Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges

MICCAI/M.D. Anderson Cancer Center Head and Neck Quantitative Imaging Working Group

doi:10.1038/sdata.2017.77

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Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges

Journal article

Open access

Peer reviewed

Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges

MICCAI/M.D. Anderson Cancer Center Head and Neck Quantitative Imaging Working Group

Scientific data, Vol.4(1), pp.170077-170077

07/04/2017

DOI: 10.1038/sdata.2017.77

PMCID: PMC5497772

PMID: 28675381

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https://doi.org/10.1038/sdata.2017.77View

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Abstract

Cancers arising from the oropharynx have become increasingly more studied in the past few years, as they are now epidemic domestically. These tumors are treated with definitive (chemo)radiotherapy, and have local recurrence as a primary mode of clinical failure. Recent data suggest that ‘radiomics’, or extraction of image texture analysis to generate mineable quantitative data from medical images, can reflect phenotypes for various cancers. Several groups have shown that developed radiomic signatures, in head and neck cancers, can be correlated with survival outcomes. This data descriptor defines a repository for head and neck radiomic challenges, executed via a Kaggle in Class platform, in partnership with the MICCAI society 2016 annual meeting.These public challenges were designed to leverage radiomics and/or machine learning workflows to discriminate HPV phenotype in one challenge (HPV status challenge) and to identify patients who will develop a local recurrence in the primary tumor volume in the second one (Local recurrence prediction challenge) in a segmented, clinically curated anonymized oropharyngeal cancer (OPC) data set.

Medical Imaging

Data Descriptor

Head and neck cancer

Predictive markers

Cancer imaging

Details

Title: Subtitle: Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges
Creators: MICCAI/M.D. Anderson Cancer Center Head and Neck Quantitative Imaging Working Group
Contributors: Guadalupe M Canahuate (Contributor) - University of Iowa, Electrical and Computer Engineering
Resource Type: Journal article
Publication Details: Scientific data, Vol.4(1), pp.170077-170077
DOI: 10.1038/sdata.2017.77
PMID: 28675381
PMCID: PMC5497772
NLM abbreviation: Sci Data
ISSN: 2052-4463
eISSN: 2052-4463
Publisher: Nature Publishing Group
Language: English
Date published: 07/04/2017
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984083245402771

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