Multi-Institutional Evaluation of Digital Tomosynthesis, Dual-Energy Radiography, and Conventional Chest Radiography for the Detection and Management of Pulmonary Nodules.

Purpose To conduct a multi-institutional, multireader study to compare the performance of digital tomosynthesis, dual-energy (DE) imaging, and conventional chest radiography for pulmonary nodule detection and management. Materials and Methods In this binational, institutional review board-approved, HIPAA-compliant prospective study, 158 subjects (43 subjects with normal findings) were enrolled at four institutions. Informed consent was obtained prior to enrollment. Subjects underwent chest computed tomography (CT) and imaging with conventional chest radiography (posteroanterior and lateral), DE imaging, and tomosynthesis with a flat-panel imaging device. Three experienced thoracic radiologists identified true locations of nodules (n = 516, 3-20-mm diameters) with CT and recommended case management by using Fleischner Society guidelines. Five other radiologists marked nodules and indicated case management by using images from conventional chest radiography, conventional chest radiography plus DE imaging, tomosynthesis, and tomosynthesis plus DE imaging. Sensitivity, specificity, and overall accuracy were measured by using the free-response receiver operating characteristic method and the receiver operating characteristic method for nodule detection and case management, respectively. Results were further analyzed according to nodule diameter categories (3-4 mm, >4 mm to 6 mm, >6 mm to 8 mm, and >8 mm to 20 mm). Results Maximum lesion localization fraction was higher for tomosynthesis than for conventional chest radiography in all nodule size categories (3.55-fold for all nodules, P < .001; 95% confidence interval [CI]: 2.96, 4.15). Case-level sensitivity was higher with tomosynthesis than with conventional chest radiography for all nodules (1.49-fold, P < .001; 95% CI: 1.25, 1.73). Case management decisions showed better overall accuracy with tomosynthesis than with conventional chest radiography, as given by the area under the receiver operating characteristic curve (1.23-fold, P < .001; 95% CI: 1.15, 1.32). There were no differences in any specificity measures. DE imaging did not significantly affect nodule detection when paired with either conventional chest radiography or tomosynthesis. Conclusion Tomosynthesis outperformed conventional chest radiography for lung nodule detection and determination of case management; DE imaging did not show significant differences over conventional chest radiography or tomosynthesis alone. These findings indicate performance likely achievable with a range of reader expertise. © RSNA, 2016 Online supplemental material is available for this article.

Estimation of the two-dimensional presampled modulation transfer function of digital radiography devices using one-dimensional test objects.

PURPOSE: The modulation transfer function (MTF) of medical imaging devices is commonly reported in the form of orthogonal one-dimensional (1D) measurements made near the vertical and horizontal axes with a slit or edge test device. A more complete description is found by measuring the two-dimensional (2D) MTF. Some 2D test devices have been proposed, but there are some issues associated with their use: (1) they are not generally available; (2) they may require many images; (3) the results may have diminished accuracy; and (4) their implementation may be particularly cumbersome. This current work proposes the application of commonly available 1D test devices for practical and accurate estimation of the 2D presampled MTF of digital imaging systems. METHODS: Theory was developed and applied to ensure adequate fine sampling of the system line spread function for 1D test devices at orientations other than approximately vertical and horizontal. Methods were also derived and tested for slit nonuniformity correction at arbitrary angle. Techniques were validated with experimental measurements at ten angles using an edge test object and three angles using a slit test device on an indirect-detection flat-panel system [GE Revolution XQ∕i (GE Healthcare, Waukesha, WI)]. The 2D MTF was estimated through a simple surface fit with interpolation based on Delaunay triangulation of the 1D edge-based MTF measurements. Validation by synthesis was also performed with simulated images from a hypothetical direct-detection flat-panel device. RESULTS: The 2D MTF derived from physical measurements yielded an average relative precision error of 0.26% for frequencies below the cutoff (2.5 mm(-1)) and approximate circular symmetry at frequencies below 4 mm(-1). While slit analysis generally agreed with the results of edge analysis, the two showed subtle differences at frequencies above 4 mm(-1). Slit measurement near 45° revealed radial asymmetry in the MTF resulting from the square pixel aperture (0.2 mm × 0.2 mm), a characteristic which was not necessarily appreciated with the orthogonal 1D MTF measurements. In simulation experiments, both slit- and edge-based measurements resolved the radial asymmetries in the 2D MTF. The average absolute relative accuracy error in the 2D MTF between the DC and cutoff (2.5 mm(-1)) frequencies was 0.13% with average relative precision error of 0.11%. Other simulation results were similar to those derived from physical data. CONCLUSIONS: Overall, the general availability, acceptance, accuracy, and ease of implementation of 1D test devices for MTF assessment make this a valuable technique for 2D MTF estimation.

