of simulated chest nodules with (A and C) 100% radiation dose and with (B and D) simulated 12% dose. Images C and D show right lower part of radiographs A and B, respectively. Diameter and attenuation of lung lesion were 3.24 and 4.00 cm, respectively (arrow in A and B). For mediastinal lesions, these were 1.62 and 2.25 cm, 0.81 and 1.38 cm, 0.81 and 1.13 cm (arrow 1, 2, and 3, respectively). Note difference in noise levels between a and b and between C and D. Lung lesion is easily appreciated in radiographs A and B, whereas subtle mediastinal lesions seem more difficult to appreciate at lower dose (D). (E and F) Graphs of number of simulated lesions detected in (A) lungs and (B) mediastinum at 100% dose and at reduced dose levels accumulated for all four observers. Note difference between lungs and mediastinum for effect of dose reduction.

8 216 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) However the technique has some disadvantages as well: (1) the radiation dose is considerably higher compared to standard digital PA images which can be in the order of a factor 2 3, (2) Reduced signal-to-noise ratio in result images since the noise of two separated images adds up into the soft tissue or bone image and contrast in the resulting images is reduced, (3) Additional hardware is needed for making images at different energies in a short time interval; e.g. fast switching filters and fast detector read out, and (4) extra images that may increase the workload Temporal subtraction Temporal subtraction comprehends subtraction of a current image and a prior image of the same patient. Standard PA images are used, so that no extra dose to the patient is needed. The technique facilitates detecting pathologic changes over time and could provide diagnostic advantages. In the result images arisen nodules hidden by bones or the heart are potentially less likely to be missed. Furthermore, infiltrative shadows should be better distinguished from breast tissue and pectoral muscles in the lung area. Subtraction of current and prior images is not straightforward because it is not likely that the two chest radiographs will have exactly matching projections. Temporal subtraction uses sophisticated warping algorithms to eliminate the effect of these differences in projection. The technique is currently only clinically used in Japan. A number of studies showed significant improvements in diagnostic accuracy with respect to nodule detection [38,39] Rib suppression techniques Eliminating ribs has already shown to be effective with dual energy suppression radiography despite the disadvantages related to this technique that are hampers implementation in routine clinical practice. An alternative rib suppression method is based on image processing techniques and has potential advantages over dual energy radiography. Major advantage of such post processing approach compared to a dual energy subtraction technique are: (1) the technique requires no additional radiation dose to patients, but uses only chest radiographs acquired with a standard digital radiography system, (2) no specialized equipment for generating dual energy X-ray exposures is required, and (3) noise levels are not necessarily increased. Digital chest radiography provides sufficient large dynamic range and high bit depth to register accurately the entire range of radiation intensities in the latent PA chest image. This implies that visibility of lesions in the lungs should improve after subtraction of intensities corresponding to ribs. One paper describes a framework for rib suppression based on regression and applied on a pixel level. Radiographs with known soft tissue and bone images obtained by dual energy imaging were used for training the framework [40]. Other authors presented more recently a comparable approach [41]. They employed a massive training artificial neural network to create a rib suppressed image also using dual energy training data. A reduction of the contrast of ribs in chest radiographs is reported in both studies. A drawback of the two methods, likewise the dual energy suppression technique, is that the resulting images suffer from additional noise. In Fig. 9 we present results for a rib supression technique comparable to a method published earlier [42]. In this technique ribs and lung fields are segmented automatically using image processing techniques. The rib signal is estimated from image and model information and subtracted from the rib (for each rib). By scaling the difference value, the degree of suppression can be varied. Fig. 9 gives a result of the method used and shows the effect of rib suppression Tomosynthesis Digital tomosynthesis is a method of producing coronal cross section images using a digital detector and a chest X-ray system with a moving X-ray tube. In tomosynthesis, a series of low-dose exposures are made by moving the X-ray tube within a limited angular range. The acquired images are processed into slices that show anatomical structures at different depths and angles. These coronal cross section images have relatively high spatial resolution in the image plane, but less resolution in the depth direction. Tomosynthesis can improve the visibility of pulmonary nodules by Fig. 9. Current implementation of the rib suppression method. The fully automatic method suppressed the dorsal parts of the ribs in both lung fields (suppressed image shown at the left).

