Development of an automated detection algorithm for patient motion blur in digital mammograms

The purpose is to develop and validate an automated method for detecting image unsharpness caused by patient motion blur in digital mammograms. The goal is that such a tool would facilitate immediate re-taking of blurred images, which has the potential to reduce the number of recalled examinations, and to ensure that sharp, high-quality mammograms are presented for reading. To meet this goal, an automated method was developed based on interpretation of the normalized image Wiener Spectrum. A preliminary algorithm was developed using 25 cases acquired using a single vendor system, read by two expert readers identifying the presence of blur, location, and severity. A predictive blur severity score was established using multivariate modeling, which had an adjusted coefficient of determination, R2 =0.63±0.02, for linear regression against the average reader-scored blur severity. A heatmap of the relative blur magnitude showed good correspondence with reader sketches of blur location, with a Spearman rank correlation of 0.70 between the algorithmestimated area fraction with blur and the maximum of the blur area fraction categories of the two readers. Given these promising results, the algorithm-estimated blur severity score and heatmap are proposed to be used to aid observer interpretation. The use of this automated blur analysis approach, ideally with feedback during an exam, could lead to a reduction in repeat appointments for technical reasons, saving time, cost, potential anxiety, and improving image quality for accurate diagnosis.</p

The impact of simulated motion blur on lesion detection performance in full field digital mammography

Objective: Motion blur is a known phenomenon in full-field digital mammography, but the impact on lesion detection is unknown. This is the first study to investigate detection performance with varying magnitudes of simulated motion blur. Method: Seven observers (15±5 years’ reporting experience) evaluated 248 cases (62 containing malignant masses, 62 containing malignant microcalcifications and 124 normal cases) for three conditions: no blurring (0 mm) and two magnitudes of simulated blurring (0.7 mm and 1.5 mm). Abnormal cases were biopsy proven. Mathematical simulation was used to provide a pixel shift in order to simulate motion blur. A free-response observer study was conducted to compare lesion detection performance for the three conditions. The equally weighted jackknife alternative free-response receiver operating characteristic (wJAFROC) was used as the figure of merit. Test alpha was set at 0.05 to control probability of Type I error. Results: wJAFROC analysis found a statistically significant difference in lesion detection performance for both masses (F(2,22) = 6.01, P=0.0084) and microcalcifications (F(2,49) = 23.14, P&lt;0.0001). The figures of merit reduced as the magnitude of simulated blurring increased. Statistical differences were found between some of the pairs investigated for the detection of masses (0.0mm v 0.7mm, and 0.0mm v 1.5mm) and all pairs for microcalcifications (0.0 mm v 0.7 mm, 0.0 mm v 1.5 mm, and 0.7 mm v 1.5 mm). No difference was detected between 0.7 mm and 1.5 mm for masses. Conclusion: Mathematical simulation of motion blur caused a statistically significant reduction in lesion detection performance. These false negative decisions could have implications for clinical practice. Advances in knowledge: This research demonstrates for the first time that motion blur has a negative and statistically significant impact on lesion detection performance digital mammography

Extra patient movement during mammographic imaging : an experimental study

Objectives: To determine if movement external to the patient occurring during mammography may be a source of image blur. Methods: Four mammography machines with seven flexible and nine fixed paddles were evaluated. In the first stage, movement at the paddle was measured mechanically using two calibrated linear potentiometers. A deformable breast phantom was used to mimic a female breast. For each paddle, the movement in millimeters and change in compression force in Newton was recorded at 0.5 and 1 second intervals respectively for 40 seconds with the phantom in an initially compressed state under a load of 80N. In the second stage, clinical audit on 28 females was conducted on one mammography machine with the 18x24cm and 24x29cm flexible paddles. Results: Movement at the paddle followed an exponential decay with a settling period of approximately 40 seconds. The compression force readings for both fixed and flexible paddles decreased exponentially with time while fixed paddles have a larger drop in compression force than flexible paddles. There is a linear relationship between movement at the paddle and change in compression force. Conclusions: Movement measured at the paddle during an exposure can be represented by a second order system. The amount of extra-patient movement during the actual exposure can be estimated using the linear relationship between movement at the paddle and the change in compression force. Advances in knowledge: This research provides a possible explanation to mammography image blurring caused by extra patient movement and proposes a theoretical model to analyze the movement

