Literature DB >> 24674411

Automatic contouring of brachial plexus using a multi-atlas approach for lung cancer radiation therapy.

Jinzhong Yang1, Arya Amini2, Ryan Williamson3, Lifei Zhang3, Yongbin Zhang3, Ritsuko Komaki4, Zhongxing Liao4, James Cox4, James Welsh4, Laurence Court3, Lei Dong5.   

Abstract

PURPOSE: To demonstrate a multi-atlas segmentation approach to facilitating accurate and consistent delineation of low-contrast brachial plexuses on computed tomographic images for lung cancer radiation therapy. METHODS AND MATERIALS: We retrospectively identified 90 lung cancer patients with treatment volumes near the brachial plexus. Ten representative patients were selected to form an atlas group, and their brachial plexuses were delineated manually. We used deformable image registration to map each atlas brachial plexus to the remaining 80 patients. In each patient, a composite contour was created from 10 individual segmentations using the simultaneous truth and performance level estimation algorithm. This auto-delineated contour was reviewed and modified appropriately for each patient. We also performed 10 leave-one-out tests using the 10 atlases to validate the segmentation accuracy and demonstrate the contouring consistency using multi-atlas segmentation.
RESULTS: The multi-atlas segmentation took less than 2 minutes to complete. Contour modification took 5 minutes compared with 20 minutes for manual contouring from scratch. The multi-atlas segmentation from the 10 leave-one-out tests had a mean 3-dimensional (3D) volume overlap of 59.2% ± 8.2% and a mean 3D surface distance of 2.4 mm ± 0.5 mm. The distances between the individual and average contours in the 10 leave-one-out tests demonstrated much better contouring consistency for modified contours than for manual contours. The auto-segmented contours did not require substantial modification, demonstrated by the good agreement between the modified and auto-segmented contours in the 80 patients. Dose volume histograms of auto-segmented and modified contours were also in good agreement, showing that editing auto-segmented contours is clinically acceptable in view of the dosimetric impact.
CONCLUSIONS: Multi-atlas segmentation greatly reduced contouring time and improved contouring consistency. Editing auto-segmented contours to delineate the brachial plexus proved to be a better clinical practice than manually contouring from scratch.
Copyright © 2013 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2013        PMID: 24674411     DOI: 10.1016/j.prro.2013.01.002

Source DB:  PubMed          Journal:  Pract Radiat Oncol        ISSN: 1879-8500


  14 in total

Review 1.  Vision 20/20: perspectives on automated image segmentation for radiotherapy.

Authors:  Gregory Sharp; Karl D Fritscher; Vladimir Pekar; Marta Peroni; Nadya Shusharina; Harini Veeraraghavan; Jinzhong Yang
Journal:  Med Phys       Date:  2014-05       Impact factor: 4.071

2.  Atlas ranking and selection for automatic segmentation of the esophagus from CT scans.

Authors:  Jinzhong Yang; Benjamin Haas; Raymond Fang; Beth M Beadle; Adam S Garden; Zhongxing Liao; Lifei Zhang; Peter Balter; Laurence Court
Journal:  Phys Med Biol       Date:  2017-11-14       Impact factor: 3.609

3.  Cardiac atlas development and validation for automatic segmentation of cardiac substructures.

Authors:  Rongrong Zhou; Zhongxing Liao; Tinsu Pan; Sarah A Milgrom; Chelsea C Pinnix; Anhui Shi; Linglong Tang; Ju Yang; Ying Liu; Daniel Gomez; Quynh-Nhu Nguyen; Bouthaina S Dabaja; Laurence Court; Jinzhong Yang
Journal:  Radiother Oncol       Date:  2016-12-08       Impact factor: 6.280

4.  Tissue-specific deformable image registration using a spatial-contextual filter.

Authors:  Yongbin Zhang; Lifei Zhang; Laurence E Court; Peter Balter; Lei Dong; Jinzhong Yang
Journal:  Comput Med Imaging Graph       Date:  2020-12-29       Impact factor: 4.790

5.  Impact of slice thickness, pixel size, and CT dose on the performance of automatic contouring algorithms.

Authors:  Kai Huang; Dong Joo Rhee; Rachel Ger; Rick Layman; Jinzhong Yang; Carlos E Cardenas; Laurence E Court
Journal:  J Appl Clin Med Phys       Date:  2021-03-29       Impact factor: 2.102

6.  The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

Authors:  Joris Van de Velde; Johan Wouters; Tom Vercauteren; Werner De Gersem; Eric Achten; Wilfried De Neve; Tom Van Hoof
Journal:  Radiat Oncol       Date:  2015-12-23       Impact factor: 3.481

7.  Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics.

Authors:  Kelly Kisling; Lifei Zhang; Hannah Simonds; Nazia Fakie; Jinzhong Yang; Rachel McCarroll; Peter Balter; Hester Burger; Oliver Bogler; Rebecca Howell; Kathleen Schmeler; Mike Mejia; Beth M Beadle; Anuja Jhingran; Laurence Court
Journal:  J Glob Oncol       Date:  2019-01

8.  Automated treatment planning of postmastectomy radiotherapy.

Authors:  Kelly Kisling; Lifei Zhang; Simona F Shaitelman; David Anderson; Tselane Thebe; Jinzhong Yang; Peter A Balter; Rebecca M Howell; Anuja Jhingran; Kathleen Schmeler; Hannah Simonds; Monique du Toit; Christoph Trauernicht; Hester Burger; Kobus Botha; Nanette Joubert; Beth M Beadle; Laurence Court
Journal:  Med Phys       Date:  2019-07-09       Impact factor: 4.071

9.  Training deep-learning segmentation models from severely limited data.

Authors:  Yao Zhao; Dong Joo Rhee; Carlos Cardenas; Laurence E Court; Jinzhong Yang
Journal:  Med Phys       Date:  2021-02-19       Impact factor: 4.071

10.  Optimal number of atlases and label fusion for automatic multi-atlas-based brachial plexus contouring in radiotherapy treatment planning.

Authors:  Joris Van de Velde; Johan Wouters; Tom Vercauteren; Werner De Gersem; Eric Achten; Wilfried De Neve; Tom Van Hoof
Journal:  Radiat Oncol       Date:  2016-01-07       Impact factor: 3.481

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