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Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Automated MR-only radiotherapy outperforms CT-based radiotherapy and decreases hands-on time for head-and-neck cancer
Iris Lauwers1, Marta Capala1, Sandeep Kaushik2,3
1Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, Netherlands (the).
Introduction:
Cancer incidence is expected to increase in Europe by 18% in eighteen years. To account for the increasing patient numbers, the workload per patient needs to be reduced. One step towards future-proof radiotherapy is automated MR-only radiotherapy as it could eliminate the need for (i) a planning CT and (ii) for manual organ at risk (OAR) delineations. The aim of this study was to evaluate the feasibility of an automated MR-only workflow for head-and-neck radiotherapy.
Method:
Automated MR-only radiotherapy consisted of a Zero-Echo-Time-based synthetic CT for dose calculations and automated T2w-based OAR delineations. Automated MR-Only RT was compared to the clinical workflow consisting of CT-based dose calculation and CT-based OAR delineations. Both approaches were benchmarked to a gold standard consisting of the planning CT for dose calculations and manual delineations on the T2w MR scan. Dice similarity coefficients (DSC), 95% Hausdorff distances and absolute DVH metrics were compared between the clinical and MR-only workflow using a linear mixed-effect model. A p-value < 0.05 was deemed significant.
Results:
Seventeen head-and-neck cancer patients were included. The automated MR-only delineations were more accurate compared to the clinical CT delineations (DSC of 0.79 vs. 0.67; 95% Hausdorff distance 4.0 vs 5.8 mm (p-values < 0.001)). The average dose calculation errors of the automated MR only RT were smaller than the clinical workflow (+0.34 Gy vs. -1.39 (p-value < 0.01)).
Discussion:
The automated MR-only head-and-neck radiotherapy workflow was more accurate than the standard CT based clinical workflow, demonstrating the feasibility of automated MR-only RT to decrease the workload for head-and-neck RT treatment preparation.
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