DEVELOPMENT OF A MULTIPLE ENERGY SYNCHROTRON BIOMEDICAL IMAGING SYSTEM

A multiple energy imaging (MEI) system that can extract multiple endogenous or induced contrast materials as well as water and bone images would be ideal for imaging of biological subjects. The continuous spectrum available from synchrotron light facilities provides a nearly perfect source for MEI. This dissertation is on a novel MEI imaging system developed for biomedical imaging applications at the BioMedical Imaging and Therapy bend magnet beamline, Canadian Light Source. The developed MEI system prepares a horizontally focused polychromatic x-ray imaging beam. Its components are: a cylindrically bent Laue single silicon (5, 1, 1) crystal monochromator, scanning and positioning stages for the subjects, flat panel (area) detector, and a data acquisition and control system. The Si crystal is bent by means of a frame bender and has a bent radius of 0.5 m. Depending on the horizontal beam width of filtered synchrotron radiation (20 to 50 keV) incident on the monochromator; the size and spectral energy range of the focused beam prepared vary, and can be up to 15 keV. The spectral energy range covers the K-edges of iodine (33.17 keV), xenon (34.56 keV), cesium (35.99 keV), and barium (37.44 keV). Iodine, xenon and barium are commonly used biomedical and clinical contrast agents. A phantom composed of six materials: iodine, xenon, cesium, barium, water, and bone was imaged using the MEI system and their projected concentrations successfully extracted. For quantification of iodine, cesium and barium, the minimum detection limit of the MEI system is about 1.0 mg/ml for iodine and barium, and 0.5 mg/ml for cesium. The estimated dose rate to the phantom imaged at a ring current of 200 mA is 8.7 mGy/s, corresponding to a cumulative dose of 1.3 Gy. A crossover correction algorithm has also been developed to suppress crossover artifacts associated with the MEI system, dual-beam KES and spectral KES systems. Potential biomedical applications of the imaging system will include projection imaging that requires any of the extracted K-edges as a contrast agent and multi-contrast K-edge imaging

Mammography machine compression paddle movement andobserver performance analysis

Full field digital mammography (FFDM) was introduced into the United Kingdom (UK) as a replacement for screen-film mammography (SFM) in 2005. Since then, individual breast screening centres have begun to report blurred images through local audits. Blurring was probably present in SFM as well, however the improvement in contrast resolution in FFDM may have made it more apparent. The sources of blurring include improper imaging techniques, patient movement caused by breathing and heart motion,the viscoelastic motion of the breast, and paddle motion. This thesis aims to test the hypothesis that paddle motion might cause image blur. It investigates whether blurring can be detected visually on technical review monitors and reporting grade monitors.The thesis presents a method to minimise paddle motion during X-ray exposure. Six papers have been published. Two of these (papers 1 and 2) investigated paddle displacement using linear potentiometers. Three investigated the influence of paddle motion on image quality. Paper 3 investigated whether paddle motion can cause image blur; paper 4 determined the minimum amount of simulated motion required for the visual detection of blurring; and paper 5 evaluated the practitioner’s ability to identify blurring on monitors with different resolutions (2.3 MP and 5 MP). The final research paper (paper 6) investigated a way to reduce paddle displacement settling time; this involved the use of a closed-loop control system.Results: In papers 1 and 2 paddle displacement followed a bi-exponential function with a settling time of approximately 40 s. The use of average paddle displacement to estimate the amount of paddle motion would underestimate the worst case of the threedifferent runs of the experiment. The estimated paddle motion would be greatly reduced if the time of exposure is delayed from 5 to 10 s. In paper 3 all metal ball bearings shown increased in diameters and the range of magnification varied from 1.04 to 1.21. T-test results shown that there was a significant difference (p < 0.05) in the ball bearing diameters between the intensity thresholding and the edge detection methods for all paddle/ compression force combinations. The ball bearing diameters calculated by the intensity thresholding method had higher variability than the edge detection method.In paper 4 the soft-edged mask method best represented the physical process that caused the blurring effect and was chosen as the standard simulation approach for motion blurring. The ratio between the vertical paddle motion and the horizontal breast motion estimated by the mathematical model is approximately 1:0.3.In paper 5 the angular size calculation shown that for a viewing distance of 75 cm the screen resolution for 5 MP and 12 MP monitors was better than the observer eyes' resolution. For a viewing distance of 30 cm the observer eyes' resolution was betterthan the screen resolution for 2.3 MP, 5 MP and 12 MP monitors. Among all three monitors, image displayed on the 12 MP monitor has the lowest loss in image quality after interpolation. In paper 6 the simulation results shown that force overshoot is possible for position control system. Force overshoot occurred almost instantaneously for step input and its magnitude is about 10 times larger than the ramp input. Force overshoot and steadystateerror can be eliminated by the use of force control system.Conclusion: The magnitude of calculated paddle motion is much lower than the minimum amount of simulated motion required for the visual detection of blurring. Mathematical models have shown that vertical paddle motion caused a smaller horizontal breast displacement when compressed. Therefore, there is no sufficientevidence to support the hypothesis that paddle motion is a cause of image blurring in FFDM

