| Title: | AI-Driven Identification of Early Imaging Biomarkers for Predicting Multi-Organ Aging and Frailty Using Whole Body MRI and PET |
| Lead Institution: | Charite - Universitatsmedizin Berlin |
| Principal investigator: |
Application 105529
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About
In this three-year research project, we will investigate a novel method for identifying people at risk of developing cancer or heart disease using artificial intelligence (AI). Our goal is to see if the age of a person's organs, as determined by MRI scans, can act as an early warning sign for these conditions. The main idea is that unhealthy organs age more quickly, and by studying organ age, doctors might predict disease likelihood and take preventive action. The basis for this project is the understanding that aging affects people and their organs differently. By looking at organ age, we hope to uncover the potential of this new marker for predicting disease risk and guiding personalised treatments. During the project, we'll first teach an AI model to identify and separate organs in MRI images. Next, using a group of patients without major diseases, the AI model will learn to predict the age of individual organs. The model will then be used on people with known major health problems, like cancer and heart disease, to estimate the biological age of their organs. Our project will also develop AI models for predicting frailty, sarcopenia, and osteoporosis. These models will consider factors like muscle mass, bone density, and functional performance measures. This will enable a more comprehensive assessment of an individual's overall health and risk for age-related conditions. By tapping into the vast UK Biobank dataset, this research could revolutionise preventive strategies and public health efforts by enabling early detection of organs at risk and other surrogate biomarkers, ideally before disease onset. The findings may lead to targeted prevention measures, reducing healthcare system strain and improving the quality of life for an aging population. Furthermore, the study's results could significantly influence public health policies, promoting healthy lifestyles and reducing risks linked to age-related conditions. In conclusion, this three-year project aims to use AI technology to explore organ age as a potential early sign of cancer and heart disease risk. If successful, this novel approach could lay the foundation for more effective prevention strategies and better public health outcomes, ultimately benefiting people in the UK and around the world.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 16614 | Segmenting Whole-Body MRI and CT for Multiorgan Anatomic Structure Delineation. | Hartmut Häntze (+31) | 2025 | Radiology Artificial Intelligence |
Enabling scientific discoveries that improve human health