Biomedical subjects

Andrew D A Maidment

Publications and source records attributed to Andrew D A Maidment.

15 recordsLinked to original sources

PubMed2006

Mammogram registration: a phantom-based evaluation of compressed breast thickness variation effects.

The temporal comparison of mammograms is complex; a wide variety of factors can cause changes in image appearance. Mammogram registration is proposed as a method to reduce the effects of these changes and potentially to emphasize genuine alterations in breast tissue. Evaluation of such registration techniques is difficult since ground truth regarding breast deformations is not available in clinical mammograms. In this paper, we propose a systematic approach to evaluate sensitivity of registration methods to various types of changes in mammograms using synthetic breast images with known deformations. As a first step, images of the same simulated breasts with various amounts of simulated physical compression have been used to evaluate a previously described nonrigid mammogram registration technique. Registration performance is measured by calculating the average displacement error over a set of evaluation points identified in mammogram pairs. Applying appropriate thickness compensation and using a preferred order of the registered images, we obtained an average displacement error of 1.6 mm for mammograms with compression differences of 1-3 cm. The proposed methodology is applicable to analysis of other sources of mammogram differences and can be extended to the registration of multimodality breast data.

Algorithms↗

PubMed2006

Quality control for digital mammography in the ACRIN DMIST trial: part I.

The Digital Mammography Imaging Screening Trial, conducted by the American College of Radiology Imaging Network, is a clinical trial designed to compare the accuracy of full-field digital mammography (FFDM) versus screen-film mammography in a screening population. Five FFDM systems from four manufacturers (Fischer, Fuji, General Electric, and Lorad) were employed in the study at 35 clinical sites. A core physics team devised and implemented tests to evaluate these systems. A detailed description of physics and quality control tests is presented, including estimates of: mean glandular dose, modulation transfer function (MTF), 2D noise power spectra, and signal-to-noise ratio (SNR). The mean glandular doses for the standard breast ranged from 0.79 to 2.98 mGy, with 1.62 mGy being the average across all units and machine types. For the five systems evaluated, the MTF dropped to 50% at markedly different percentages (22% to 87%) of the Nyquist limit, indicating that factors other than detector element (del) size have an important effect on spatial resolution. Noise power spectra and SNR were measured; however, we found that it was difficult to standardize and compare these between units. For each machine type, the performance as measured by the tests was very consistent, and no predictive benefit was seen for many of the tests during the 2-year period of the trial. It was found that, after verification of proper operation during acceptance testing, if systems failed they generally did so suddenly rather than through gradual deterioration of performance. Because of the relatively short duration of this study further, investigation of the long-term failure characteristics of these systems is advisable.

Algorithms↗

PubMed2006

Quality control for digital mammography: part II. Recommendations from the ACRIN DMIST trial.

The Digital Mammography Imaging Screening Trial (DMIST), conducted under the auspices of the American College of Radiology Imaging Network (ACRIN), is a clinical trial designed to compare the accuracy of digital versus screen-film mammography in a screening population [E. Pisano et al., ACRIN 6652-Digital vs. Screen-Film Mammography, ACRIN (2001)]. Part I of this work described the Quality Control program developed to ensure consistency and optimal operation of the digital equipment. For many of the tests, there were no failures during the 24 months imaging was performed in DMIST. When systems failed, they generally did so suddenly rather than through gradual deterioration of performance. In this part, the utility and effectiveness of those tests are considered. This suggests that after verification of proper operation, routine extensive testing would be of minimal value. A recommended set of tests is presented including additional and improved tests, which we believe meet the intent and spirit of the Mammography Quality Standards Act regulations to ensure that full-field digital mammography systems are functioning correctly, and consistently producing mammograms of excellent image quality.

Breast↗

PubMed2005

Evaluation of a novel method of noise reduction using computer-simulated mammograms.

A novel method of noise reduction has been tested for mammography using computer-simulated images for which the truth is known exactly. This method is based on comparing two images. The images are compared at different scales, using a cross-correlation function as a measure of similarity to define the image modifications in the wavelet domain. The computer-simulated images were calculated for noise-free primary radiation using a quasi-realistic voxel phantom. Two images corresponding to slightly different geometry were produced. Gaussian noise was added with certain properties to simulate quantum noise. The added noise could be reduced by >70% using the proposed method without any noticeable corruption of the structures. It is possible to save 50% dose in mammography by producing two images (each 25% of the dose for a standard mammogram). Additionally, a reduction of the anatomical noise and, therefore, better detection rates of breast cancer in mammography are possible.

