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Lehto A, Schumacher J, Kasper E, Teipel S, Hermann A, Prudlo J. Loss of the ipsilateral silent period in amyotrophic lateral sclerosis is associated with reduced white matter integrity in the motor section of the corpus callosum. J Neurol Sci 2024; 466:123267. [PMID: 39378795 DOI: 10.1016/j.jns.2024.123267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 09/06/2024] [Accepted: 10/02/2024] [Indexed: 10/10/2024]
Abstract
OBJECTIVE Interhemispheric neurons in the motor section of the corpus callosum have an inhibitory effect on neurons of the contralateral motor cortex. Three quarters of patients with amyotrophic laterals sclerosis (ALS) show impaired transcallosal inhibition. We aimed to investigate whether structural changes co-occur with this functional impairment and to explore its phenotypic correlates. METHODS The demographic, clinical, and neuropsychological data of 127 ALS patients were analysed. Transcallosal inhibition was assessed with an ipsilateral silent period (iSP) protocol using transcranial magnetic stimulation. Patients were categorised based on an iSP response or its loss, and the groups were characterised by demographic, clinical, and neuropsychological variables. Diffusion-weighted images from a subset of 63 patients were analysed using tractography, and white matter (WM) structural integrity metrics were compared across groups. RESULTS 54 % of patients displayed iSP loss. The average free-water-corrected fractional anisotropy values within the callosal tract between the primary motor cortices were lower for patients with iSP loss compared to patients with an iSP response. There were no group differences based on other diffusivity metrics. The groups did not differ regarding any of the demographic, clinical, or neuropsychological variables. INTERPRETATION We found reduced WM integrity in the motor section of the corpus callosum that differentiated ALS patients with iSP loss from patients with an iSP response, but with a small effect size. Nevertheless, the underlying pathological substrate and potential genetic drivers for these structural and functional changes in a subset of ALS patients remain to be satisfactorily investigated.
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Affiliation(s)
- Annaliis Lehto
- Translational Neurodegeneration Section "Albrecht Kossel", Department of Neurology, Rostock University Medical Center, Rostock, Germany; Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Rostock-Greifswald, Rostock, Germany
| | - Julia Schumacher
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Rostock-Greifswald, Rostock, Germany; Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Elisabeth Kasper
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Rostock-Greifswald, Rostock, Germany; Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Stefan Teipel
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Rostock-Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Andreas Hermann
- Translational Neurodegeneration Section "Albrecht Kossel", Department of Neurology, Rostock University Medical Center, Rostock, Germany; Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Rostock-Greifswald, Rostock, Germany
| | - Johannes Prudlo
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Rostock-Greifswald, Rostock, Germany; Department of Neurology, Rostock University Medical Center, Rostock, Germany.
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2
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Khamaysa M, El Mendili M, Marchand V, Querin G, Pradat PF. Quantitative spinal cord imaging: Early ALS diagnosis and monitoring of disease progression. Rev Neurol (Paris) 2024:S0035-3787(24)00657-X. [PMID: 39547910 DOI: 10.1016/j.neurol.2024.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 08/23/2024] [Accepted: 10/08/2024] [Indexed: 11/17/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive degeneration of motor neurons in the cortex, brainstem, and spinal cord. This degeneration leads to muscular weakness, progressively impairing motor functions and ultimately resulting in respiratory failure. The clinical, genetic, and pathological heterogeneity of ALS, combined with the absence of reliable biomarkers, significantly challenge the efficacy of therapeutic trials. Despite these hurdles, neuroimaging, and particularly spinal cord imaging, has emerged as a promising tool. It provides insights into the involvement of both upper and lower motor neurons. Quantitative spinal imaging has the potential to facilitate early diagnosis, enable accurate monitoring of disease progression, and refine the design of clinical trials. In this review, we explore the utility of spinal cord imaging within the broader context of developing spinal imaging biomarkers in ALS. We focus on a both diagnostic and prognostic biomarker in ALS, highlighting its pivotal role in elucidating the disease's underlying pathology. We also discuss the existing limitations and future avenues for research, aiming to bridge the translational gap between academic research and its application in clinical practice and therapeutic trials.
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Affiliation(s)
- M Khamaysa
- Laboratoire d'Imagerie Biomédicale, Inserm, Sorbonne Université, CNRS, Paris, France
| | - M El Mendili
- Laboratoire d'Imagerie Biomédicale, Inserm, Sorbonne Université, CNRS, Paris, France
| | - V Marchand
- Laboratoire d'Imagerie Biomédicale, Inserm, Sorbonne Université, CNRS, Paris, France
| | - G Querin
- Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, AP-HP, Paris, France
| | - P-F Pradat
- Laboratoire d'Imagerie Biomédicale, Inserm, Sorbonne Université, CNRS, Paris, France; Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, AP-HP, Paris, France.
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3
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Metzger M, Dukic S, McMackin R, Giglia E, Mitchell M, Bista S, Costello E, Peelo C, Tadjine Y, Sirenko V, McManus L, Buxo T, Fasano A, Chipika R, Pinto-Grau M, Schuster C, Heverin M, Coffey A, Broderick M, Iyer PM, Mohr K, Gavin B, Pender N, Bede P, Muthuraman M, Hardiman O, Nasseroleslami B. Distinct Longitudinal Changes in EEG Measures Reflecting Functional Network Disruption in ALS Cognitive Phenotypes. Brain Topogr 2024; 38:3. [PMID: 39367160 PMCID: PMC11452478 DOI: 10.1007/s10548-024-01078-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 08/24/2024] [Indexed: 10/06/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is characterised primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. We have shown previously that resting-state EEG captures dysfunction in motor and cognitive networks in ALS. However, the longitudinal development of these dysfunctional patterns, especially in networks linked with cognitive-behavioural functions, remains unclear. Longitudinal studies on non-motor changes in ALS are essential to further develop our understanding of disease progression, improve care and enhance the evaluation of new treatments. To address this gap, we examined 124 ALS individuals with 128-channel resting-state EEG recordings, categorised by cognitive impairment (ALSci, n = 25), behavioural impairment (ALSbi, n = 58), or non-impaired (ALSncbi, n = 53), with 12 participants meeting the criteria for both ALSci and ALSbi. Using linear mixed-effects models, we characterised the general and phenotype-specific longitudinal changes in brain network, and their association with cognitive performance, behaviour changes, fine motor symptoms, and survival. Our findings revealed a significant decline in [Formula: see text]-band spectral power over time in the temporal region along with increased [Formula: see text]-band power in the fronto-temporal region in the ALS group. ALSncbi participants showed widespread β-band synchrony decrease, while ALSci participants exhibited increased co-modulation correlated with verbal fluency decline. Longitudinal network-level changes were specific of ALS subgroups and correlated with motor, cognitive, and behavioural decline, as well as with survival. Spectral EEG measures can longitudinally track abnormal network patterns, serving as a candidate stratification tool for clinical trials and personalised treatments in ALS.
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Affiliation(s)
- Marjorie Metzger
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland.
| | - Stefan Dukic
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, 3584 CG, The Netherlands
| | - Roisin McMackin
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
- Discipline of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin 2, D02 R590, Ireland
| | - Eileen Giglia
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Matthew Mitchell
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Saroj Bista
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Emmet Costello
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Colm Peelo
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Yasmine Tadjine
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Vladyslav Sirenko
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Lara McManus
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Teresa Buxo
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Antonio Fasano
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Rangariroyashe Chipika
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, D02 R590 Dublin 2, Dublin 2, Ireland
| | - Marta Pinto-Grau
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Christina Schuster
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, D02 R590 Dublin 2, Dublin 2, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Amina Coffey
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Michael Broderick
- Trinity Centre for Bioengineering, Trinity College Dublin, University of Dublin, D02 R590 Dublin 2, Dublin 2, Ireland
| | - Parameswaran M Iyer
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Kieran Mohr
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Brighid Gavin
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Niall Pender
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, D02 R590 Dublin 2, Dublin 2, Ireland
| | - Muthuraman Muthuraman
- Neural Engineering with Signal Analytics and Artificial Intelligence, Department of Neurology, University Hospital Würzburg, 97080, Würzburg, Germany
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin 2, D02 PN40, Ireland
- Beaumont Hospital, D09 V2N0 Dublin 9, Dublin, Ireland
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Room 5.43, 152-160 Pearse Street, Dublin 2, D02 R590, Ireland
- FutureNeuro - SFI Research Centre for Chronic and Rare Neurological Diseases, Royal College of Surgeons, D02 YN77 Dublin 2, Dublin 2, Ireland
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4
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Tu S, Vucic S, Kiernan MC. Pathological insights derived from neuroimaging in amyotrophic lateral sclerosis: emerging clinical applications. Curr Opin Neurol 2024; 37:577-584. [PMID: 38958573 DOI: 10.1097/wco.0000000000001295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
PURPOSE OF REVIEW Neuroimaging has been instrumental in shaping current understanding of the pathoanatomical signature of amyotrophic lateral sclerosis (ALS) across clinically well defined patient cohorts. The potential utility of imaging as an objective disease marker, however, remains poorly defined. RECENT FINDINGS Increasingly advanced quantitative and computational imaging studies have highlighted emerging clinical applications for neuroimaging as a complementary clinical modality for diagnosis, monitoring, and modelling disease propagation. Multimodal neuroimaging has demonstrated novel approaches for capturing primary motor disease. Extra-motor subcortical dysfunction is increasingly recognized as key modulators of disease propagation. SUMMARY The neural signature of cortical and subcortical dysfunction in ALS has been well defined at the population level. Objective metrics of focal primary motor dysfunction are increasingly sensitive and translatable to the individual patient level. Integrity of extra-motor subcortical abnormalities are recognized to represent critical pathways of the ALS disease 'connectome', predicting pathological spread. Neuroimaging plays a pivotal role in capturing upper motor neuron pathology in ALS. Their potential clinical role as objective disease markers for disease classification, longitudinal monitoring, and prognosis in ALS have become increasingly well defined.
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Affiliation(s)
- Sicong Tu
- Brain and Mind Centre
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney
- Neuroscience Research Australia
| | - Steve Vucic
- Brain and Nerve Research Center, The University of Sydney, Sydney, New South Wales, Australia
| | - Matthew C Kiernan
- Brain and Mind Centre
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney
- Neuroscience Research Australia
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5
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Xiao XY, Zeng JY, Cao YB, Tang Y, Zou ZY, Li JQ, Chen HJ. Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study. Quant Imaging Med Surg 2024; 14:5774-5788. [PMID: 39144033 PMCID: PMC11320503 DOI: 10.21037/qims-24-236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 06/17/2024] [Indexed: 08/16/2024]
Abstract
Background Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity. Methods This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R. Results In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05). Conclusions The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.
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Affiliation(s)
- Xin-Yun Xiao
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jing-Yi Zeng
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yun-Bin Cao
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Ying Tang
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Zhang-Yu Zou
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jian-Qi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Hua-Jun Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
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Christidi F, Kleinerova J, Tan EL, Delaney S, Tacheva A, Hengeveld JC, Doherty MA, McLaughlin RL, Hardiman O, Siah WF, Chang KM, Lope J, Bede P. Limbic Network and Papez Circuit Involvement in ALS: Imaging and Clinical Profiles in GGGGCC Hexanucleotide Carriers in C9orf72 and C9orf72-Negative Patients. BIOLOGY 2024; 13:504. [PMID: 39056697 PMCID: PMC11273537 DOI: 10.3390/biology13070504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 06/26/2024] [Accepted: 07/05/2024] [Indexed: 07/28/2024]
Abstract
Background: While frontotemporal involvement is increasingly recognized in Amyotrophic lateral sclerosis (ALS), the degeneration of limbic networks remains poorly characterized, despite growing evidence of amnestic deficits, impaired emotional processing and deficits in social cognition. Methods: A prospective neuroimaging study was conducted with 204 individuals with ALS and 111 healthy controls. Patients were stratified for hexanucleotide expansion status in C9orf72. A deep-learning-based segmentation approach was implemented to segment the nucleus accumbens, hypothalamus, fornix, mammillary body, basal forebrain and septal nuclei. The cortical, subcortical and white matter components of the Papez circuit were also systematically evaluated. Results: Hexanucleotide repeat expansion carriers exhibited bilateral amygdala, hypothalamus and nucleus accumbens atrophy, and C9orf72 negative patients showed bilateral basal forebrain volume reductions compared to controls. Both patient groups showed left rostral anterior cingulate atrophy, left entorhinal cortex thinning and cingulum and fornix alterations, irrespective of the genotype. Fornix, cingulum, posterior cingulate, nucleus accumbens, amygdala and hypothalamus degeneration was more marked in C9orf72-positive ALS patients. Conclusions: Our results highlighted that mesial temporal and parasagittal subcortical degeneration is not unique to C9orf72 carriers. Our radiological findings were consistent with neuropsychological observations and highlighted the importance of comprehensive neuropsychological testing in ALS, irrespective of the underlying genotype.
