Medical physics 3.0 versus 1.0: A case study in digital radiography quality control.

PURPOSE: The study illustrates how a renewed approach to medical physics, Medical Physics 3.0 (MP3.0), can identify performance decrement of digital radiography (DR) systems when conventional Medical Physics 1.0 (MP1.0) methods fail. METHODS: MP1.0 tests included traditional annual tests plus the manufacturer's automated Quality Assurance Procedures (QAP) of a DR system before and after a radiologist's image quality (IQ) complaint repeated after service intervention. Further analysis was conducted using nontraditional MP3.0 tests including longitudinal review of QAP results from a 15-yr database, exposure-dependent signal-to-noise (SNR2 ), clinical IQ, and correlation with the institutional service database. Clinical images were analyzed in terms of IQ metrics by the Duke University Clinical Imaging Physics Group using previously validated software. RESULTS: Traditional metrics did not indicate discrepant system performance at any time. QAP reported a decrease in contrast-to-noise ratio (CNR) after detector replacement, but remained above the manufacturer's action limit. Clinical images showed increased lung noise (Ln), mediastinum noise (Mn), and subdiaphragm-lung contrast (SLc), and decreased lung gray level (Lgl) following detector replacement. After detector recalibration, QAP CNR improved, but did not return to previous levels. Lgl and SLc no longer significantly differed from before detector recalibration; however, Ln and Mn remained significantly different. Exposure-dependent SNR2 documented the detector operating within acceptable limits 9 yr previously but subsequently becoming miscalibrated sometime before four prior annual tests. Service records revealed catastrophic failure of the computer containing the original detector calibration from 11 yr prior. It is likely that the incorrect calibration backup file was uploaded at that time. CONCLUSIONS: MP1.0 tests failed to detect substandard system performance, but MP3.0 methods determined the root cause of the problem. MP3.0 exploits the wealth of data with more sensitive performance indicators. Data analytics are powerful tools whose proper application could facilitate early intervention in degraded system performance.

Automated quality control assessment of clinical chest images.

PURPOSE: The purpose of this study was to determine whether a proposed suite of objective image quality metrics for digital chest radiographs is useful for monitoring image quality in a clinical setting unique from the one where the metrics were developed. METHODS: Seventeen gridless AP chest radiographs from a GE Optima portable digital radiography (DR) unit ("sub-standard" images; Group 2) and 17 digital PA chest radiographs ("standard-of-care" images; Group 1) and 15 gridless (non-routine) PA chest radiographs (images with a gross technical error; Group 3) from a Discovery DR unit were chosen for analysis. Group 2 images were acquired with a lower kVp (100 vs 125) and shorter source-to-image distance (127 cm vs 183 cm) and were expected to have lower quality than Group 1 images. Group 3 images were expected to have degraded contrast vs Group 1 images. Images were anonymized and securely transferred to the Duke University Clinical Imaging Physics Group for analysis using software described and validated previously. Individual image quality was reported in terms of lung gray level, lung detail, lung noise, rib-lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. Metrics were compared across groups. To improve precision of means and confidence intervals for routine exams, an additional 66 PA images were acquired, processed, and pooled with Group 1. Three observer studies were conducted to assess whether humans were able to identify images classified by the algorithm as abnormal. RESULTS: Metrics agreed with published Quality Consistency Ranges with three exceptions: higher lung gray level, lower rib-lung contrast, and lower subdiaphragm-lung contrast. Higher (stored) bit depth (14 vs 12) accounted for higher lung gray level values in our images. Values were most internally consistent for Group 1. The most sensitive metric for distinguishing between groups was mediastinum noise, followed closely by lung noise. The least sensitive metrics were mediastinum detail and rib-lung contrast. The algorithm was more sensitive than human observers at detecting suboptimal diagnostic quality images. CONCLUSIONS: The software appears promising for objectively and automatically identifying suboptimal images in a clinical imaging operation. The results can be used to establish local quality consistency ranges and action limits per facility preferences.

