Journal article
FDG PET based prediction of response in head and neck cancer treatment: Assessment of new quantitative imaging features
PLoS One, Vol.14(4), e0215465
2019
DOI: 10.1371/journal.pone.0215465
PMCID: PMC6474600
PMID: 31002689
Abstract
18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is now a standard diagnostic imaging test performed in patients with head and neck cancer for staging, re-staging, radiotherapy planning, and outcome assessment. Currently, quantitative analysis of FDG PET scans is limited to simple metrics like maximum standardized uptake value, metabolic tumor volume, or total lesion glycolysis, which have limited predictive value. The goal of this work was to assess the predictive potential of new (i.e., nonstandard) quantitative imaging features on head and neck cancer outcome. This retrospective study analyzed fifty-eight pre- and post-treatment FDG PET scans of patients with head and neck squamous cell cancer to calculate five standard and seventeen new features at baseline and post-treatment. Cox survival regression was used to assess the predictive potential of each quantitative imaging feature on disease-free survival. Analysis showed that the post-treatment change of the average tracer uptake in the rim background region immediately adjacent to the tumor normalized by uptake in the liver represents a novel PET feature that is associated with disease-free survival (HR 1.95; 95% CI 1.27, 2.99) and has good discriminative performance (c index 0.791). The reported findings define a promising new direction for quantitative imaging biomarker research in head and neck squamous cell cancer and highlight the potential role of new radiomics features in oncology decision making as part of precision medicine.
Details
- Title: Subtitle
- FDG PET based prediction of response in head and neck cancer treatment: Assessment of new quantitative imaging features
- Creators
- Reinhard R Beichel - University of Iowa, Electrical and Computer EngineeringEthan J Ulrich - University of IowaBrian J Smith - University of Iowa, BiostatisticsChristian Bauer - University of Iowa, Electrical and Computer EngineeringBartley Brown - University of IowaThomas Casavant - University of Iowa, Electrical and Computer EngineeringJohn J Sunderland - University of Iowa, RadiologyMichael M Graham - University of Iowa, RadiologyJohn M Buatti - University of Iowa, Radiation Oncology
- Resource Type
- Journal article
- Publication Details
- PLoS One, Vol.14(4), e0215465
- Publisher
- United States
- DOI
- 10.1371/journal.pone.0215465
- PMID
- 31002689
- PMCID
- PMC6474600
- ISSN
- 1932-6203
- eISSN
- 1932-6203
- Grant note
- U24 CA180918 / NCI NIH HHS UL1 TR002537 / NCATS NIH HHS P30 CA086862 / NCI NIH HHS U01 CA140206 / NCI NIH HHS
- Language
- English
- Date published
- 2019
- Academic Unit
- Neurosurgery; Electrical and Computer Engineering; Biostatistics; Physics and Astronomy; Holden Comprehensive Cancer Center; Roy J. Carver Department of Biomedical Engineering; Radiology; Otolaryngology; Radiation Oncology
- Record Identifier
- 9983769800102771
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