ESTRO 2025 - Abstract Book

S1054

Clinical – Head & neck

ESTRO 2025

Conclusion: DL methods demonstrated comparable performance to classical ML approaches. Integrating ClinVars risk scores with CL enhanced WSI embeddings, improving PFS prediction accuracy in cross-validation. Future work will focus on expanding the dataset and optimizing the model to enhance generalizability and performance on the test set.

Keywords: Contrastive Learning, Clin. vars., Histopathology.

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Digital Poster EORTC 2014-HNCG PROLoNg: Pembrolizumab and Radiotherapy for OLigometastatic squamous cell carcinoma of the head and Neck, randomized phase III trial Jordi Giralt 1,2 , Daan Nevens 3 , Irene Brana 4,2 , Raquel Granado 1 , Beatriz Gutierrez 5 , Margarita Martin 6,2 , Jon Cacicedo 7 , Pierluigi Bonomo 8 , Ciro Franzese 9,10 , Nicola Alessandro Iacovelli 11 , Paolo Bossi 12 , Piet Ost 13 , Eleonore Longton 14 , Laurence Goethals 15 , Brigitta G Baumert 16 , Olgun Eliçin 17 , Oliver Riesterer 18 , Frank Zimmermann 19 , Daniel R Zwahlen 20 , Thomas Zilli 21 , Nick Reynaert 22 , Anne-Sophie Govaerts 23 , Enrico Clementel 23 , Jean-Pascal Machiels 24,25 , Panagiotis Balermpas 26 1 Department of Radiation Oncology, Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology, Barcelona, Barcelona, Spain. 2 AECC, Scientific Foundation of the Spanish Association Against Cancer, Madrid, Spain. 3 Iridium Kankernetwerk, Radiation Oncology Department, Universiteit Antwerpen, Antwerp, Belgium. 4 Department of Medical Oncology, Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology, Barcelona, Spain. 5 Department of Radiation Oncology, ICO Badalona, Hospital Universitari Germans Trias i Pujol, Badalona, Spain.