Evaluation of cassette-based digital radiography detectors using standardized image quality metrics: AAPM TG-150 Draft Image Detector Tests.

The purpose of this study was to evaluate several of the standardized image quality metrics proposed by the American Association of Physics in Medicine (AAPM) Task Group 150. The task group suggested region-of-interest (ROI)-based techniques to measure nonuniformity, minimum signal-to-noise ratio (SNR), number of anomalous pixels, and modulation transfer function (MTF). This study evaluated the effects of ROI size and layout on the image metrics by using four different ROI sets, assessed result uncertainty by repeating measurements, and compared results with two commercially available quality control tools, namely the Carestream DIRECTVIEW Total Quality Tool (TQT) and the GE Healthcare Quality Assurance Process (QAP). Seven Carestream DRX-1C (CsI) detectors on mobile DR systems and four GE FlashPad detectors in radiographic rooms were tested. Images were analyzed using MATLAB software that had been previously validated and reported. Our values for signal and SNR nonuniformity and MTF agree with values published by other investigators. Our results show that ROI size affects nonuniformity and minimum SNR measurements, but not detection of anomalous pixels. Exposure geometry affects all tested image metrics except for the MTF. TG-150 metrics in general agree with the TQT, but agree with the QAP only for local and global signal nonuniformity. The difference in SNR nonuniformity and MTF values between the TG-150 and QAP may be explained by differences in the calculation of noise and acquisition beam quality, respectively. TG-150's SNR nonuniformity metrics are also more sensitive to detector nonuniformity compared to the QAP. Our results suggest that fixed ROI size should be used for consistency because nonuniformity metrics depend on ROI size. Ideally, detector tests should be performed at the exact calibration position. If not feasible, a baseline should be established from the mean of several repeated measurements. Our study indicates that the TG-150 tests can be used as an independent standardized procedure for detector performance assessment.

Genome Sequences of Gordonia Bacteriophages Obliviate, UmaThurman, and Guacamole.

We describe three newly isolated phages-Obliviate, UmaThurman, and Guacamole-that infect Gordonia terrae 3612. The three genomes are related to one another but are not closely related to other previously sequenced phages or prophages. The three phages are predicted to use integration-dependent immunity systems as described in several mycobacteriophages.

Essentials and guidelines for clinical medical physics residency training programs: executive summary of AAPM Report Number 249.

There is a clear need for established standards for medical physics residency training. The complexity of techniques in imaging, nuclear medicine, and radiation oncology continues to increase with each passing year. It is therefore imperative that training requirements and competencies are routinely reviewed and updated to reflect the changing environment in hospitals and clinics across the country. In 2010, the AAPM Work Group on Periodic Review of Medical Physics Residency Training was formed and charged with updating AAPM Report Number 90. This work group includes AAPM members with extensive experience in clinical, professional, and educational aspects of medical physics. The resulting report, AAPM Report Number 249, concentrates on the clinical and professional knowledge needed to function independently as a practicing medical physicist in the areas of radiation oncology, imaging, and nuclear medicine, and constitutes a revision to AAPM Report Number 90. This manuscript presents an executive summary of AAPM Report Number 249.

Evaluation of a commercial cardiac motion phantom for dual-energy chest radiography.

Misregistration due to cardiac motion causes artifacts in two-exposure dual-energy subtraction images, in both the soft-tissue-only image and the bone-only image. Two previous investigations have attempted to avoid misregistration artifacts by using cardiac gating of the first and second exposures. The severity of misregistration was affected by the heart rate, the time interval between the low- and high-energy exposures, the total duration of the two exposures, and the phase of the cardiac cycle at the start of the exposure sequence. We sought to determine whether a commercial phantom with a simulated beating heart can be used to investigate the factors affecting misregistration in dual-energy chest radiography. We made dual-energy images of the phantom in postero-anterior orientation using the indirect digital radiography system (GE XQ/i). We acquired digital images at heart rates between 40 beats per minute and 120 beats per minute and transferred them to a computer, where the area of the artifact on the silhouette of the heart was measured from both soft-tissue-only and bone-only images. For comparison, we measured misregistration in clinical dual-energy subtraction images by the same method. Generally speaking, without synchronization of the exposure sequence with the cardiac cycle, the area of the misregistration artifact increased with heart rate for both the phantom and clinical images. However, the phantom exaggerated the magnitude of misregistration relative to clinical images. Although this phantom was designed for horizontal operation and computed tomography imaging, it can be used in an upright configuration to simulate heart motion for investigation of dual-energy misregistration artifacts and control.

