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.

Realistic phantoms to characterize dosimetry in pediatric CT.

BACKGROUND: The estimation of organ doses and effective doses for children receiving CT examinations is of high interest. Newer, more realistic anthropomorphic body models can provide information on individual organ doses and improved estimates of effective dose. MATERIALS AND METHODS: Previously developed body models representing 50th-percentile individuals at reference ages (newborn, 1, 5, 10 and 15 years) were modified to represent 10th, 25th, 75th and 90th height percentiles for both genders and an expanded range of ages (3, 8 and 13 years). We calculated doses for 80 pediatric reference phantoms from simulated chest-abdomen-pelvis exams on a model of a Philips Brilliance 64 CT scanner. Individual organ and effective doses were normalized to dose-length product (DLP) and fit as a function of body diameter. RESULTS: We calculated organ and effective doses for 80 reference phantoms and plotted them against body diameter. The data were well fit with an exponential function. We found DLP-normalized organ dose to correlate strongly with body diameter (R2>0.95 for most organs). Similarly, we found a very strong correlation with body diameter for DLP-normalized effective dose (R2>0.99). Our results were compared to other studies and we found average agreement of approximately 10%. CONCLUSION: We provide organ and effective doses for a total of 80 reference phantoms representing normal-stature children ranging in age and body size. This information will be valuable in replacing the types of vendor-reported doses available. These data will also permit the recording and tracking of individual patient doses. Moreover, this comprehensive dose database will facilitate patient matching and the ability to predict patient-individualized dose prior to examination.

Patient-specific dose calculations for pediatric CT of the chest, abdomen and pelvis.

BACKGROUND: Organ dose is essential for accurate estimates of patient dose from CT. OBJECTIVE: To determine organ doses from a broad range of pediatric patients undergoing diagnostic chest-abdomen-pelvis CT and investigate how these relate to patient size. MATERIALS AND METHODS: We used a previously validated Monte Carlo simulation model of a Philips Brilliance 64 multi-detector CT scanner (Philips Healthcare, Best, The Netherlands) to calculate organ doses for 40 pediatric patients (M:F = 21:19; range 0.6-17 years). Organ volumes and positions were determined from the images using standard segmentation techniques. Non-linear regression was performed to determine the relationship between volume CT dose index (CTDIvol)-normalized organ doses and abdominopelvic diameter. We then compared results with values obtained from independent studies. RESULTS: We found that CTDIvol-normalized organ dose correlated strongly with exponentially decreasing abdominopelvic diameter (R(2) > 0.8 for most organs). A similar relationship was determined for effective dose when normalized by dose-length product (R(2) = 0.95). Our results agreed with previous studies within 12% using similar scan parameters (e.g., bowtie filter size, beam collimation); however results varied up to 25% when compared to studies using different bowtie filters. CONCLUSION: Our study determined that organ doses can be estimated from measurements of patient size, namely body diameter, and CTDIvol prior to CT examination. This information provides an improved method for patient dose estimation.