Automated detection of mass lesions in dedicated breast CT: a preliminary study.

PURPOSE: To develop an automated method to detect breast masses on dedicated breast CT (BCT) volumes and to conduct a preliminary evaluation of its performance. This method can be used in a computer-aided detection (CADe) system for noncontrast enhanced BCT. METHODS: The database included patient images, which were acquired under an IRB-approved protocol. The database in this study consisted of 132 cases. 50 cases contained 58 malignant masses, and 23 cases contained 24 benign masses. 59 cases did not contain any biopsy-proven lesions. Each case consisted of an unenhanced CT volume of a single breast. First, each breast was segmented into adipose and glandular tissues using a fuzzy c-means clustering algorithm. The glandular breast regions were then sampled at a resolution of 2 mm. At each sampling step, a 3.5-cm(3) volume-of-interest was subjected to constrained region segmentation and 17 characteristic features were extracted, yielding 17 corresponding feature volumes. Four features were selected using step-wise feature selection and merged with linear discriminant analysis trained in the task of distinguishing between normal breast glandular regions and masses. Detection performance was measured using free-response receiver operating characteristic analysis (FROC) with leave-one-case-out evaluation. RESULTS: The feature selection stage selected features that characterized the shape and margin strength of the segmented region. CADe sensitivity per case was 84% (std = 4.2%) at 2.6 (std = 0.06) false positives per volume, or 6 × 10(-3) per slice (at an average of 424 slices per volume in this data set). CONCLUSIONS: This preliminary study demonstrates the feasibility of our approach for CADe for BCT.

Cone-beam CT dose and imaging performance evaluation with a modular, multipurpose phantom.

PURPOSE: A modular phantom for dosimetry and imaging performance evaluation in cone-beam computed tomography (CBCT) is reported, providing a tool for quantitative technical assessment that can be adapted to a broad variety of CBCT imaging configurations and clinical applications. METHODS: The phantom presents a set of modules that can be ordered in various configurations suitable to a particular CBCT system. Modules include slabs containing a uniform medium, low-contrast inserts, line-spread features, and disk features suitable to measurement of image uniformity, noise, noise-power spectrum (NPS), contrast, contrast-to-noise ratio (CNR), Hounsfield (HU) accuracy, linearity, spatial resolution modulation transfer function (MTF), and magnitude of cone-beam artifact. Automated software recognizes the phantom configuration in DICOM images and provides structured reporting of such test measures. In any modular configuration, the phantom permits measurement of air kerma in central and peripheral locations with an air ionization chamber (e.g., Farmer chamber). The utility and adaptability of the phantom were demonstrated across a spectrum of CBCT systems, including scanners for orthopaedic imaging (Carestream OnSight 3D, Rochester NY), breast imaging (Doheny prototype, UC Davis), image-guided surgery (IGS, Medtronic O-arm, Littleton MA), angiography (Siemens Artis Zeego, Forcheim Germany), and image-guided radiation therapy (IGRT, Elekta Synergy XVI, Stockholm Sweden). RESULTS: The phantom provided a consistent platform for quantitative assessment of dose and imaging performance compatible with a broad spectrum of CBCT systems. The purpose of the survey was not to obtain head-to-head performance comparison of systems designed for such distinct clinical applications. Rather, the survey demonstrated the suitability of the phantom to a broad spectrum of systems in a manner that provides characterization pertinent to disparate applications and imaging tasks. For example: the orthopaedic CBCT system (pertinent clinical tasks relating to high-resolution bone imaging) was shown to achieve MTF consistent with imaging of high-contrast trabecular bone structures (i.e., the MTF reduced to 10% at spatial frequency, f 10  = 1.2 mm-1 ); the breast system (even higher-resolution imaging of microcalcifications) exhibited f 10  = 2.2 mm-1 ; the IGS system (tasks including both bone and soft-tissue contrast resolution) provided f 10  = 0.9 mm-1 and soft-tissue CNR  = 1.64; the angiography system (soft-tissue body interventions) demonstrated CNR  = 1.2 in soft tissues approximating liver lesions; and the IGRT system (pertinent tasks emphasizing HU linearity and image uniformity) showed linear response with HU values ( R 2  = 1), with a cupping artifact ( t cup  = 5.8%) due to x-ray scatter. CONCLUSIONS: The phantom provides an adaptable, quantitative basis for CBCT dosimetry and imaging performance evaluation suitable to a broad variety of CBCT systems. The dosimetry and image quality metrics are consistent with up-to-date methods for rigorous, quantitative, physics testing and should be suitable to emerging standards for CBCT quality assurance.