Plate-specific gain map correction for the improvement of detective quantum efficiency in computed radiography.

PURPOSE: The purpose of this work is to improve the noise power spectrum (NPS), and thus the detective quantum efficiency (DQE), of computed radiography (CR) images by correcting for spatial gain variations specific to individual imaging plates. CR devices have not traditionally employed gain-map corrections, unlike the case with flat-panel detectors, because of the multiplicity of plates used with each reader. The lack of gain-map correction has limited the DQE(f) at higher exposures with CR. This current work describes a feasible solution to generating plate-specific gain maps. METHODS: Ten high-exposure open field images were taken with an RQA5 spectrum, using a sixth generation CR plate suspended in air without a cassette. Image values were converted to exposure, the plates registered using fiducial dots on the plate, the ten images averaged, and then high-pass filtered to remove low frequency contributions from field inhomogeneity. A gain-map was then produced by converting all pixel values in the average into fractions with mean of one. The resultant gain-map of the plate was used to normalize subsequent single images to correct for spatial gain fluctuation. To validate performance, the normalized NPS (NNPS) for all images was calculated both with and without the gain-map correction. Variations in the quality of correction due to exposure levels, beam voltage/spectrum, CR reader used, and registration were investigated. RESULTS: The NNPS with plate-specific gain-map correction showed improvement over the noncorrected case over the range of frequencies from 0.15 to 2.5 mm(-1). At high exposure (40 mR), NNPS was 50%-90% better with gain-map correction than without. A small further improvement in NNPS was seen from carefully registering the gain-map with subsequent images using small fiducial dots, because of slight misregistration during scanning. Further improvement was seen in the NNPS from scaling the gain map about the mean to account for different beam spectra. CONCLUSIONS: This study demonstrates that a simple gain-map can be used to correct for the fixed-pattern noise in a given plate and thus improve the DQE of CR imaging. Such a method could easily be implemented by manufacturers because each plate has a unique bar code and the gain-map for all plates associated with a reader could be stored for future retrieval. These experiments indicated that an improvement in NPS (and hence, DQE) is possible, depending on exposure level, over a wide range of frequencies with this technique.

Automated lung segmentation in digital chest tomosynthesis.

PURPOSE: The purpose of this study was to develop an automated lung segmentation method for computerized detection of lung nodules in digital chest tomosynthesis. METHODS: The authors collected 45 digital tomosynthesis scans and manually segmented reference lung regions in each scan to assess the performance of the method. The authors automated the technique by calculating the edge gradient in an original image for enhancing lung outline and transforming the edge gradient image to polar coordinate space. The authors then employed a dynamic programming technique to delineate outlines of the unobscured lungs in the transformed edge gradient image. The lung outlines were converted back to the original image to provide the final segmentation result. The above lung segmentation algorithm was first applied to the central reconstructed tomosynthesis slice because of the absence of ribs overlapping lung structures. The segmented lung in the central slice was then used to guide lung segmentation in noncentral slices. The authors evaluated the segmentation method by using (1) an overlap rate of lung regions, (2) a mean absolute distance (MAD) of lung borders, (3) a Hausdorff distance of lung borders between the automatically segmented lungs and manually segmented reference lungs, and (4) the fraction of nodules included in the automatically segmented lungs. RESULTS: The segmentation method achieved mean overlap rates of 85.7%, 88.3%, and 87.0% for left lungs, right lungs, and entire lungs, respectively; mean MAD of 4.8, 3.9, and 4.4 mm for left lungs, right lungs, and entire lungs, respectively; and mean Hausdorrf distance of 25.0 mm, 25.5 mm, and 30.1 mm for left lungs, right lungs, and entire lungs, respectively. All of the nodules inside the reference lungs were correctly included in the segmented lungs obtained with the lung segmentation method. CONCLUSIONS: The method achieved relatively high accuracy for lung segmentation and will be useful for computer-aided detection of lung nodules in digital tomosynthesis.

