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MICCAI 2018 – Computational Precision Medicine Challenge: 18F-FDG PET Radiomics Risk Stratifiers in Head and Neck Cancer

2022·0 Zitationen·FigshareOpen Access
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Abstract

The Computational Precision Medicine (CPM) 2018 was held on September 16, in Granada (Spain), in conjunction with MICCAI 2018. As part of the CPM program, a series of imaging Grand Challenges were offered, hosted by kaggle. <br><br>This competition, "18F-FDG PET Radiomics Risk Stratifiers in Head and Neck Cancer", was organized as a Medical Image Computing and Computer Assisted Intervention (MICCAI) Computational Precision Medicine (CPM) grand challenge. Contestants weretasked to predict, using primary tumor 18F-FDG PET-derived radiomics features +/- matched clinical data, whether a tumor arising from the oropharynx will be controlled by definitive radiation treatment (RT). The head and neck radiation oncology team from University of Texas MD Anderson Cancer Center (MDACC) have curated and harmonized a multi-institutional dataset of 248 oropharynx cancer (OPC) patients, using our in-house 'LAMBDA-RAD' data management platform. Scans came from six different institutes from: the US (MDACC), Canada [four different clinical institutions in Québec: Hôpital Général Juif de Montréal (HGJ), Centre Hospitalier Universitaire de Sherbrooke (CHUS), Centre Hopitalier de l'Université de Montréal (CHUM) and Hôpital Maisonneuve-Rosemont de Montréal (HMR)], and Europe (MAASTRO Clinic, The Netherlands).<br><br>The challenge was open from June 15, 2018, 11:59 p.m. toAug. 30, 2018, midnight UT; this repository serves as FAIR (re)use durable repository for challenge data.<br>Details on the 2018 CPM Challenges can be found at: https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=37224869 <br><br>The "18F-FDG PET Radiomics Risk Stratifiers in Head and Neck Cancer" challenge website (archived) can be viewed at: https://web.archive.org/web/20190106050801/http://miccai.cloudapp.net/competitions/77and at: https://web.archive.org/web/20210418000112/https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=37224869<br>The kaggle-in-class host page for the challenge and results can be found at: https://www.kaggle.com/c/pet-radiomics-challenges.<br><br><br>

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Radiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and ApplicationsArtificial Intelligence in Healthcare and Education
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