Quantitative brainstem and spinal MRI in amyotrophic lateral sclerosis: implications for predicting noninvasive ventilation needs

Khamaysa, M.; Lefort, M.; Pélégrini-Issac, M.; Lackmy-Vallée, A.; Mendili, M. M. El; Preuilh, A.; Devos, D.; Bruneteau, G.; Salachas, F.; Lenglet, T.; Amador, Md. M.; Le Forestier, N.; Hesters, A.; Gonzalez, J.; Rolland, A.-S.; Desnuelle, C.; Chupin, M.; Querin, G.; Georges, M.; Morelot-Panzini, C.; Marchand-Pauvert, V.; Pradat, P.-F.; ,

doi:10.1007/s00415-023-12045-x

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…In this study, we used a single inferior (caudal) brainstem mask to track ascending projections to the cerebellum as a proxy of the “spinocerebellar tracts”, but we concede that this is a suboptimal approach. High-resolution spinal data can now be reliably acquired with cardiac and respiratory gating in ALS [ 82 ] and correlated with clinical metrics [ 83 , 84 ]. Spinal protocols in ALS have also been successfully utilised in diagnostic applications [ 85 ] and to describe presymptomatic changes in C9orf72 [ 86 ].…”

Section: Discussionmentioning

confidence: 99%

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Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study

Kleinerova,

Tahedl,

Tan

et al. 2024

J Neurol

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Background Primary lateral sclerosis (PLS) is traditionally solely associated with progressive upper motor neuron dysfunction manifesting in limb spasticity, gait impairment, bulbar symptoms and pseudobulbar affect. Recent studies have described frontotemporal dysfunction in some patients resulting in cognitive manifestations. Cerebellar pathology is much less well characterised despite sporadic reports of cerebellar disease. Methods A multi-timepoint, longitudinal neuroimaging study was conducted to characterise the evolution of both intra-cerebellar disease burden and cerebro-cerebellar connectivity. The volumes of deep cerebellar nuclei, cerebellar cortical volumes, cerebro-cerebellar structural and functional connectivity were assessed longitudinally in a cohort of 43 individuals with PLS. Results Cerebello-frontal, -temporal, -parietal, -occipital and cerebello-thalamic structural disconnection was detected at baseline based on radial diffusivity (RD) and cerebello-frontal decoupling was also evident based on fractional anisotropy (FA) alterations. Functional connectivity changes were also detected in cerebello-frontal, parietal and occipital projections. Volume reductions were identified in the vermis, anterior lobe, posterior lobe, and crura. Among the deep cerebellar nuclei, the dorsal dentate was atrophic. Longitudinal follow-up did not capture statistically significant progressive changes. Significant primary motor cortex atrophy and inter-hemispheric transcallosal degeneration were also captured. Conclusions PLS is not only associated with upper motor neuron dysfunction, but cerebellar cortical volume loss and deep cerebellar nuclear atrophy can also be readily detected. In addition to intra-cerebellar disease burden, cerebro-cerebellar connectivity alterations also take place. Our data add to the evolving evidence of widespread neurodegeneration in PLS beyond the primary motor regions. Cerebellar dysfunction in PLS is likely to exacerbate bulbar, gait and dexterity impairment and contribute to pseudobulbar affect.

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Section: Discussionmentioning

confidence: 99%

“…Spinal protocols in ALS have also been successfully utilised in diagnostic applications [ 85 ] and to describe presymptomatic changes in C9orf72 [ 86 ]. Combined spinal and cerebral datasets are increasingly evaluated in ALS to accurately explore the substrate of clinical phenomena [ 83 ].…”

Section: Discussionmentioning

confidence: 99%

Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study

Kleinerova,

Tahedl,

Tan

et al. 2024

J Neurol

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Quantitative spinal cord imaging: Early ALS diagnosis and monitoring of disease progression

Khamaysa,

El Mendili,

Marchand

et al. 2024

Revue Neurologique

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Deep Neural Networks Comparison for MRI Segmentation of the Brainstem

Oh,

Pélégrini-Issac,

Urien

et al. 2024

2024 IEEE International Symposium on Biomedical Imaging (ISBI)

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Deep learning networks are the standard for medical image segmentation, yet the network architectures in medical applications are poorly understood. A precise segmentation of the brainstem is crucial in neurological conditions like Amyotrophic Lateral Sclerosis (ALS), which is a rare neurodegenerative disease affecting respiratory muscles by weakening motor neurons in the brain and spinal cord, but it is challenging due to the lack and low resolution of Magnetic Resonance Imaging (MRI) data. In this context, this paper explores neural network properties for brainstem segmentation and presents an efficient model with strong results. We find that minimal gains come from transfer learning in the encoder while optimizing the decoder and loss function improves performance. Our work also provides valuable insights into model components for MRI segmentation of the brainstem.

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Quantitative brainstem and spinal MRI in amyotrophic lateral sclerosis: implications for predicting noninvasive ventilation needs

Cited by 3 publications

References 41 publications

Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study

Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study

Quantitative spinal cord imaging: Early ALS diagnosis and monitoring of disease progression

Deep Neural Networks Comparison for MRI Segmentation of the Brainstem

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