Abstract
Background: Advances in the field of radiotherapy planning have led to faster and more accurate planning for patients receiving radiation. One source of this advancement is the use of AI programs to assist with marking target structures and organs at risk (OAR) in a process known as contouring, on patient imaging. This is especially important regarding the HN, given the number and complexity of the organs in this region. Methods: Two AI programs dubbed V1 and V2 were utilized to generate contours for four OAR in Eclipse (v15.5, Varian Medical Systems, Inc.). Contours were generated from computed tomography (CT) images of three separate patients receiving radiotherapy for HN cancer at a rural tertiary care center. Dice Similarity Coefficients (DSC), a measure of the spatial overlap between image sets, were calculated between contours created in a medical student-physician team (denoted the G contours) and the AI program contours. Each CT slice for the G, V1, and V2 contours was also scored by a separate medical physicist and radiation oncologist team; these scores were termed subjective scores (SS). A score of 100% corresponded to all slices being deemed acceptable for radiotherapy planning for a given OAR. Results: The average DSC for the V1 and V2 packages compared to the G contours were 64.6% and 61.6%, respectively (via matched pairs two-tailed t-test: mean difference = -2.98, p-value = 0.03). All SS were above 89%, and the overall average OAR SS were 94.3%, 95.4%, and 92.5% (for the G, V1, and V2 contours, respectively). Two-tailed paired Student’s t-tests between each AI program and the G contours yielded a p-value > 0.05 for the V2 program only. Conclusion: The V1 and V2 auto contouring packages created OAR contours with similar DSC, though the V1 package demonstrated slightly better overlap with the G contours. SS for the V2 program only were not statistically different from the G contours. This implies the V2 package can create clinically useful contours for HN OAR, at the cost of a slightly decreased DSC compared to V1, translating to faster radiotherapy planning, helping both radiotherapy planning teams and patients alike.
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