Train-METASTRA is a retrospective study that will be performed in order to collect a large and harmonised amount of clinical and imaging data concerning vertebral metastases, focusing in particular on the risk of fractures. This type of dataset will be created from the medical records of 2000 patients admitted in the last ten years in the four European clinical centers participating in METASTRA project: "COMPUTER-AIDED EFFECTIVE FRACTURE RISK STRATIFICATION OF PATIENTS WITH VERTEBRAL METASTASES FOR PERSONALISED TREATMENT THROUGH ROBUST COMPUTATIONAL MODELS VALIDATED IN CLINICAL SETTINGS", funded by the European Union under the call "HORIZON-HLTH-2022-TOOL-12-two-stage/Computational models for new patient stratification strategies". The project is coordinated by the University of Bologna (UNIBO) (PI prof. Luca Cristofolini) and involves 15 European partners, including Sarl Voisin Consulting Life Sciences VCLS, University of Szeged (Hungary), University of Sheffield (UK) and FrontEndART (Hungary). This type of dataset is not currently available in the literature and it will be pivotal to the development of the METASTRA computational models for the stratification of the risk of fracture of patients affected by spinal metastases.
Study Type
OBSERVATIONAL
Enrollment
356
Extraction of clinical and radiographic data related to patients' history from medical records
Charite - Universitaetsmedizin Berlin
Berlin, Germany
Budai Egeszsegkozpont Zrt
Budapest, Hungary
Universitair Medisch Centrum Utrecht
Utrecht, Netherlands
risk factors for vertebral fracture
The primary objective of the study is to identify the main relevant characteristics to be used for stratifying the patients with vertebral metastases based on their risk of fracture.
Time frame: at the baseline
risk factors for vertebral fracture
The primary objective of the study is to identify the main relevant demographic, clinical and radiographic characteristics to be used for stratifying the patients with vertebral metastases based on their risk of fracture.
Time frame: through study completion, an average of 1 year
Critical metastases
To classify critical metastases
Time frame: after 1 year
AI-based models
To train the data-driven computational models (METASTRA-AI) developed within the project
Time frame: after 1 year
Physiology-based biomechanical models
To inform the physiology-based biomechanical models (METASTRA-VPH) developed within the project
Time frame: after 1 year
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