Artifacts↗

PubMed2005

Validation of MTF measurement for digital mammography quality control.

The modulation transfer function (MTF) describes the spatial resolution properties of imaging systems. In this work, the accuracy of our implementation of the edge method for calculating the presampled MTF was examined. Synthetic edge images with known MTF were used as gold standards for determining the robustness of the edge method. These images simulated realistic data from clinical digital mammography systems, and contained intrinsic system factors that could affect the MTF accuracy, such as noise, scatter, and flat-field nonuniformities. Our algorithm is not influenced by detector dose variations for MTF accuracy up to 1/2 the sampling frequency. We investigated several methods for noise reduction, including truncating the supersampled line spread function (LSF), windowing the LSF, applying a local exponential fit to the LSF, and applying a monotonic constraint to the supersampled edge spread function. Only the monotonic constraint did not introduce a systematic error; the other methods could result in MTF underestimation. Overall, our edge method consistently computed MTFs which were in good agreement with the true MTF. The edge method was then applied to images from a commercial storage-phosphor based digital mammography system. The calculated MTF was affected by the size (sides of 2.5, 5, or 10 cm) and the composition (lead or tungsten) of the edge device. However, the effects on the MTF were observed only with regard to the low frequency drop (LFD). Scatter nonuniformity was dependent on edge size, and could lead to slight underestimation of LFD. Nevertheless, this negative effect could be minimized by using an edge of 5 cm or larger. An edge composed of lead is susceptible to L-fluorescence, which causes overestimation of the LFD. The results of this work are intended to underline the need for clear guidelines if the MTF is to be given a more crucial role in acceptance tests and routine assessment of digital mammography systems: the MTF algorithm and edge object test tool need to be publicly validated.

Algorithms↗

PubMed2004

Cumulative radiation dose caused by radiologic studies in critically ill trauma patients.

BACKGROUND: Critically ill trauma patients undergo many radiologic studies, but the cumulative radiation dose is unknown. The purpose of this study was to estimate the cumulative effective dose (CED) of radiation resulting from radiologic studies in critically ill trauma patients. METHODS: The study group was composed of trauma patients at an urban Level I trauma center with surgical intensive care unit length of stay (LOS) greater than 30 days. The radiology records were reviewed. A typical effective dose per study for each type of plain film radiograph, computed tomographic scan, fluoroscopic study, and nuclear medicine study was used to calculate CED. RESULTS: Forty-six patients met criteria. The mean surgical intensive care unit and hospital LOS were 42.7 +/- 14.0 and 59.5 +/- 28.5 days, respectively. The mean Injury Severity Score was 32.2 +/- 15.0. The mean number of studies per patient was 70.1 +/- 29.0 plain film radiographs, 7.8 +/- 4.1 computed tomographic scans, 2.5 +/- 2.6 fluoroscopic studies, and 0.065 +/- 0.33 nuclear medicine study. The mean CED was 106 +/- 59 mSv per patient (range, 11-289 mSv; median, 104 mSv). Among age, mechanism, Injury Severity Score, and LOS, there was no statistically significant predictor of high CED. The mean CED in the study group was 30 times higher than the average yearly radiation dose from all sources for individuals in the United States. The theoretical additional morbidity attributable to radiologic studies was 0.78%. CONCLUSION: From a radiobiologic perspective, risk-to-benefit ratios of radiologic studies are favorable, given the importance of medical information obtained. Current practice patterns regarding use of radiologic studies appear to be acceptable.

Accidents, Traffic↗

PubMed2003

Ultraviolet protectants: causative agents for screen and image artifacts in radiography.

PURPOSE: To determine the specific causative agent(s) and mechanism of formation of opacity artifacts seen on some radiographs acquired at the authors' facility. MATERIALS AND METHODS: Various substances likely to come into contact with technologists' hands were tested. Initial test results showed that a hand lotion with sun protection produced artifacts similar to the ones seen clinically and left no visible evidence on the screen after cleaning. Further experimental findings showed that substances without sun protection did not produce the artifacts, while other products with sun protection did produce artifacts. The four most commonly used active ingredients (ultraviolet [UV] filters) in products with sun protection were tested to determine if they produced artifacts. The temporal dependence and penetration depth of the causative agent(s) were determined. A sample of screens commonly used in radiology departments was tested to determine if artifacts were produced. RESULTS: Each of the UV filters tested caused artifacts when added to a lotion that had no sun protection and did not produce artifacts by itself. The UV filters quickly penetrated the protective layer of the screens and therefore could not be removed with conventional cleaning methods. Artifacts appeared only when using screens with a primary emission in the UV portion of the spectrum. CONCLUSION: The UV filters in the products with sun protection absorb the UV light emitted by the screens and cause artifacts. Screens with UV emissions are susceptible to artifacts from the use of UV protectants.

