Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
667-03-008 ISMRM Abstract

Impact of Compressed-Sensing MRI on Brain Age: Whithin-Subject Comparison of Conventional and Accelerated T1 Sequences

Primary: Neuro - Aging
Secondary: Acquisition & Reconstruction - Subsampling: Parallel imaging, compressed sensing and low-rank modeling
667-03-008 · MR Acquisition Gems · Thursday, 14 May, 1:40 PM–2:35 PM · Digital Posters Row H
Keywords: Machine learning Brain Age Estimation T1-weighted Imaging Prediction bias MRI harmonization
Accepted
Paula Caballero 1,2, Rafael Navarro1,2, Álvaro Planchuelo-Gómez1,3, Raul Moro4, Santiago Aja-Fernández1,3, Angel Luis Guerrero5, Rodrigo de Luis García1,3
1Image Processing Laboratory, UNIVERSIDAD DE VALLADOLID, Valladolid, Spain
2Headache Unit, Department of Neurology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
3LPI-BIVa, Health Research Institute of Valladolid (IBioVALL), Valladolid, Spain
4Department of Radiology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
5Department of Medicine, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
Presenting Author: Paula Caballero

Synopsis

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References

1. Franke K, Gaser C. Ten years of BrainAGE as a neuroimaging biomarker of brain aging. Front Neurol. 2019;10:789. — DOI: 10.3389/fneur.2019.00789. PMID: 31474922. [doi] [pmid]
2. Cole JH, Franke K. Predicting age using neuroimaging: what is its true promise? Trends Neurosci. 2017;40(12):681–690. — DOI: 10.1016/j.tins.2017.10.001 PMID: 29074032 [doi] [pmid]
3. Wood D. A., et al. Optimising brain age estimation through transfer learning: A suite of pre-trained foundation models for improved performance and generalisability in a clinical setting. Hum Brain Mapp. 2024;45(4):e26625. — DOI: 10.1002/hbm.26625, PMID: 38433665. [doi] [pmid]
4. Leonardsen EH, et al. Deep neural networks learn general and clinically relevant representations of the ageing brain. NeuroImage. 2022;256:119210. — DOI: 10.1016/j.neuroimage.2022.119210, PMID: 35462035 [doi] [pmid]
5. Henschel L, et al. FastSurfer-a fast and accurate deep learning based neuroimaging pipeline. NeuroImage. 2020;219:117012. — DOI: 10.1016/j.neuroimage.2020.117012, PMID: 32526386. [doi] [pmid]
6. Klein A, Tourville J. 101 labeled brain images and a consistent human cortical labeling protocol. Front Neurosci. 2012;6:171. — DOI: 10.3389/fnins.2012.00171, PMID: 23227001. [doi] [pmid]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/667-03-008