The long-term impact of a performance improvement continuing medical education intervention on osteoporosis screening.

INTRODUCTION: The purpose of this study is to determine whether a performance improvement continuing medical education (PI CME) initiative that utilizes quality improvement (QI) principles is effective in producing sustainable change in practice to improve the screening of patients at risk for osteoporosis. METHODOLOGY: A health care center participated in a PI CME program designed to increase appropriate osteoporosis screening. There were eight 1-hour educational sessions for this activity over a 9-month period. Thirteen providers completed all 3 stages of the PI CME program. A variety of other clinicians, in addition to the 13 providers, participated in the educational sessions. Data were collected at the beginning and end of the PI CME activity and at three intervals during the 5 years after the completion of the activity. RESULTS: The percentage of tests for osteoporosis ordered and performed increased significantly from Stage A to Stage C of the PI CME activity and continued to increase after the completion of the PI CME activity. Follow-up data at 4 and 40 months (for ordering and performing osteoporosis screening) and 49 months (for performing the screening only) reflect the impact of the PI CME activity plus the continuing QI interventions. The percentage of BMD tests ordered continued to increase substantially over the post-PI CME periods: 4 and 40 months (F(3,46) = 4.04, p < .05). Similarly, the percentage of BMD tests performed continued to increase at 4, 40, and 49 months after the conclusion of the PI CME activity (F(4,55) = 12.55, p < .0001). DISCUSSION: The data indicate that PI CME utilizing QI principles can be effective in producing sustainable change in practice to improve the screening of patients at risk for osteoporosis. Further research is needed to determine the extent to which such changes can be directly attributed to this type of intervention.

Gain and offset calibration reduces variation in exposure-dependent SNR among systems with identical digital flat-panel detectors.

PURPOSE: The conditions under which vendor performance criteria for digital radiography systems are obtained do not adequately simulate the conditions of actual clinical imaging with respect to radiographic technique factors, scatter production, and scatter control. Therefore, the relationship between performance under ideal conditions and performance in clinical practice remains unclear. Using data from a large complement of systems in clinical use, the authors sought to develop a method to establish expected performance criteria for digital flat-panel radiography systems with respect to signal-to-noise ratio (SNR) versus detector exposure under clinical conditions for thoracic imaging. METHODS: The authors made radiographic exposures of a patient-equivalent chest phantom at 125 kVp and 180 cm source-to-image distance. The mAs value was modified to produce exposures above and below the mAs delivered by automatic exposure control. Exposures measured free-in-air were corrected to the imaging plane by the inverse square law, by the attenuation factor of the phantom, and by the Bucky factor of the grid for the phantom, geometry, and kilovolt peak. SNR was evaluated as the ratio of the mean to the standard deviation (SD) of a region of interest automatically selected in the center of each unprocessed image. Data were acquired from 18 systems, 14 of which were tested both before and after gain and offset calibration. SNR as a function of detector exposure was interpolated using a double logarithmic function to stratify the data into groups of 0.2, 0.5, 1.0, 2.0, and 5.0 mR exposure (1.8, 4.5, 9.0, 18, and 45 microGy air KERMA) to the detector. RESULTS: The mean SNR at each exposure interval after calibration exhibited linear dependence on the mean SNR before calibration (r2=0.9999). The dependence was greater than unity (m = 1.101 +/- 0.006), and the difference from unity was statistically significant (p <0.005). The SD of mean SNR after calibration also exhibited linear dependence on the SD of the mean SNR before calibration (r2 = 0.9997). This dependence was less than unity (m = 0.822 +/- 0.008), and the difference from unity was also statistically significant (p < 0.005). Systems were separated into two groups: systems with a precalibration SNR higher than the median SNR (N = 7), and those with a precalibration SNR lower than the median SNR (N= 7). Posthoc analysis was performed to correct for expanded false positive results. After calibration, the authors noted differences in mean SNR within both high and low groups, but these differences were not statistically significant at the 0.05 level. SNR data from four additional systems and one system from those previously tested after replacement of its detector were compared to the 95% confidence intervals (CI) calculated from the postcalibration SNR data. The comparison indicated that four of these five systems were consistent with the CI derived from the previously tested 14 systems after calibration. Two systems from the paired group that remained outside the CI were studied further. One system was remedied with a grid replacement. The nonconformant behavior of the other system was corrected by replacing the image receptor. CONCLUSIONS: Exposure-dependent SNR measurements under conditions simulating thoracic imaging allowed us to develop criteria for digital flat-panel imaging systems from a single manufacturer. These measurements were useful in identifying systems with discrepant performance, including one with a defective grid, one with a defective detector, and one that had not been calibrated for gain and offset. The authors also found that the gain and offset calibration reduces variation in exposure-dependent SNR performance among the systems.