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Affiliation(s)
- Foteini Christidi
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Jana Kleinerova
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Siobhan Delaney
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
| | - Asya Tacheva
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
| | | | - Mark A. Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
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7
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Ghaderi S, Fatehi F, Kalra S, Mohammadi S, Batouli SAH. Quantitative susceptibility mapping in amyotrophic lateral sclerosis: automatic quantification of the magnetic susceptibility in the subcortical nuclei. Amyotroph Lateral Scler Frontotemporal Degener 2024:1-12. [PMID: 38957123 DOI: 10.1080/21678421.2024.2372648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 06/14/2024] [Indexed: 07/04/2024]
Abstract
Objective: Previous studies have suggested a link between dysregulation of cortical iron levels and neuronal loss in amyotrophic lateral sclerosis (ALS) patients. However, few studies have reported differences in quantitative susceptibility mapping (QSM) values in subcortical nuclei between patients with ALS and healthy controls (HCs). Methods: MRI was performed using a 3 Tesla Prisma scanner (64-channel head coil), including 3D T1-MPRAGE and multi-echo 3D GRE for QSM reconstruction. Automated QSM segmentation was used to measure susceptibility values in the subcortical nuclei, which were compared between the groups. Correlations with clinical scales were analyzed. Group comparisons were performed using independent t-tests, with p < 0.05 considered significant. Correlations were assessed using Pearson's correlation, with p < 0.05 considered significant. Cohen's d was reported to compare the standardized mean difference (SMD) of QSM. Results: Twelve patients with limb-onset ALS (mean age 48.7 years, 75% male) and 13 age-, sex-, and handedness-matched HCs (mean age 44.6 years, 69% male) were included. Compared to HCs, ALS patients demonstrated significantly lower susceptibility in the left caudate nucleus (CN) (SMD = -0.845), right CN (SMD = -0.851), whole CN (SMD = -1.016), and left subthalamic nucleus (STN) (SMD = -1.000). Susceptibility in the left putamen (SMD = -0.857), left thalamus (SMD = -1.081), and whole thalamus (SMD = -0.968) was significantly higher in the patients. The susceptibility of the substantia nigra (SN), CN, and pulvinar was positively correlated with disease duration. Conclusions: QSM detects abnormal iron accumulation patterns in the subcortical gray matter of ALS patients, which correlates with disease characteristics, supporting its potential as a neuroimaging biomarker.
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Affiliation(s)
- Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzad Fatehi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Neurology Department, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada, and
- Department of Medicine, Division of Neurology, University of Alberta, Edmonton, Canada
| | - Sana Mohammadi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Amir Hossein Batouli
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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8
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Dharmadasa T, Pavey N, Tu S, Menon P, Huynh W, Mahoney CJ, Timmins HC, Higashihara M, van den Bos M, Shibuya K, Kuwabara S, Grosskreutz J, Kiernan MC, Vucic S. Novel approaches to assessing upper motor neuron dysfunction in motor neuron disease/amyotrophic lateral sclerosis: IFCN handbook chapter. Clin Neurophysiol 2024; 163:68-89. [PMID: 38705104 DOI: 10.1016/j.clinph.2024.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 02/08/2024] [Accepted: 04/14/2024] [Indexed: 05/07/2024]
Abstract
Identifying upper motor neuron (UMN) dysfunction is fundamental to the diagnosis and understanding of disease pathogenesis in motor neuron disease (MND). The clinical assessment of UMN dysfunction may be difficult, particularly in the setting of severe muscle weakness. From a physiological perspective, transcranial magnetic stimulation (TMS) techniques provide objective biomarkers of UMN dysfunction in MND and may also be useful to interrogate cortical and network function. Single, paired- and triple pulse TMS techniques have yielded novel diagnostic and prognostic biomarkers in MND, and have provided important pathogenic insights, particularly pertaining to site of disease onset. Cortical hyperexcitability, as heralded by reduced short interval intracortical inhibition (SICI) and increased short interval intracortical facilitation, has been associated with the onset of lower motor neuron degeneration, along with patterns of disease spread, development of specific clinical features such as the split hand phenomenon, and may provide an indication about the rate of disease progression. Additionally, reduction of SICI has emerged as a potential diagnostic aid in MND. The triple stimulation technique (TST) was shown to enhance the diagnostic utility of conventional TMS measures in detecting UMN dysfunction in MND. Separately, sophisticated brain imaging techniques have uncovered novel biomarkers of neurodegeneration that have bene associated with progression. The present review will discuss the utility of TMS and brain neuroimaging derived biomarkers of UMN dysfunction in MND, focusing on recently developed TMS techniques and advanced neuroimaging modalities that interrogate structural and functional integrity of the corticomotoneuronal system, with an emphasis on pathogenic, diagnostic, and prognostic utility.
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Affiliation(s)
- Thanuja Dharmadasa
- Department of Neurology, The Royal Melbourne Hospital City Campus, Parkville, Victoria, Australia
| | - Nathan Pavey
- Brain and Nerve Research Center, The University of Sydney, Sydney, Australia
| | - Sicong Tu
- Brain and Mind Centre, The University of Sydney, and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Parvathi Menon
- Brain and Nerve Research Center, The University of Sydney, Sydney, Australia
| | - William Huynh
- Brain and Mind Centre, The University of Sydney, and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Colin J Mahoney
- Brain and Mind Centre, The University of Sydney, and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Hannah C Timmins
- Brain and Mind Centre, The University of Sydney, and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Mana Higashihara
- Department of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Mehdi van den Bos
- Brain and Nerve Research Center, The University of Sydney, Sydney, Australia
| | - Kazumoto Shibuya
- Neurology, Chiba University, Graduate School of Medicine, Chiba, Japan
| | - Satoshi Kuwabara
- Neurology, Chiba University, Graduate School of Medicine, Chiba, Japan
| | - Julian Grosskreutz
- Precision Neurology, Excellence Cluster Precision Medicine in Inflammation, University of Lübeck, University Hospital Schleswig-Holstein Campus, Lübeck, Germany
| | - Matthew C Kiernan
- Brain and Mind Centre, The University of Sydney, and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Steve Vucic
- Brain and Nerve Research Center, The University of Sydney, Sydney, Australia.
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9
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Nigri A, Stanziano M, Fedeli D, Manera U, Ferraro S, Medina Carrion JP, Palermo S, Lequio L, Denegri F, Agosta F, Spinelli EG, Filippi M, Grisoli M, Valentini MC, De Mattei F, Canosa A, Calvo A, Chiò A, Bruzzone MG, Moglia C. Distinct neural signatures of pulvinar in C9orf72 amyotrophic lateral sclerosis mutation carriers and noncarriers. Eur J Neurol 2024; 31:e16266. [PMID: 38469975 PMCID: PMC11235848 DOI: 10.1111/ene.16266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 01/30/2024] [Accepted: 02/15/2024] [Indexed: 03/13/2024]
Abstract
BACKGROUND AND PURPOSE Thalamic alterations have been reported as a major feature in presymptomatic and symptomatic patients carrying the C9orf72 mutation across the frontotemporal dementia-amyotrophic lateral sclerosis (ALS) spectrum. Specifically, the pulvinar, a high-order thalamic nucleus and timekeeper for large-scale cortical networks, has been hypothesized to be involved in C9orf72-related neurodegenerative diseases. We investigated whether pulvinar volume can be useful for differential diagnosis in ALS C9orf72 mutation carriers and noncarriers and how underlying functional connectivity changes affect this region. METHODS We studied 19 ALS C9orf72 mutation carriers (ALSC9+) accurately matched with wild-type ALS (ALSC9-) and ALS mimic (ALSmimic) patients using structural and resting-state functional magnetic resonance imaging data. Pulvinar volume was computed using automatic segmentation. Seed-to-voxel functional connectivity analyses were performed using seeds from a pulvinar functional parcellation. RESULTS Pulvinar structural integrity had high discriminative values for ALSC9+ patients compared to ALSmimic (area under the curve [AUC] = 0.86) and ALSC9- (AUC = 0.77) patients, yielding a volume cutpoint of approximately 0.23%. Compared to ALSmimic, ALSC9- showed increased anterior, inferior, and lateral pulvinar connections with bilateral occipital-temporal-parietal regions, whereas ALSC9+ showed no differences. ALSC9+ patients when compared to ALSC9- patients showed reduced pulvinar-occipital connectivity for anterior and inferior pulvinar seeds. CONCLUSIONS Pulvinar volume could be a differential biomarker closely related to the C9orf72 mutation. A pulvinar-cortical circuit dysfunction might play a critical role in disease progression and development, in both the genetic phenotype and ALS wild-type patients.
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Affiliation(s)
- Anna Nigri
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Mario Stanziano
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
| | - Davide Fedeli
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Umberto Manera
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
- Azienda Ospedaliero‐Universitaria Città della Salute e della Scienza di Torino, SC Neurologia 1UTurinItaly
| | - Stefania Ferraro
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
- School of Life Science and Technology, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | | | - Sara Palermo
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Laura Lequio
- Neuroradiology UnitCTO Hospital, AOU Città della Salute e della Scienza di TorinoTurinItaly
| | - Federica Denegri
- Neuroradiology UnitCTO Hospital, AOU Città della Salute e della Scienza di TorinoTurinItaly
| | - Federica Agosta
- Neuroimaging Research Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Neurology UnitIRCCS San Raffaele Scientific InstituteMilanItaly
- Vita‐Salute San Raffaele UniversityMilanItaly
| | - Edoardo Gioele Spinelli
- Neuroimaging Research Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Neurology UnitIRCCS San Raffaele Scientific InstituteMilanItaly
- Neurorehabilitation UnitIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Neurology UnitIRCCS San Raffaele Scientific InstituteMilanItaly
- Vita‐Salute San Raffaele UniversityMilanItaly
- Neurorehabilitation UnitIRCCS San Raffaele Scientific InstituteMilanItaly
- Neurophysiology ServiceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Marina Grisoli
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | | | - Filippo De Mattei
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
- Azienda Ospedaliero‐Universitaria Città della Salute e della Scienza di Torino, SC Neurologia 1UTurinItaly
| | - Antonio Canosa
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
- Azienda Ospedaliero‐Universitaria Città della Salute e della Scienza di Torino, SC Neurologia 1UTurinItaly
| | - Andrea Calvo
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
- Azienda Ospedaliero‐Universitaria Città della Salute e della Scienza di Torino, SC Neurologia 1UTurinItaly
| | - Adriano Chiò
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
- Azienda Ospedaliero‐Universitaria Città della Salute e della Scienza di Torino, SC Neurologia 1UTurinItaly
- Institute of Cognitive Sciences and TechnologiesNational Council of ResearchRomeItaly
| | | | - Cristina Moglia
- ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
- Azienda Ospedaliero‐Universitaria Città della Salute e della Scienza di Torino, SC Neurologia 1UTurinItaly
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10
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Mohammadi S, Ghaderi S, Fatehi F. MRI biomarkers and neuropsychological assessments of hippocampal and parahippocampal regions affected by ALS: A systematic review. CNS Neurosci Ther 2024; 30:e14578. [PMID: 38334254 PMCID: PMC10853901 DOI: 10.1111/cns.14578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/11/2023] [Accepted: 12/13/2023] [Indexed: 02/10/2024] Open
Abstract
BACKGROUND AND OBJECTIVE Amyotrophic lateral sclerosis (ALS) is a progressive motor and extra-motor neurodegenerative disease. This systematic review aimed to examine MRI biomarkers and neuropsychological assessments of the hippocampal and parahippocampal regions in patients with ALS. METHODS A systematic review was conducted in the Scopus and PubMed databases for studies published between January 2000 and July 2023. The inclusion criteria were (1) MRI studies to assess hippocampal and parahippocampal regions in ALS patients, and (2) studies reporting neuropsychological data in patients with ALS. RESULTS A total of 46 studies were included. Structural MRI revealed hippocampal atrophy, especially in ALS-FTD, involving specific subregions (CA1, dentate gyrus). Disease progression and genetic factors impacted atrophy patterns. Diffusion tensor imaging (DTI) showed increased mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and decreased fractional anisotropy (FA) in the hippocampal tracts and adjacent regions, indicating loss of neuronal and white matter integrity. Functional MRI (fMRI) revealed reduced functional connectivity (FC) between the hippocampus, parahippocampus, and other regions, suggesting disrupted networks. Perfusion MRI showed hypoperfusion in parahippocampal gyri. Magnetic resonance spectroscopy (MRS) found changes in the hippocampus, indicating neuronal loss. Neuropsychological tests showed associations between poorer memory and hippocampal atrophy or connectivity changes. CA1-2, dentate gyrus, and fimbria atrophy were correlated with worse memory. CONCLUSIONS The hippocampus and the connected regions are involved in ALS. Hippocampal atrophy disrupted connectivity and metabolite changes correlate with cognitive and functional decline. Specific subregions can be particularly affected. The hippocampus is a potential biomarker for disease monitoring and prognosis.
