Abstract

Background: While atlas segmentation (AS) has proven to be a time-saving and promising method for radiation therapy contouring, optimal methods for its use have not been well-established. Therefore, we investigated the relationship between the size of the atlas patient population and the atlas segmentation auto contouring (AC) performance.Methods: A total of 110 patients' head planning CT images were selected. The mandible and thyroid were selected for this study. The mandibles and thyroids of the patient population were carefully segmented by two skilled clinicians. Of the 110 patients, 100 random patients were registered to 5 different atlas libraries as atlas patients, in groups of 20 to 100, with increments of 20. AS was conducted for each of the remaining 10 patients, either by simultaneous atlas segmentation (SAS) or independent atlas segmentation (IAS). The AS duration of each target patient was recorded. To validate the accuracy of the generated contours, auto contours were compared to manually generated contours (MC) using a volume-overlap-dependent metric, Dice Similarity Coefficient (DSC), and a distance-dependent metric, Hausdorff Distance (HD).Results: In both organs, as the population increased from n = 20 to n = 60, the results showed better convergence. Generally, independent cases produced better performance than simultaneous cases. For the mandible, the best performance was achieved by n = 60 [DSC = 0.92 (0.01) and HD = 6.73 (1.31) mm] and the worst by n = 100 [DSC = 0.90 (0.03) and HD = 10.10 (6.52) mm] atlas libraries. Similar results were achieved with the thyroid; the best performance was achieved by n = 60 [DSC = 0.79 (0.06) and HD = 10.17 (2.89) mm] and the worst by n = 100 [DSC = 0.72 (0.13) and HD = 12.88 (3.94) mm] atlas libraries. Both IAS and SAS showed similar results. Manual contouring of the mandible and thyroid required an average of 1,044 (±170.15) seconds, while AS required an average of 46.4 (±2.8) seconds.Conclusions: The performance of AS AC generally increased as the population of the atlas library increased. However, the performance does not drastically vary in the larger atlas libraries in contrast to the logic that bigger atlas library should lead to better results. In fact, the results do not vary significantly toward the larger atlas library. It is necessary for the institutions to independently research the optimal number of subjects.

Highlights

  • Manual contouring of target and critical structures is resource intensive aspect of the radiotherapy planning process

  • We focused on evaluating the optimal number of atlas patients (AP) required by the atlas library to automatically generate accurate segmentation volume for the mandible and thyroid in head and neck cancer treatment

  • Resulting auto contouring (AC) of mandible and thyroid were compared with the gold standard manually segmented contours (MC) to achieve mean Dice Similarity Coefficient (DSC) and mean Hausdorff Distance (HD)

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Summary

Introduction

Manual contouring of target and critical structures is resource intensive aspect of the radiotherapy planning process. Atlas segmentation involves the process of aligning the target patient (TP) to the “template” patient through “template alignment” for the contours available within the atlas library. Once the contours are aligned to the anatomical structures of TP, these contours will undergo “label fusion” process, where deformation of the contours of selected AP is performed to match the anatomical structure of the TP. This overall process of atlas segmentation enables automatic segmentation for OAR and target contouring with considerable accuracy. To our knowledge, there have been no studies regarding the optimal number of patients needed to populate an atlas library for auto-segmentation, or regarding a reasonable explanation for patient characteristics. We investigated the relationship between the size of the atlas patient population and the atlas segmentation auto contouring (AC) performance

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