One year's results from a server-based system for performing reject analysis and exposure analysis in computed radiography.

Rejected images represent both unnecessary radiation exposure to patients and inefficiency in the imaging operation. Rejected images are inherent to projection radiography, where patient positioning and alignment are integral components of image quality. Patient motion and artifacts unique to digital image receptor technology can result in rejected images also. We present a centralized, server-based solution for the collection, archival, and distribution of rejected image and exposure indicator data that automates the data collection process. Reject analysis program (RAP) and exposure indicator data were collected and analyzed during a 1-year period. RAP data were sorted both by reason for repetition and body part examined. Data were also stratified by clinical area for further investigation. The monthly composite reject rate for our institution fluctuated between 8% and 10%. Positioning errors were the main cause of repeated images (77.3%). Stratification of data by clinical area revealed that areas where computed radiography (CR) is seldom used suffer from higher reject rates than areas where it is used frequently. S values were log-normally distributed for examinations performed under either manual or automatic exposure control. The distributions were positively skewed and leptokurtic. S value decreases due to radiologic technology student rotations, and CR plate reader calibrations were observed. Our data demonstrate that reject analysis is still necessary and useful in the era of digital imaging. It is vital though that analysis be combined with exposure indicator analysis, as digital radiography is not self-policing in terms of exposure. When combined, the two programs are a powerful tool for quality assurance.

An exposure indicator for digital radiography: AAPM Task Group 116 (executive summary).

Digital radiographic imaging systems, such as those using photostimulable storage phosphor, amorphous selenium, amorphous silicon, CCD, and MOSFET technology, can produce adequate image quality over a much broader range of exposure levels than that of screen/film imaging systems. In screen/film imaging, the final image brightness and contrast are indicative of over- and underexposure. In digital imaging, brightness and contrast are often determined entirely by digital postprocessing of the acquired image data. Overexposure and underexposures are not readily recognizable. As a result, patient dose has a tendency to gradually increase over time after a department converts from screen/film-based imaging to digital radiographic imaging. The purpose of this report is to recommend a standard indicator which reflects the radiation exposure that is incident on a detector after every exposure event and that reflects the noise levels present in the image data. The intent is to facilitate the production of consistent, high quality digital radiographic images at acceptable patient doses. This should be based not on image optical density or brightness but on feedback regarding the detector exposure provided and actively monitored by the imaging system. A standard beam calibration condition is recommended that is based on RQA5 but uses filtration materials that are commonly available and simple to use. Recommendations on clinical implementation of the indices to control image quality and patient dose are derived from historical tolerance limits and presented as guidelines.

