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. 2019 Jun;37(2):134-142.
doi: 10.3857/roj.2019.00038. Epub 2019 Jun 30.

Auto-segmentation of head and neck organs at risk in radiotherapy and its dependence on anatomic similarity

Anantharaman Ayyalusamy  1   2 , Subramani Vellaiyan  2   3 , Shanmuga Subramanian  1   2 , Arivarasan Ilamurugu  1 , Shyama Satpathy  1 , Mohammed Nauman  1 , Gowtham Katta  1 , Aneesha Madineni  1
Affiliations

Auto-segmentation of head and neck organs at risk in radiotherapy and its dependence on anatomic similarity

Anantharaman Ayyalusamy et al. Radiat Oncol J. 2019 Jun.

Abstract

Purpose: The aim is to study the dependence of deformable based auto-segmentation of head and neck organs-at-risks (OAR) on anatomy matching for a single atlas based system and generate an acceptable set of contours.

Methods: A sample of ten patients in neutral neck position and three atlas sets consisting of ten patients each in different head and neck positions were utilized to generate three scenarios representing poor, average and perfect anatomy matching respectively and auto-segmentation was carried out for each scenario. Brainstem, larynx, mandible, cervical oesophagus, oral cavity, pharyngeal muscles, parotids, spinal cord, and trachea were the structures selected for the study. Automatic and oncologist reference contours were compared using the dice similarity index (DSI), Hausdroff distance and variation in the centre of mass (COM).

Results: The mean DSI scores for brainstem was good irrespective of the anatomy matching scenarios. The scores for mandible, oral cavity, larynx, parotids, spinal cord, and trachea were unacceptable with poor matching but improved with enhanced bony matching whereas cervical oesophagus and pharyngeal muscles had less than acceptable scores for even perfect matching scenario. HD value and variation in COM decreased with better matching for all the structures.

Conclusion: Improved anatomy matching resulted in better segmentation. At least a similar setup can help generate an acceptable set of automatic contours in systems employing single atlas method. Automatic contours from average matching scenario were acceptable for most structures. Importance should be given to head and neck position during atlas generation for a single atlas based system.

Keywords: Head and neck cancer; Organs at risk; Radiotherapy planning.

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Conflict of interest statement

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Figures

Fig. 1.
Fig. 1.
The mean dice similarity index (DSI) scores with error bars for structures from the three matching scenarios.
Fig. 2.
Fig. 2.
Axial and sagittal views of reference and auto contours overlaid on a sample patient for the three scenarios.
Fig. 3.
Fig. 3.
The mean Hausdorff distance (HD) values with error bars for structures from the three matching scenarios.
Fig. 4.
Fig. 4.
Centre of mass for three scenarios: S1, S2, and S3 represent the poor, average, and perfect matching scenarios, respectively.
See this image and copyright information in PMC

References

    1. Chao KS, Bhide S, Chen H, et al. Reduce in variation and improve efficiency of target volume delineation by a computer-assisted system using a deformable image registration approach. Int J Radiat Oncol Biol Phys. 2007;68:1512–21. - PubMed
    1. Reed VK, Woodward WA, Zhang L, et al. Automatic segmentation of whole breast using atlas approach and deformable image registration. Int J Radiat Oncol Biol Phys. 2009;73:1493–500. - PMC - PubMed
    1. Sharp G, Fritscher KD, Pekar V, et al. Vision 20/20: perspectives on automated image segmentation for radiotherapy. Med Phys. 2014;41:050902. - PMC - PubMed
    1. Lim JY, Leech M. Use of auto-segmentation in the delineation of target volumes and organs at risk in head and neck. Acta Oncol. 2016;55:799–806. - PubMed
    1. Ayyalusamy A, Vellaiyan S, Shanmugam S, et al. Feasibility of offline head & neck adaptive radiotherapy using deformed planning CT electron density mapping on weekly cone beam computed tomography. Br J Radiol. 2017;90:20160420. - PMC - PubMed

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