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Comparative study with new accuracy metrics for target volume contouring in PET image guided radiation therapy

  • Tony Shepherd
  • , Mika Teras
  • , Reinhard R. Beichel
  • , Ronald Boellaard
  • , Michel Bruynooghe
  • , Volker Dicken
  • , Mark J. Gooding
  • , Peter J. Julyan
  • , John A. Lee
  • , Sébastien Lefevre
  • , Michael Mix
  • , Valery Naranjo
  • , Xiaodong Wu
  • , Habib Zaidi
  • , Ziming Zeng
  • , Heikki Minn
  • University of Turku
  • University of Iowa
  • SenoCAD Research GmbH
  • FraunhoferMEVIS-Institute ForMedical Image Computing
  • Mirada Medical
  • The Christie NHS Foundation Trust
  • Université catholique de Louvain
  • Université de Bretagne Sud
  • University Hospital Freiburg
  • Labhuman Inter-University Research Institute for Bioengineering
  • University of Geneva
  • Aberystwyth University

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The impact of positron emission tomography (PET) on radiation therapy is held back by poor methods of defining functional volumes of interest. Many new software tools are being proposed for contouring target volumes but the different approaches are not adequately compared and their accuracy is poorly evaluated due to the ill-definition of ground truth. This paper compares the largest cohort to date of established, emerging and proposed PET contouring methods, in terms of accuracy and variability. We emphasize spatial accuracy and present a new metric that addresses the lack of unique ground truth. Thirty methods are used at 13 different institutions to contour functional volumes of interest in clinical PET/CT and a custom-built PET phantom representing typical problems in image guided radiotherapy. Contouring methods are grouped according to algorithmic type, level of interactivity and how they exploit structural information in hybrid images. Experiments reveal benefits of high levels of user interaction, as well as simultaneous visualization of CT images and PET gradients to guide interactive procedures. Method-wise evaluation identifies the danger of over-automation and the value of prior knowledge built into an algorithm.

Original languageEnglish
Article number6211429
Pages (from-to)2006-2024
Number of pages19
JournalIEEE transactions on medical imaging
Volume31
Issue number11
DOIs
Publication statusPublished - 1 Dec 2012

Keywords

  • Human computer interaction
  • image segmentation
  • oncology
  • performance evaluation
  • phantoms
  • positron emission tomography (PET)

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