The Current State of Physics Plan Review Training in Medical Physics Residency Programs in North America.

PURPOSE: This study aimed to identify the current state of residency training in physics plan reviews. METHODS AND MATERIALS: A voluntary, anonymous survey was sent to all program directors of accredited therapeutic medical physics residency programs in North America. Survey questions were developed to determine whether and how residents are trained in physics plan reviews. Survey questions were developed using expert validation and cognitive pretesting. RESULTS: Using a prospectively approved study (COMIRB 18-1073), responses were collected from 70 program directors, representing a 70% response rate. All respondents (100%) designated patient safety to be the purpose of physics plan reviews. Of the respondents, 94% indicated that physicists should first receive training in physics plan reviews while in a residency program. The vast majority of respondents (99%) provide training to residents in physics plan reviews. Although 57 programs (81% of respondents) have residents perform physics plan reviews as part of clinical practice (with varying levels of independence), 13 programs (19% of respondents) do not. The majority of respondents use the following training methods: observe staff physicists (96%), perform supervised reviews on actual patients for training or clinical practice (93%), use a checklist (80%), and read reference materials (62%). Although simulation plans with embedded errors would be implemented by 71% of respondents, they are currently used in only 19% of programs. CONCLUSIONS: The present study is the first to characterize chart-check teaching practices in medical physics residency programs. The vast majority of programs currently train residents in physics plan reviews. The most common teaching methods are observing and performing physics plan reviews, but there is variability in the level of resident involvement in clinical practice for physics plan reviews. There is room for the field to consider advancing current training methods, which is especially important given the critical roles that physics plan reviews have with regard to patient safety.

Predicting radiation pneumonitis after stereotactic ablative radiation therapy in patients previously treated with conventional thoracic radiation therapy.

PURPOSE: To determine the incidence of and risk factors for radiation pneumonitis (RP) after stereotactic ablative radiation therapy (SABR) to the lung in patients who had previously undergone conventional thoracic radiation therapy. METHODS AND MATERIALS: Seventy-two patients who had previously received conventionally fractionated radiation therapy to the thorax were treated with SABR (50 Gy in 4 fractions) for recurrent disease or secondary parenchymal lung cancer (T<4 cm, N0, M0, or Mx). Severe (grade≥3) RP and potential predictive factors were analyzed by univariate and multivariate logistic regression analyses. A scoring system was established to predict the risk of RP. RESULTS: At a median follow-up time of 16 months after SABR (range, 4-56 months), 15 patients had severe RP (14 [18.9%] grade 3 and 1 [1.4%] grade 5) and 1 patient (1.4%) had a local recurrence. In univariate analyses, Eastern Cooperative Oncology Group performance status (ECOG PS) before SABR, forced expiratory volume in 1 second (FEV1), and previous planning target volume (PTV) location were associated with the incidence of severe RP. The V10 and mean lung dose (MLD) of the previous plan and the V10-V40 and MLD of the composite plan were also related to RP. Multivariate analysis revealed that ECOG PS scores of 2-3 before SABR (P=.009), FEV1≤65% before SABR (P=.012), V20≥30% of the composite plan (P=.021), and an initial PTV in the bilateral mediastinum (P=.025) were all associated with RP. CONCLUSIONS: We found that severe RP was relatively common, occurring in 20.8% of patients, and could be predicted by an ECOG PS score of 2-3, an FEV1≤65%, a previous PTV spanning the bilateral mediastinum, and V20≥30% on composite (previous RT+SABR) plans. Prospective studies are needed to validate these predictors and the scoring system on which they are based.

Use of weekly 4DCT-based ventilation maps to quantify changes in lung function for patients undergoing radiation therapy.

PURPOSE: A method has been proposed to calculate ventilation maps from four-dimensional computed tomography (4DCT) images. Weekly 4DCT data were acquired throughout the course of radiation therapy for patients with lung cancer. The purpose of our work was to use ventilation maps calculated from weekly 4DCT data to study how ventilation changed throughout radiation therapy. METHODS: Quantitative maps representing ventilation were generated for six patients. Deformable registration was used to link corresponding lung volume elements between the inhale and exhale phases of the 4DCT dataset. Following spatial registration, corresponding Hounsfield units were input into a density-change-based model for quantifying the local ventilation. The ventilation data for all weeks were registered to the pretreatment ventilation image set. We quantitatively analyzed the data by defining regions of interest (ROIs) according to dose (V(20)) and lung lobe and by tracking the weekly ventilation of each ROI throughout treatment. The slope of the linear fit to the weekly ventilation data was used to evaluate the change in ventilation throughout treatment. A positive slope indicated an increase in ventilation, a negative slope indicated a decrease in ventilation, and a slope of 0 indicated no change. The dose ROI ventilation and slope data were used to study how ventilation changed throughout treatment as a function of dose. The lung lobe ROI ventilation data were used to study the impact of the presence of tumor on pretreatment ventilation. In addition, the lobe ROI data were used to study the impact of tumor reduction on ventilation change throughout treatment. RESULTS: Using the dose ROI data, we found that three patients had an increase in weekly ventilation as a function of dose (slopes of 1.1, 1.4, and 1.5) and three patients had no change or a slight decrease in ventilation as a function of dose (slopes of 0.3, -0.6, -0.5). Visually, pretreatment ventilation appeared to be lower in the lobes that contained tumor. Pretreatment ventilation was 39% for lobes that contained tumor and 54% for lobes that did not contain tumor. The difference in ventilation between the two groups was statistically significant (p = 0.017). When the weekly lobe ventilation data were qualitatively observed, two distinct patterns emerged. When the tumor volume in a lobe was reduced, ventilation increased in the lobe. When the tumor volume was not reduced, the ventilation distribution did not change. The average slope of the group of lobes that contained tumors that shrank was 1.18, while the average slope of the group that did not contain tumors (or contained tumors that did not shrink) was -0.32. The slopes for the two groups were significantly different (p = 0.014). CONCLUSIONS: We did not find a consistent pattern of ventilation change as a function of radiation dose. Pretreatment ventilation was significantly lower for lobes that contained tumor, due to occlusion of the central airway. The weekly lobe ventilation data indicated that when tumor volume shrinks, ventilation increases, and when the thoracic anatomy is not visibly changed, ventilation is likely to remain unchanged.