GEANT4 Monte Carlo simulations for virtual clinical trials in breast X-ray imaging: Proof of concept.

Virtual clinical trials (VCT) are in-silico reproductions of medical examinations, which adopt digital models of patients and simulated devices. They are intended to produce clinically equivalent outcome data avoiding long execution times, ethical issues related to radiation induced risks and huge costs related to real clinical trials with a patient population. In this work, we present a platform for VCT in 2D and 3D X-ray breast imaging. The VCT platform uses Monte Carlo simulations based on the Geant4 toolkit and patient breast models derived from a cohort of high resolution dedicated breast CT (BCT) volume data sets. Projection images of the breast and three-dimensional glandular dose maps are generated for a given breast model, by simulating both 2D full-field digital mammography (DM) and 3D BCT examinations. Uncompressed voxelized breast models were derived from segmented patient images. Compressed versions of the digital breast phantoms for DM were generated using a previously published digital compression algorithm. The Monte Carlo simulation framework has the capability of generating and tracking ~105 photons/s using a server equipped with 16-cores and 3.0 GHz clock speed. The VCT platform will provide a framework for scanner design optimization, comparison between different scanner designs and between different modalities or protocols on computational breast models, without the need for scanning actual patients as in conventional clinical trials.

The myth of the 50-50 breast.

PURPOSE: For dosimetry and for work in optimization of x-ray imaging of the breast, it is commonly assumed that the breast is composed of 50% fibroglandular tissue and 50% fat. The purpose of this study was to assess whether this assumption was realistic. METHODS: First, data obtained from an experimental breast CT scanner were used to validate an algorithm that measures breast density from digitized film mammograms. Density results obtained from a total of 2831 women, including 191 women receiving CT and from mammograms of 2640 women from three other groups, were then used to estimate breast compositions. RESULTS: Mean compositions, expressed as percent fibroglandular tissue (including the skin), varied from 13.7% to 25.6% among the groups with an overall mean of 19.3%. The mean compressed breast thickness for the mammograms was 5.9 cm (sigma = 1.6 cm). 80% of the women in our study had volumetric breast density less than 27% and 95% were below 45%. CONCLUSIONS: Based on the results obtained from the four groups of women in our study, the "50-50" breast is not a representative model of the breast composition.

A microPET/CT system for in vivo small animal imaging.

A microCT scanner was designed, fabricated and integrated with a previously reported microPET II scanner (Tai et al 2003 Phys. Med. Biol. 48 1519, Yang et al 2004 Phys. Med. Biol. 49 2527), forming a dual modality system for in vivo anatomic and molecular imaging of the mouse. The system was designed to achieve high-spatial-resolution and high-sensitivity PET images with adequate CT image quality for anatomic localization and attenuation correction with low x-ray dose. The system also has relatively high throughput for screening, and a flexible gantry and user interface. X-rays were produced by a 50 kVp, 1.5 mA fixed tungsten anode tube, with a focal spot size of 70 microm. The detector was a 5 x 5 cm(2) photodiode detector incorporating 48 microm pixels on a CMOS array and a fast gadolinium oxysulfide (GOS) intensifying screen. The microCT system has a flexible C-arm gantry design with adjustable detector positioning, which acquires CT projection images around the common microPET/CT bed. The design and the initial characterization of the microCT system is described, and images of the first mouse scans with microPET/CT scanning protocols are shown.