An image-based technique to assess the perceptual quality of clinical chest radiographs.

PURPOSE: Current clinical image quality assessment techniques mainly analyze image quality for the imaging system in terms of factors such as the capture system modulation transfer function, noise power spectrum, detective quantum efficiency, and the exposure technique. While these elements form the basic underlying components of image quality, when assessing a clinical image, radiologists seldom refer to these factors, but rather examine several specific regions of the displayed patient images, further impacted by a particular image processing method applied, to see whether the image is suitable for diagnosis. In this paper, the authors developed a novel strategy to simulate radiologists' perceptual evaluation process on actual clinical chest images. METHODS: Ten regional based perceptual attributes of chest radiographs were determined through an observer study. Those included lung grey level, lung detail, lung noise, rib-lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. Each attribute was characterized in terms of a physical quantity measured from the image algorithmically using an automated process. A pilot observer study was performed on 333 digital chest radiographs, which included 179 PA images with 10:1 ratio grids (set 1) and 154 AP images without grids (set 2), to ascertain the correlation between image perceptual attributes and physical quantitative measurements. To determine the acceptable range of each perceptual attribute, a preliminary quality consistency range was defined based on the preferred 80% of images in set 1. Mean value difference (µ(1) - µ(2)) and variance ratio (σ(1) (2)/σ(2) (2)) were investigated to further quantify the differences between the selected two image sets. RESULTS: The pilot observer study demonstrated that our regional based physical quantity metrics of chest radiographs correlated very well with their corresponding perceptual attributes. The distribution comparisons, mean value difference estimations, and variance ratio estimations of each physical quantity between sets of images from two different techniques matched our expectation that the image quality of set 1 should be better than that of set 2. CONCLUSIONS: The measured physical quantities provide a robust reflection of perceptual image quality in clinical images. The methodology can be readily applied for automated evaluation of perceptual image quality in clinical chest radiographs.

Biplane correlation imaging: a feasibility study based on phantom and human data.

The objective of this study was to implement and evaluate the performance of a biplane correlation imaging (BCI) technique aimed to reduce the effect of anatomic noise and improve the detection of lung nodules in chest radiographs. Seventy-one low-dose posterior-anterior images were acquired from an anthropomorphic chest phantom with 0.28° angular separations over a range of ±10° along the vertical axis within an 11 s interval. Similar data were acquired from 19 human subjects with institutional review board approval and informed consent. The data were incorporated into a computer-aided detection (CAD) algorithm in which suspect lesions were identified by examining the geometrical correlation of the detected signals that remained relatively constant against variable anatomic backgrounds. The data were analyzed to determine the effect of angular separation, and the overall sensitivity and false-positives for lung nodule detection. The best performance was achieved for angular separations of the projection pairs greater than 5°. Within that range, the technique provided an order of magnitude decrease in the number of false-positive reports when compared with CAD analysis of single-view images. Overall, the technique yielded ~1.1 false-positive per patient with an average sensitivity of 75%. The results indicated that the incorporation of angular information can offer a reduction in the number of false-positives without a notable reduction in sensitivity. The findings suggest that the BCI technique has the potential for clinical implementation as a cost-effective technique to improve the detection of subtle lung nodules with lowered rate of false-positives.

An analysis of the mechanical parameters used for finite element compression of a high-resolution 3D breast phantom.

PURPOSE: The authors previously introduced a methodology to generate a realistic three-dimensional (3D), high-resolution, computer-simulated breast phantom based on empirical data. One of the key components of such a phantom is that it provides a means to produce a realistic simulation of clinical breast compression. In the current study, they have evaluated a finite element (FE) model of compression and have demonstrated the effect of a variety of mechanical properties on the model using a dense mesh generated from empirical breast data. While several groups have demonstrated an effective compression simulation with lower density finite element meshes, the presented study offers a mesh density that is able to model the morphology of the inner breast structures more realistically than lower density meshes. This approach may prove beneficial for multimodality breast imaging research, since it provides a high level of anatomical detail throughout the simulation study. METHODS: In this paper, the authors describe methods to improve the high-resolution performance of a FE compression model. In order to create the compressible breast phantom, dedicated breast CT data was segmented and a mesh was generated with 4-noded tetrahedral elements. Using an explicit FE solver to simulate breast compression, several properties were analyzed to evaluate their effect on the compression model including: mesh density, element type, density, and stiffness of various tissue types, friction between the skin and the compression plates, and breast density. Following compression, a simulated projection was generated to demonstrate the ability of the compressible breast phantom to produce realistic simulated mammographic images. RESULTS: Small alterations in the properties of the breast model can change the final distribution of the tissue under compression by more than 1 cm; which ultimately results in different representations of the breast model in the simulated images. The model properties that impact displacement the most are mesh density, friction between the skin and the plates, and the relative stiffness of the different tissue types. CONCLUSIONS: The authors have developed a 3D, FE breast model that can yield high spatial resolution breast deformations under uniaxial compression for imaging research purposes and demonstrated that small changes in the mechanical properties can affect images generated using the phantom.