Optimizing digital radiography of children.

Pediatric projection imaging differs from imaging of the adult patient. Children are smaller, more radiosensitive, and less compliant than their adult counterparts. Their characteristics affect the way projection imaging is practiced and how dose is optimized. Computed radiography (CR) and digital radiography (DR) have been embraced by pediatric practitioners in order to reduce dose and improve image quality. Unfortunately, dose optimization with CR and DR has been hampered by a lack of definition of appropriate exposure levels, a lack of standardization in exposure factor feedback, and a lack of understanding of the fundamentals of CR and DR technology. The potential for over-exposure exists with both CR and DR. Both the Society for Pediatric Radiology and the American Association of Physicists in Medicine recognize the promise and shortcomings of CR and DR technology and have taken steps to join with manufacturers in improving the practice of CR and DR imaging. Although the risks inherent in pediatric projection imaging with CR and DR are low, efforts to reduce dose are worthwhile, so long as diagnostic quality is maintained. Long-standing recommendations for limiting radiation dose in pediatric projection imaging are still applicable to CR and DR.

Consequences of modern anthropometric dimensions for radiographic techniques and patient radiation exposures.

Radiographic techniques are devised on the basis of anatomic dimensions. Inaccurate dimensions can cause radiographs to be exposed inappropriately and patient radiation exposures to be calculated incorrectly. The source of anatomic dimensions in common usage dates back to 1948. The objective of this study was to compare traditional and modern anthropometric data, use modern dimensions to estimate potential errors in patient exposure, and suggest modified technique guidelines. Anthropometry software was used to derive modern anatomic dimensions. Data from routine annual testing were analyzed to develop an x-ray generator output curve. Published tabulated data were used to determine the relationship between tissue half-value layer and kilovoltage. These relationships were used to estimate entrance skin exposure and create a provisional technique guide. While most anatomic regions were actually larger than previously indicated, some were similar, and a few were smaller. Accordingly, exposure estimates were higher, similar, or lower, depending on the anatomic region. Exposure estimates using modern dimensions for clinically significant regions of the trunk were higher than those calculated with traditional dimensions. Exposures of the postero-anterior chest, lateral chest, antero-posterior (AP) abdomen, male AP pelvis, and female AP pelvis were larger by 48%, 31%, 54%, 52%, and 112%, respectively. The dimensions of bony regions of the anatomy, such as the joints and skull, were unchanged. These findings are consistent with the idea that anatomic areas where fat is deposited are larger in the modern U.S. population than they were in previous years. Exposure techniques for manual radiography and calculations of patient dose for automatic exposure control radiography should be adjusted according to the modern dimensions. Population radiation exposure estimates calculated in national surveys should also be modified appropriately.

Measurement of CT radiation profile width using CR imaging plates.

This paper describes the procedure for using a Fuji computed radiography (CR) imaging plate (IP) for the measurement of computed tomography (CT) radiation profiles. Two sources of saturation in the data from the IP, signal and quantization, were characterized to establish appropriate exposure and processing conditions for accurate measurements. The IP generated similar profiles compared to those obtained from digitized ready-pack films, except at the profile edges, where the exposure level is low. However, when IP pixel values are converted to exposure, CR and digitized film profiles are in agreement. The full width at half maximum (FWHM) of the CT radiation profile was determined from the relationship between pixel value and exposure and compared to FWHM of the digitized optical density profile from film. To estimate the effect of scattering by the cassette material, radiation profiles were acquired from IPs enclosed in a cassette or in a paper envelope. The presence of the cassette made no difference in the value determined for FWHM. With proper exposure and processing conditions, the FWHM of 5, 10, and 15 mm collimated beams were measured using IPs to be 7.1, 11.9, and 17.0 mm and using film to be 7.2, 12.2, and 16.8 mm, respectively. Our results suggest that, under appropriate conditions, the estimation of the width of the CT radiation profile using Fuji CR is comparable to the measurement from film density described in American Association of Physicists in Medicine (AAPM) Report No. 39. Although our experiment was conducted using Fuji CR, we anticipate that CR plates from other vendors could be successfully used to measure CT beam profiles because of similar empirical relationships between pixel value and exposure.