9 W.J.H. Veldkamp et al. / European Journal of Radiology 72 (2009) producing cross section images without overprojection of ribs and overlying vasculature [43]. The actual effectiveness of tomosynthesis is currently under study in a US national screening trial [43]. In tomosynthesis, the initial projection images show the anatomy from different orientations due to parallax. They are shifted and added together to render structures in one plane in sharp focus. As a result objects in other planes are blurred out in the resulting image. Deblurring algorithms are applied to eliminate the blurring of structures that are out-of-plane. A recent paper reports that a typical set of acquisition parameters for chest imaging is 71 projection images, 20 total tube movement, and 5 mm spacing of reconstructed sections. The overall radiation exposure to the patient has been reported to be comparable to a former FS lateral chest image. The entire acquisition sequence is completed in 11 s (which is within a single breath hold for most patients) [43]. 6. Conclusions and perspective Digital chest radiography has many advantages over film-screen radiography, including improved diagnostic quality especially in areas of high attenuation (mediastinum, upper abdomen, retrocardiac) and lower dose to the patient. There are a wide variety of technically different digital systems, flat-panel detectors and slot-scanning systems are related to excellent image quality. The introduction of new techniques (tomosynthesis, dual energy, temporal subtraction and rib suppression) enables to further improve diagnostic accuracy. These techniques however must be further developed and validated on a larger scale. A drawback may be the extra images that are added to the workload of the radiologist. In conclusion, digital chest radiography is a time efficient and inexpensive investigation of low dose and good diagnostic quality. Optimizations and innovations may further improve the diagnostic accuracy. References [1] European Commission. Council Directive 97/43/EURATOM of 30 June 1997 on Health Protection of Individuals Against the Dangers of Ionising Radiation in Relation to Medical Exposure, and Repealing Directive 84/466/EURATOM. Official Journal of the European Communities L-180/ [2] Teeuwisse W, Geleijns J, Veldkamp W. An inter-hospital comparison of patient dose based on clinical indications. European Radiology 2007;17(7): [3] McAdams HP, Samei E, Dobbins III J, Tourassi GD, Ravin CE. Recent advances in chest radiography. Radiology 2006;241(3): [4] Daffner R. Clinical Radiology, the Essentials. 2nd ed. Baltimore: Williams & Wilkins; [5] Bushberg JT, Seibert JA, Leidholdt EM, Boone JM. Image quality. The Essential Physics of Medical Imaging. 2nd ed. Philadelphia: Lippincott Williams & Wilkins; pp [6] Samei E, Flynn MJ, Peterson E, Eyler WR. Subtle lung nodules: influence of local anatomic variations on detection. Radiology 2003;228(1): [7] Bath M, Hakansson M, Borjesson S, et al. Nodule detection in digital chest radiography: effect of anatomical noise. Radiation Protection Dosimetry 2005;114(1 3): [8] Hakansson M, Bath M, Borjesson S, Kheddache S, Johnsson AA, Mansson LG. Nodule detection in digital chest radiography: effect of system noise. Radiation Protection Dosimetry 2005;114(1 3): [9] Veldkamp WJ, Kroft LJ, van Delft JP, Geleijns J. A technique for simulating the effect of dose reduction on image quality in digital chest radiography. Journal of Digital Imaging 2008, [10] Cowen AR, Davies AG, Kengyelics SM. Advances in computed radiography systems and their physical imaging characteristics. Clinical Radiology 2007;62(12): [11] Aufrichtig R. Comparison of low contrast detectability between a digital amorphous silicon and a screen-film based imaging system for thoracic radiography. Medical Physics 1999;26(7): [12] Kroft LJM, Geleijns J, Mertens BJA, Veldkamp WJH, Zonderland HM, de Roos A. Digital slot-scan charge-coupled device radiography versus amber and bucky screen-film radiography for detection of simulated nodules and interstitial disease in a chest phantom. Radiology 2004;231(1): [13] Veldkamp WJ, Kroft LJ, Mertens BJ, Geleijns J. Digital slot-scan charge-coupled device radiography versus amber and bucky screen-film radiography: comparison of image quality in a phantom study. Radiology 2005;235(3): [14] Kroft LJ, Veldkamp WJ, Mertens BJ, Boot MV, Geleijns J. Comparison of eight different digital chest radiography systems: variation in detection of simulated chest disease. AJR American Journal of Roentgenology 2005;185(2): [15] Samei E, Saunders RS, Lo JY, et al. Fundamental imaging characteristics of a slotscan digital chest radiographic system. Medical Physics 2004;31(9): [16] Borasi G, Nitrosi A, Ferrari P, Tassoni D. On site evaluation of three flat panel detectors