Tomosynthesis imaging: at a translational crossroads.

Tomosynthesis is a decades-old technique for section imaging that has seen a recent upsurge in interest due to its promise to provide three-dimensional information at lower dose and potentially lower cost than CT in certain clinical imaging situations. This renewed interest in tomosynthesis began in the late 1990s as a new generation of flat-panel detectors became available; these detectors were the one missing piece of the picture that had kept tomosynthesis from enjoying significant utilization earlier. In the past decade, tomosynthesis imaging has been investigated in a variety of clinical imaging situations, but the two most prominent have been in breast and chest imaging. Tomosynthesis has the potential to substantially change the way in which breast cancer and pulmonary nodules are detected and managed. Commercial tomosynthesis devices are now available or on the horizon. Many of the remaining research activities with tomosynthesis will be translational in nature and will involve physicist and clinician alike. This overview article provides a forward-looking assessment of the translational questions facing tomosynthesis imaging and anticipates some of the likely research and clinical activities in the next five years.

Stochastic noise characteristics in matrix inversion tomosynthesis (MITS).

Matrix inversion tomosynthesis (MITS) uses known imaging geometry and linear systems theory to deterministically separate in-plane detail from residual tomographic blur in a set of conventional tomosynthesis ("shift-and-add") planes. A previous investigation explored the effect of scan angle (ANG), number of projections (N), and number of reconstructed planes (NP) on the MITS impulse response and modulation transfer function characteristics, and concluded that ANG = 20 degrees, N = 71, and NP = 69 is the optimal MITS imaging technique for chest imaging on our prototype tomosynthesis system. This article examines the effect of ANG, N, and NP on the MITS exposure-normalized noise power spectra (ENNPS) and seeks to confirm that the imaging parameters selected previously by an analysis of the MITS impulse response also yield reasonable stochastic properties in MITS reconstructed planes. ENNPS curves were generated for experimentally acquired mean-subtracted projection images, conventional tomosynthesis planes, and MITS planes with varying combinations of the parameters ANG, N, and NP. Image data were collected using a prototype tomosynthesis system, with 11.4 cm acrylic placed near the image receptor to produce lung-equivalent beam hardening and scattered radiation. Ten identically acquired tomosynthesis data sets (realizations) were collected for each selected technique and used to generate ensemble mean images that were subtracted from individual image realizations prior to noise power spectra (NPS) estimation. NPS curves were normalized to account for differences in entrance exposure (as measured with an ion chamber), yielding estimates of the ENNPS for each technique. Results suggest that mid- and high-frequency noise in MITS planes is fairly equivalent in magnitude to noise in conventional tomosynthesis planes, but low-frequency noise is amplified in the most anterior and posterior reconstruction planes. Selecting the largest available number of projections (N = 71) does not incur any appreciable additive electronic noise penalty compared to using fewer projections for roughly equivalent cumulative exposure. Stochastic noise is minimized by maximizing N and NP but increases with increasing ANG. The noise trend results for NP and ANG are contrary to what would be predicted by simply considering the MITS matrix conditioning and likely result from the interplay between noise correlation and the polarity of the MITS filters. From this study, the authors conclude that the previously determined optimal MITS imaging strategy based on impulse response considerations produces somewhat suboptimal stochastic noise characteristics, but is probably still the best technique for MITS imaging of the chest.

Methodology for generating a 3D computerized breast phantom from empirical data.

