The purpose of this study was to evaluate the ability of an aperture complexity metric for volumetric-modulated arc therapy (VMAT) plans to predict plan delivery accuracy. We developed a complexity analysis tool as a plug-in script to Varian’s Eclipse treatment planning system. This script reports the modulation of plans, arcs, and individual control points for VMAT plans using a previously developed complexity metric. The calculated complexities are compared to that of 649 VMAT plans previously treated at our institution from 2013 to mid-2015. We used the VMAT quality assurance (QA) results from the 649 treated plans, plus 62 plans that failed pretreatment QA, to validate the ability of the complexity metric to predict plan deliverability. We used a receiver operating characteristic (ROC) analysis to determine an appropriate complexity threshold value above which a plan should be considered for reoptimization before it moves further through our planning workflow. The average complexity metric for the 649 treated plans analyzed with the script was 0.132 mm−1 with a standard deviation of 0.036 mm−1. We found that when using a threshold complexity value of 0.180 mm−1, the true positive rate for correctly identifying plans that failed QA was 44%, and the false-positive rate was 7%. Used clinically with this threshold, the script can identify overly modulated plans and thus prevent a significant portion of QA failures. Reducing VMAT plan complexity has a number of important clinical benefits, including improving plan deliverability and reducing treatment time. Use of the complexity metric during both the planning and QA processes can reduce the number of QA failures and improve the quality of VMAT plans used for treatment.

Purpose The incidence of colorectal cancer (CRC) in Ghana has increased eightfold since the 1960s. In 2011, national guidelines were set forth recommending all patients aged 50–70 years old undergo annual CRC screening with fecal occult blood testing (FOBT), but adherence to these guidelines is poor and screening rates remain low for unclear reasons. Methods We performed semi-structured interviews with 28 Ghanaians including physicians ( n = 14) and patients ( n = 14) from the Komfo Anokye Teaching Hospital in Kumasi, Ghana, to better understand the factors driving screening adherence and perceived barriers identified in an earlier quantitative study. Results Participants reported sociocultural factors such as reliance on alternative medicine or religion, lack of education, and financial burden as community-level barriers to CRC screening. At the system level, screening was limited by insufficient access to FOBT as well as a perceived lack of national prioritization. This was described as inadequate efforts from the Ministry of Health regarding national education as well as lack of incorporation of CRC screening into the National Health Insurance Scheme. Conclusion Several community- and system-level barriers exist to widespread screening of CRC in Ghana. A multi-level approach will be required to improve rates of CRC screening and ultimately reduce the burden of CRC in Ghana.

BACKGROUND: Patients undergoing colectomy may be at risk for postoperative regret, which is associated with worse quality of life, higher rates of depression, and poorer health outcomes. A better understanding of factors associated with decisional regret may allow surgeons to better tailor preoperative discussions to mitigate the risk of regret. OBJECTIVE:This study aimed to identify factors associated with regret in patients undergoing elective and urgent/emergent colectomy. DESIGN:A retrospective cohort study. SETTING:The Michigan Surgical Quality Collaborative, a 73-hospital collaborative, which collects clinical data on general surgery operations.PATIENTS: Patients aged >18 years who underwent elective or urgent/emergent colectomy between January 2017 and March 2020 and who completed a decision regret survey. MAIN OUTCOME MEASURES:Any degree of postoperative regret. RESULTS:Of 3638 patients, 2,530 (70%) underwent elective and 1108 (30%) underwent urgent/emergent colectomy. Overall, 381 (10.5%) patients reported regret, with higher rates among the urgent/emergent setting compared with the elective cohort (13.0% vs 9.4%; p < 0.001). In the elective cohort, regret was associated with length of stay >7 days (OR, 2.32; 95% CI, 1.06-5.07), postoperative complication (OR, 1.95; 95% CI, 1.36-2.79), and readmission (OR, 1.90; 95% CI, 1.22-2.95). Elective colectomies for cancer/adenoma/polyp were associated with lower odds of regret (OR, 0.68; 95% CI, 0.50-0.91). In the urgent/emergent cohort, regret was associated with female sex (OR, 1.69; 95% CI, 1.15-2.50) and nonhome discharge destination (OR, 1.61; 95% CI, 0.04-1.03).LIMITATIONS: Hospitals used different sampling strategies, limiting our ability to calculate a true response rate and characterize nonresponders. CONCLUSIONS:One in 10 patients reported regret after colectomy with higher rates in those undergoing urgent/ emergent colectomy. Factors associated with regret were different between surgical settings. Efforts are needed to mitigate patients' risk of regret with individualized discussions contingent on surgical settings to better align expectations and outcomes.

Purpose: We have introduced an automated script into the VMAT planning process to visualize and understand plan characteristics in comparison to past plans including number of arcs, arc weighting, and arc modulation. Methods: Varian's Eclipse Scripting Application Programming Interface (API) was used to create a script to compare new VMAT plans to past clinical VMAT plans, during and after the planning process. A graphical user interface was developed to display the results for straightforward analysis and interpretation. Analysis of previously treated plans from the past two years was used to design the data layout and organizational categories. In addition, a method was developed to automatically update the script as new plans are generated. Results: Plan data are represented in a histogram format, which is updateable with additional treatment plans by uploading a comma separated value file with the new patients’ information. The current script has the ability to display the number of arcs, the MU per arc and per control point, and the degree of modulation in each control point compared to all past VMAT plans. The user can filter the histogram by treatment site to easily compare the current plan to other plans of the same site, or to all sites. The histogram also contains the total number of plans being compared, the average value of the metric being examined, and the standard deviation of that metric. The script has been built with a modular framework such that additional plan metrics can be added as they are developed. Conclusions: The script interface provides easy to understand feedback on quality metrics of VMAT plans compared to other plans for the same body site. The script enables dosimetrists to ensure consistent plan quality, and assists physicists in checking plans prior to pre‐treatment quality assurance measurements. This project was supported in part by P01CA059827.

Purpose: Volumetric modulated arc therapy (VMAT) plans can become excessively complex with little additional dosimetric benefit due to the degenerative nature of inverse planning. Our goal is to improve the efficiency and quality of the VMAT planning process through the use of an automated complexity metric script. Methods: A metric that quantifies the complexity of VMAT plans by evaluating individual segment modulation was developed at our institution. This metric finds the ratio of the MLC leaf side length over aperture area for each control point, and calculates an MU‐weighted average of all controls points in the plan. A plug‐in script was created to enable use of the metric within our commercial treatment planning system. The script calculates the complexity metric and then compares it to metrics from previous clinical VMAT plans, all of which have passed patient specific pre‐treatment quality assurance. To set a threshold complexity value, we used the complexity metric script to analyze 517 clinical VMAT plans created in 2013–14 that passed QA (composite analysis, 95% of points passing 4%/1mm) and 57 that failed QA. This threshold was optimized based on the resulting true and false positive rates. Results: With the clinically set threshold, the complexity metric has a true positive rate of 44% for identifying plans that failed QA with a corresponding false positive rate of 6%. The false positives correspond to highly modulated plans, which may benefit from being reoptimized even though they initially passed patient specific QA. Conclusion: Our in‐house complexity metric script has the ability to streamline the VMAT planning and treatment process by alerting the planner when overly complex plans are generated. Those plans can be reoptimized before pre‐treatment QA is performed to attempt to reduce the plan complexity and therefore improve the plan delivery accuracy. This project was supported in part by P01CA059827.