Enhanced Diagnostic Imaging and Clinical Tools for Sarcoma Advanced Risk Calculation and Outcome Model Assessment (PREDICT-SARCOMA)

Inspiratie

AI-driven imaging advances to transform sarcoma risk assessment and accelerate treatment for young patients

Periode

Looptijd

48 months

Deel van call / Programma

Projectpartners

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Umcutrecht

MRIguidance

Deeploy With Text

Philips

This project is a collaboration between academic researchers and private industry partners, working together to improve the diagnosis and treatment of children and adolescents with sarcoma — a rare and aggressive type of cancer. By combining medical imaging, artificial intelligence (AI), and innovative data analysis, this public-private partnership aims to build smarter tools for better risk assessment and faster, more tailored treatment.

Each year, around 50 children and young adults in the Netherlands are diagnosed with rhabdomyosarcoma or Ewing sarcoma. These cancers are difficult to treat, and survival rates have not improved significantly in the last two decades. One major reason is the lack of early, reliable imaging tools to predict how a tumour will respond to treatment. Without these tools, doctors must wait until months after treatment begins to see if it is working — often too late to make important changes. To improve outcomes, we need faster and more accurate ways to assess treatment response.

This project will develop new ways to analyse medical scans, using AI and machine learning. It will improve MRI techniques to better visualise the tumour’s structure and combine this with PET/CT scan data collected from hundreds of patients across Europe. The research team will also create tools to automatically identify and analyse tumours on scans, saving time and increasing consistency. Generative AI will help overcome the challenge of limited data in rare diseases.

By 2030, this project aims to deliver AI-based methods for better tumour analysis and risk prediction. These tools will lay the foundation for faster, more personalised treatment decisions. The results will not only benefit future research and clinical care but may also lead to new diagnostic products developed by the involved industrial partners. This ensures long-term impact on healthcare innovation for young cancer patients.