The initial process for creating a flexible three-dimensional computer-generated breast phantom based on empirical data is described. Dedicated breast computed-tomography data were processed to suppress noise and scatter artifacts in the reconstructed image set. An automated algorithm was developed to classify the breast into its primary components. A preliminary phantom defined using subdivision surfaces was generated from the segmented data. To demonstrate potential applications of the phantom, simulated mammographic image data were acquired of the phantom using a simplistic compression model and an analytic projection algorithm directly on the surface model. The simulated image was generated using a model for a polyenergetic cone-beam projection of the compressed phantom. The methods used to create the breast phantom generate resulting images that have a high level of tissue structure detail available and appear similar to actual mammograms. Fractal dimension measurements of simulated images of the phantom are comparatively similar to measurements from images of real human subjects. A realistic and geometrically defined breast phantom that can accurately simulate imaging data may have many applications in breast imaging research.

Effective DQE (eDQE) and speed of digital radiographic systems: an experimental methodology.

Prior studies on performance evaluation of digital radiographic systems have primarily focused on the assessment of the detector performance alone. However, the clinical performance of such systems is also substantially impacted by magnification, focal spot blur, the presence of scattered radiation, and the presence of an antiscatter grid. The purpose of this study is to evaluate an experimental methodology to assess the performance of a digital radiographic system, including those attributes, and to propose a new metric, effective detective quantum efficiency (eDQE), a candidate for defining the efficiency or speed of digital radiographic imaging systems. The study employed a geometric phantom simulating the attenuation and scatter properties of the adult human thorax and a representative indirect flat-panel-based clinical digital radiographic imaging system. The noise power spectrum (NPS) was derived from images of the phantom acquired at three exposure levels spanning the operating range of the clinical system. The modulation transfer function (MTF) was measured using an edge device positioned at the surface of the phantom, facing the x-ray source. Scatter measurements were made using a beam stop technique. The eDQE was then computed from these measurements, along with measures of phantom attenuation and x-ray flux. The MTF results showed notable impact from the focal spot blur, while the NPS depicted a large component of structured noise resulting from use of an antiscatter grid. The eDQE was found to be an order of magnitude lower than the conventional DQE. At 120 kVp, eDQE(0) was in the 8%-9% range, fivefold lower than DQE(0) at the same technique. The eDQE method yielded reproducible estimates of the system performance in a clinically relevant context by quantifying the inherent speed of the system, that is, the actual signal to noise ratio that would be measured under clinical operating conditions.

Detector or system? Extending the concept of detective quantum efficiency to characterize the performance of digital radiographic imaging systems.

PURPOSE: To develop an experimental method for measuring the effective detective quantum efficiency (eDQE) of digital radiographic imaging systems and evaluate its use in select imaging systems. MATERIALS AND METHODS: A geometric phantom emulating the attenuation and scatter properties of the adult human thorax was employed to assess eight imaging systems in a total of nine configurations. The noise power spectrum (NPS) was derived from images of the phantom acquired at three exposure levels spanning the operating range of the system. The modulation transfer function (MTF) was measured by using an edge device positioned at the anterior surface of the phantom. Scatter measurements were made by using a beam-stop technique. All measurements, including those of phantom attenuation and estimates of x-ray flux, were used to compute the eDQE. RESULTS: The MTF results showed notable degradation owing to focal spot blur. Scatter fractions ranged between 11% and 56%, depending on the system. The eDQE(0) results ranged from 1%-17%, indicating a reduction of up to one order of magnitude and different rank ordering and performance among systems, compared with that implied in reported conventional detective quantum efficiency results from the same systems. CONCLUSION: The eDQE method was easy to implement, yielded reproducible results, and provided a meaningful reflection of system performance by quantifying image quality in a clinically relevant context. The difference in the magnitude of the measured eDQE and the ideal eDQE of 100% provides a great opportunity for improving the image quality of radiographic and mammographic systems while reducing patient dose.

Digital tomosynthesis of the chest.

Digital tomosynthesis is a technique that generates an arbitrary number of section images of a patient from a single pass of the x-ray tube. It is under investigation for application to a number of clinical detection tasks, and has recently been implemented in commercial devices for chest radiography. Tomosynthesis provides improved visibility of structures in the chest, such as pulmonary nodules, airways, and spine. This review article outlines the components of a typical tomosynthesis system, and presents examples of improved pulmonary nodule detection from a clinical trial in human subjects. Possible implementation strategies for use in chest imaging are discussed.

Importance of point-by-point back projection correction for isocentric motion in digital breast tomosynthesis: relevance to morphology of structures such as microcalcifications.