The continued evolution of the credit system.

In its ongoing support of continuous physician professional development, the American Medical Association (AMA) for use in the AMA Physician's Recognition Award has adopted 2 new learning platforms: Performance Improvement (PI) and Internet Point of Care (PoC). This article highlights the process that led to their adoption and places these new forms of continuing and physician professional development in the framework of existing continuing medical education (CME). The article calls for new research that revisits existing data on physician learning and prepares to incorporate provider experience with "practice situated" forms of CME. The Conjoint Committee on CME may serve as an important contributor to this process by enabling valuable dialogue among stakeholder organizations.

Assessment of display performance for medical imaging systems: executive summary of AAPM TG18 report.

Digital imaging provides an effective means to electronically acquire, archive, distribute, and view medical images. Medical imaging display stations are an integral part of these operations. Therefore, it is vitally important to assure that electronic display devices do not compromise image quality and ultimately patient care. The AAPM Task Group 18 (TG18) recently published guidelines and acceptance criteria for acceptance testing and quality control of medical display devices. This paper is an executive summary of the TG18 report. TG18 guidelines include visual, quantitative, and advanced testing methodologies for primary and secondary class display devices. The characteristics, tested in conjunction with specially designed test patterns (i.e., TG18 patterns), include reflection, geometric distortion, luminance, the spatial and angular dependencies of luminance, resolution, noise, glare, chromaticity, and display artifacts. Geometric distortions are evaluated by linear measurements of the TG18-QC test pattern, which should render distortion coefficients less than 2%/5% for primary/secondary displays, respectively. Reflection measurements include specular and diffuse reflection coefficients from which the maximum allowable ambient lighting is determined such that contrast degradation due to display reflection remains below a 20% limit and the level of ambient luminance (Lamb) does not unduly compromise luminance ratio (LR) and contrast at low luminance levels. Luminance evaluation relies on visual assessment of low contrast features in the TG18-CT and TG18-MP test patterns, or quantitative measurements at 18 distinct luminance levels of the TG18-LN test patterns. The major acceptable criteria for primary/ secondary displays are maximum luminance of greater than 170/100 cd/m2, LR of greater than 250/100, and contrast conformance to that of the grayscale standard display function (GSDF) of better than 10%/20%, respectively. The angular response is tested to ascertain the viewing cone within which contrast conformance to the GSDF is better than 30%/60% and LR is greater than 175/70 for primary/secondary displays, or alternatively, within which the on-axis contrast thresholds of the TG18-CT test pattern remain discernible. The evaluation of luminance spatial uniformity at two distinct luminance levels across the display faceplate using TG18-UNL test patterns should yield nonuniformity coefficients smaller than 30%. The resolution evaluation includes the visual scoring of the CX test target in the TG18-QC or TG18-CX test patterns, which should yield scores greater than 4/6 for primary/secondary displays. Noise evaluation includes visual evaluation of the contrast threshold in the TG18-AFC test pattern, which should yield a minimum of 3/2 targets visible for primary/secondary displays. The guidelines also include methodologies for more quantitative resolution and noise measurements based on MTF and NPS analyses. The display glare test, based on the visibility of the low-contrast targets of the TG18-GV test pattern or the measurement of the glare ratio (GR), is expected to yield scores greater than 3/1 and GRs greater than 400/150 for primary/secondary displays. Chromaticity, measured across a display faceplate or between two display devices, is expected to render a u',v' color separation of less than 0.01 for primary displays. The report offers further descriptions of prior standardization efforts, current display technologies, testing prerequisites, streamlined procedures and timelines, and TG18 test patterns.