Alexander R Delaney1, Max Dahele2, Ben J Slotman2, Wilko F A R Verbakel2. 1. Cancer Center Amsterdam, Department of Radiation Oncology, VU University Medical Center, The Netherlands. Electronic address: a.delaney@vumc.nl. 2. Cancer Center Amsterdam, Department of Radiation Oncology, VU University Medical Center, The Netherlands.
Abstract
BACKGROUND AND PURPOSE: Current standards for organ-at-risk (OAR) contouring encourage anatomical accuracy which can be resource intensive. Certain OARs may be suitable for alternative delineation strategies. We investigated whether simplified salivary and swallowing structure contouring can still lead to good OAR sparing in automated head and neck cancer (HNC) plans. MATERIALS AND METHODS: For 15 HNC patients, knowledge-based plans (KBPs) using RapidPlan™ were created using: (1) standard clinical contours for all OARs (benchmark-plans), (2) automated knowledge-based contours for the salivary glands, with standard contours for the remaining OARs (SS-plans) and (3) simplified contours (SC-plans) consisting of quick-to-draw tubular structures to account for the oral cavity, salivary glands and swallowing muscles. Individual clinical OAR contours in a RapidPlan™ model were combined to create composite salivary/swallowing structures. These were matched to tube-contours to create SC-plans. All plans were compared based on dose to anatomically accurate clinical OAR contours. RESULTS: Salivary gland delineation in SS-plans required on average 2 min, compared with 7 min for manual delineation of all tubular-contours. Automated atlas-based contours overlapped with, on average, 71% of clinical salivary gland contours while tube-contours overlapped with 95%/75%/93% of salivary gland/oral cavity/swallowing structure contours. On average, SC-plans were comparable to benchmark-plans and SS-plans, with average differences in composite salivary and swallowing structure dose ≤2 Gy and <1 Gy respectively. CONCLUSIONS: Simplified-contours could be created quickly and resulted in clinically acceptable HNC VMAT plans. They can be combined with automated planning to facilitate the implementation of advanced radiotherapy, even when resources are limited.
BACKGROUND AND PURPOSE: Current standards for organ-at-risk (OAR) contouring encourage anatomical accuracy which can be resource intensive. Certain OARs may be suitable for alternative delineation strategies. We investigated whether simplified salivary and swallowing structure contouring can still lead to good OAR sparing in automated head and neck cancer (HNC) plans. MATERIALS AND METHODS: For 15 HNC patients, knowledge-based plans (KBPs) using RapidPlan™ were created using: (1) standard clinical contours for all OARs (benchmark-plans), (2) automated knowledge-based contours for the salivary glands, with standard contours for the remaining OARs (SS-plans) and (3) simplified contours (SC-plans) consisting of quick-to-draw tubular structures to account for the oral cavity, salivary glands and swallowing muscles. Individual clinical OAR contours in a RapidPlan™ model were combined to create composite salivary/swallowing structures. These were matched to tube-contours to create SC-plans. All plans were compared based on dose to anatomically accurate clinical OAR contours. RESULTS: Salivary gland delineation in SS-plans required on average 2 min, compared with 7 min for manual delineation of all tubular-contours. Automated atlas-based contours overlapped with, on average, 71% of clinical salivary gland contours while tube-contours overlapped with 95%/75%/93% of salivary gland/oral cavity/swallowing structure contours. On average, SC-plans were comparable to benchmark-plans and SS-plans, with average differences in composite salivary and swallowing structure dose ≤2 Gy and <1 Gy respectively. CONCLUSIONS: Simplified-contours could be created quickly and resulted in clinically acceptable HNC VMAT plans. They can be combined with automated planning to facilitate the implementation of advanced radiotherapy, even when resources are limited.
Authors: Michael V Sherer; Diana Lin; Sharif Elguindi; Simon Duke; Li-Tee Tan; Jon Cacicedo; Max Dahele; Erin F Gillespie Journal: Radiother Oncol Date: 2021-05-11 Impact factor: 6.901
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Authors: Kimberly J Jasmer; Kristy E Gilman; Kevin Muñoz Forti; Gary A Weisman; Kirsten H Limesand Journal: J Clin Med Date: 2020-12-18 Impact factor: 4.964