Digital breast tomosynthesis is a three-dimensional imaging technique that provides an arbitrary set of reconstruction planes in the breast from a limited-angle series of projection images acquired while the x-ray tube moves. Traditional shift-and-add (SAA) tomosynthesis reconstruction is a common mathematical method to line up each projection image based on its shifting amount to generate reconstruction slices. With parallel-path geometry of tube motion, the path of the tube lies in a plane parallel to the plane of the detector. The traditional SAA algorithm gives shift amounts for each projection image calculated only along the direction of x-ray tube movement. However, with the partial isocentric motion of the x-ray tube in breast tomosynthesis, small objects such as microcalcifications appear blurred (for instance, about 1-4 pixels in blur for a microcalcification in a human breast) in traditional SAA images in the direction perpendicular to the direction of tube motion. Some digital breast tomosynthesis algorithms reported in the literature utilize a traditional one-dimensional SAA method that is not wholly suitable for isocentric motion. In this paper, a point-by-point back projection (BP) method is described and compared with traditional SAA for the important clinical task of evaluating morphology of small objects such as microcalcifications. Impulse responses at different three-dimensional locations with five different combinations of imaging acquisition parameters were investigated. Reconstruction images of microcalcifications in a human subject were also evaluated. Results showed that with traditional SAA and 45 degrees view angle of tube movement with respect to the detector, at the same height above the detector, the in-plane blur artifacts were obvious for objects farther away from x-ray source. In a human subject, the appearance of calcifications was blurred in the direction orthogonal to the tube motion with traditional SAA. With point-by-point BP, the appearance of calcifications was sharper. The point-by-point BP method demonstrated improved rendition of microcalcifications in the direction perpendicular to the tube motion direction. With wide angles or for imaging of larger breasts, this point-by-point BP rather than the traditional SAA should also be considered as the basis of further deblurring algorithms that work in conjunction with the BP method.

Multiprojection correlation imaging for improved detection of pulmonary nodules.

OBJECTIVE: The purpose of this study was the development and preliminary evaluation of multiprojection correlation imaging with 3D computer-aided detection (CAD) on chest radiographs for cost- and dose-effective improvement of early detection of pulmonary nodules. SUBJECTS AND METHODS: Digital chest radiographs of 10 configurations of a chest phantom and of seven human subjects were acquired in multiple angular projections with an acquisition time of 11 seconds (single breath-hold) and total exposure comparable with that of a posteroanterior chest radiograph. An initial 2D CAD algorithm with two difference-of-gaussians filters and multilevel thresholds was developed with an independent database of 44 single-view chest radiographs with confirmed lesions. This 2D CAD algorithm was used on each projection image to find likely suspect nodules. The CAD outputs were reconstructed in 3D, reinforcing signals associated with true nodules while simultaneously decreasing false-positive findings produced by overlapping anatomic features. The performance of correlation imaging was tested on two to 15 projection images. RESULTS: Optimum performance of correlation imaging was attained when nine projection images were used. Compared with conventional, single-view CAD, correlation imaging decreased as much as 79% the frequency of false-positive findings in phantom cases at a sensitivity level of 65%. The corresponding reduction in false-positive findings in the cases of human subjects was 78%. CONCLUSION: Although limited by a relatively simple CAD implementation and a small number of cases, the findings suggest that correlation imaging performs substantially better than single-view CAD and may greatly enhance identification of subtle solitary pulmonary nodules on chest radiographs.

Optimization of the matrix inversion tomosynthesis (MITS) impulse response and modulation transfer function characteristics for chest imaging.

Matrix inversion tomosynthesis (MITS) uses linear systems theory, along with a priori knowledge of the imaging geometry, to deterministically distinguish between true structure and overlying tomographic blur in a set of conventional tomosynthesis planes. In this paper we examine the effect of total scan angle (ANG), number of input projections (N), and plane separation/number of reconstructed planes (NP) on the MITS impulse response (IR) and modulation transfer function (MTF), with the purpose of optimizing MITS imaging of the chest. MITS IR and MTF data were generated by simulating the imaging of a very thin wire, using various combinations of ANG, N, and NP. Actual tomosynthesis data of an anthropomorphic chest phantom were acquired with a prototype experimental system, using the same imaging parameter combinations as those in the simulations. Thoracic projection data from two human subjects were collected for corroboration of the system response analysis in vivo. Results suggest that ANG=20 degrees, N=71, NP=69 is the optimal combination for MITS chest imaging given the inherent constraints of our prototype system. MITS chest data from human subjects demonstrates that the selected imaging strategy can effectively produce high-quality MITS thoracic images in vivo.

