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Vienna, Austria

ESTRO 2025

Session

Radiomics, functional and biological imaging and outcome prediction
Digital Poster
Physics
Improving DVH based analysis of clinical outcomes using modern statistical techniques. A systematic answer to multiple comparisons concerns
Mirek Fatyga, USA
E25-4
Using post-radiotherapy MRI T2-maps to automatically detect and localize radiation-induced pneumonitis in lung tumor patients
Christopher Kurz, Germany
E25-884
Prostate R2* measurements on an MR-Linac are repeatable and sensitive to treatment-induced changes
Christopher Moore, United Kingdom
E25-900
Non-invasive Prediction of Secondary Enucleation Risk in Uveal Melanoma Based on Pretreatment CT and MR Imaging Prior to Stereotactic Radiotherapy
Yagiz Yedekci, Turkey
E25-959
Impact of intrinsic phenotypes and therapies on cancer prognosis: stratifying patients and tailoring treatments in precision medicine
Qijian Lu,
E25-1054
Longitudinal analysis of radiomic features in liver cancer patients treated with magnetic resonance-guided radiotherapy (MRgRT)
Alina Paunoiu, Switzerland
E25-1091
Attention-based vision classifier to predict late radiation toxicity from MR images acquired early after radiotherapy of a murine model
Bao Ngoc Huynh, Norway
E25-1242
a preliminary study of radiation enteritis associated with temporal sequencing of total neoadjuvant therapy in locally advanced rectal cancer
Chenying Ma, China
E25-1286
Temporal validation of [18F]FDG PET-radiomic models for distant-relapse-free-survival after radio-chemotherapy for pancreatic adenocarcinoma
Monica Maria Vincenzi, Italy
E25-1436
Texture analysis of optical coherence tomography angiography for detecting microstructural changes in skin cancer lesions post kV-based radiotherapy
Gerd Heilemann, Austria
E25-1444
A.I. generated prediction model for treatment response after SBRT in melanoma brain metastases
Donato Pezzulla, Italy
E25-1449
Predicting Hematologic Toxicity in Advanced Cervical Cancer Patients Using Interpretable Machine Learning Models Based on Radiomics and Dosimetrics
Qianxi Ni, China
E25-103
Predicting Tumor Voxel Dose-Response of Head and Neck Cancer Using Deep Learning: Impact of FDG-PET Imaging Feedback Timing and HPV Status
Shupeng Chen, USA
E25-1663
Unsupervised machine-learning identifies patient clusters associated to treatment response after SBRT in oligometastatic gynaecological cancer
Savino Cilla, Italy
E25-1876
Repeatability and reproducibility of diffusion-weighted MRI of rectal cancer on a MR-Linac
Jonas Habrich, Germany
E25-1945
Deep learning-based recurrence prediction of nasopharyngeal carcinoma
Weigang Hu, China
E25-1955
Machine learning decision tree models for multiclass classification prognosis after palliative radiotherapy in patient with advanced cancer.
Costanza Maria Donati, Italy
E25-1988
Radiomics-based explainable artificial intelligence to predict treatment response following lung stereotactic body radiation therapy
Savino Cilla , Italy
E25-2012
Planning CT radiomic features for predicting loco-regional recurrence in head-and-neck cancer
Ceilidh Welsh, United Kingdom
E25-2047
CT image based multi-task deep learning model to predict treatment response and overall survival of esophageal squamous cell carcinoma
Qiang Cao, China
E25-2232
Machine Learning Algorithms for Predicting Risk of Recurrence After Total Neoadjuvant Therapy in Locally Advanced Rectal Cancer
Ricardo Oyarzun Silva, Spain
E25-2238
Z-Rad: the swiss pocket knife for radiomics
Maksym Fritsak, Switzerland
E25-264
Evaluating secondary cancer risk of prostate radiotherapy treatments using a reparametrized version of Shuryak's model
Beatriz Sanchez Nieto, Chile
E25-2247
Machine Learning-Based Prediction of Dermatitis in Hypofractionated Breast Radiotherapy Patients: Combined Clinical, Radiomic, and Dosiomic Analysis
Yen-Ting Liu, Taiwan
E25-2283
Multi-omics-based prognostic prediction for locally advanced hypopharyngeal cancer treated with postoperative chemoradiotherapy: a dual-center study
Sixue Dong, China
E25-2295
Voxel-based analysis for better predicting genitourinary toxicity after stereotactic prostate reirradiation
Carlos Sosa-Marrero, France
E25-2336
Exploring MR-Linac data using classic neuroimaging fMRI analysis
Peter Koopmans, The Netherlands
E25-2409
Deep learning enables accurate quantification of imaging biomarkers from intravoxel incoherent motion modelling with a clinical set of b-values
Marte Kåstad Høiskar, Norway
E25-2557
Texture Feature Stability and Reproducibility for Assessment of Early Radiotherapy Response in Uterine Cervical Cancer
Ulrika Björeland, Sweden
E25-2564
A technical framework aiding quantitative evaluations of contrast-enhanced T1-weighted MRI after proton therapy: a feasibility study on meningioma
Alessia Bazani, Italy
