MICCAI HECKTOR 2022

The video of the scientific session at MICCAI 2022 is available on the Pathable platform:
https://miccai2022.pathable.eu/meetings/virtual/t4aGBCzfXxNNLkNSj

Following the success of the first two editions of the HECKTOR challenge in 2020 and 2021, this challenge will be presented at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. Two tasks are proposed this year (participants can choose to participate in either or both tasks):

Task 1: The automatic segmentation of Head and Neck (H&N) primary tumors and lymph nodes (new!) in FDG-PET/CT images;
Task 2: The prediction of patient outcomes, namely Recurrence-Free Survival (RFS) from the FDG-PET/CT images and available clinical data.

Head and Neck (H&N) cancers are among the most common cancers worldwide (5th leading cancer by incidence) [Parkin et al. 2005]. Radiotherapy combined with cetuximab has been established as standard treatment [Bonner et al. 2010]. However, locoregional failures remain a major challenge and occur in up to 40% of patients in the first two years after the treatment [Chajon et al. 2013]. Recently, several radiomics studies based on Positron Emission Tomography (PET) and Computed Tomography (CT) imaging were proposed to better identify patients with a worse prognosis in a non-invasive fashion and by exploiting already available images such as these acquired for diagnosis and treatment planning [Vallières et al. 2017; Bogowicz et al. 2017; Castelli et al. 2017]. Although highly promising, these methods were validated on 100-400 patients. Further validation on larger cohorts (e.g. 500-3000 patients) is required to ensure an adequate ratio between the number of variables and observations in order to avoid an overestimation of the generalization performance. Achieving such a validation requires the manual delineation of primary tumors and nodal metastases for every patient and in three dimensions, which is intractable and error-prone.

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