Artifacts↗

PubMed2003

Classification of galactograms with ramification matrices: preliminary results.

RATIONALE AND OBJECTIVES: The poor specificity of galactography, the imaging modality generally indicated in cases of nipple discharge, has led to a large number of biopsies with negative results. A quantitative scheme for classifying galactographic findings might help reduce the number of such biopsies in the future. As a first step toward that goal, the authors have studied one quantitative method for describing the branching of ducts by using ramification matrices (R matrices), and the correlation of the values of the matrix elements with clinical findings. MATERIALS AND METHODS: The ductal trees were manually segmented for 25 galactographic views from 15 patients, and corresponding R matrices were calculated. Patients were divided into two groups: those with no reported galactographic findings (NF) and those with reported findings (RF) of ductal ectasia, cysts, or papilloma. In a leave-one-out fashion, the authors evaluated a classification scheme that was based on R-matrix coefficients and used a Bayesian decision rule. The effects of segmentation were tested by successively removing each of the terminal ducts and computing the corresponding matrices of the pruned trees. RESULTS: With use of a single R-matrix element, 92% and 62% of NF and RF cases were correctly classified, respectively (P = .007). With use of two elements, 83% and 77% of NF and RF cases were correctly classified, but this result was not statistically significant (P = .108). In a test of robustness, an analysis of pruned trees yielded an average root-mean-square fractional difference of 9.7% between the elements of the original and the R matrix averaged over all pruned trees. CONCLUSION: The preliminary analysis indicates that it may be possible to identify cases with reported galactographic findings by using R matrices.

Adult↗

PubMed2003

Conditioning data for calculation of the modulation transfer function.

A method for conditioning data used in the measurement of the modulation transfer function (MTF) is discussed. This method is based upon imposing the constraint that the edge spread function (ESF) is monotonic. The advantages of this technique, when applicable, are demonstrated with simulated examples for which the true MTF is known. The application of this technique in the measurement of the MTF of a digital detector in clinical use is also demonstrated.

Algorithms↗

PubMed2003

Mammogram synthesis using a three-dimensional simulation. III. Modeling and evaluation of the breast ductal network.

A method is proposed for realistic simulation of the breast ductal network as part of a computer three-dimensional (3-D) breast phantom. The ductal network is simulated using tree models. Synthetic trees are generated based upon a description of ductal branching by ramification matrices (R matrices), whose elements represent the probabilities of branching at various levels of a tree. We simulated the ductal network of the breast, consisting of multiple lobes, by random binary trees (RBT). Each lobe extends from the ampulla and consists of branching ductal segments of decreasing size, and the associated terminal ductal-lobular units. The lobes follow curved paths that project from the nipple toward the chest wall. We have evaluated the RBT model by comparing manually-traced ductal networks from 25 projections of ductal lobes in clinical galactograms and manually-traced networks from 23 projections of synthetic RBTs. A root-mean-square (rms) fractional error of 41%, between the R-matrix elements corresponding to clinical and synthetic images, was computed. This difference was influenced by projection and segmentation artifacts and by the limited number of available images. In addition, we analyzed 23 synthetic trees generated using R matrices computed from clinical images. A comparison of these synthetic and clinical images yielded a rms fractional error of 11%, suggesting the possibility that a more appropriate model of the ductal branching morphology may be developed. Rejection of the RBT model also suggests the existence of a relationship between ductal branching morphology and the state of mammary developmentand pathology.

Algorithms↗

PubMed2003

Effects of quantum noise and binocular summation on dose requirements in stereoradiography.

In the case of a quantum-noise limited detector, signal detection theory suggests that stereoradiographic images can be acquired with one half of the per-image dose needed for a standard radiographic projection, as information from the two stereo images can be combined. Previously, film-screen stereoradiography has been performed using the same per-image dose as in projection radiography, i.e., doubling the total dose. In this paper, the assumption of a possible decrease in dose for stereoradiography was tested by a series of contrast-detail experiments, using phantom images acquired over a range of exposures. The number of visible details, the effective reduction of the dose, and the effective decrease in the threshold signal-to-noise ratio were determined using human observers under several display and viewing conditions. These results were averaged over five observers and compared with multiple readings by a single observer and with the results of an additional observer with limited stereoscopic acuity. Experimental results show that the total dose needed to produce a stereoradiographic image pair is approximately 1.1 times the dose needed for a single projection in standard radiography, indicating that under these conditions the human visual system demonstrates almost ideal binocular summation.

