Faculty Bibliography

Dosimetric accuracy of a volumetric modulated arc therapy (VMAT) plan is directly related to the beam model, particularly with multileaf collimator characterization. Inappropriate dosimetric leaf gap (DLG) value can lead to a suboptimal beam model, with significant failure in patient-specific quality assurance (PSQA) of VMAT plans. This study addressed the systematic issue of beam modeling and developed a practical method to determine the optimal DLG value for a beam model. Several complex VMAT plans were selected for the quality assurance analysis using the variable DLG values. The results of three-dimensional (3D) Gamma analysis as a function of the DLG at 3%/3 mm, 2%/2 mm, and 1%/1 mm criteria were fitted by a polynomial curve. The DLG value corresponding to the maximum Gamma passing rate for each polynomial fitting function was derived, and the average was calculated to be the optimal DLG value for each model. The 3D Gamma analysis was repeated with the optimal DLG value to verify the dosimetric accuracy of each VMAT case by PSQA. Gamma passing rates are seen to vary considerably with the DLG values and different analysis criteria (3%/3 mm, 2%/2 mm, and 1%/1 mm) for each case. The optimal DLG derived for each model was 1.16 mm and 1.10 mm, much larger than the measured value (about 0.3 mm). The beam models with the optimal DLG was able to produce an average Gamma passing rate of 97.1% (range, 94.6%- 99.1%) at 3%/3 mm and 93.5% (range, 89.0%- 96.5%) at 2%/2 mm for one beam model, and 97.1% (range, 94.8%- 99.1%) at 3%/3 mm, and 93.3% (range, 88.8%- 96.7%) at 2%/2 mm for another. The overall accuracy of dose calculation for VMAT plans should be optimized with a compromise of varied modulation complexities in a beam model. We have developed a practical method to derive the optimal DLG value for each beam model based on the Gamma passing criterion. This technique should be applicable in general for all beam energies and patient cases.

Food and beverage marketing contributes to poor dietary choices among adults and children. As consumers spend more time on the Internet, food and beverage companies have increased their online marketing efforts. Studies have shown food companies' online promotions use a variety of marketing techniques to promote mostly energy-dense, nutrient-poor products, but no studies have compared the online marketing techniques and nutritional quality of products promoted on food companies' international websites. For this descriptive study, we developed a qualitative codebook to catalogue the marketing themes used on 18 international corporate websites associated with the world's three largest fast food and beverage companies (i.e. Coca-Cola, McDonald's, Kentucky Fried Chicken). Nutritional quality of foods featured on those websites was evaluated based on quantitative Nutrient Profile Index scores and food category (e.g. fried, fresh). Beverages were sorted into categories based on added sugar content. We report descriptive statistics to compare the marketing techniques and nutritional quality of products featured on the company websites for the food and beverage company websites in two high-income countries (HICs), Germany and the United States, two upper-middle-income countries (UMICs), China and Mexico, and two lower-middle-income countries (LMICs), India and the Philippines. Of the 406 screenshots captured from company websites, 67.8% depicted a food or beverage product. HICs' websites promoted diet food or beverage products/ healthier alternatives (e. g. baked chicken sandwich) significantly more often on their pages (25%), compared to LMICs (14.5%). Coca-Cola featured diet products significantly more frequently on HIC websites compared to LMIC websites. Charities were featured more often on webpages in LMICs (15.4%) compared to UMICs (2.6%) and HICs (2.3%). This study demonstrates that companies showcase healthier products in wealthier countries and advertise their philanthropic activities in lower income countries, which is concerning given the negative effect of nutrition transition (double burden of overnutrition and undernutrition) on burden of non-communicable diseases and obesity in lower income countries.

Recently published Medical Physics Practice Guideline 5.a. (MPPG 5.a.) by American Association of Physicists in Medicine (AAPM) sets the minimum requirements for treatment planning system (TPS) dose algorithm commissioning and quality assurance (QA). The guideline recommends some validation tests and tolerances based primarily on published AAPM task group reports and the criteria used by IROC Houston. We performed the commissioning and validation of the dose algorithms for both megavoltage photon and electron beams on three linacs following MPPG 5.a. We designed the validation experiments in an attempt to highlight the evaluation method and tolerance criteria recommended by the guideline. It seems that comparison of dose profiles using in-water scan is an effective technique for basic photon and electron validation. IMRT/VMAT dose calculation is recommended to be tested with some TG-119 and clinical cases, but no consensus of the tolerance exists. Extensive validation tests have provided the better understanding of the accuracy and limitation of a specific dose calculation algorithm. We believe that some tests and evaluation criteria given in the guideline can be further refined

We present an example when profile measurement and modeling of an Elekta Agility multileaf collimator (MLC) had a large effect specifically on arc therapy plan quality assurance (QA) results using ArcCheck. ArcCheck absolute dose measurements of these plans were systematically lower than planned by 3-10%. Failing QA results were seen even with unmodulated static and conformal arcs. Furthermore, the effect was found to be dependent on collimator angle, with worse results associated with near-zero collimator angles. In contrast, step-and-shoot QA results were not affected. Changing the beam model to match steeper profile measurements obtained using a different measurement device resolved the problem. This case study demonstrates that conventional gamma index analysis can be sensitive to small profile modeling changes.