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Affiliation(s)
- Sana Mohammadi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
- Department of Medical Sciences, School of MedicineIran University of Medical SciencesTehranIran
| | - Sadegh Ghaderi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
| | - Farzad Fatehi
- Neuromuscular Research Center, Department of Neurology, Shariati HospitalTehran University of Medical SciencesTehranIran
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11
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Spinelli EG, Ghirelli A, Basaia S, Canu E, Castelnovo V, Cividini C, Russo T, Schito P, Falzone YM, Riva N, Filippi M, Agosta F. Structural and Functional Brain Network Connectivity at Different King's Stages in Patients With Amyotrophic Lateral Sclerosis. Neurology 2024; 102:e207946. [PMID: 38165325 PMCID: PMC10962907 DOI: 10.1212/wnl.0000000000207946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 09/27/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES There is currently no validated disease-stage biomarker for amyotrophic lateral sclerosis (ALS). The identification of quantitative and reproducible markers of disease stratification in ALS is fundamental for study design definition and inclusion of homogenous patient cohorts into clinical trials. Our aim was to assess the rearrangements of structural and functional brain connectivity underlying the clinical stages of ALS, to suggest objective, reproducible measures provided by MRI connectomics mirroring disease staging. METHODS In this observational study, patients with ALS and healthy controls (HCs) underwent clinical evaluation and brain MRI on a 3T scanner. Patients were classified into 4 groups, according to the King's staging system. Structural and functional brain connectivity matrices were obtained using diffusion tensor and resting-state fMRI data, respectively. Whole-brain network-based statistics (NBS) analysis and comparisons of intraregional and inter-regional connectivity values using analysis of covariance models were performed between groups. Correlations between MRI and clinical/cognitive measures were tested using Pearson coefficient. RESULTS One hundred four patients with ALS and 61 age-matched and sex-matched HCs were included. NBS and regional connectivity analyses demonstrated a progressive decrease of intranetwork and internetwork structural connectivity of sensorimotor regions at increasing ALS stages in our cohort, compared with HCs. By contrast, functional connectivity showed divergent patterns between King's stages 3 (increase in basal ganglia and temporal circuits [p = 0.04 and p = 0.05, respectively]) and 4 (frontotemporal decrease [p = 0.03]), suggesting a complex interplay between opposite phenomena in late stages of the disease. Intraregional sensorimotor structural connectivity was correlated with ALS Functional Rating Scale-revised (ALSFRS-r) score (r = 0.31, p < 0.001) and upper motor neuron burden (r = -0.25, p = 0.01). Inter-regional frontal-sensorimotor structural connectivity was also correlated with ALSFRS-r (r = 0.24, p = 0.02). No correlations with cognitive measures were found. DISCUSSION MRI of the brain allows to demonstrate and quantify increasing disruption of structural connectivity involving the sensorimotor networks in ALS, mirroring disease stages. Frontotemporal functional disconnection seems to characterize only advanced disease phases. Our findings support the utility of MRI connectomics to stratify patients and stage brain pathology in ALS in a reproducible way, which may mirror clinical progression.
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Affiliation(s)
- Edoardo G Spinelli
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alma Ghirelli
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Veronica Castelnovo
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tommaso Russo
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paride Schito
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Yuri M Falzone
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nilo Riva
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- From the Neuroimaging Research Unit (E.G.S., A.G., S.B., E.C., V.C., C.C., M.F., F.A.), Division of Neuroscience, and Neurology Unit (E.G.S., A.G., T.R., P.S., Y.M.F., M.F., F.A.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (E.G.S., A.G., T.R., M.F., F.A.); Neurorehabilitation Unit (N.R., M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
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12
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Abstract
Although the past two decades have produced exciting discoveries in the genetics and pathology of amyotrophic lateral sclerosis (ALS), progress in developing an effective therapy remains slow. This review summarizes the critical discoveries and outlines the advances in disease characterization, diagnosis, imaging, and biomarkers, along with the current status of approaches to ALS care and treatment. Additional knowledge of the factors driving disease progression and heterogeneity will hopefully soon transform the care for patients with ALS into an individualized, multi-prong approach able to prevent disease progression sufficiently to allow for a dignified life with limited disability.
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Affiliation(s)
- Hristelina Ilieva
- Jefferson Weinberg ALS Center, Thomas Jefferson University, Philadelphia, PA, USA
| | | | - Justin Kwan
- National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA
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13
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Jellinger KA. The Spectrum of Cognitive Dysfunction in Amyotrophic Lateral Sclerosis: An Update. Int J Mol Sci 2023; 24:14647. [PMID: 37834094 PMCID: PMC10572320 DOI: 10.3390/ijms241914647] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/21/2023] [Accepted: 09/21/2023] [Indexed: 10/15/2023] Open
Abstract
Cognitive dysfunction is an important non-motor symptom in amyotrophic lateral sclerosis (ALS) that has a negative impact on survival and caregiver burden. It shows a wide spectrum ranging from subjective cognitive decline to frontotemporal dementia (FTD) and covers various cognitive domains, mainly executive/attention, language and verbal memory deficits. The frequency of cognitive impairment across the different ALS phenotypes ranges from 30% to 75%, with up to 45% fulfilling the criteria of FTD. Significant genetic, clinical, and pathological heterogeneity reflects deficits in various cognitive domains. Modern neuroimaging studies revealed frontotemporal degeneration and widespread involvement of limbic and white matter systems, with hypometabolism of the relevant areas. Morphological substrates are frontotemporal and hippocampal atrophy with synaptic loss, associated with TDP-43 and other co-pathologies, including tau deposition. Widespread functional disruptions of motor and extramotor networks, as well as of frontoparietal, frontostriatal and other connectivities, are markers for cognitive deficits in ALS. Cognitive reserve may moderate the effect of brain damage but is not protective against cognitive decline. The natural history of cognitive dysfunction in ALS and its relationship to FTD are not fully understood, although there is an overlap between the ALS variants and ALS-related frontotemporal syndromes, suggesting a differential vulnerability of motor and non-motor networks. An assessment of risks or the early detection of brain connectivity signatures before structural changes may be helpful in investigating the pathophysiological mechanisms of cognitive impairment in ALS, which might even serve as novel targets for effective disease-modifying therapies.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, A-1150 Vienna, Austria
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14
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Pisharady PK, Eberly LE, Adanyeguh IM, Manousakis G, Guliani G, Walk D, Lenglet C. Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis. COMMUNICATIONS MEDICINE 2023; 3:84. [PMID: 37328685 DOI: 10.1038/s43856-023-00318-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 06/06/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Recent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord. METHODS We acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section. RESULTS We demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics. CONCLUSIONS Our findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.
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Affiliation(s)
- Pramod Kumar Pisharady
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA.
| | - Lynn E Eberly
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Isaac M Adanyeguh
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Georgios Manousakis
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Gaurav Guliani
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - David Walk
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
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15
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Chen H, Hu Z, Ke Z, Xu Y, Bai F, Liu Z. Aberrant Multimodal Connectivity Pattern Involved in Default Mode Network and Limbic Network in Amyotrophic Lateral Sclerosis. Brain Sci 2023; 13:brainsci13050803. [PMID: 37239275 DOI: 10.3390/brainsci13050803] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/07/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that progressively affects bulbar and limb function. Despite increasing recognition of the disease as a multinetwork disorder characterized by aberrant structural and functional connectivity, its integrity agreement and its predictive value for disease diagnosis remain to be fully elucidated. In this study, we recruited 37 ALS patients and 25 healthy controls (HCs). High-resolution 3D T1-weighted imaging and resting-state functional magnetic resonance imaging were, respectively, applied to construct multimodal connectomes. Following strict neuroimaging selection criteria, 18 ALS and 25 HC patients were included. Network-based statistic (NBS) and the coupling of grey matter structural-functional connectivity (SC-FC coupling) were performed. Finally, the support vector machine (SVM) method was used to distinguish the ALS patients from HCs. Results showed that, compared with HCs, ALS individuals exhibited a significantly increased functional network, predominantly encompassing the connections between the default mode network (DMN) and the frontoparietal network (FPN). The increased structural connections predominantly involved the inter-regional connections between the limbic network (LN) and the DMN, the salience/ventral attention network (SVAN) and FPN, while the decreased structural connections mainly involved connections between the LN and the subcortical network (SN). We also found increased SC-FC coupling in DMN-related brain regions and decoupling in LN-related brain regions in ALS, which could differentiate ALS from HCs with promising capacity based on SVM. Our findings highlight that DMN and LN may play a vital role in the pathophysiological mechanism of ALS. Additionally, SC-FC coupling could be regarded as a promising neuroimaging biomarker for ALS and shows important clinical potential for early recognition of ALS individuals.
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Affiliation(s)
- Haifeng Chen
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
- Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210008, China
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Zheqi Hu
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
- Medical School of Nanjing University, Nanjing University, Nanjing 210093, China
| | - Zhihong Ke
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
- Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing 211166, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
- Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210008, China
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
- Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210008, China
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Zhuo Liu
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
- Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210008, China
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
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16
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Cannon AE, Zürrer WE, Zejlon C, Kulcsar Z, Lewandowski S, Piehl F, Granberg T, Ineichen BV. Neuroimaging findings in preclinical amyotrophic lateral sclerosis models-How well do they mimic the clinical phenotype? A systematic review. Front Vet Sci 2023; 10:1135282. [PMID: 37205225 PMCID: PMC10185801 DOI: 10.3389/fvets.2023.1135282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 04/10/2023] [Indexed: 05/21/2023] Open
Abstract
Background and objectives Animal models for motor neuron diseases (MND) such as amyotrophic lateral sclerosis (ALS) are commonly used in preclinical research. However, it is insufficiently understood how much findings from these model systems can be translated to humans. Thus, we aimed at systematically assessing the translational value of MND animal models to probe their external validity with regards to magnetic resonance imaging (MRI) features. Methods In a comprehensive literature search in PubMed and Embase, we retrieved 201 unique publications of which 34 were deemed eligible for qualitative synthesis including risk of bias assessment. Results ALS animal models can indeed present with human ALS neuroimaging features: Similar to the human paradigm, (regional) brain and spinal cord atrophy as well as signal changes in motor systems are commonly observed in ALS animal models. Blood-brain barrier breakdown seems to be more specific to ALS models, at least in the imaging domain. It is noteworthy that the G93A-SOD1 model, mimicking a rare clinical genotype, was the most frequently used ALS proxy. Conclusions Our systematic review provides high-grade evidence that preclinical ALS models indeed show imaging features highly reminiscent of human ALS assigning them a high external validity in this domain. This opposes the high attrition of drugs during bench-to-bedside translation and thus raises concerns that phenotypic reproducibility does not necessarily render an animal model appropriate for drug development. These findings emphasize a careful application of these model systems for ALS therapy development thereby benefiting refinement of animal experiments. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022373146.
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Affiliation(s)
| | | | - Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin Victor Ineichen
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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17
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Castelnovo V, Canu E, De Mattei F, Filippi M, Agosta F. Basal ganglia alterations in amyotrophic lateral sclerosis. Front Neurosci 2023; 17:1133758. [PMID: 37090799 PMCID: PMC10113480 DOI: 10.3389/fnins.2023.1133758] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 03/09/2023] [Indexed: 04/09/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) has traditionally been associated with brain damage involving the primary motor cortices and corticospinal tracts. In the recent decades, most of the research studies in ALS have focused on extra-motor and subcortical brain regions. The aim of these studies was to detect additional biomarkers able to support the diagnosis and to predict disease progression. The involvement of the frontal cortices, mainly in ALS cases who develop cognitive and/or behavioral impairment, is amply recognized in the field. A potential involvement of fronto-temporal and fronto-striatal connectivity changes in the disease evolution has also been reported. On this latter regard, there is still a shortage of studies which investigated basal ganglia (BG) alterations and their role in ALS clinical manifestation and progression. The present review aims to provide an overview on the magnetic resonance imaging studies reporting structural and/or functional BG alterations in patients with ALS, to clarify the role of BG damage in the disease clinical evolution and to propose potential future developments in this field.
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Affiliation(s)
- Veronica Castelnovo
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Filippo De Mattei
- ALS Center, SC Neurologia 1U, AOU Città della Salute e della Scienza of Torino, Turin, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- *Correspondence: Federica Agosta,
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18
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Dey A, Luk CC, Ishaque A, Ta D, Srivastava O, Krebs D, Seres P, Hanstock C, Beaulieu C, Korngut L, Frayne R, Zinman L, Graham S, Genge A, Briemberg H, Kalra S. Motor cortex functional connectivity is associated with underlying neurochemistry in ALS. J Neurol Neurosurg Psychiatry 2023; 94:193-200. [PMID: 36379713 PMCID: PMC9985743 DOI: 10.1136/jnnp-2022-329993] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/18/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To identify structural and neurochemical properties that underlie functional connectivity impairments of the primary motor cortex (PMC) and how these relate to clinical findings in amyotrophic lateral sclerosis (ALS). METHODS 52 patients with ALS and 52 healthy controls, matched for age and sex, were enrolled from 5 centres across Canada for the Canadian ALS Neuroimaging Consortium study. Resting-state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy data were acquired. Functional connectivity maps, diffusion metrics and neurometabolite ratios were obtained from the analyses of the acquired multimodal data. A clinical assessment of foot tapping (frequency) was performed to examine upper motor neuron function in all participants. RESULTS Compared with healthy controls, the primary motor cortex in ALS showed reduced functional connectivity with sensory (T=5.21), frontal (T=3.70), temporal (T=3.80), putaminal (T=4.03) and adjacent motor (T=4.60) regions. In the primary motor cortex, N-acetyl aspartate (NAA, a neuronal marker) ratios and diffusion metrics (mean, axial and radial diffusivity, fractional anisotropy (FA)) were altered. Within the ALS cohort, foot tapping frequency correlated with NAA (r=0.347) and white matter FA (r=0.537). NAA levels showed associations with disturbed functional connectivity of the motor cortex. CONCLUSION In vivo neurochemistry may represent an effective imaging marker of impaired motor cortex functional connectivity in ALS.
