ESTRO 2024 - Abstract Book

S1233

Clinical - Head & neck

ESTRO 2024

In our present study, multi-Omics models manifested better prognostic performance than monomics models for the laryngeal cancer with a small sample. Besides, Various integration methodologies yielded different outcomes, and a machine learning- based ‘soft voting’ integration technique showed the best performance.

Keywords: Laryngeal cancer, Prognostic model, Multi-Omics

References:

1. van Griethuysen, J.J.M., et al., Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Research, 2017. 77(21): p. e104-e107.

2. Zwanenburg, A., et al., The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. Radiology, 2020. 295(2): p. 328-338.

3. Morelli, L., et al., A Dosiomics Analysis Based on Linear Energy Transfer and Biological Dose Maps to Predict Local Recurrence in Sacral Chordomas after Carbon-Ion Radiotherapy. Cancers, 2022. 15(1).

4. Lecler, A., et al., Combining Multiple Magnetic Resonance Imaging Sequences Provides Independent Reproducible Radiomics Features. Scientific Reports, 2019. 9(1): p. 2068.

5. Kumari, S., D. Kumar, and M. Mittal, An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier. International Journal of Cognitive Computing in Engineering, 2021. 2: p. 40-46.

6. Liu, J., et al. Predictive Classifier for Cardiovascular Disease Based on Stacking Model Fusion. Processes, 2022. 10, DOI: 10.3390/pr10040749.

7. Boehm, K.M., et al., Harnessing multimodal data integration to advance precision oncology. Nat Rev Cancer, 2022. 22(2): p. 114-126.

931

Digital Poster

Clinical Outcome of PBS Proton Therapy in patients with sinonasal undifferentiated carcinoma

Alexey Cherchik 1 , Damien Charles Weber 1,2,3 , Barbara Bachtiary 1

1 Paul Scherrer Institute, Center for Proton Therapy, Villigen, Switzerland. 2 Bern University Hospital, University of Bern, Radiation Oncology, Inselspital, Bern, Switzerland. 3 University Hospital of Zurich, University of Zurich, Radiation Oncology, Zurich, Switzerland

Purpose/Objective:

To evaluate the effectiveness and tolerability of high-dose pencil beam scanning proton therapy (PBS-PT) for the treatment of sinonasal undifferentiated carcinoma (SNUC).