Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
669-02-003 ISMRM Abstract

Integrating MR imaging, clinical, and lifestyle data to predict organ-specific aging

Primary: Analysis Methods - Multi-Modal Learning with LLMs/VLMs
Secondary: Neuro - Aging
669-02-003 · Neuroimaging Biomarkers Across the Spectrum of Brain Disorders · Thursday, 14 May, 9:25 AM–10:20 AM · Digital Posters Row J
Keywords: Data Analysis Aging Multi-organ Multimodal Learning Representation learning
Accepted
Veronika Ecker 1,2, Tim Förster2, Sergios Gatidis1,3, Thomas Küstner1, Bin Yang2
1Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University Hospital of Tuebingen, Tuebingen, Germany
2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
3Department of Radiology, Stanford University, Stanford, United States of America
Presenting Author: Veronika Ecker

Synopsis

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References

1. Ecker et al. Deep regression for biological age estimation in multiple organs: investigation on 40,000 subjects of the UK Biobank. ICASSP, 2024.
2. Ecker et al. MRI-based Biological Age Estimation for Multiple Organs in the UK Biobank Cohort. ISMRM, 2024.
3. Salih et al. Conceptual Overview of Biological Age Estimation. Aging Dis. 1;14(3):583-588, 2023.
4. Shah et al. Environmental and genetic predictors of human cardiovascular ageing. Nat Commun 14, 4941, 2023.
5. Jonsson et al. Brain age prediction using deep learning uncovers associated sequence variants. vol. 10, no. 1, p. 5409. Number: 1 Publisher: Nature Publishing Group, 2019.
6. Armanious et al. Age-Net: An MRI-Based Iterative Framework for Brain Biological Age Estimation. IEEE Transactions on Medical Imaging. PP. 1-1. 10.1109, 2021.
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15. Bai et al. Automated cardiovascular magnetic resonance image analysis with fully convolutional networks. J Cardiovasc Magn Reson. 20(1):65, 2018.
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18. Chen et al. A simple framework for contrastive learning of visual representations. JMLR, 2020.
19. Barbano et al. Contrastive Learning for Regression in Multi-Site Brain Age Prediction. ISBI, 2023.
20. Kingma et al. Adam: A Method for Stochastic Optimization. International Conference on Learning Representations. ICLR, 2014.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/669-02-003