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Affiliation(s)
- Avyarthana Dey
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada.,Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Collin C Luk
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Abdullah Ishaque
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada.,Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Daniel Ta
- Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Ojas Srivastava
- Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Dennell Krebs
- Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Peter Seres
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Chris Hanstock
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Lawrence Korngut
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Richard Frayne
- Seaman Family Magnetic Resonance Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada.,Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Lorne Zinman
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Simon Graham
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Angela Genge
- The Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
| | - Hannah Briemberg
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada .,Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
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19
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Sako W, Haji S, Abe T, Osaki Y, Matsumoto Y, Harada M, Izumi Y. M1/precuneus ratio as a surrogate marker of upper motor neuron sign in ALS. J Neurol Sci 2023; 445:120548. [PMID: 36640663 DOI: 10.1016/j.jns.2023.120548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
OBJECTIVE To investigate whether primary motor cortex (M1) volume measured with an automated approach in MRI reflects upper motor neuron dysfunction and whether it can serve as a potential diagnostic and/or disease-tracking biomarker for amyotrophic lateral sclerosis (ALS). METHODS In this retrospective study, we enrolled 95 subjects, including 33 possible or laboratory supported probable ALS, 26 probable or definite ALS (Prob/Def), 2 primary lateral sclerosis patients, 8 progressive muscular atrophy patients, 19 normal controls (NC) and 7 ALS patients having a second structural MRI scan. Some subjects also underwent functional MRI. We calculated M1, primary sensory cortex, precuneus volumes, and total gray matter volume (TGMV) with FreeSurfer. The sensorimotor network (SMN) was identified using independent component analysis. RESULTS The M1/precuneus ratio showed a significant difference between the NC and Prob/Def groups (p < 0.05). The diagnostic accuracy of the M1/precuneus ratio was moderate for distinguishing Prob/Def from NC (cutoff = 1.00, sensitivity = 0.42, specificity = 0.90). Two of eight cases without upper motor neuron dysfunction could be diagnosed with ALS using M1/precuneus ratio as a surrogate marker. A negative correlation between M1/precuneus ratio and functional activity was found in Brodmann area 6 in the SMN in all subjects. TGMV tended to decrease with disease progression (p = 0.04). INTERPRETATION The M1/precuneus volume ratio, associated with the SMN, may have potential as a surrogate biomarker of upper motor neuron dysfunction in ALS. Furthermore, TGMV may serve as an ALS disease-tracking biomarker.
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Affiliation(s)
- Wataru Sako
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan; Department of Neurology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan.
| | - Shotaro Haji
- Department of Neurology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Takashi Abe
- Department of Radiology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Yusuke Osaki
- Department of Neurology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Yuki Matsumoto
- Department of Radiology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Masafumi Harada
- Department of Radiology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Yuishin Izumi
- Department of Neurology, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
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20
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Sennfält S, Pagani M, Fang F, Savitcheva I, Estenberg U, Ingre C. FDG-PET shows weak correlation between focal motor weakness and brain metabolic alterations in ALS. Amyotroph Lateral Scler Frontotemporal Degener 2023:1-10. [PMID: 36755485 DOI: 10.1080/21678421.2023.2174881] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Objective: Amyotrophic lateral sclerosis (ALS) is a clinically heterogenous disease, typically presenting with focal motor weakness that eventually generalizes. Weather there is a correlation between focal motor weakness and metabolic alterations in specific areas of the brain has not been thoroughly explored. This study aims to systematically investigate this by using fluorodeoxyglucose-positron emission tomography (FDG-PET), including longitudinal imaging. Methods: This observational imaging study included 131 ALS patients diagnosed and examined with FDG-PET at the ALS Clinical Research Center at the Karolinska University Hospital in Stockholm, Sweden. Thirteen ALS patients had a second scan and were analyzed longitudinally. The findings were compared to 39 healthy controls examined at the University Medical Center of Gröningen, the Netherlands. Results: There was a general pattern of brain metabolic alterations consistent with previously reported findings in ALS, namely hypometabolism in frontal regions and hypermetabolism in posterior regions. A higher symptom burden was associated with increased hypometabolism and decreased hypermetabolism. However, there was no clear correlation between focal motor weakness and specific metabolic alterations, neither when analyzing focal motor weakness with concomitant upper motor neuron signs or when including all focal motor weakness. Longitudinal FDG-PET imaging showed inconsistent results with little correlation between progression of motor weakness and metabolic alterations. Conclusion: Our results support the disease model of ALS as a diffuse process since no clear correlation was seen between focal motor weakness and specific metabolic alterations. However, there is need for further research on a larger number of patients, particularly including longitudinal imaging.
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Affiliation(s)
- Stefan Sennfält
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Marco Pagani
- Institute of Cognitive Sciences and Technologies, C.N.R, Rome, Italy.,Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, and
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Irina Savitcheva
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, and
| | - Ulrika Estenberg
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, and
| | - Caroline Ingre
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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21
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Toh C, Keslake A, Payne T, Onwuegbuzie A, Harding J, Baster K, Hoggard N, Shaw PJ, Wilkinson ID, Jenkins TM. Analysis of brain and spinal MRI measures in a common domain to investigate directional neurodegeneration in motor neuron disease. J Neurol 2023; 270:1682-1690. [PMID: 36509983 PMCID: PMC9971079 DOI: 10.1007/s00415-022-11520-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/26/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) of the brain and cervical spinal cord is often performed in diagnostic evaluation of suspected motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). Analysis of MRI-derived tissue damage metrics in a common domain facilitates group-level inferences on pathophysiology. This approach was applied to address competing hypotheses of directionality of neurodegeneration, whether anterograde, cranio-caudal dying-forward from precentral gyrus or retrograde, dying-back. METHODS In this cross-sectional study, MRI was performed on 75 MND patients and 13 healthy controls. Precentral gyral thickness was estimated from volumetric T1-weighted images using FreeSurfer, corticospinal tract fractional anisotropy (FA) from diffusion tensor imaging using FSL, and cross-sectional cervical cord area between C1-C8 levels using Spinal Cord Toolbox. To analyse these multimodal data within a common domain, individual parameter estimates representing tissue damage at each corticospinal tract level were first converted to z-scores, referenced to healthy control norms. Mixed-effects linear regression models were then fitted to these z-scores, with gradients hypothesised to represent directionality of neurodegeneration. RESULTS At group-level, z-scores did not differ significantly between precentral gyral and intracranial corticospinal tract tissue damage estimates (regression coefficient - 0.24, [95% CI - 0.62, 0.14], p = 0.222), but step-changes were evident between intracranial corticospinal tract and C1 (1.14, [95% CI 0.74, 1.53], p < 0.001), and between C5 and C6 cord levels (0.98, [95% CI 0.58, 1.38], p < 0.001). DISCUSSION Analysis of brain and cervical spinal MRI data in a common domain enabled investigation of pathophysiological hypotheses in vivo. A cranio-caudal step-change in MND patients was observed, and requires further investigation in larger cohorts.
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Affiliation(s)
- C Toh
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - A Keslake
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - T Payne
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - A Onwuegbuzie
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - J Harding
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - K Baster
- School of Mathematics and Statistics, University of Sheffield, Sheffield, UK
| | - N Hoggard
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - P J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - I D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - T M Jenkins
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK.
- Royal Perth Hospital, Victoria Square, Perth, WA, 6000, Australia.
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22
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Ashhurst JF, Tu S, Timmins HC, Kiernan MC. Progress, development, and challenges in amyotrophic lateral sclerosis clinical trials. Expert Rev Neurother 2022; 22:905-913. [PMID: 36543326 DOI: 10.1080/14737175.2022.2161893] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Amyotrophic Lateral Sclerosis (ALS) brings unique challenges to a clinical trial setting, due in part to relatively low disease prevalence coupled with a poor prognosis, in addition to the complexities linked to disease heterogeneity. As critical understanding of the disease develops, particularly in relation to clinical phenotype and the mechanisms of disease progression, so too new concepts evolve in relation to clinical trials, including the advent of precision therapy, targeted to subgroups of ALS patients. AREAS COVERED Individualized, or precision medicine in ALS recognizes the heterogeneous nature of the disease and utilizes information such as the clinical phenotype of the disease, clinical biomarkers, and genotyping to promote a tailored approach to treatment. Separate to these considerations, the present review will discuss clinical trial design and how this can be improved to better match patient and investigator needs in ALS clinical trials. EXPERT OPINION Precision therapy will promote a more focused treatment approach, with the goal of improving clinical outcomes for ALS patients. An increased community awareness of ALS, coupled with significant industry and philanthropic funding for ALS research, is accelerating this process.
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Affiliation(s)
| | - Sicong Tu
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - Hannah C Timmins
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - Matthew C Kiernan
- Brain and Mind Centre, University of Sydney, Camperdown, Australia.,Department of Neurology, Royal Prince Alfred Hospital, Sydney, Australia
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23
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Chipika RH, Mulkerrin G, Pradat PF, Murad A, Ango F, Raoul C, Bede P. Cerebellar pathology in motor neuron disease: neuroplasticity and neurodegeneration. Neural Regen Res 2022; 17:2335-2341. [PMID: 35535867 PMCID: PMC9120698 DOI: 10.4103/1673-5374.336139] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Amyotrophic lateral sclerosis is a relentlessly progressive multi-system condition. The clinical picture is dominated by upper and lower motor neuron degeneration, but extra-motor pathology is increasingly recognized, including cerebellar pathology. Post-mortem and neuroimaging studies primarily focus on the characterization of supratentorial disease, despite emerging evidence of cerebellar degeneration in amyotrophic lateral sclerosis. Cardinal clinical features of amyotrophic lateral sclerosis, such as dysarthria, dysphagia, cognitive and behavioral deficits, saccade abnormalities, gait impairment, respiratory weakness and pseudobulbar affect are likely to be exacerbated by co-existing cerebellar pathology. This review summarizes in vivo and post mortem evidence for cerebellar degeneration in amyotrophic lateral sclerosis. Structural imaging studies consistently capture cerebellar grey matter volume reductions, diffusivity studies readily detect both intra-cerebellar and cerebellar peduncle white matter alterations and functional imaging studies commonly report increased functional connectivity with supratentorial regions. Increased functional connectivity is commonly interpreted as evidence of neuroplasticity representing compensatory processes despite the lack of post-mortem validation. There is a scarcity of post-mortem studies focusing on cerebellar alterations, but these detect pTDP-43 in cerebellar nuclei. Cerebellar pathology is an overlooked facet of neurodegeneration in amyotrophic lateral sclerosis despite its contribution to a multitude of clinical symptoms, widespread connectivity to spinal and supratentorial regions and putative role in compensating for the degeneration of primary motor regions.
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Affiliation(s)
- Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Grainne Mulkerrin
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Aizuri Murad
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Fabrice Ango
- The Neuroscience Institute of Montpellier (INM), INSERM, CNRS, Montpellier, France
| | - Cédric Raoul
- The Neuroscience Institute of Montpellier (INM), INSERM, CNRS, Montpellier, France
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland; Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
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24
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Zejlon C, Nakhostin D, Winklhofer S, Pangalu A, Kulcsar Z, Lewandowski S, Finnsson J, Piehl F, Ingre C, Granberg T, Ineichen BV. Structural magnetic resonance imaging findings and histopathological correlations in motor neuron diseases—A systematic review and meta-analysis. Front Neurol 2022; 13:947347. [PMID: 36110394 PMCID: PMC9468579 DOI: 10.3389/fneur.2022.947347] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesThe lack of systematic evidence on neuroimaging findings in motor neuron diseases (MND) hampers the diagnostic utility of magnetic resonance imaging (MRI). Thus, we aimed at performing a systematic review and meta-analysis of MRI features in MND including their histopathological correlation.MethodsIn a comprehensive literature search, out of 5941 unique publications, 223 records assessing brain and spinal cord MRI findings in MND were eligible for a qualitative synthesis. 21 records were included in a random effect model meta-analysis.ResultsOur meta-analysis shows that both T2-hyperintensities along the corticospinal tracts (CST) and motor cortex T2*-hypointensitites, also called “motor band sign”, are more prevalent in ALS patients compared to controls [OR 2.21 (95%-CI: 1.40–3.49) and 10.85 (95%-CI: 3.74–31.44), respectively]. These two imaging findings correlate to focal axonal degeneration/myelin pallor or glial iron deposition on histopathology, respectively. Additionally, certain clinical MND phenotypes such as amyotrophic lateral sclerosis (ALS) seem to present with distinct CNS atrophy patterns.ConclusionsAlthough CST T2-hyperintensities and the “motor band sign” are non-specific imaging features, they can be leveraged for diagnostic workup of suspected MND cases, together with certain brain atrophy patterns. Collectively, this study provides high-grade evidence for the usefulness of MRI in the diagnostic workup of suspected MND cases.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182682.
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Affiliation(s)
- Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Dominik Nakhostin
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | | | - Johannes Finnsson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Caroline Ingre
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- *Correspondence: Benjamin Victor Ineichen
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25
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Juengling FD, Wuest F, Kalra S, Agosta F, Schirrmacher R, Thiel A, Thaiss W, Müller HP, Kassubek J. Simultaneous PET/MRI: The future gold standard for characterizing motor neuron disease-A clinico-radiological and neuroscientific perspective. Front Neurol 2022; 13:890425. [PMID: 36061999 PMCID: PMC9428135 DOI: 10.3389/fneur.2022.890425] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 07/20/2022] [Indexed: 01/18/2023] Open
Abstract
Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives.