Intercomparison of methods for image quality characterization. I. Modulation transfer function.

The modulation transfer function (MTF) and the noise power spectrum (NPS) are widely recognized as the most relevant metrics of resolution and noise performance in radiographic imaging. These quantities have commonly been measured using various techniques, the specifics of which can have a bearing on the accuracy of the results. As a part of a study aimed at comparing the relative performance of different techniques, in this paper we report on a comparison of two established MTF measurement techniques: one using a slit test device [Dobbins et al., Med. Phys. 22, 1581-1593 (1995)] and another using a translucent edge test device [Samei et al., Med. Phys. 25, 102-113 (1998)], with one another and with a third technique using an opaque edge test device recommended by a new international standard (IEC 62220-1, 2003). The study further aimed to substantiate the influence of various acquisition and processing parameters on the estimated MTF. The slit test device was made of 2 mm thick Pb slabs with a 12.5 microm opening. The translucent edge test device was made of a laminated and polished Pt(0.9)Ir(0.1). alloy foil of 0.1 mm thickness. The opaque edge test device was made of a 2 mm thick W slab. All test devices were imaged on a representative indirect flat-panel digital radiographic system using three published beam qualities: 70 kV with 0.5 mm Cu filtration, 70 kV with 19 mm Al filtration, and 74 kV with 21 mm Al filtration (IEC-RQA5). The latter technique was also evaluated in conjunction with two external beam-limiting apertures (per IEC 62220-1), and with the tube collimator limiting the beam to the same area achieved with the apertures. The presampled MTFs were deduced from the acquired images by Fourier analysis techniques, and the results analyzed for relative values and the influence of impacting parameters. The findings indicated that the measurement technique has a notable impact on the resulting MTF estimate, with estimates from the overall IEC method 4.0% +/- 0.2% lower than that of Dobbins et al. and 0.7% +/- 0.4% higher than that of Samei et al. averaged over the zero to cutoff frequency range. Over the same frequency range, keeping beam quality and limitation constant, the average MTF estimate obtained with the edge techniques differed by up to 5.2% +/- 0.2% from that of the slit, with the opaque edge providing lower MTF estimates at lower frequencies than those obtained with the translucent edge or slit. The beam quality impacted the average estimated MTF by as much as 3.7% +/- 0.9% while the use of beam limiting devices alone increased the average estimated MTF by as much as 7.0% +/- 0.9%. While the slit method is inherently very sensitive to misalignment, both edge techniques were found to tolerate misalignments by as much as 6 cm. The results suggest the use of the opaque edge test device and the tube internal collimator for beam limitation in order to achieve an MTF result most reflective of the overall performance of the imaging system and least susceptible to misalignment and scattered radiation. Careful attention to influencing factors is warranted to achieve accurate results.

Intercomparison of methods for image quality characterization. II. Noise power spectrum.

Second in a two-part series comparing measurement techniques for the assessment of basic image quality metrics in digital radiography, in this paper we focus on the measurement of the image noise power spectrum (NPS). Three methods were considered: (1) a method published by Dobbins et al. [Med. Phys. 22, 1581-1593 (1995)], (2) a method published by Samei et al. [Med. Phys. 30, 608-622 (2003)], and (3) a new method sanctioned by the International Electrotechnical Commission (IEC 62220-1, 2003), developed as part of an international standard for the measurement of detective quantum efficiency. In addition to an overall comparison of the estimated NPS between the three techniques, the following factors were also evaluated for their effect on the measured NPS: horizontal versus vertical directional dependence, the use of beam-limiting apertures, beam spectrum, and computational methods of NPS analysis, including the region-of-interest (ROI) size and the method of ROI normalization. Of these factors, none was found to demonstrate a substantial impact on the amplitude of the NPS estimates (< or = 3.1% relative difference in NPS averaged over frequency, for each factor considered separately). Overall, the three methods agreed to within 1.6% +/- 0.8% when averaged over frequencies > 0.15 mm(-1).

Population of 224 realistic human subject-based computational breast phantoms.

PURPOSE: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. METHODS: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. RESULTS: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. CONCLUSIONS: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.