E25-2671
Tumor nuclear size as a biomarker for post-radiotherapy survival in gynecological malignancy: development of a multivariable prediction model
Shirin A. Enger, Canada
E25-2825
Development of Multi-organ Dual-Omics machine learning models for predicting trismus in post-radiotherapy nasopharyngeal carcinoma patients
Si Wing Tsui, Hong Kong (SAR) China
E25-277
Deep Radiomic Analyses of Genomics and Oncologic Scans (DRAGONs)
Pritha Roy, India
E25-2935
Voxel-Based Analysis for Predicting Recurrence in Post-Operative Glioblastoma Using Magnetic Resonance Spectroscopy Imaging: Beyond the Cho/NAA Ratio
Wafae Labriji, France
E25-2965
Spinal cord toxicity following reirradiation: an NTCP model accounting for recovery
Vitali Moiseenko, USA
E25-3016
Artificial intelligence quantification of tumour lymphocyte infiltration enables colorectal cancer patients stratification to predict survival
Zhuoyan Shen, United Kingdom
E25-3078
Quantitative MR and delta-radiomics for longitudinal monitoring of treatment response following prostate cancer radiation therapy
Annette Haworth, Australia
E25-3317
Exploring the performance gap between GTV and radiological lesion-based radiomics predicting adenoid cystic carcinoma progression after proton therapy
Silvia Molinelli, Italy
E25-3352
3D Printing a Textured Radiomics Phantom for CT Scanner Analysis
Peter McHale, United Kingdom
E25-3373
Temporal analysis of 4DCT subregional respiratory dynamics based on machine learning for lung function assessment
Zihan Li, Hong Kong (SAR) China
E25-3427
Spatial and temporal changes in functional magnetic resonance imaging parameters in cervical cancer chemoradiotherapy
Mohammed Abdul-Latif, United Kingdom
E25-3474
Can perfusion MRI improve radiotherapy target delineation of glioblastoma?
Alejandra Mendez Romero, The Netherlands
E25-3496
Diffusion Weighted Imaging Acquired on MR-LINACs in MR-guided Radiotherapy: A Systematic Review
Darren MC Poon, Hong Kong (SAR) China
E25-386
Radiomics in Preoperative Evaluation of Thymic Epithelial Tumours: An Indian Context
Hannah Thomas, India
E25-3516
Technical and biological validation of prostate ADC measured on an MR-Linac: comparisons with a diagnostic MR scanner and with histology
Christopher Moore, United Kingdom
E25-3585
Radiomics for Therapeutic Planning in Laryngeal Cancer: Predicting Cartilage Invasion on Preoperative CT
Cesare Guida, Italy
E25-3661
AI-assisted quantitative CT analysis of pulmonary changes after single-fraction, breath-hold SABR for peripheral lung tumors
Omar Bohoudi, The Netherlands
E25-3694
Artificial Intelligence in the prediction of clinical response in patients with COVID-19 pneumonia treated with low-dose pulmonary radiotherapy.
Victor Hernandez, Spain
E25-3738
Construction and Validation of a Transformer-based Integrated Model for Predicting Radiation-Induced Lung Injury in Elderly Esophageal Cancer Patients
Xin Yang, China
E25-3774
Multi-modality AI predictor of lung cancer immunotherapy treatment response of Durable Response (DR)
Jue Jiang, USA
E25-3820
AI-based metrics detecting the impact on outcome of individual variability in contouring CTV
Gabriele Palazzo, Italy
E25-3831
Machine learning integration for prognostic modeling in PSMA-PET-driven salvage radiotherapy for biochemical recurrence post-prostatectomy
Alessio Giuseppe Morganti, Italy
E25-3878
Prototyping digital twins for radiotherapy: patient-specific microvasculature and its evolution during treatment
Luca Possenti, Italy
E25-3941
SBRT in oligometastatic patients: radiomics for predicting local control
CAROLINA DE LA PINTA, Spain
E25-530
Tumor Early Response to Radiotherapy Associates with Peritumoral Microbiota Composition in Oropharyngeal Cancer Patients
Benedetta Dionisi Ferrera, Italy
E25-4077
Principal component analysis improves performances of survival models using radiomics and deep learning
Neo Christopher Chung, Poland
E25-4134
Artificial intelligence and radiomics-based models to predict clinical response to low-dose radiotherapy in arthrodegenerative pathology.
Victor Hernandez, Spain
E25-4438
Overall Survival Prediction in Head and Neck Cancers Leveraging Pre-treatment Clinical Variables and Pathology Reports
Shirin A. Enger, Canada
E25-4524
Perfusion MRI-radiomics for non-invasive differentiation of tumour progression and radionecrosis in stereotactic radiosurgery patients
Catherine Coolens, Canada
E25-4580
Hypoxia mapping from diffusion MRI to differentiate patients with recurrence after peripheral zone prostate cancer radiotherapy
Valentin Septiers, France
E25-686
Developing A Novel Time-to-Event Dosiomics Model to Predict Treatment Failure in NSCLC Patients Receiving Stereotactic Body Radiotherapy
SHUO WANG, USA
E25-709
Quantifying robustness of positron emission tomography radiomics features with a dedicated phantom
Joel Poder, Australia
E25-779