Treatment plan quality assessment for radiotherapy of rectal cancer patients using prediction of organ-at-risk dose metrics.

BACKGROUND AND PURPOSE: Radiotherapy centers frequently lack simple tools for periodic treatment plan verification and feedback on current plan quality. It is difficult to measure treatment quality over different years or during the planning process. Here, we implemented plan quality assurance (QA) by developing a database of dose-volume histogram (DVH) metrics and a prediction model. These tools were used to assess automatically optimized treatment plans for rectal cancer patients, based on cohort analysis. MATERIAL AND METHODS: A treatment plan QA framework was established and an overlap volume histogram based model was used to predict DVH parameters for cohorts of patients treated in 2018 and 2019 and grouped according to planning technique. A training cohort of 22 re-optimized treatment plans was used to make the prediction model. The prediction model was validated on 95 automatically generated treatment plans (automatically optimized cohort) and 93 manually optimized plans (manually optimized cohort). RESULTS: For the manually optimized cohort, on average the prediction deviated less than 0.3 ± 1.4 Gy and -4.3 ± 5.5 Gy, for the mean doses to the bowel bag and bladder, respectively; for the automatically optimized cohort a smaller deviation was observed: -0.1 ± 1.1 Gy and -0.2 ± 2.5 Gy, respectively. The interquartile range of DVH parameters was on average smaller for the automatically optimized cohort, indicating less variation within each parameter compared to manual planning. CONCLUSION: An automated framework to monitor treatment quality with a DVH prediction model was successfully implemented clinically and revealed less variation in DVH parameters for automated in comparison to manually optimized plans. The framework also allowed for individual feedback and DVH estimation.

Stereotypic information about drinkers and students' observed alcohol intake: an experimental study on prototype-behavior relations in males and females in a naturalistic drinking context.

BACKGROUND: Cross-sectional and longitudinal research has shown that favorable drinker prototypes (i.e., perceptions about the typical drinker) are related to higher levels of alcohol consumption in adolescents and college students. So far, few studies have experimentally tested the causality of this relationship and it is not clear what type of manipulation affects drinker prototypes and drinking levels. METHODS: In an experimental 1-factor design with two levels, we tested the short-term effects of exposing students to either positive or negative stereotypic information about drinkers on their drinker prototypes and actual drinking behaviors. We exposed 192 male and female college students to positive drinker prototype information (drinkers in general were presented as being attractive, sociable and successful), or to negative information (unattractive, unsociable and unsuccessful). Subsequently, participants' levels of alcohol consumption were observed unobtrusively while they were interacting with peers in a naturalistic drinking context, namely a bar lab. RESULTS: Participants exposed to positive stereotypic information about drinkers reported more favorable drinker prototypes than participants exposed to negative stereotypic information. Multilevel analyses revealed that men's subsequent alcohol consumption in the bar lab was higher in the positive prototype condition than in the negative prototype condition. For women, no prototype effects on alcohol use were found. CONCLUSIONS: These findings underline that drinker prototypes affect actual alcohol use in men and suggest that changing perceptions of drinkers may be a useful tool in alcohol prevention programs.