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Volume 24, Number 2, 2019

Improved error detection using a divided treatment plan in volume modulated arc therapy

Kazuo Tarutani, Masao Tanooka, Hiroshi Doi, Masayuki Fujiwara, Koichiro Yamakado


Aim We sought to improve error detection ability during volume modulated arc therapy (VMAT) by dividing and evaluating the treatment plan. Background VMAT involves moving a beam source delivering radiation to tumor tissue through an arc, which significantly decreases treatment time. Treatment planning for VMAT involves many parameters. Quality assurance before treatment is a major focus of research. Materials and methods We used an established VMAT prostate treatment plan and divided it into 12° × 30° sections. In all the sections, only image data that generated errors in one segment and those that were integrally acquired were evaluated by a gamma analysis. This was done with five different patient plans. Results The integrated image data resulting from errors in each section was 100% (tolerance 0.5 mm/0.5%) in the gamma analysis result in all image data. Division of the treatment plans produced a shift in the mean value of each gamma analysis in the cranial, left, and ventral directions of 94.59%, 98.83%, 96.58%, and the discrimination ability improved. Conclusion The error discrimination ability was improved by dividing and verifying the portal imaging.

Signature: Rep Pract Oncol Radiother, 2019; 24(2) : 133-141

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