James T. Dobbins

Digital x-ray tomosynthesis: current state of the art and clinical potential.

Digital x-ray tomosynthesis is a technique for producing slice images using conventional x-ray systems. It is a refinement of conventional geometric tomography, which has been known since the 1930s. In conventional geometric tomography, the x-ray tube and image receptor move in synchrony on opposite sides of the patient to produce a plane of structures in sharp focus at the plane containing the fulcrum of the motion; all other structures above and below the fulcrum plane are blurred and thus less visible in the resulting image. Tomosynthesis improves upon conventional geometric tomography in that it allows an arbitrary number of in-focus planes to be generated retrospectively from a sequence of projection radiographs that are acquired during a single motion of the x-ray tube. By shifting and adding these projection radiographs, specific planes may be reconstructed. This topical review describes the various reconstruction algorithms used to produce tomosynthesis images, as well as approaches used to minimize the residual blur from out-of-plane structures. Historical background and mathematical details are given for the various approaches described. Approaches for optimizing the tomosynthesis image are given. Applications of tomosynthesis to various clinical tasks, including angiography, chest imaging, mammography, dental imaging and orthopaedic imaging, are also described.

DQE(f) of four generations of computed radiography acquisition devices.

Measurements were made of the MTF(f), NPS(f), and DQE(f) of four generations of computed radiography (CR) imaging plates and three generations of CR image readers. The MTF generally showed only a minor change between generations of plates and readers, but the DQE(f) has improved substantially from a very early plate/reader combination to a more recent one. The DQE in the more recent plate/reader combination is 1.3X greater at low frequencies and about 3X greater at high frequencies than the much earlier versions. Thus there has been substantial improvement in the imaging performance obtainable with CR since some of the early observer studies which indicated poorer performance with CR than with screen-film.

Effects of undersampling on the proper interpretation of modulation transfer function, noise power spectra, and noise equivalent quanta of digital imaging systems

The proper understanding of modulation transfer function (MTF), noise power spectra (NPS), and noise equivalent quanta (NEQ) in digital systems is significantly hampered when the systems are undersampled. Undersampling leads to three significant complications: (1) MTF and NPS do not behave as transfer amplitude and variance, respectively, of a single sinusoid, (2) the response of a digital system to a delta function is not spatially invariant and therefore does not fulfill certain technical requirements of classical analysis, and (3) NEQ loses its common meaning as maximum available SNR2 (signal-to-noise) at a particular frequency. These three complications cause the comparisons of MTF and NEQ between undersampled digital systems to depend on the frequency content of the images being evaluated. A tutorial of MTF, NPS, and NEQ concepts for digital systems is presented, along with a complete theoretical treatment of the above-mentioned complications from undersampling.

A rapid and automatic image registration algorithm with subpixel accuracy

A number of digital imaging techniques in medicine require the combination of multiple images. Using these techniques, it is essential that the images be adequately aligned and registered prior to addition, subtraction, or any other combination of the images. This paper describes an alignment routine developed to register an image of a fixed object containing a global offset error, rotation error, and magnification error relative to a second image. The described routine uses sparsely sampled regional correlation in a novel way to reduce computation time and avoid the use of markers and human interaction. The result is a fast, robust, and automatic alignment algorithm, with accuracy better than about 0.2 pixel in a test with clinical computed radiography images.

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).

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.

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.

Chest tomosynthesis: Technical principles and clinical update

Digital tomosynthesis is a radiographic technique that can produce an arbitrary number of section images of a patient from a single pass of the X-ray tube. It utilizes a conventional X-ray tube, a flat-panel detector, a computer-controlled tube mover, and special reconstruction algorithms to produce section images. While it does not have the depth resolution of computed tomography (CT), tomosynthesis provides some of the tomographic benefits of CT but at lower cost and radiation dose than CT. Compared to conventional chest radiography, chest tomosynthesis results in improved visibility of normal structures such as vessels, airway and spine. By reducing visual clutter from overlying normal anatomy, it also enhances detection of small lung nodules. This review article outlines the components of a tomosynthesis system, discusses results regarding improved lung nodule detection from the recent literature, and presents examples of nodule detection from a clinical trial in human subjects. Possible implementation strategies for use in clinical chest imaging are discussed.

Digital tomosynthesis of the chest for lung nodule detection: Interim sensitivity results from an ongoing NIH‐sponsored trial

The authors report interim clinical results from an ongoing NIH-sponsored trial to evaluate digital chest tomosynthesis for improving detectability of small lung nodules. Twenty-one patients undergoing computed tomography (CT) to follow up lung nodules were consented and enrolled to receive an additional digital PA chest radiograph and digital tomosynthesis exam. Tomosynthesis was performed with a commercial CsI/a-Si flat-panel detector and a custom-built tube mover. Seventy-one images were acquired in 11 s, reconstructed with the matrix inversion tomosynthesis algorithm at 5-mm plane spacing, and then averaged (seven planes) to reduce noise and low-contrast artifacts. Total exposure for tomosynthesis imaging was equivalent to that of 11 digital PA radiographs (comparable to a typical screen-film lateral radiograph or two digital lateral radiographs). CT scans (1.25-mm section thickness) were reviewed to confirm presence and location of nodules. Three chest radiologists independently reviewed tomosynthesis images and PA chest radiographs to confirm visualization of nodules identified by CT. Nodules were scored as: definitely visible, uncertain, or not visible. 175 nodules (diameter range 3.5-25.5 mm) were seen by CT and grouped according to size: < 5, 5-10, and > 10 mm. When considering as true positives only nodules that were scored definitely visible, sensitivities for all nodules by tomosynthesis and PA radiography were 70% (+/- 5%) and 22% (+/- 4%), respectively, (p < 0.0001). Digital tomosynthesis showed significantly improved sensitivity of detection of known small lung nodules in all three size groups, when compared to PA chest radiography.

Quantitative evaluation of noise reduction strategies in dual-energy imaging.

In this paper we describe a quantitative evaluation of the performance of three dual-energy noise reduction algorithms: Kalenders correlated noise reduction (KCNR), noise clipping (NOC), and edge-predictive adaptive smoothing (EPAS). These algorithms were compared to a simple smoothing filter approach, using the variance and noise power spectrum measurements of the residual noise in dual-energy images acquired with an a-Si TFT flat-panel x-ray detector. An estimate of the true noise was made through a new method with subpixel accuracy by subtracting an individual image from an ensemble average image. The results indicate that in the lung regions of the tissue image, all three algorithms reduced the noise by similar percentages at high spatial frequencies (KCNR=88%, NOC=88%, EPAS=84%, NOC/KCNR=88%) and somewhat less at low spatial frequencies (KCNR=45%, NOC=54%, EPAS=52%, NOC/KCNR=55%). At low frequencies, the presence of edge artifacts from KCNR made the performance worse, thus NOC or NOC combined with KCNR performed best. At high frequencies, KCNR performed best in the bone image, yet NOC performed best in the tissue image. Noise reduction strategies in dual-energy imaging can be effective and should focus on blending various algorithms depending on anatomical locations.