title: Automatic contouring of brachial plexus using a multi-atlas approach for lung cancer radiotherapy.
abstract: OBJECTIVE
  To demonstrate a multi-atlas segmentation approach to facilitating accurate and consistent delineation of low-contrast brachial plexuses on CT images for lung cancer radiotherapy.
  
  
  METHODS
  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 (STAPLE) 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 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.
authors.affiliation: Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX.
authors.forename: Jinzhong
authors.initials: J
authors.lastname: Yang
authors.forename: Arya
authors.initials: A
authors.lastname: Amini
authors.forename: Ryan
authors.initials: R
authors.lastname: Williamson
authors.forename: Lifei
authors.initials: L
authors.lastname: Zhang
authors.forename: Yongbin
authors.initials: Y
authors.lastname: Zhang
authors.forename: Ritsuko
authors.initials: R
authors.lastname: Komaki
authors.forename: Zhongxing
authors.initials: Z
authors.lastname: Liao
authors.forename: James
authors.initials: J
authors.lastname: Cox
authors.forename: James
authors.initials: J
authors.lastname: Welsh
authors.forename: Laurence
authors.initials: L
authors.lastname: Court
authors.forename: Lei
authors.initials: L
authors.lastname: Dong
keywords: STAPLE; brachial plexus; deformable image registration; multi-atlas segmentation