Evaluation of the BreastSimulator software platform for breast tomography.

The aim of this work was the evaluation of the software BreastSimulator, a breast x-ray imaging simulation software, as a tool for the creation of 3D uncompressed breast digital models and for the simulation and the optimization of computed tomography (CT) scanners dedicated to the breast. Eight 3D digital breast phantoms were created with glandular fractions in the range 10%-35%. The models are characterised by different sizes and modelled realistic anatomical features. X-ray CT projections were simulated for a dedicated cone-beam CT scanner and reconstructed with the FDK algorithm. X-ray projection images were simulated for 5 mono-energetic (27, 32, 35, 43 and 51 keV) and 3 poly-energetic x-ray spectra typically employed in current CT scanners dedicated to the breast (49, 60, or 80 kVp). Clinical CT images acquired from two different clinical breast CT scanners were used for comparison purposes. The quantitative evaluation included calculation of the power-law exponent, ß, from simulated and real breast tomograms, based on the power spectrum fitted with a function of the spatial frequency, f, of the form S(f) = α/f ß . The breast models were validated by comparison against clinical breast CT and published data. We found that the calculated ß coefficients were close to that of clinical CT data from a dedicated breast CT scanner and reported data in the literature. In evaluating the software package BreastSimulator to generate breast models suitable for use with breast CT imaging, we found that the breast phantoms produced with the software tool can reproduce the anatomical structure of real breasts, as evaluated by calculating the ß exponent from the power spectral analysis of simulated images. As such, this research tool might contribute considerably to the further development, testing and optimisation of breast CT imaging techniques.

Spectrum of bone marrow morphologic findings in hepatitis C patients with and without prior liver transplantation.

INTRODUCTION: Cytopenia is a common hematologic finding in patients with HCV infection. Only a few studies have addressed bone marrow (BM) morphologic findings in these patients. No systemic study has been performed in these patients with liver transplantation (LT). METHODS: We retrospectively examined BMs in 49 hepatitis C patients with and without prior LT (n = 19 and n = 30). RESULTS: Among the patients with an available complete blood count (n = 46), the majority of them presented with cytopenia involving one or multiple cell lineages including unicytopenia (13%, n = 6), bicytopenia (31%, n = 14), and pancytopenia (43%, n = 20). Examination of the BM revealed a wide spectrum of morphologic findings ranging from benign reactive processes to overt malignant processes which included myeloid, lymphoid, and plasma cell neoplasms. The severity of cytopenia was not correlated with cirrhosis or antiviral therapy. However, the severity of cytopenia was partly correlated with splenomegaly or LT (P < 0.05). CONCLUSIONS: Cytopenia is a common finding in hepatitis C patients. Hypersplenism or LT has an adverse impact on some blood cell counts. Lastly, hepatitis C patients present with a wide spectrum of BM findings including malignant neoplasms, which indicates a diagnostic value of BM examination in these patients.

Radiological Protection in Cone Beam Computed Tomography (CBCT). ICRP Publication 129.

The objective of this publication is to provide guidance on radiological protection in the new technology of cone beam computed tomography (CBCT). Publications 87 and 102 dealt with patient dose management in computed tomography (CT) and multi-detector CT. The new applications of CBCT and the associated radiological protection issues are substantially different from those of conventional CT. The perception that CBCT involves lower doses was only true in initial applications. CBCT is now used widely by specialists who have little or no training in radiological protection. This publication provides recommendations on radiation dose management directed at different stakeholders, and covers principles of radiological protection, training, and quality assurance aspects. Advice on appropriate use of CBCT needs to be made widely available. Advice on optimisation of protection when using CBCT equipment needs to be strengthened, particularly with respect to the use of newer features of the equipment. Manufacturers should standardise radiation dose displays on CBCT equipment to assist users in optimisation of protection and comparisons of performance. Additional challenges to radiological protection are introduced when CBCT-capable equipment is used for both fluoroscopy and tomography during the same procedure. Standardised methods need to be established for tracking and reporting of patient radiation doses from these procedures. The recommendations provided in this publication may evolve in the future as CBCT equipment and applications evolve. As with previous ICRP publications, the Commission hopes that imaging professionals, medical physicists, and manufacturers will use the guidelines and recommendations provided in this publication for implementation of the Commission's principle of optimisation of protection of patients and medical workers, with the objective of keeping exposures as low as reasonably achievable, taking into account economic and societal factors, and consistent with achieving the necessary medical outcomes.