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Affiliation(s)
- Freimut D. Juengling
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Faculty of Medicine, University Bern, Bern, Switzerland
| | - Frank Wuest
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Neurology, University of Alberta, Edmonton, AB, Canada
| | - Federica Agosta
- Division of Neuroscience, San Raffaele Scientific Institute, University Vita Salute San Raffaele, Milan, Italy
| | - Ralf Schirrmacher
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
- Medical Isotope and Cyclotron Facility, University of Alberta, Edmonton, AB, Canada
| | - Alexander Thiel
- Lady Davis Institute for Medical Research, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Wolfgang Thaiss
- Department of Nuclear Medicine, University of Ulm Medical Center, Ulm, Germany
- Department of Diagnostic and Interventional Radiology, University of Ulm Medical Center, Ulm, Germany
| | - Hans-Peter Müller
- Department of Neurology, Ulm University Medical Center, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, Ulm University Medical Center, Ulm, Germany
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26
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Colvin LE, Foster ZW, Stein TD, Thakore-James M, Salajegheh MK, Carr K, Spencer KR, Rauf NA, Adams L, Averill JG, Walker SE, Robey I, Alvarez VE, Huber BR, McKee AC, Kowall NW, Brady CB. Utility of the ALSFRS-R for predicting ALS and comorbid disease neuropathology: The Veterans Affairs Biorepository Brain Bank. Muscle Nerve 2022; 66:167-174. [PMID: 35585776 PMCID: PMC9308705 DOI: 10.1002/mus.27635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 05/09/2022] [Accepted: 05/13/2022] [Indexed: 01/03/2023]
Abstract
INTRODUCTION/AIMS The amyotrophic lateral sclerosis (ALS) functional rating scale-revised (ALSFRS-R) is commonly used to track ALS disease progression; however, there are gaps in the literature regarding the extent to which the ALSFRS-R relates to underlying central nervous system (CNS) pathology. The current study explored the association between ALSFRS-R (total and subdomain) scores and postmortem neuropathology (both ALS-specific and comorbid disease). METHODS Within our sample of 93 military veterans with autopsy-confirmed ALS, we utilized hierarchical cluster analysis (HCA) to identify discrete profiles of motor dysfunction based on ALSFRS-R subdomain scores. We examined whether emergent clusters were associated with neuropathology. Separate analyses of variance and covariance with post-hoc comparisons were performed to examine relevant cluster differences. RESULTS Analyses revealed significant correlations between ALSFRS-R total and subdomain scores with some, but not all, neuropathological variables. The HCA illustrated three groups: Cluster 1-predominantly diffuse functional impairment; Cluster 2-spared respiratory/bulbar and impaired motor function; and Cluster 3-spared bulbar and impaired respiratory, and fine and gross motor function. Individuals in Cluster 1 (and to a lesser degree, Cluster 3) exhibited greater accumulation of ALS-specific neuropathology and less comorbid neuropathology than those in Cluster 2. DISCUSSION These results suggest that discrete patterns of motor dysfunction based on ALSFRS-R subdomain scores are related to postmortem neuropathology. Findings support use of ALSFRS-R subdomain scores to capture the heterogeneity of clinical presentation and disease progression in ALS, and may assist researchers in identifying endophenotypes for separate assessment in clinical trials.
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Affiliation(s)
| | | | - Thor D. Stein
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA
| | - Manisha Thakore-James
- VA Boston Healthcare System, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
| | - M. Kian Salajegheh
- VA Boston Healthcare System, Boston, MA
- Harvard Medical School, Boston, MA
- Brigham and Women’s Hospital
| | | | | | | | | | | | | | - Ian Robey
- Southern Arizona VA Healthcare System, Tucson, Arizona
| | - Victor E. Alvarez
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
| | - Bertrand R. Huber
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
| | - Ann C. McKee
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
- Department of Veterans Affairs Medical Center, Bedford, MA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA
| | - Neil W. Kowall
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, MA
| | - Christopher B. Brady
- VA Boston Healthcare System, Boston, MA
- Boston University School of Medicine, Boston, MA
- Harvard Medical School, Boston, MA
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27
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Liu S, Zhao Y, Ren Q, Zhang D, Shao K, Lin P, Yuan Y, Dai T, Zhang Y, Li L, Li W, Shan P, Meng X, Wang Q, Yan C. Amygdala abnormalities across disease stages in patients with sporadic amyotrophic lateral sclerosis. Hum Brain Mapp 2022; 43:5421-5431. [PMID: 35866384 PMCID: PMC9704775 DOI: 10.1002/hbm.26016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 06/14/2022] [Accepted: 06/26/2022] [Indexed: 01/15/2023] Open
Abstract
To examine selective atrophy patterns and resting-state functional connectivity (FC) alterations in the amygdala at different stages of amyotrophic lateral sclerosis (ALS), and to explore any correlations between amygdala abnormalities and neuropsychiatric symptoms. We used the King's clinical staging system for ALS to divide 83 consecutive patients with ALS into comparable subgroups at different disease stages. We explored the pattern of selective amygdala subnucleus atrophy and amygdala-based whole-brain FC alteration in these patients and 94 healthy controls (HCs). Cognitive and emotional functions were also evaluated using a neuropsychological test battery. There were no significant differences between ALS patients at King's stage 1 and HCs for any amygdala subnucleus volumes. Compared with HCs, ALS patients at King's stage 2 had significantly lower left accessory basal nucleus and cortico-amygdaloid transition volumes. Furthermore, ALS patients at King's stage 3 demonstrated significant reductions in most amygdala subnucleus volumes and global amygdala volumes compared with HCs. Notably, amygdala-cuneus FC was increased in ALS patients at King's stage 3. Specific subnucleus volumes were significantly associated with Mini-Mental State Examination scores and Hamilton Anxiety Rating Scale scores in ALS patients. In conclusions, our study provides a comprehensive profile of amygdala abnormalities in ALS patients. The pattern of amygdala abnormalities in ALS patients differed greatly across King's clinical disease stages, and amygdala abnormalities are an important feature of patients with ALS at relatively advanced stages. Moreover, our findings suggest that amygdala volume may play an important role in anxiety and cognitive dysfunction in ALS patients.
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Affiliation(s)
- Shuangwu Liu
- School of Medicine, Cheeloo College of MedicineShandong UniversityJinanChina,Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina,School of Nursing and Rehabilitation, Cheeloo College of MedicineShandong UniversityJinanChina
| | - Yuying Zhao
- Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina
| | - Qingguo Ren
- Department of RadiologyQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoChina
| | - Dong Zhang
- Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina
| | - Kai Shao
- Mitochondrial Medicine LaboratoryQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoShandongChina,Department of Clinical LaboratoryQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoChina
| | - Pengfei Lin
- Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina
| | - Ying Yuan
- Sleep Medicine CenterQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoChina
| | - Tingjun Dai
- Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina
| | - Yongqing Zhang
- Department of NeurologyQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoChina
| | - Ling Li
- Department of NeurologyQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoChina
| | - Wei Li
- Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina
| | - Peiyan Shan
- Department of GerontologyQilu Hospital of Shandong UniversityJinanChina
| | - Xiangshui Meng
- Department of RadiologyQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoChina
| | - Qian Wang
- Department of RadiologyQilu Hospital of Shandong UniversityJinanChina
| | - Chuanzhu Yan
- Department of NeurologyResearch Institute of Neuromuscular and Neurodegenerative Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong UniversityJinanChina,Mitochondrial Medicine LaboratoryQilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong UniversityQingdaoShandongChina
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28
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Romano A, Trosi Lopez E, Liparoti M, Polverino A, Minino R, Trojsi F, Bonavita S, Mandolesi L, Granata C, Amico E, Sorrentino G, Sorrentino P. The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment. Neuroimage Clin 2022; 35:103095. [PMID: 35764029 PMCID: PMC9241102 DOI: 10.1016/j.nicl.2022.103095] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/31/2022] [Accepted: 06/19/2022] [Indexed: 10/25/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = -7.40), and the MiToS (p = 0.0025; β = -4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho = -0.6041, p = 0.0003) and MiToS scales (Spearman's rho = -0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.
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Affiliation(s)
- Antonella Romano
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Emahnuel Trosi Lopez
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Marianna Liparoti
- Department of Social and Developmental Psychology, University of Rome "Sapienza", Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Simona Bonavita
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Laura Mandolesi
- Department of Humanistic Studies, University of Naples Federico II, via Porta di Massa 1, 80133, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy
| | - Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, EPFL, Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy; Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy; Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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29
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Münch M, Müller HP, Behler A, Ludolph AC, Kassubek J. Segmental alterations of the corpus callosum in motor neuron disease: A DTI and texture analysis in 575 patients. Neuroimage Clin 2022; 35:103061. [PMID: 35653913 PMCID: PMC9163839 DOI: 10.1016/j.nicl.2022.103061] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/15/2022] [Accepted: 05/26/2022] [Indexed: 10/29/2022]
Abstract
INTRODUCTION Within the core neuroimaging signature of amyotrophic lateral sclerosis (ALS), the corpus callosum (CC) is increasingly recognized as a consistent feature. The aim of this study was to investigate the sensitivity and specificity of the microstructural segmental CC morphology, assessed by diffusion tensor imaging (DTI) and high-resolution T1-weighted (T1w) imaging, in a large cohort of ALS patients including different clinical phenotypes. METHODS In a single-centre study, 575 patients with ALS (classical phenotype, N = 432; restricted phenotypes primary lateral sclerosis (PLS) N = 55, flail arm syndrome (FAS) N = 45, progressive bulbar palsy (PBP) N = 22, lower motor neuron disease (LMND) N = 21) and 112 healthy controls underwent multiparametric MRI, i.e. volume-rendering T1w scans and DTI. Tract-based fractional anisotropy statistics (TFAS) was applied to callosal tracts of CC areas I-V, identified from DTI data (tract-of-interest (TOI) analysis), and texture analysis was applied to T1w data. In order to further specify the callosal alterations, a support vector machine (SVM) algorithm was used to discriminate between motor neuron disease patients and controls. RESULTS The analysis of white matter integrity revealed predominantly FA reductions for tracts of the callosal areas I, II, and III (with highest reductions in callosal area III) for all ALS patients and separately for each phenotype when compared to controls; texture analysis demonstrated significant alterations of the parameters entropy and homogeneity for ALS patients and all phenotypes for the CC areas I, II, and III (with again highest reductions in callosal area III) compared to controls. With SVM applied on multiparametric callosal parameters of area III, a separation of all ALS patients including phenotypes from controls with 72% sensitivity and 73% specificity was achieved. These results for callosal area III parameters could be improved by an SVM of six multiparametric callosal parameters of areas I, II, and III, achieving a separation of all ALS patients including phenotypes from controls with 84% sensitivity and 85% specificity. DISCUSSION The multiparametric MRI texture and DTI analysis demonstrated substantial alterations of the frontal and central CC with most significant alterations in callosal area III (motor segment) in ALS and separately in all investigated phenotypes (PLS, FAS, PBP, LMND) in comparison to controls, while no significant differences were observed between ALS and its phenotypes. The combination of the texture and the DTI parameters in an unbiased SVM-based approach might contribute as a neuroimaging marker for the assessment of the CC in ALS, including subtypes.
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Affiliation(s)
| | | | - Anna Behler
- Department of Neurology, University of Ulm, Germany
| | - Albert C Ludolph
- Department of Neurology, University of Ulm, Germany; German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Germany; German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany.
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30
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Goutman SA, Hardiman O, Al-Chalabi A, Chió A, Savelieff MG, Kiernan MC, Feldman EL. Recent advances in the diagnosis and prognosis of amyotrophic lateral sclerosis. Lancet Neurol 2022; 21:480-493. [PMID: 35334233 PMCID: PMC9513753 DOI: 10.1016/s1474-4422(21)00465-8] [Citation(s) in RCA: 171] [Impact Index Per Article: 57.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 11/24/2021] [Accepted: 12/16/2021] [Indexed: 12/14/2022]
Abstract
The diagnosis of amyotrophic lateral sclerosis can be challenging due to its heterogeneity in clinical presentation and overlap with other neurological disorders. Diagnosis early in the disease course can improve outcomes as timely interventions can slow disease progression. An evolving awareness of disease genotypes and phenotypes and new diagnostic criteria, such as the recent Gold Coast criteria, could expedite diagnosis. Improved prognosis, such as that achieved with the survival model from the European Network for the Cure of ALS, could inform the patient and their family about disease course and improve end-of-life planning. Novel staging and scoring systems can help monitor disease progression and might potentially serve as clinical trial outcomes. Lastly, new tools, such as fluid biomarkers, imaging modalities, and neuromuscular electrophysiological measurements, might increase diagnostic and prognostic accuracy.
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Affiliation(s)
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, and Department of Neurology, King's College London, London, UK
| | - Adriano Chió
- Rita Levi Montalcini Department of Neurosciences, University of Turin, Turin, Italy
| | | | - Matthew C Kiernan
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia; Department of Neurology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Eva L Feldman
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA.
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31
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Pandya S, Maia PD, Freeze B, Menke RAL, Talbot K, Turner MR, Raj A. Modeling seeding and neuroanatomic spread of pathology in amyotrophic lateral sclerosis. Neuroimage 2022; 251:118968. [PMID: 35143975 PMCID: PMC10729776 DOI: 10.1016/j.neuroimage.2022.118968] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 01/26/2022] [Accepted: 02/02/2022] [Indexed: 12/12/2022] Open
Abstract
The neurodegenerative disorder amyotrophic lateral sclerosis (ALS) is characterized by the progressive loss of upper and lower motor neurons, with pathological involvement of cerebral motor and extra-motor areas in a clinicopathological spectrum with frontotemporal dementia (FTD). A key unresolved issue is how the non-random distribution of pathology in ALS reflects differential network vulnerability, including molecular factors such as regional gene expression, or preferential spread of pathology via anatomical connections. A system of histopathological staging of ALS based on the regional burden of TDP-43 pathology observed in postmortem brains has been supported to some extent by analysis of distribution of in vivo structural MRI changes. In this paper, computational modeling using a Network Diffusion Model (NDM) was used to investigate whether a process of focal pathological 'seeding' followed by structural network-based spread recapitulated postmortem histopathological staging and, secondly, whether this had any correlation to the pattern of expression of a panel of genes implicated in ALS across the healthy brain. Regionally parcellated T1-weighted MRI data from ALS patients (baseline n=79) was studied in relation to a healthy control structural connectome and a database of associated regional cerebral gene expression. The NDM provided strong support for a structural network-based basis for regional pathological spread in ALS, but no simple relationship to the spatial distribution of ALS-related genes in the healthy brain. Interestingly, OPTN gene was identified as a significant but a weaker non-NDM contributor within the network-gene interaction model (LASSO). Intriguingly, the critical seed regions for spread within the model were not within the primary motor cortex but basal ganglia, thalamus and insula, where NDM recapitulated aspects of the postmortem histopathological staging system. Within the ALS-FTD clinicopathological spectrum, non-primary motor structures may be among the earliest sites of cerebral pathology.
