Journal article
Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach
Medical physics (Lancaster), Vol.43(6), pp.2948-2964
06/2016
DOI: 10.1118/1.4948679
PMCID: PMC4874930
PMID: 27277044
Abstract
Purpose:\nThe purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans.\nMethods:\nA semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts.\nResults:\nSegmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach.\nConclusions:\nLack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.
Details
- Title: Subtitle
- Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach
- Creators
- Reinhard R Beichel - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242; The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242; and Department of Internal Medicine, The University of Iowa, Iowa City, Iowa 52242Markus Van Tol - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242Ethan J Ulrich - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242Christian Bauer - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242Tangel Chang - Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242Kristin A Plichta - Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242Brian J Smith - Department of Biostatistics, The University of Iowa, Iowa City, Iowa 52242John J Sunderland - Department of Radiology, The University of Iowa, Iowa City, Iowa 52242Michael M Graham - Department of Radiology, The University of Iowa, Iowa City, Iowa 52242Milan Sonka - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa 52242; Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242; and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242John M Buatti - Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242 and The Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242
- Resource Type
- Journal article
- Publication Details
- Medical physics (Lancaster), Vol.43(6), pp.2948-2964
- DOI
- 10.1118/1.4948679
- PMID
- 27277044
- PMCID
- PMC4874930
- NLM abbreviation
- Med Phys
- ISSN
- 0094-2405
- eISSN
- 2473-4209
- Number of pages
- 17
- Grant note
- P30CA086862; U01CA140206; U24CA180918 / National Cancer Institute (NCI) (http://dx.doi.org/10.13039/100000054)\nR01EB004640 / National Institute of Biomedical Imaging and Bioengineering (NIBIB) (http://dx.doi.org/10.13039/100000070)
- Language
- English
- Date published
- 06/2016
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Biostatistics; Physics and Astronomy; Radiation Oncology; Injury Prevention Research Center; Neurosurgery; Otolaryngology; Holden Comprehensive Cancer Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9983997314802771
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