Depth Perception↗

PubMed2003

Diagnostic accuracy of digital mammography in patients with dense breasts who underwent problem-solving mammography: effects of image processing and lesion type.

PURPOSE: To determine effects of lesion type (calcification vs mass) and image processing on radiologist's performance for area under the receiver operating characteristic curve (AUC), sensitivity, and specificity for detection of masses and calcifications with digital mammography in women with mammographically dense breasts. MATERIALS AND METHODS: This study included 201 women who underwent digital mammography at seven U.S. and Canadian medical centers. Three image-processing algorithms were applied to the digital images, which were acquired with Fischer, General Electric, and Lorad digital mammography units. Eighteen readers participated in the reader study (six readers per algorithm). Baseline values for reader performance with screen-film mammograms were obtained through the additional interpretation of 179 screen-film mammograms. A repeated-measures analysis of covariance allowing unequal slopes was used in each of the nine analyses (AUC, sensitivity, and specificity for each of three machines). Bonferroni correction was used. RESULTS: Although lesion type did not affect the AUC or sensitivity for Fischer digital images, it did affect specificity (P =.0004). For the General Electric digital images, AUC, sensitivity, and specificity were not affected by lesion type. For Lorad digital images, the results strongly suggested that lesion type affected AUC and sensitivity (P <.0001). None of the three image-processing methods tested affected the AUC, sensitivity, or specificity for the Fischer, General Electric, or Lorad digital images. CONCLUSION: Findings in this study indicate that radiologist's interpretation accuracy in interpreting digital mammograms depends on lesion type. Interpretation accuracy was not influenced by the image-processing method.

Area Under Curve↗

PubMed2002

Aliasing effects in digital images of line-pair phantoms.

Line-pair phantoms are commonly used for evaluating screen-film systems. When imaged digitally, aliasing effects give rise to additional periodic patterns. This paper examines one such effect that medical physicists are likely to encounter, and which can be used as an indicator of super-resolution.

Artifacts↗

PubMed2002

Mammogram synthesis using a 3D simulation. I. Breast tissue model and image acquisition simulation.

A method is proposed for generating synthetic mammograms based upon simulations of breast tissue and the mammographic imaging process. A computer breast model has been designed with a realistic distribution of large and medium scale tissue structures. Parameters controlling the size and placement of simulated structures (adipose compartments and ducts) provide a method for consistently modeling images of the same simulated breast with modified position or acquisition parameters. The mammographic imaging process is simulated using a compression model and a model of the x-ray image acquisition process. The compression model estimates breast deformation using tissue elasticity parameters found in the literature and clinical force values. The synthetic mammograms were generated by a mammogram acquisition model using a monoenergetic parallel beam approximation applied to the synthetically compressed breast phantom.

Breast Neoplasms↗

PubMed2002

Mammogram synthesis using a 3D simulation. II. Evaluation of synthetic mammogram texture.

We have evaluated a method for synthesizing mammograms by comparing the texture of clinical and synthetic mammograms. The synthesis algorithm is based upon simulations of breast tissue and the mammographic imaging process. Mammogram texture was synthesized by projections of simulated adipose tissue compartments. It was hypothesized that the synthetic and clinical texture have similar properties, assuming that the mammogram texture reflects the 3D tissue distribution. The size of the projected compartments was computed by mathematical morphology. The texture energy and fractal dimension were also computed and analyzed in terms of the distribution of texture features within four different tissue regions in clinical and synthetic mammograms. Comparison of the cumulative distributions of the mean features computed from 95 mammograms showed that the synthetic images simulate the mean features of the texture of clinical mammograms. Correlation of clinical and synthetic texture feature histograms, averaged over all images, showed that the synthetic images can simulate the range of features seen over a large group of mammograms. The best agreement with clinical texture was achieved for simulated compartments with radii of 4-13.3 mm in predominantly adipose tissue regions, and radii of 2.7-5.33 and 1.3-2.7 mm in retroareolar and dense fibroglandular tissue regions, respectively.

Adipose Tissue↗