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Affiliation(s)
- Sneha Pandya
- Department of Radiology, Weill Cornell Medicine, 1300 York Avenue, New York, NY, United States.
| | - Pedro D Maia
- Department of Mathematics, University of Texas at Arlington, TX, United States
| | - Benjamin Freeze
- Scripps Health/MD Anderson Cancer Center, Department of Radiology, CA, United States
| | - Ricarda A L Menke
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, West Wing Level 6, Oxford OX2 7PZ, United Kingdom
| | - Kevin Talbot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, West Wing Level 6, Oxford OX2 7PZ, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
| | - Ashish Raj
- Department of Radiology, Weill Cornell Medicine, 1300 York Avenue, New York, NY, United States; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94121, United States.
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32
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Mejia AF, Koppelmans V, Jelsone-Swain L, Kalra S, Welsh RC. Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS. Neuroimage 2022; 255:119180. [PMID: 35395402 PMCID: PMC9580623 DOI: 10.1016/j.neuroimage.2022.119180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 03/28/2022] [Accepted: 04/03/2022] [Indexed: 11/13/2022] Open
Abstract
Longitudinal fMRI studies hold great promise for the study of neurodegenerative diseases, development and aging, but realizing their full potential depends on extracting accurate fMRI-based measures of brain function and organization in individual subjects over time. This is especially true for studies of rare, heterogeneous and/or rapidly progressing neurodegenerative diseases. These often involve small samples with heterogeneous functional features, making traditional group-difference analyses of limited utility. One such disease is amyotrophic lateral sclerosis (ALS), a severe disease resulting in extreme loss of motor function and eventual death. Here, we use an advanced individualized task fMRI analysis approach to analyze a rich longitudinal dataset containing 190 hand clench fMRI scans from 16 ALS patients (78 scans) and 22 age-matched healthy controls (112 scans) Specifically, we adopt our cortical surface-based spatial Bayesian general linear model (GLM), which has high power and precision to detect activations in individual subjects, and propose a novel longitudinal extension to leverage information shared across visits. We perform all analyses in native surface space to preserve individua anatomical and functional features. Using mixed-effects models to subsequently study the relationship between size of activation and ALS disease progression, we observe for the first time an inverted U-shaped trajectory o motor activations: at relatively mild motor disability we observe enlarging activations, while at higher levels of motor disability we observe severely diminished activation, reflecting progression toward complete loss of motor function. We further observe distinct trajectories depending on clinical progression rate, with faster progressors exhibiting more extreme changes at an earlier stage of disability. These differential trajectories suggest that initial hyper-activation is likely attributable to loss of inhibitory neurons, rather than functional compensation as earlier assumed. These findings substantially advance scientific understanding of the ALS disease process. This study also provides the first real-world example of how surface-based spatial Bayesian analysis of task fMRI can further scientific understanding of neurodegenerative disease and other phenomena. The surface-based spatial Bayesian GLM is implemented in the BayesfMRI R package
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Affiliation(s)
- Amanda F Mejia
- Department of Statistics, Indiana University, Bloomington, IN, USA.
| | | | - Laura Jelsone-Swain
- Department of Psychology, University of South Carolina Aiken, Aiken, SC, USA
| | - Sanjay Kalra
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Robert C Welsh
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
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33
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Tendler BC, Hanayik T, Ansorge O, Bangerter-Christensen S, Berns GS, Bertelsen MF, Bryant KL, Foxley S, van den Heuvel MP, Howard AFD, Huszar IN, Khrapitchev AA, Leonte A, Manger PR, Menke RAL, Mollink J, Mortimer D, Pallebage-Gamarallage M, Roumazeilles L, Sallet J, Scholtens LH, Scott C, Smart A, Turner MR, Wang C, Jbabdi S, Mars RB, Miller KL. The Digital Brain Bank, an open access platform for post-mortem imaging datasets. eLife 2022; 11:e73153. [PMID: 35297760 PMCID: PMC9042233 DOI: 10.7554/elife.73153] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Olaf Ansorge
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sarah Bangerter-Christensen
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen ZooFrederiksbergDenmark
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Department of Radiology, University of ChicagoChicagoUnited States
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Amy FD Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alexandre A Khrapitchev
- Medical Research Council Oxford Institute for Radiation Oncology, University of OxfordOxfordUnited Kingdom
| | - Anna Leonte
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the WitwatersrandJohannesburgSouth Africa
| | - Ricarda AL Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Duncan Mortimer
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Menuka Pallebage-Gamarallage
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Stem Cell and Brain Research Institute, Université Lyon 1, INSERMBronFrance
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis. Neurol Res Int 2022; 2022:1838682. [PMID: 35178253 PMCID: PMC8844436 DOI: 10.1155/2022/1838682] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 01/13/2022] [Indexed: 12/11/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.
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Thome J, Steinbach R, Grosskreutz J, Durstewitz D, Koppe G. Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics. Hum Brain Mapp 2022; 43:681-699. [PMID: 34655259 PMCID: PMC8720197 DOI: 10.1002/hbm.25679] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 09/27/2021] [Indexed: 12/19/2022] Open
Abstract
Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional connectivity between brain regions by linear methods highlight the role of brain function. These studies have yet to be combined with brain structure and nonlinear functional features. We investigate the role of linear and nonlinear functional brain features, and the benefit of combining brain structure and function for ALS classification. ALS patients (N = 97) and healthy controls (N = 59) underwent structural and functional resting state magnetic resonance imaging. Based on key hubs of resting state networks, we defined three feature sets comprising brain volume, resting state functional connectivity (rsFC), as well as (nonlinear) resting state dynamics assessed via recurrent neural networks. Unimodal and multimodal random forest classifiers were built to classify ALS. Out-of-sample prediction errors were assessed via five-fold cross-validation. Unimodal classifiers achieved a classification accuracy of 56.35-61.66%. Multimodal classifiers outperformed unimodal classifiers achieving accuracies of 62.85-66.82%. Evaluating the ranking of individual features' importance scores across all classifiers revealed that rsFC features were most dominant in classification. While univariate analyses revealed reduced rsFC in ALS patients, functional features more generally indicated deficits in information integration across resting state brain networks in ALS. The present work undermines that combining brain structure and function provides an additional benefit to diagnostic classification, as indicated by multimodal classifiers, while emphasizing the importance of capturing both linear and nonlinear functional brain properties to identify discriminative biomarkers of ALS.
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Affiliation(s)
- Janine Thome
- Department of Theoretical Neuroscience, Central Institute of Mental Health Mannheim, Medical Faculty MannheimHeidelberg UniversityGermany
- Clinic for Psychiatry and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty MannheimHeidelberg UniversityGermany
| | - Robert Steinbach
- Hans Berger Department of NeurologyJena University HospitalJenaGermany
| | - Julian Grosskreutz
- Precision Neurology, Department of NeurologyUniversity of LuebeckLuebeckGermany
| | - Daniel Durstewitz
- Department of Theoretical Neuroscience, Central Institute of Mental Health Mannheim, Medical Faculty MannheimHeidelberg UniversityGermany
| | - Georgia Koppe
- Department of Theoretical Neuroscience, Central Institute of Mental Health Mannheim, Medical Faculty MannheimHeidelberg UniversityGermany
- Clinic for Psychiatry and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty MannheimHeidelberg UniversityGermany
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Cividini C, Basaia S, Spinelli EG, Canu E, Castelnovo V, Riva N, Cecchetti G, Caso F, Magnani G, Falini A, Filippi M, Agosta F. Amyotrophic Lateral Sclerosis-Frontotemporal Dementia: Shared and Divergent Neural Correlates Across the Clinical Spectrum. Neurology 2022; 98:e402-e415. [PMID: 34853179 PMCID: PMC8793105 DOI: 10.1212/wnl.0000000000013123] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 11/19/2021] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND AND OBJECTIVES A significant overlap between amyotrophic lateral sclerosis (ALS) and behavioral variant of frontotemporal dementia (bvFTD) has been observed at clinical, genetic, and pathologic levels. Within this continuum of presentations, the presence of mild cognitive or behavioral symptoms in patients with ALS has been consistently reported, although it is unclear whether this is to be considered a distinct phenotype or rather a natural evolution of ALS. Here, we used mathematical modeling of MRI connectomic data to decipher common and divergent neural correlates across the ALS-frontotemporal dementia (FTD) spectrum. METHODS We included 83 patients with ALS, 35 patients with bvFTD, and 61 healthy controls, who underwent clinical, cognitive, and MRI assessments. Patients with ALS were classified according to the revised Strong criteria into 54 ALS with only motor deficits (ALS-cn), 21 ALS with cognitive or behavioral involvement (ALS-ci/bi), and 8 ALS with bvFTD (ALS-FTD). First, we assessed the functional and structural connectivity patterns across the ALS-FTD spectrum. Second, we investigated whether and where MRI connectivity alterations of patients with ALS with any degree of cognitive impairment (i.e., ALS-ci/bi and ALS-FTD) resembled more the pattern of damage of one (ALS-cn) or the other end (bvFTD) of the spectrum, moving from group-level to single-subject analysis. RESULTS As compared with controls, extensive structural and functional disruption of the frontotemporal and parietal networks characterized bvFTD (bvFTD-like pattern), while a more focal structural damage within the sensorimotor-basal ganglia areas characterized ALS-cn (ALS-cn-like pattern). ALS-ci/bi patients demonstrated an ALS-cn-like pattern of structural damage, diverging from ALS-cn with similar motor impairment for the presence of enhanced functional connectivity within sensorimotor areas and decreased functional connectivity within the bvFTD-like pattern. On the other hand, patients with ALS-FTD resembled both structurally and functionally the bvFTD-like pattern of damage with, in addition, the structural ALS-cn-like damage in the motor areas. DISCUSSION Our findings suggest a maladaptive role of functional rearrangements in ALS-ci/bi concomitantly with similar structural alterations compared to ALS-cn, supporting the hypothesis that ALS-ci/bi might be considered as a phenotypic variant of ALS, rather than a consequence of disease worsening.
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Affiliation(s)
- Camilla Cividini
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Silvia Basaia
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Edoardo G Spinelli
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Elisa Canu
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Veronica Castelnovo
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Nilo Riva
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Giordano Cecchetti
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Francesca Caso
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Giuseppe Magnani
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Andrea Falini
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy
| | - Federica Agosta
- From the Neuroimaging Research Unit, Division of Neuroscience (C.C., S.B., E.G.S., E.C., V.C., G.C., M.F., F.A.), Neurorehabilitation Unit (N.R., M.F.), Neurology Unit (G.C., F.C., G.M., M.F., F.A.), Neuroradiology Unit (A.F.), CERMAC (A.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute; and Vita-Salute San Raffaele University (C.C., E.G.S., V.C., G.C., A.F., M.F., F.A.), Milan, Italy.
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Finegan E, Siah WF, Li Hi Shing S, Chipika RH, Hardiman O, Bede P. Cerebellar degeneration in primary lateral sclerosis: an under-recognized facet of PLS. Amyotroph Lateral Scler Frontotemporal Degener 2022; 23:542-553. [PMID: 34991421 DOI: 10.1080/21678421.2021.2023188] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
While primary lateral sclerosis (PLS) has traditionally been regarded as a pure upper motor neuron disorder, recent clinical, neuroimaging and postmortem studies have confirmed significant extra-motor involvement. Sporadic reports have indicated that in addition to the motor cortex and corticospinal tracts, the cerebellum may also be affected in PLS. Cerebellar manifestations are difficult to ascertain in PLS as the clinical picture is dominated by widespread upper motor neuron signs. The likely contribution of cerebellar dysfunction to gait disturbance, falls, pseudobulbar affect and dysarthria may be overlooked in the context of progressive spasticity. The objective of this study is the comprehensive characterization of cerebellar gray and white matter degeneration in PLS using multiparametric quantitative neuroimaging methods to systematically evaluate each cerebellar lobule and peduncle. Forty-two patients with PLS and 117 demographically-matched healthy controls were enrolled in a prospective MRI study. Complementary volumetric and voxelwise analyses revealed focal cerebellar alterations instead of global cerebellar atrophy. Bilateral gray matter volume reductions were observed in lobules III, IV and VIIb. Significant diffusivity alterations within the superior cerebellar peduncle indicate disruption of the main cerebellar outflow tracts. These findings suggest that the considerable intra-cerebellar disease-burden is coupled with concomitant cerebro-cerebellar connectivity disruptions. While cerebellar dysfunction is challenging to demonstrate clinically, cerebellar pathology is likely to be a significant contributor to disability in PLS.
