Dosimetric Effects Due to Inter-Observer Variability of Organ Contouring When Utilizing a Knowledge-Based Planning System for Prostate Cancer

Purpose: Radiotherapy is a widely accepted standard of care for early-stage prostate cancer, and it is believed that the plan quality and treatment outcome are associated with contour accuracy of both the target and organs-at-risk (OAR). The purposes of this study are to 1) assess geometric and dosimetric uncertainties due to inter-observer contour variabilities and 2) evaluate the effectiveness of geometric indicators to predict target dosimetry in prostate radiotherapy. Methods: Twenty prostate patients were selected for this retrospective study. Five experienced clinicians created unique structure sets containing prostate, seminal vesicles, bladder, and rectum for each patient. A fully automated script and knowledge-based planning routine were utilized to create standardized and unbiased plans that could be used to evaluate changes in isodose distributions due to inter-observer variability in structure segmentation. Plans were created on a “gold-standard” structure set, as well as on each of the user-defined structure sets. Results: Inter-observer variability of contours during structure segmentation was very low for clearly defined organs such as the bladder but increased for organs without well-defined borders (prostate, seminal vesicles, and rectum). For plans generated with the user-defined structure sets, strong/moderate correlations were observed between the geometric indicators for target structure agreement and target coverage for both low-risk and intermediate-risk patient groups, while OAR indicators showed no correlation to final dosimetry. Conclusions: Target delineation is crucial in order to maintain adequate dosimetric coverage regardless of the associated inter-observer uncertainties in OAR contours that had a limited impact upon final dosimetry.

Automated Linac QA Using Scripting and Varian Developer Mode

Purpose: Linac quality assurance (QA) can be time consuming involving set up, execution, analysis and subject to user variability. The purpose of this study is to develop qualitative automation tools for mechanical and imaging QA to improve efficiency, consistency, and accuracy. Methods and Materials: Traditionally QA has been performed with graph paper, film, and multiple phantoms. Analysis consists of ruler and vendor provided software. We have developed a single four-phantom method for QA procedures including light-radiation coincidence, imaging quality, table motion and Isocentricity and separately cone beam computed tomography. XML scripts were developed to execute a series of tasks using Varian’s Truebeam Developer Mode. Non-phantom QA procedures have also been developed including field size, dose rate, MLC position, MLC and gantry speed, star shot, Winston-Lutz and Half Beam Block. All analysis is performed using inhouse MATLAB codes. Results: Overall time savings were 2.2 hours per Linac per month. Consistency improvements (standard deviation, STD) were observed for some tests. For example: field size improved from 0.11 mm to 0.04 mm and table motion improved from 0.17 mm to 0.12 mm. CBCT STD improved from 0.99 mm to 0.61 mm for slice thickness. No STD change was observed for Isocentricity test. We noticed an increase in STD from 0.33 mm to 0.41 mm for light-radiation coincidence test. There was a small drop in field size accuracy. Isocentricity showed an increase in measurement accuracy from 0.47 mm to 0.15 mm. Table motion increased in accuracy from 0.20 mm to 0.16 mm. Conclusion: Automation is a viable, accurate and efficient option for monthly and annual QA.