for digital radiography. Medical Physics 2003;30(7): [17] Samei E, Flynn MJ. An experimental comparison of detector performance for direct and indirect digital radiography systems. Medical Physics 2003;30(4): [18] Kotter E, Langer M. Digital radiography with large-area flat-panel detectors. European Radiology 2002;12(10): [19] Schaefer-Prokop C, Neitzel U, Venema HW, Uffmann M, Prokop M. Digital chest radiography: an update on modern technology, dose containment and control of image quality. European Radiology 2008;18(9): [20] Black C, Bagust A, Boland A, et al. The clinical effectiveness and costeffectiveness of computed tomography screening for lung cancer: systematic reviews. Health Technology Assessment 2006;10(3), iii x, 1. [21] Shah PK, Austin JHM, White CS, et al. Missed non-small cell lung cancer: radiographic findings of potentially resectable lesions evident only in retrospect. Radiology 2003;226(1): [22] Austin JHM, Romney BM, Goldsmith LS. Missed bronchogenic-carcinoma - radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect. Radiology 1992;182(1): [23] Bath M, Hakansson M, Tingberg A, Mansson LG. Method of simulating dose reduction for digital radiographic systems. Radiation Protection Dosimetry 2005;114(1 3): [24] Treiber O, Wanninger F, Fuhr H, Panzer W, Regulla D, Winkler G. An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography. Physics in Medicine and Biology 2003;48(4):449 66, [25] Frush DP, Slack CC, Hollingsworth CL, et al. Computer-simulated radiation dose reduction for abdominal multidetector CT of pediatric patients. American Journal of Roentgenology 2002;179(5): [26] Mayo JR, Whittall KP, Leung AN, et al. Simulated dose reduction in conventional chest CT: validation study. Radiology 1997;202(2): [27] van Gelder RE, Venema HW, Serlie IWO, et al. CT Colonography at different radiation dose levels: feasibility of dose reduction. Radiology 2002;224(1): [28] Veldkamp W, Kroft L, van Delft J, Geleijns J. A Technique for simulating the effect of dose reduction on image quality in digital chest radiography. Jornal of Digital Imaging 2008, [29] Kroft LJM, Veldkamp WJH, Mertens BJA, Van Delft JPA, Geleijns J. Dose reduction in digital chest radiography and perceived image quality. British Journal of Radiology 2007;80(960): [30] Kroft LJ, Veldkamp WJ, Mertens BJ, van Delft JP, Geleijns J. Detection of simulated nodules on clinical radiographs: dose reduction at digital posteroanterior chest radiography. Radiology 2006;241(2): [31] Metz S, Damoser P, Hollweck R, et al. Chest radiography with a digital flat-panel detector: experimental receiver operating characteristic analysis. Radiology 2005;234(3): [32] Launders JH, Cowen AR. A comparison of the threshold detail detectability of a screen-film combination and computed radiology under conditions relevant to high-kvp chest radiography. Physics in Medicine and Biology 1995;40(8): [33] Chotas HG, Floyd CE, Dobbins JT, Ravin CE. Digital chest radiography with photostimulable storage phosphors - signal-to-noise ratio as a function of kilovoltage with matched exposure risk. Radiology 1993;186(2): [34] Uffmann M, Neitzel U, Prokop M, et al. Flat-Panel-Detector chest radiography: effect of tube voltage on image quality. Radiology 2005;235(2): [35] Ullman G, Sandborg M, Dance DR, Hunt RA, Carlsson GA. Towards optimization in digital chest radiography using monte carlo modelling. Physics in Medicine and Biology 2006;51(11): [36] Dobbins JT, Samei E, Chotas HG, et al. Chest radiography: optimization of x-ray spectrum for cesium iodide-amorphous silicon flat-panel detector. Radiology 2003;226(1): [37] Fischbach F, Freund T, Rottgen R, Engert U, Felix R, Ricke J. Dual-energy chest radiography with a flat-panel digital detector: revealing calcified chest abnormalities. American Journal of Roentgenology 2003;181(6): [38] Difazio MC, MacMahon H, Xu XW, et al. Digital chest radiography: effect of temporal subtraction images on detection accuracy. Radiology 1997;202(2): [39] Uozumi T, Nakamura K, Watanabe H, Nakata H, Katsuragawa S, Doi K. ROC analysis of detection of metastatic pulmonary nodules on digital chest radiographs with temporal subtraction. Academic Radiology 2001;8(9): [40] Loog M, van Ginneken B, Schilham AM. Filter Learning: Application to Suppression of Bony Structures From Chest Radiographs. To appear in: Medical Image Analysis [41] Suzuki K, Abe H, MacMahon H, Doi K. Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN). IEEE Transactions on Medical Imaging 2006;25(4): [42] Vogelsang F, Kohnen M, Mahlke J. Model-based analysis of chest radiographs. image processing; In: Proceedings of SPIE International Symposium on Medical Imaging [43] Dobbins JT, McAdams HP, Godfrey DJ, Li CM. Digital tomosynthesis of the chest. Journal of Thoracic Imaging 2008;23(2):86 92.