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Affiliation(s)
- Eoin Finegan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital Dublin, Dublin, Ireland
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18F-FDG-PET correlates of aging and disease course in ALS as revealed by distinct PVC approaches. Eur J Radiol Open 2022; 9:100394. [PMID: 35059473 PMCID: PMC8760536 DOI: 10.1016/j.ejro.2022.100394] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 12/23/2021] [Accepted: 01/06/2022] [Indexed: 11/23/2022] Open
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Li Q, Zhu W, Wen X, Zang Z, Da Y, Lu J. Different sensorimotor mechanism in fast and slow progression amyotrophic lateral sclerosis. Hum Brain Mapp 2021; 43:1710-1719. [PMID: 34931392 PMCID: PMC8886636 DOI: 10.1002/hbm.25752] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 11/22/2021] [Accepted: 12/01/2021] [Indexed: 11/12/2022] Open
Abstract
The huge heterogeneity of the disease progression rate may cause inconsistent findings between local activity and functional connectivity of the primary sensorimotor area (PSMA) in amyotrophic lateral sclerosis (ALS). For illustration of this hypothesis, resting-state fMRI (RS-fMRI) data were collected and analyzed on 38 "definite" or "probable" ALS patients (19 fast and 19 slow, cut off median = 0.41) and 37 matched healthy controls. Amplitude of low frequency fluctuations (ALFFs) and functional connectivity strength (FCS) were analyzed within the PSMA. There was a decreased ALFF (pFDR <.05) and FCS (p = .022) in all ALS patients. The two metrics shared about 50% of variance (R = .7) and both showed significant positive correlation with ALS Functional Rating Scale-Revised (ALSFRS-R) in the fast (p values <.034) but not in the slow progression groups. Interestingly, when regressing out the ALFF, the PSMA network FCS, especially the inter-hemisphere FCS, showed negative correlation with the ALSFRS-R score in the slow (R = -.54, p = .026) but not the fast progression group. In summary, the current results suggest that RS-fMRI local activity and network functional connectivity accounts for the severity differently in the slow and fast progression ALS patients.
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Affiliation(s)
- Qianwen Li
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Wenjia Zhu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xinmei Wen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yuwei Da
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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40
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Ishaque A, Ta D, Khan M, Zinman L, Korngut L, Genge A, Dionne A, Briemberg H, Luk C, Yang YH, Beaulieu C, Emery D, Eurich DT, Frayne R, Graham S, Wilman A, Dupré N, Kalra S. Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis. Hum Brain Mapp 2021; 43:1519-1534. [PMID: 34908212 PMCID: PMC8886653 DOI: 10.1002/hbm.25738] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 11/22/2021] [Accepted: 11/25/2021] [Indexed: 01/17/2023] Open
Abstract
Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T0 ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T0 and Tmax (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at Tmax than at T0 . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.
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Affiliation(s)
- Abdullah Ishaque
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Daniel Ta
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Muhammad Khan
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Lorne Zinman
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
| | - Lawrence Korngut
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Angela Genge
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, Montreal, Canada
| | - Annie Dionne
- Département des Sciences Neurologiques, Hôpital de l'Enfant-Jésus, CHU de Québec, Quebec City, Canada
| | - Hannah Briemberg
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Collin Luk
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Yee-Hong Yang
- Department of Computing Science, University of Alberta, Edmonton
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Derek Emery
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Canada
| | - Dean T Eurich
- School of Public Health, University of Alberta, Edmonton, Canada
| | - Richard Frayne
- Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Seaman Family MR Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Canada
| | - Simon Graham
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Alan Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Nicolas Dupré
- Neuroscience Axis, CHU de Québec, Université Laval, Quebec City, Canada.,Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, Canada
| | - Sanjay Kalra
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.,Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
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41
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Ahmed RM, Bocchetta M, Todd EG, Tse NY, Devenney EM, Tu S, Caga J, Hodges JR, Halliday GM, Irish M, Kiernan MC, Piguet O, Rohrer JD. Tackling clinical heterogeneity across the amyotrophic lateral sclerosis-frontotemporal dementia spectrum using a transdiagnostic approach. Brain Commun 2021; 3:fcab257. [PMID: 34805999 PMCID: PMC8599039 DOI: 10.1093/braincomms/fcab257] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 07/31/2021] [Accepted: 08/18/2021] [Indexed: 11/28/2022] Open
Abstract
The disease syndromes of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) display considerable clinical, genetic and pathological overlap, yet mounting evidence indicates substantial differences in progression and survival. To date, there has been limited examination of how profiles of brain atrophy might differ between clinical phenotypes. Here, we address this longstanding gap in the literature by assessing cortical and subcortical grey and white matter volumes on structural MRI in a large cohort of 209 participants. Cognitive and behavioural changes were assessed using the Addenbrooke’s Cognitive Examination and the Cambridge Behavioural Inventory. Relative to 58 controls, behavioural variant FTD (n = 58) and ALS–FTD (n = 41) patients displayed extensive atrophy of frontoinsular, cingulate, temporal and motor cortices, with marked subcortical atrophy targeting the hippocampus, amygdala, thalamus and striatum, with atrophy further extended to the brainstem, pons and cerebellum in the latter group. At the other end of the spectrum, pure-ALS patients (n = 52) displayed considerable frontoparietal atrophy, including right insular and motor cortices and pons and brainstem regions. Subcortical regions included the bilateral pallidum and putamen, but to a lesser degree than in the ALS–FTD and behavioural variant FTD groups. Across the spectrum the most affected region in all three groups was the insula, and specifically the anterior part (76–90% lower than controls). Direct comparison of the patient groups revealed disproportionate temporal atrophy and widespread subcortical involvement in ALS–FTD relative to pure-ALS. In contrast, pure-ALS displayed significantly greater parietal atrophy. Both behavioural variant FTD and ALS–FTD were characterized by volume decrease in the frontal lobes relative to pure-ALS. The motor cortex and insula emerged as differentiating structures between clinical syndromes, with bilateral motor cortex atrophy more pronounced in ALS–FTD compared with pure-ALS, and greater left motor cortex and insula atrophy relative to behavioural variant FTD. Taking a transdiagnostic approach, we found significant associations between abnormal behaviour and volume loss in a predominantly frontoinsular network involving the amygdala, striatum and thalamus. Our findings demonstrate the presence of distinct atrophy profiles across the ALS–FTD spectrum, with key structures including the motor cortex and insula. Notably, our results point to subcortical involvement in the origin of behavioural disturbances, potentially accounting for the marked phenotypic variability typically observed across the spectrum.
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Affiliation(s)
- Rebekah M Ahmed
- Memory and Cognition Clinic, Institute of Clinical Neurosciences, Royal Prince Alfred Hospital, Sydney 2050, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London WC1E, UK
| | - Emily G Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London WC1E, UK
| | - Nga Yan Tse
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Emma M Devenney
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Sicong Tu
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Jashelle Caga
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - John R Hodges
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia.,School of Psychology and Brain and Mind Centre, The University of Sydney, Sydney 2050, Australia
| | - Glenda M Halliday
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Muireann Irish
- School of Psychology and Brain and Mind Centre, The University of Sydney, Sydney 2050, Australia
| | - Matthew C Kiernan
- Memory and Cognition Clinic, Institute of Clinical Neurosciences, Royal Prince Alfred Hospital, Sydney 2050, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Olivier Piguet
- School of Psychology and Brain and Mind Centre, The University of Sydney, Sydney 2050, Australia
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London WC1E, UK
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42
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Tahedl M, Li Hi Shing S, Finegan E, Chipika RH, Lope J, Hardiman O, Bede P. Propagation patterns in motor neuron diseases: Individual and phenotype-associated disease-burden trajectories across the UMN-LMN spectrum of MNDs. Neurobiol Aging 2021; 109:78-87. [PMID: 34656922 DOI: 10.1016/j.neurobiolaging.2021.04.031] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/29/2021] [Accepted: 04/13/2021] [Indexed: 01/18/2023]
Abstract
Motor neuron diseases encompass a divergent group of conditions with considerable differences in clinical manifestations, survival, and genetic vulnerability. One of the key aspects of clinical heterogeneity is the preferential involvement of upper (UMN) and lower motor neurons (LMN). While longitudinal imaging patters are relatively well characterized in ALS, progressive cortical changes in UMN,- and LMN-predominant conditions are seldom evaluated. Accordingly, the objective of this study is the juxtaposition of longitudinal trajectories in 3 motor neuron phenotypes; a UMN-predominant syndrome (PLS), a mixed UMN-LMN condition (ALS), and a lower motor neuron condition (poliomyelitis survivors). A standardized imaging protocol was implemented in a prospective, multi-timepoint longitudinal study with a uniform follow-up interval of 4 months. Forty-five poliomyelitis survivors, 61 patients with amyotrophic lateral sclerosis (ALS), and 23 patients with primary lateral sclerosis (PLS) were included. Cortical thickness alterations were evaluated in a dual analysis pipeline, using standard cortical thickness analyses, and a z-score-based individualized approach. Our results indicate that PLS patients exhibit rapidly progressive cortical thinning primarily in motor regions; ALS patients show cortical atrophy in both motor and extra-motor regions, while poliomyelitis survivors exhibit cortical thickness gains in a number of cerebral regions. Our findings suggest that dynamic cortical changes in motor neuron diseases may depend on relative UMN and/or LMN involvement, and increased cortical thickness in LMN-predominant conditions may represent compensatory, adaptive processes.
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Affiliation(s)
- Marlene Tahedl
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland; Department of Psychiatry and Psychotherapy and Institute for Psychology, University of Regensburg, 93053 Regensburg, Germany
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland; Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France.
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43
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Pathological neural networks and artificial neural networks in ALS: diagnostic classification based on pathognomonic neuroimaging features. J Neurol 2021; 269:2440-2452. [PMID: 34585269 PMCID: PMC9021106 DOI: 10.1007/s00415-021-10801-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/07/2021] [Accepted: 09/09/2021] [Indexed: 12/26/2022]
Abstract
The description of group-level, genotype- and phenotype-associated imaging traits is academically important, but the practical demands of clinical neurology centre on the accurate classification of individual patients into clinically relevant diagnostic, prognostic and phenotypic categories. Similarly, pharmaceutical trials require the precision stratification of participants based on quantitative measures. A single-centre study was conducted with a uniform imaging protocol to test the accuracy of an artificial neural network classification scheme on a cohort of 378 participants composed of patients with ALS, healthy subjects and disease controls. A comprehensive panel of cerebral volumetric measures, cortical indices and white matter integrity values were systematically retrieved from each participant and fed into a multilayer perceptron model. Data were partitioned into training and testing and receiver-operating characteristic curves were generated for the three study-groups. Area under the curve values were 0.930 for patients with ALS, 0.958 for disease controls, and 0.931 for healthy controls relying on all input imaging variables. The ranking of variables by classification importance revealed that white matter metrics were far more relevant than grey matter indices to classify single subjects. The model was further tested in a subset of patients scanned within 6 weeks of their diagnosis and an AUC of 0.915 was achieved. Our study indicates that individual subjects may be accurately categorised into diagnostic groups in an observer-independent classification framework based on multiparametric, spatially registered radiology data. The development and validation of viable computational models to interpret single imaging datasets are urgently required for a variety of clinical and clinical trial applications.
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44
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Lewis MJ, Shomper JL, Williamson BG, Vansteenkiste DP, Bibi KF, Lim SHY, Kowal JB, Coates JR. Brain diffusion tensor imaging in dogs with degenerative myelopathy. J Vet Intern Med 2021; 35:2342-2349. [PMID: 34410026 PMCID: PMC8478048 DOI: 10.1111/jvim.16248] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 07/29/2021] [Accepted: 08/03/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Degenerative myelopathy (DM) in dogs shares similarities with superoxide dismutase 1-associated human amyotrophic lateral sclerosis (ALS). Brain microstructural lesions are quantified using diffusion tensor imaging (DTI) in ALS patients. OBJECTIVE Characterize brain neurodegenerative changes in DM-affected dogs using DTI. ANIMALS Sixteen DM-affected and 8 control dogs. METHODS Prospective observational study. Brain DTI was performed at baseline and every 3 months on DM-affected dogs and compared to controls. Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated on specified regions of interest. Gait scores (0, normal to 14, tetraplegia) were assigned at each scan. Diffusion tensor imaging values in DM-affected dogs were compared to controls, gait scores, and evaluated over time. RESULTS Mean age was 5.7 years (SD 3.2) in controls and 9.7 years (SD 1.4) in DM-affected dogs. In DM-affected dogs, mean baseline gait score was 4 (SD 1), and mean score change from baseline to last scan was 4.82 (SD 2.67). Nine dogs had ≤3 scans; 7 had >3 scans. Accounting for age, no differences in DTI indices were identified for any brain or proximal spinal cord regions between DM-affected dogs and controls (P > .05). Diffusion tensor imaging values poorly correlated with gait scores (R2 < .2). No significant changes were identified in diffusion indices over time (P > .05). CONCLUSIONS AND CLINICAL IMPORTANCE Diffusion tensor imaging indices did not differentiate DM-affected from control dogs, detect longitudinal changes, or differentiate disease severity. Findings do not yet support brain DTI as an imaging biomarker.