Simulated lesion, human observer performance comparison between thin-section dedicated breast CT images versus computed thick-section simulated projection images of the breast.

The objective of this study was to compare the lesion detection performance of human observers between thin-section computed tomography images of the breast, with thick-section (>40 mm) simulated projection images of the breast. Three radiologists and six physicists each executed a two alterative force choice (2AFC) study involving simulated spherical lesions placed mathematically into breast images produced on a prototype dedicated breast CT scanner. The breast image data sets from 88 patients were used to create 352 pairs of image data. Spherical lesions with diameters of 1, 2, 3, 5, and 11 mm were simulated and adaptively positioned into 3D breast CT image data sets; the native thin section (0.33 mm) images were averaged to produce images with different slice thicknesses; average section thicknesses of 0.33, 0.71, 1.5 and 2.9 mm were representative of breast CT; the average 43 mm slice thickness served to simulate simulated projection images of the breast.The percent correct of the human observer's responses were evaluated in the 2AFC experiments. Radiologists lesion detection performance was significantly (p < 0.05) better in the case of thin-section images, compared to thick section images similar to mammography, for all but the 1 mm lesion diameter lesions. For example, the average of three radiologist's performance for 3 mm diameter lesions was 92% correct for thin section breast CT images while it was 67% for the simulated projection images. A gradual reduction in observer performance was observed as the section thickness increased beyond about 1 mm. While a performance difference based on breast density was seen in both breast CT and the projection image results, the average radiologist performance using breast CT images in dense breasts outperformed the performance using simulated projection images in fatty breasts for all lesion diameters except 11 mm. The average radiologist performance outperformed that of the average physicist observer, however trends in performance were similar. Human observers demonstrate significantly better mass-lesion detection performance on thin-section CT images of the breast, compared to thick-section simulated projection images of the breast.

Color mammography. Image generation and receiver operating characteristic evaluation.

Color mammography is a technique whereby dual-energy mammographic image data are used to calculate a calcium image; the calcium image is colorized and overlaid onto the conventional (lower energy) gray scale mammogram for radiologist viewing. This technique is presented as a practical way to use the increased calcium sensitivity of dual-energy mammography without requiring an increase in the number of images that the radiologist must read, and without subjecting the radiologist to the unfamiliar appearance of the dual-energy subtracted images. Using straightforward imaging theory, the acquisition techniques for both conventional and dual-energy mammography were optimized, and the optimal technique factors were used to generate a series of computer-simulated mammographic images that were used in a receiver operating characteristic (ROC) comparative study. Ideal observer ROC experiments indicate that (dual-energy) calcium images yield consistently higher sensitivity and specificity to the presence of calcifications, regardless of the amount of tissue "clutter," whereas conventional mammography results show degraded detectability performance as tissue contrast increases. Using human observers viewing simulated images, color mammography delivered greater calcification detectability than conventional mammography.

Scattered energy deposition under shielding.

Monte Carlo methods are used to generate line spread functions describing dose distributions at a variety of depths within a homogeneous water phantom. The line spread function data are convolved with a step function that represents the edge of a primary radiation field. The dosimetric information beyond the edge of the field is reported in the form of tissue-air ratios for three different beam spectra in the diagnostic energy range.

A fluoroscopy-based computed tomography scanner for small specimen research.