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.

Comparing the accuracy of four-dimensional photon dose calculations with three-dimensional calculations using moving and deforming phantoms.

PURPOSE: Four-dimensional (4D) dose calculation algorithms, which explicitly incorporate respiratory motion in the calculation of doses, have the potential to improve the accuracy of dose calculations in thoracic treatment planning; however, they generally require greater computing power and resources than currently used for three-dimensional (3D) dose calculations. The purpose of this work was to quantify the increase in accuracy of 4D dose calculations versus 3D dose calculations. METHODS: The accuracy of each dose calculation algorithm was assessed using measurements made with two phantoms. Specifically, the authors used a rigid moving anthropomorphic thoracic phantom and an anthropomorphic thoracic phantom with a deformable lung insert. To incorporate a clinically relevant range of scenarios, they programed the phantoms to move and deform with two motion patterns: A sinusoidal motion pattern and an irregular motion pattern that was extracted from an actual patient's breathing profile. For each combination of phantom and motion pattern, three plans were created: A single-beam plan, a multiple-beam plan, and an intensity-modulated radiation therapy plan. Doses were calculated using 4D dose calculation methods as well as conventional 3D dose calculation methods. The rigid moving and deforming phantoms were irradiated according to the three treatment plans and doses were measured using thermoluminescent dosimeters (TLDs) and radiochromic film. The accuracy of each dose calculation algorithm was assessed using measured-to-calculated TLD doses and a gamma analysis. RESULTS: No significant differences were observed between the measured-to-calculated TLD ratios among 4D and 3D dose calculations. The gamma results revealed that 4D dose calculations had significantly greater percentage of pixels passing the 5%/3 mm criteria than 3D dose calculations. CONCLUSIONS: These results indicate no significant differences in the accuracy between the 4D and the 3D dose calculation methods inside the gross tumor volume. On the other hand, the film results demonstrated that the 4D dose calculations provided greater accuracy than 3D dose calculations in heterogeneous dose regions. The increase in accuracy of the 4D dose calculations was evident throughout the planning target volume.

Verification of four-dimensional photon dose calculations.

Recent work in the area of thoracic treatment planning has been focused on trying to explicitly incorporate patient-specific organ motion in the calculation of dose. Four-dimensional (4D) dose calculation algorithms have been developed and incorporated in a research version of a commercial treatment planning system (Pinnacle3, Philips Medical Systems, Milpitas, CA). Before these 4D dose calculations can be used clinically, it is necessary to verify their accuracy with measurements. The primary purpose of this study therefore was to evaluate and validate the accuracy of a 4D dose calculation algorithm with phantom measurements. A secondary objective was to determine whether the performance of the 4D dose calculation algorithm varied between different motion patterns and treatment plans. Measurements were made using two phantoms: A rigid moving phantom and a deformable phantom. The rigid moving phantom consisted of an anthropomorphic thoracic phantom that rested on a programmable motion platform. The deformable phantom used the same anthropomorphic thoracic phantom with a deformable insert for one of the lungs. Two motion patterns were investigated for each phantom: A sinusoidal motion pattern and an irregular motion pattern extracted from a patient breathing profile. A single-beam plan, a multiple-beam plan, and an intensity-modulated radiation therapy plan were created. Doses were calculated in the treatment planning system using the 4D dose calculation algorithm. Then each plan was delivered to the phantoms and delivered doses were measured using thermoluminescent dosimeters (TLDs) and film. The measured doses were compared to the 4D-calculated doses using a measured-to-calculated TLD ratio and a gamma analysis. A relevant passing criteria (3% for the TLD and 5% /3 mm for the gamma metric) was applied to determine if the 4D dose calculations were accurate to within clinical standards. All the TLD measurements in both phantoms satisfied the passing criteria. Furthermore, 42 of the 48 evaluated films fulfilled the passing criteria. All films that did not pass the criteria were from the rigid phantom moving with irregular motion. The author concluded that if patient breathing is reproducible, the 4D dose calculations are accurate to within clinically acceptable standards. Furthermore, they found no statistically significant differences in the performance of the 4D dose calculation algorithm between treatment plans.