The impact of simulated motion blur on breast cancer detection performance in full field digital mammography (FFDM)

Objective: Full-field Digital Mammography (FFDM) is employed in breast screening for the early detection of breast cancer. High quality, artefact free, diagnostic images are crucial to the accuracy of this process. Unwanted motion during the image acquisition phase and subsequent image blurring is an unfortunate occurrence in some FFDM images. The research detailed in this thesis seeks to understand the impact of motion blur on cancer detection performance in FFDM images using novel software to perform simulation of motion, an observer study to measure the lesion detection performance and physical measures to assess the impact of simulated motion blur on image characteristics of the lesions. Method: Seven observers (15±5 years’ reporting experience) evaluated 248 cases (62 containing malignant masses, 62 containing malignant microcalcifications and 124 normal cases) for three conditions: no motion blur (0.0 mm) and two magnitudes of simulated motion blur (0.7 mm and 1.5 mm). Abnormal cases were biopsy proven. A free-response observer study was conducted to compare lesion detection performance for the three conditions. Equally weighted jackknife alternative free-response receiver operating characteristic (wJAFROC) was used as the figure of merit. A secondary analysis of data was deemed important to simulate ‘double reporting’. In this secondary analysis, six of the observers are combined with the seventh observer to evaluate the impact of combined free-response data for lesion detection and to assess if combined two observers data could reduce the impact of simulated motion blur on detection performance. To compliment this, the physical characteristics of the lesions were obtained under the three conditions in order to assess any change in characteristics of the lesions when blur is present in the image. The impact of simulated motion blur on physical characteristics of malignant masses was assessed using a conspicuity index; for microcalcifications, a new novel metric, known as dispersion index, was used. Results: wJAFROC analysis found a statistically significant difference in lesion detection performance for both masses (F (2,22) = 6.01, P=0.0084) and microcalcifications (F(2,49) = 23.14, P&lt;0.0001). For both lesion types, the figure of merit reduced as the magnitude of simulated motion blur increased. Statistical differences were found between some of the pairs investigated for the detection of masses (0.0mm v 0.7mm, and 0.0mm v 1.5mm) and all pairs for microcalcifications (0.0 mm v 0.7 mm, 0.0 mm v 1.5 mm, and 0.7 mm v 1.5 mm). No difference was detected between 0.7 mm and 1.5 mm for masses. For combined two observers’ data of masses, there was no statistically significant difference between single and combined free-response data for masses (F(1,6) = 4.04, p=0.1001, -0.031 (-0.070, 0.008) [treatment difference (95% CI)]. For combined data of microcalcifications, there was a statistically significant difference between single and combined free-response data (F(1,6) = 12.28, p=0.0122, -0.056 (-0.095, -0.017) [treatment difference (95% CI)]. Regarding the physical measures of masses, conspicuity index increases as the magnitude of simulated motion blur increases. Statistically significant differences were demonstrated for 0.0–0.7 mm t(22)=-6.158 (p&lt;0.000); 0.0–1.5 mm t(22)=-6.273 (p&lt;0.000); and 0.7–1.5 mm (t(22)=-6.231 (p&lt;0.000). Lesion edge angle decreases as the magnitude of simulated motion blur increases. Statistically significant differences were demonstrated for 0.0–0.7 mm t(22)=3.232 (p&lt;0.004); for 0.0–1.5 mm t(22)=6.592 (p&lt;0.000); and 0.7–1.5mm t(22)=2.234 (p&lt;0.036). For the grey level change there was no statistically significant difference as simulated motion blur increases to 0.7 and then to 1.5mm. For image noise there was a statistically significant difference, where noise reduced as simulated motion blur increased: 0.0–0.7 mm t(22)=22.95 (p&lt;0.000); 0.0–1.5mm t(22)=24.66 (p&lt;0.000); 0.7–1.5 mm t(22)=18.11 (p&lt;0.000). For microcalcifications, simulated motion blur had a negative impact on the ‘dispersion index’. Conclusion: Mathematical simulations of motion blur resulted in a statistically significant reduction in lesion detection performance. This reduction in performance could have implications for clinical practice. Simulated motion blur has a negative impact on the edge angle of breast masses and a negative impact on the image characteristics of microcalcifications. These changes in the image lesion characteristics appear to have a negative effect on the visual identification of breast cancer