RATIONALE AND OBJECTIVES: A small-laboratory computed tomography (CT) system using a fluoroscopic system and a personal computer was fabricated and tested. The motivation for building this specimen scanner was to provide medical researchers with the capability of using CT as a practical tool in their research, as well as to provide an opportunity for hands-on CT instruction. METHODS AND MATERIALS: The CT system was constructed using mostly off-the-shelf items; however, the CT stage itself was custom fabricated and software development was necessary. In addition, a personal computer and a standard fluoroscopy system were used. RESULTS: The spatial resolution was found to match the 228-microns sampling limitation, yielding approximately 2 line pairs per mm. Iodine contrast sensitivity studies showed that 1% solution of 370 mg/ml iodine solution was easily detected (P = .05). CONCLUSIONS: A small CT scanner for specimen research can be economically constructed, and is capable of good performance. The authors found substantial interest on the part of small animal researchers involved in a wide variety of medical research.

Neural networks in radiologic diagnosis. I. Introduction and illustration.

Artificial neural networks (NNs) process information in a manner similar to the way the human brain is thought to process information. Neural networks have potential application in radiology as an artificial intelligence technique that can provide computer-aided diagnostic assistance for the practicing radiologist. The basic characteristics of NNs and the manner in which information propagates through an NN are discussed in nontechnical language, to assist the diagnostic radiologist in understanding the basic principles of neurocomputing. Computer-aided diagnosis selection in pediatric chest radiography using NNs is discussed in a companion article.

Neural networks in radiologic diagnosis. II. Interpretation of neonatal chest radiographs.

A neural network (NN) system was trained to choose one or more diagnoses from a list of 12 possible diagnoses, based on 21 radiographic observations made on each of a series of neonatal chest radiographs. Initially, an experienced pediatric radiologist provided both the radiographic observations and ranked differential diagnoses for each of 77 neonatal chest radiographs in the preliminary phase used to train the NN. Subsequently, two pediatric radiologists (one of whom provided the initial training-phase data) independently read a series of 103 neonatal chest radiographs (different from the training set) and compiled a list of radiographic findings and differential diagnoses for each radiograph. The trained NN was then asked to provide a list of differential diagnoses for each case from the radiologists' lists of findings. Agreement between the network and each radiologist independently was greater than between the two radiologists. Both the positive and negative agreement between the network and either radiologist was greater than the inter-radiologist agreements for most of the diagnostic endpoints.

Scatter correction algorithm for digitally acquired radiographs: theory and results.

A scatter correction algorithm for digitally acquired radiographs (SCADAR) is presented. SCADAR requires the acquisition of two digital images, taken at different object-to-detector distances. These two images are digitally magnification compensated, and subtracted. The primary component in the resulting difference image delta is mathematically eliminated, and hence the delta image is used as a measure of the local contribution of scattered radiation. A gray scale transformation is used to transform the delta image to a scattered component image, which is then smoothed by Fourier filtering, using a matched filter to increase the signal-to-noise ratio. The smoothed scatter image is then subtracted from its corresponding original image, resulting in the corrected SCADAR image. Implementation of SCADAR can result in a large increase in image contrast, and a significant reduction in shading due to scattered radiation effects. The mathematical derivation of the algorithm is developed, and experimental verification is given for some of the principles used. Using experimental images acquired from scattering phantoms, the results of SCADAR on various image parameters such as contrast and detail signal-to-noise ratio are discussed.

Parametrized x-ray absorption in diagnostic radiology from Monte Carlo calculations: implications for x-ray detector design.

The integral dose to the patient and image signal to noise ratio (SNR) are inexorably coupled in x-ray-based diagnostic imaging. Advancements and optimal design of imaging devices need to consider the SNR as well as patient dose. The figure of merit, FOM = (SNR)2/(integral dose), is a useful parameter in optimizing detector designs because it is independent of input exposure, and therefore eliminates exposure as a design consideration. Although numerical calculation of the SNR is relatively straightforward in most cases, the integral dose calculation is made complex due to its scatter component's high dependency on both x-ray energy and patient thickness. Monte Carlo calculations over a range of monoenergetic x-ray energies were used to calculate total energy absorption, and the results are parametrized using polynomial expressions. The results are shown to be applicable to any arbitrary polyenergetic spectrum. An example using the above FOM is given to illustrate the utility of the parametrized results. The parametrized results may prove useful in the computer simulations of x-ray detector systems where the above FOM is utilized.

