7 research outputs found

    Impact of Using Unedited CT-Based DIR-Propagated Autocontours on Online ART for Pancreatic SBRT

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    PURPOSE: To determine the dosimetric impact of using unedited autocontours in daily plan adaptation of patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiotherapy using tumor tracking. MATERIALS AND METHODS: The study included 98 daily CT scans of 35 LAPC patients. All scans were manually contoured (MAN), and included the PTV and main organs-at-risk (OAR): stomach, duodenum and bowel. Precision and MIM deformable image registration (DIR) methods followed by contour propagation were used to generate autocontour sets on the daily CT scans. Autocontours remained unedited, and were compared to MAN on the whole organs and at 3, 1 and 0.5 cm from the PTV. Manual and autocontoured OAR were used to generate daily plans using the VOLOâ„¢ optimizer, and were compared to non-adapted plans. Resulting planned doses were compared based on PTV coverage and OAR dose-constraints. RESULTS: Overall, both algorithms reported a high agreement between unclipped MAN and autocontours, but showed worse results when being evaluated on the clipped structures at 1 cm and 0.5 cm from the PTV. Replanning with unedited autocontours resulted in better OAR sparing than non-adapted plans for 95% and 84% plans optimized using Precision and MIM autocontours, respectively, and obeyed OAR constraints in 64% and 56% of replans. CONCLUSION: For the majority of fractions, manual correction of autocontours could be avoided or be limited to the region closest to the PTV. This practice could further reduce the overall timings of adaptive radiotherapy workflows for patients with LAPC

    Technical feasibility of online adaptive stereotactic treatments in the abdomen on a robotic radiosurgery system

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    BACKGROUND AND PURPOSE: Stereotactic body radiotherapy (SBRT) has been proven to be beneficial for several disease sites in the (lower) abdomen. However, the quality of the treatment plan, based on a single planning computed tomography (CT), can be compromised due to large inter-fraction motion of the target and organs at risk (OARs) in this anatomical region. The aim of this study was to investigate the feasibility of online adaptive SBRT treatments on a robotic radiosurgery system and to record estimated total treatment times. MATERIALS AND METHODS: For two disease sites, locally advanced pancreatic cancer (LAPC) and oligometastatic lymph nodes, four patients with repeat CTs were included in the feasibility study. Quick treatment plan templates were generated based on the planning CT and validated by running them on the plan and fraction CTs. For two cases a dummy run was performed and the individual steps were timed. Dose delivery was the largest contributor to the total treatment time, followed by contour adaptation. RESULTS: Running the quick plan templates resulted in plans similar to unrestricted plans, obeying the OAR constraints. The dummy runs showed that online adaptive treatments were completed in 64 to 83 min respectively for oligometastases and LAPC, comparable to other clinically available solutions. CONCLUSIONS: This study showed the feasibility of online re-planning for two challenging disease sites within a clinically acceptable time frame on a robotic radiosurgery system, making use of commercially available elements that are not integrated by the vendor

    Comparison of Daily Online Plan Adaptation Strategies for a Cohort of Pancreatic Cancer Patients Treated with SBRT

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    Purpose: To study the trade-offs of three online strategies to adapt treatment plans of patients with locally advanced pancreatic carcinoma (LAPC) treated using the CyberKnife with tumor tracking. Methods and Materials: A total of 35 planning computed tomography scans and 98 daily in-room computed tomography scans were collected from 35 patients with LAPC. Planned dose distributions, optimized with VOLO, were evaluated on manually contoured daily anatomies to collect daily doses. Three strategies were tested to adapt treatment plans: (1) unrestricted full replanning using a patient-specific plan template, (2) time-restricted replanning on organs at risk (OARs) within 3 cm from the planning target volume (PTV) structure, and (3) dose realignment optimization to stay within OAR constraints. Dose distributions resulting from each plan adaptation strategy were dosimetrically compared by means of gross tumor volume (GTV), PTV coverage, and OAR tolerances. Results: Planned doses did not result in dose-constraint violations for 28 of 98 daily anatomies. None of the suggested plan adaptation strategies improved planned doses significantly for this subset. For 70 of the 98 reported violations, the median (interquartile range) PTV coverage of the planned dose was 84% (76% to 86%). After plan adaptation, unrestricted replanning achieved clinically acceptable plans in 93% of these fractions, time-restricted replanning in 90%, and dose realignment in 74%, at median computational times of 8.5, 3, and 0.5 minutes. Over all 98 fractions, PTV coverage was reduced: –1% (–3% to 1%), –2% (–5% to 0%), and –2% (–8% to 0%) after each strategy, respectively. In 3 of 70 fractions, none of the suggested strategies achieved clinically acceptable OAR dose volumes. Conclusions: Unrestricted replanning was the most time-consuming method but reached the highest number of successfully adapted plans. Time-restricted replanning and dose realignment resulted in a high number of plans within dose constraints. Depending on the resources available, an adaptive strategy can be selected for each patient to address the specific anatomic challenges on the treatment day. The increase in the complexity of the strategy corresponds with an increasing number of successfully adapted plans
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