V A Andrianarison1, M Laouiti2, O Fargier-Bochaton3, G Dipasquale3, X Wang4, N P Nguyen5, R Miralbell3, V Vinh-Hung6. 1. Radiation Oncology, CHU de Martinique, boulevard Pasteur, 97200 Fort-de-France, Martinique; Joseph-Ravoahangy-Andrianavalona University Hospital, Antananarivo 101, Madagascar. 2. Radiation Oncology, hôpital Fribourgeois, 1708 Fribourg, Switzerland. 3. Radiation Oncology, Geneva University Hospitals, 1205 Geneva, Switzerland. 4. Radiation Oncology, Tianjin Union Medical Center, Tianjin 300121, China. 5. Radiation Oncology, Howard University Hospital, Washington DC 20060, United States. 6. Radiation Oncology, CHU de Martinique, boulevard Pasteur, 97200 Fort-de-France, Martinique. Electronic address: anhxang@gmail.com.
Abstract
PURPOSE: To measure the impact of contouring on worktime in the adjuvant radiation treatment of breast cancer, and to identify factors that might affect the measurements. MATERIAL AND METHODS: The dates and times of contouring clinical target volumes and organs at risk were recorded by a senior and by two junior radiation oncologists. Outcome measurements were contour times and the time from start to approval. The factors evaluated were patient age, type of surgery, radiation targets and setup, operator, planning station, part of the day and day of the week on which the contouring started. The Welch test was used to comparatively assess the measurements. RESULTS: Two hundred and three cases were included in the analysis. The mean contour time per patient was 34minutes for a mean of 4.72 structures, with a mean of 7.1minutes per structure. The clinical target volume and organs at risk times did not differ significantly. The mean time from start to approval per patient was 29.4hours. Factors significantly associated with longer contour times were breast-conserving surgery (P=0.026), prone setup (P=0.002), junior operator (P<0.0001), Pinnacle planning station (P=0.026), contouring start in the morning (P=0.001), and contouring start by the end of the week (P<0.0001). Factors significantly associated with time from start to approval were age (P=0.038), junior operator (P<0.0001), planning station (P=0.016), and contouring start by the end of the week (P=0.004). CONCLUSION: Contouring is a time-consuming process. Each delineated structure influences worktime, and many factors may be targeted for optimization of the workflow. These preliminary data will serve as basis for future prospective studies to determine how to establish a cost-effective solution.
PURPOSE: To measure the impact of contouring on worktime in the adjuvant radiation treatment of breast cancer, and to identify factors that might affect the measurements. MATERIAL AND METHODS: The dates and times of contouring clinical target volumes and organs at risk were recorded by a senior and by two junior radiation oncologists. Outcome measurements were contour times and the time from start to approval. The factors evaluated were patient age, type of surgery, radiation targets and setup, operator, planning station, part of the day and day of the week on which the contouring started. The Welch test was used to comparatively assess the measurements. RESULTS: Two hundred and three cases were included in the analysis. The mean contour time per patient was 34minutes for a mean of 4.72 structures, with a mean of 7.1minutes per structure. The clinical target volume and organs at risk times did not differ significantly. The mean time from start to approval per patient was 29.4hours. Factors significantly associated with longer contour times were breast-conserving surgery (P=0.026), prone setup (P=0.002), junior operator (P<0.0001), Pinnacle planning station (P=0.026), contouring start in the morning (P=0.001), and contouring start by the end of the week (P<0.0001). Factors significantly associated with time from start to approval were age (P=0.038), junior operator (P<0.0001), planning station (P=0.016), and contouring start by the end of the week (P=0.004). CONCLUSION: Contouring is a time-consuming process. Each delineated structure influences worktime, and many factors may be targeted for optimization of the workflow. These preliminary data will serve as basis for future prospective studies to determine how to establish a cost-effective solution.
Keywords:
Breast; Contouring; Delineation; Délinéation; Organe à risque; Organs at risk; Sein; Target volumes; Temps de travail; Volume cible; Worktime
Authors: Dong Joo Rhee; Carlos E Cardenas; Hesham Elhalawani; Rachel McCarroll; Lifei Zhang; Jinzhong Yang; Adam S Garden; Christine B Peterson; Beth M Beadle; Laurence E Court Journal: Med Phys Date: 2019-09-26 Impact factor: 4.071
Authors: Minsong Cao; Bradley Stiehl; Victoria Y Yu; Ke Sheng; Amar U Kishan; Robert K Chin; Yingli Yang; Dan Ruan Journal: Front Oncol Date: 2020-09-23 Impact factor: 6.244