| Title: | Lifespan neurodegeneration of the human brain in multiple sclerosis |
| Journal: | Human Brain Mapping |
| Published: | 24 Aug 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37615064/ |
| DOI: | https://doi.org/10.1002/hbm.26464 |
| URL: | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hbm.26464 |
Publication 9714
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Abstract
Atrophy related to multiple sclerosis (MS) has been found at the early stages of the disease. However, the archetype dynamic trajectories of the neurodegenerative process, even prior to clinical diagnosis, remain unknown. We modeled the volumetric trajectories of brain structures across the entire lifespan using 40,944 subjects (38,295 healthy controls and 2649 MS patients). Then, we estimated the chronological progression of MS by assessing the divergence of lifespan trajectories between normal brain charts and MS brain charts. Chronologically, the first affected structure was the thalamus, then the putamen and the pallidum (around 4 years later), followed by the ventral diencephalon (around 7 years after thalamus) and finally the brainstem (around 9 years after thalamus). To a lesser extent, the anterior cingulate gyrus, insular cortex, occipital pole, caudate and hippocampus were impacted. Finally, the precuneus and accumbens nuclei exhibited a limited atrophy pattern. Subcortical atrophy was more pronounced than cortical atrophy. The thalamus was the most impacted structure with a very early divergence in life. Our experiments showed that lifespan models of most impacted structures could be an important tool for future preclinical/prodromal prognosis and monitoring of MS.</p>
7 Authors
- Pierrick Coupé
- Vincent Planche
- Boris Mansencal
- Reda A. Kamroui
- Ismail Koubiyr
- José V. Manjòn
- Thomas Tourdias
1 Application
| Application ID | Title |
|---|---|
| 80509 | Holistic bigdata lifespan modeling of brain trajectory for automatic diagnostic of neurodegenerative diseases based on advanced deep learning methods |
Enabling scientific discoveries that improve human health