Equivalent spectra as a measure of beam quality.

The concept of the equivalent spectrum (Seq) is introduced, where Seq is defined as an idealized energy spectrum which results in identical attenuation properties as the actual spectrum of a given x-ray tube. Seq is described by two parameters, the equivalent aluminum filtration Aleq and the equivalent kilovoltage kVeq, which are evaluated iteratively using aluminum attenuation data. Published spectral data are used to demonstrate the merits of the equivalent spectrum technique, and experimental results are also presented. The technique is shown to be sensitive to changes in total filtration and, indirectly, to the waveform properties of the x-ray system. The use of the Seq may result in a better description of spectral properties for reporting purposes, and aid in standardizing radiographic techniques within an institution.

Determination of the presampled MTF in computed tomography.

A technique for measuring the presampled MTF in CT scanners is described. The technique uses a simple phantom consisting of approximately 0.050 mm aluminum foil sandwiched by flat plastic or tissue-equivalent slabs. The aluminum foil is slightly angled with respect to the reconstruction matrix, and CT images are acquired. The acquired CT image yields an angled slit image that can be used to synthesize the presampled line spread function (LSF). The presampled MTF is calculated from the presampled LSF. The technique is a direct extension of that proposed by Fujita et al. [IEEE Trans. Med. Imaging 11, 34-39 (1992)] for MTF calculation on digital radiography images. While the MTF in clinical CT scanners often reaches negligible amplitude below the Nyquist frequency, the technique is easy to implement, requires inexpensive materials, is robust to aliasing, and is more resilient to noise due to greater data averaging than conventional PSF-integration techniques. Use of the proposed technique is illustrated on a clinical multiple detector array scanner, and MTFs are shown for several common reconstruction kernels. It is likely that the proposed technique would be useful for all tomographic imaging systems, including single photon emission computed tomography, positron emission tomography, magnetic resonance imaging and ultrasound scanners.

X-ray spectral reconstruction from attenuation data using neural networks.

An artificial neural network using input data derived from attenuation measurements was trained to generate spectral profiles (relative number of photons versus energy). Once the relative spectral distribution is reconstructed, absolute spectra (number of photons per unit exposure spectral distribution is reconstructed, absolute spectra (number of photons per unit exposure versus energy) can be calculated. A neural network was trained on spectra generated mathematically using the Birch-Marshall model, combined with attenuation data, calculated from the spectra by numerical integration. Whereas attenuation data can be calculated in a straightforward manner from the x-ray spectra, the reverse is not true. Several neural networks were successfully taught to reconstruct the spectra, given the attenuation data. The networks were tested using kV/inherent filtration combinations that were not in the training set, and the performance of the reconstruction was excellent. Noise in the attenuation data was simulated to test the effects of noise propagation in the reconstruction. The effects of network architecture and data averaging on noise propagation were investigated. Experimentally determined spectral data complied by Fewell were also used to train a neural network, and the results of the reconstruction were also found to be excellent.

The three parameter equivalent spectra as an index of beam quality.

A parametric spectral model based on the work of Birch and Marshall is used to characterize the x-ray spectra of a specific x-ray system. Using least-squares comparison between measured and calculated attenuation data, an equivalent spectrum (EQSPEC) is iteratively found which very closely matches the measured attenuation characteristics of the x-ray system. The resulting parametric spectrum is a function of the anode angle (theta), equivalent kilovoltage (kVeq), and the equivalent aluminum filtration (Aleq), and these three parameters can serve as very concise yet very accurate indices of beam quality. The utility of the EQSPEC for characterization and reporting of x-ray spectra (and thus beam quality) may have numerous applications in diagnostic imaging procedures where spectral quality is an important consideration.