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Affiliation(s)
- Melissa J. Lewis
- Department of Veterinary Clinical SciencesCollege of Veterinary Medicine, Purdue UniversityWest LafayetteINUSA
| | - Jeremy L. Shomper
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
| | - Baye G. Williamson
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
| | - Daniella P. Vansteenkiste
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
| | - Katherine F. Bibi
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
| | - Stefanie H. Y. Lim
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
| | - Joseph B. Kowal
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
| | - Joan R. Coates
- Department of Veterinary Medicine and SurgeryUniversity of Missouri, College of Veterinary MedicineColumbiaMOUSA
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45
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Gilmore M, Elman L, Babu S, Andres P, Floeter MK. Measuring disease progression in primary lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener 2021; 21:59-66. [PMID: 33602016 DOI: 10.1080/21678421.2020.1837179] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Quantitative measures of disease severity are essential outcome measures for clinical trials. The slow progression of disease in primary lateral sclerosis (PLS) requires clinical measures that are sensitive to changes occurring within the time frame of a clinical trial. Proposed clinical outcome measures include the PLS functional rating scale (PLSFRS), burden scores derived from clinical examination findings, and quantitative measures of motor performance. The PLSFRS has good inter-rater reliability and showed greater longitudinal change over 6- and 12-months compared to the revised ALS functional rating scale. Examination-based upper motor neuron burden (UMNB) scales also have good reliability, and longitudinal studies are in process. Quantitative measures of strength, dexterity, gait, and speech have the potential to provide objective and precise measures of clinical change, but have been the least studied in persons with PLS.
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Affiliation(s)
- Madison Gilmore
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Lauren Elman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Suma Babu
- Sean M Healy & AMG Center for ALS, Massachusetts General Hospital, Boston, MA, USA
| | - Patricia Andres
- Neurological Clinical Research Institute, Massachusetts General Hospital, Boston, MA, USA
| | - Mary Kay Floeter
- National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
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46
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Abstract
OBJECTIVE Advanced neuroimaging techniques may offer the potential to monitor disease progression in amyotrophic lateral sclerosis (ALS), a neurodegenerative, multisystem disease that still lacks therapeutic outcome measures. We aim to investigate longitudinal functional and structural magnetic resonance imaging (MRI) changes in a cohort of patients with ALS monitored for one year after diagnosis. METHODS Resting state functional MRI, diffusion tensor imaging (DTI), and voxel-based morphometry analyses were performed in 22 patients with ALS examined by six-monthly MRI scans over one year. RESULTS During the follow-up period, patients with ALS showed reduced functional connectivity only in some extramotor areas, such as the middle temporal gyrus in the left frontoparietal network after six months and in the left middle frontal gyrus in the default mode network after one year without showing longitudinal changes of cognitive functions. Moreover, after six months, we reported in the ALS group a decreased fractional anisotropy (P = .003, Bonferroni corrected) in the right uncinate fasciculus. Conversely, we did not reveal significant longitudinal changes of functional connectivity in the sensorimotor network, as well as of gray matter (GM) atrophy or of DTI metrics in motor areas, although clinical measures of motor disability showed significant decline throughout the three time points. CONCLUSION Our findings highlighted that progressive impairment of extramotor frontotemporal networks may precede the appearance of executive and language dysfunctions and GM changes in ALS. Functional connectivity changes in cognitive resting state networks might represent candidate radiological markers of disease progression.
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47
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Lin Z, Kim E, Ahmed M, Han G, Simmons C, Redhead Y, Bartlett J, Pena Altamira LE, Callaghan I, White MA, Singh N, Sawiak S, Spires-Jones T, Vernon AC, Coleman MP, Green J, Henstridge C, Davies JS, Cash D, Sreedharan J. MRI-guided histology of TDP-43 knock-in mice implicates parvalbumin interneuron loss, impaired neurogenesis and aberrant neurodevelopment in amyotrophic lateral sclerosis-frontotemporal dementia. Brain Commun 2021; 3:fcab114. [PMID: 34136812 PMCID: PMC8204366 DOI: 10.1093/braincomms/fcab114] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 04/13/2021] [Accepted: 04/17/2021] [Indexed: 01/01/2023] Open
Abstract
Amyotrophic lateral sclerosis and frontotemporal dementia are overlapping diseases in which MRI reveals brain structural changes in advance of symptom onset. Recapitulating these changes in preclinical models would help to improve our understanding of the molecular causes underlying regionally selective brain atrophy in early disease. We therefore investigated the translational potential of the TDP-43Q331K knock-in mouse model of amyotrophic lateral sclerosis-frontotemporal dementia using MRI. We performed in vivo MRI of TDP-43Q331K knock-in mice. Regions of significant volume change were chosen for post-mortem brain tissue analyses. Ex vivo computed tomography was performed to investigate skull shape. Parvalbumin neuron density was quantified in post-mortem amyotrophic lateral sclerosis frontal cortex. Adult mutants demonstrated parenchymal volume reductions affecting the frontal lobe and entorhinal cortex in a manner reminiscent of amyotrophic lateral sclerosis-frontotemporal dementia. Subcortical, cerebellar and brain stem regions were also affected in line with observations in pre-symptomatic carriers of mutations in C9orf72, the commonest genetic cause of both amyotrophic lateral sclerosis and frontotemporal dementia. Volume loss was also observed in the dentate gyrus of the hippocampus, along with ventricular enlargement. Immunohistochemistry revealed reduced parvalbumin interneurons as a potential cellular correlate of MRI changes in mutant mice. By contrast, microglia was in a disease activated state even in the absence of brain volume loss. A reduction in immature neurons was found in the dentate gyrus, indicative of impaired adult neurogenesis, while a paucity of parvalbumin interneurons in P14 mutant mice suggests that TDP-43Q331K disrupts neurodevelopment. Computerized tomography imaging showed altered skull morphology in mutants, further suggesting a role for TDP-43Q331K in development. Finally, analysis of human post-mortem brains confirmed a paucity of parvalbumin interneurons in the prefrontal cortex in sporadic amyotrophic lateral sclerosis and amyotrophic lateral sclerosis linked to C9orf72 mutations. Regional brain MRI changes seen in human amyotrophic lateral sclerosis-frontotemporal dementia are recapitulated in TDP-43Q331K knock-in mice. By marrying in vivo imaging with targeted histology, we can unravel cellular and molecular processes underlying selective brain vulnerability in human disease. As well as helping to understand the earliest causes of disease, our MRI and histological markers will be valuable in assessing the efficacy of putative therapeutics in TDP-43Q331K knock-in mice.
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Affiliation(s)
- Ziqiang Lin
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 9RT, UK
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Eugene Kim
- BRAIN Centre (Biomarker Research And Imaging for Neuroscience), Department of Neuroimaging, IoPPN, King’s College London, London SE5 9NU, UK
| | - Mohi Ahmed
- Centre for Craniofacial and Regenerative Biology, Floor 27 Tower Wing, Guy’s Hospital, King’s College London, London SE1 9RT, UK
| | - Gang Han
- Molecular Neurobiology Group, Institute of Life Sciences, School of Medicine, Swansea University, Swansea SA2 8PP, UK
| | - Camilla Simmons
- BRAIN Centre (Biomarker Research And Imaging for Neuroscience), Department of Neuroimaging, IoPPN, King’s College London, London SE5 9NU, UK
| | - Yushi Redhead
- Centre for Craniofacial and Regenerative Biology, Floor 27 Tower Wing, Guy’s Hospital, King’s College London, London SE1 9RT, UK
| | - Jack Bartlett
- Molecular Neurobiology Group, Institute of Life Sciences, School of Medicine, Swansea University, Swansea SA2 8PP, UK
| | - Luis Emiliano Pena Altamira
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 9RT, UK
| | - Isobel Callaghan
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 9RT, UK
| | - Matthew A White
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 9RT, UK
| | - Nisha Singh
- BRAIN Centre (Biomarker Research And Imaging for Neuroscience), Department of Neuroimaging, IoPPN, King’s College London, London SE5 9NU, UK
- School of Biomedical Engineering & Imaging Sciences, St Thomas' Hospital, King's College London, 4th floor Lambeth Wing, London SE1 7EH, UK
| | - Stephen Sawiak
- Department of Clinical Neurosciences, Cambridge University, Cambridge CB2 0QQ, UK
| | - Tara Spires-Jones
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - Anthony C Vernon
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 9RT, UK
| | | | - Jeremy Green
- Centre for Craniofacial and Regenerative Biology, Floor 27 Tower Wing, Guy’s Hospital, King’s College London, London SE1 9RT, UK
| | - Christopher Henstridge
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
- Division of Systems Medicine, School of Medicine, University of Dundee, Dundee DD1 9SY, UK
| | - Jeffrey S Davies
- Molecular Neurobiology Group, Institute of Life Sciences, School of Medicine, Swansea University, Swansea SA2 8PP, UK
| | - Diana Cash
- BRAIN Centre (Biomarker Research And Imaging for Neuroscience), Department of Neuroimaging, IoPPN, King’s College London, London SE5 9NU, UK
| | - Jemeen Sreedharan
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 9RT, UK
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48
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Fullam T, Statland J. Upper Motor Neuron Disorders: Primary Lateral Sclerosis, Upper Motor Neuron Dominant Amyotrophic Lateral Sclerosis, and Hereditary Spastic Paraplegia. Brain Sci 2021; 11:brainsci11050611. [PMID: 34064596 PMCID: PMC8151104 DOI: 10.3390/brainsci11050611] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 05/02/2021] [Accepted: 05/10/2021] [Indexed: 11/16/2022] Open
Abstract
Following the exclusion of potentially reversible causes, the differential for those patients presenting with a predominant upper motor neuron syndrome includes primary lateral sclerosis (PLS), hereditary spastic paraplegia (HSP), or upper motor neuron dominant ALS (UMNdALS). Differentiation of these disorders in the early phases of disease remains challenging. While no single clinical or diagnostic tests is specific, there are several developing biomarkers and neuroimaging technologies which may help distinguish PLS from HSP and UMNdALS. Recent consensus diagnostic criteria and use of evolving technologies will allow more precise delineation of PLS from other upper motor neuron disorders and aid in the targeting of potentially disease-modifying therapeutics.
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49
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Barry RL, Babu S, Anteraper SA, Triantafyllou C, Keil B, Rowe OE, Rangaprakash D, Paganoni S, Lawson R, Dheel C, Cernasov PM, Rosen BR, Ratai EM, Atassi N. Ultra-high field (7T) functional magnetic resonance imaging in amyotrophic lateral sclerosis: a pilot study. NEUROIMAGE-CLINICAL 2021; 30:102648. [PMID: 33872993 PMCID: PMC8060594 DOI: 10.1016/j.nicl.2021.102648] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 03/17/2021] [Accepted: 03/23/2021] [Indexed: 12/24/2022]
Abstract
Participants with ALS exhibited impaired function between the cortex and cerebellum. The cerebellum is associated with complex motor and cognitive processing tasks. These findings add to the growing number of ALS reports implicating the cerebellum.
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the central nervous system that results in a progressive loss of motor function and ultimately death. It is critical, yet also challenging, to develop non-invasive biomarkers to identify, localize, measure and/or track biological mechanisms implicated in ALS. Such biomarkers may also provide clues to identify potential molecular targets for future therapeutic trials. Herein we report on a pilot study involving twelve participants with ALS and nine age-matched healthy controls who underwent high-resolution resting state functional magnetic resonance imaging at an ultra-high field of 7 Tesla. A group-level whole-brain analysis revealed a disruption in long-range functional connectivity between the superior sensorimotor cortex (in the precentral gyrus) and bilateral cerebellar lobule VI. Post hoc analyses using atlas-derived left and right cerebellar lobule VI revealed decreased functional connectivity in ALS participants that predominantly mapped to bilateral postcentral and precentral gyri. Cerebellar lobule VI is a transition zone between anterior motor networks and posterior non-motor networks in the cerebellum, and is associated with a wide range of key functions including complex motor and cognitive processing tasks. Our observation of the involvement of cerebellar lobule VI adds to the growing number of studies implicating the cerebellum in ALS. Future avenues of scientific investigation should consider how high-resolution imaging at 7T may be leveraged to visualize differences in functional connectivity disturbances in various genotypes and phenotypes of ALS along the ALS-frontotemporal dementia spectrum.
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Affiliation(s)
- Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA.
| | - Suma Babu
- Sean M. Healey & AMG Center for ALS at Massachusetts General Hospital, Department of Neurology, Neurological Clinical Research Institute, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Sheeba Arnold Anteraper
- Department of Psychology, Northeastern University, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Christina Triantafyllou
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Siemens Healthineers, Erlangen, Germany
| | - Boris Keil
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Mittelhessen University of Applied Sciences, Department of Life Science Engineering, Institute of Medical Physics and Radiation Protection, Giessen, Germany
| | - Olivia E Rowe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - D Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Sabrina Paganoni
- Sean M. Healey & AMG Center for ALS at Massachusetts General Hospital, Department of Neurology, Neurological Clinical Research Institute, Boston, MA, USA; Spaulding Rehabilitation Hospital, Charlestown, MA, USA; Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, USA
| | - Robert Lawson
- Sean M. Healey & AMG Center for ALS at Massachusetts General Hospital, Department of Neurology, Neurological Clinical Research Institute, Boston, MA, USA
| | - Christina Dheel
- Sean M. Healey & AMG Center for ALS at Massachusetts General Hospital, Department of Neurology, Neurological Clinical Research Institute, Boston, MA, USA
| | - Paul M Cernasov
- Sean M. Healey & AMG Center for ALS at Massachusetts General Hospital, Department of Neurology, Neurological Clinical Research Institute, Boston, MA, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Division of Neuroradiology, Massachusetts General Hospital, Boston, MA, USA
| | - Nazem Atassi
- Sean M. Healey & AMG Center for ALS at Massachusetts General Hospital, Department of Neurology, Neurological Clinical Research Institute, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Sanofi Genzyme, Cambridge, MA, USA
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Cognitive dysfunction in amyotrophic lateral sclerosis: can we predict it? Neurol Sci 2021; 42:2211-2222. [PMID: 33772353 PMCID: PMC8159827 DOI: 10.1007/s10072-021-05188-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/15/2021] [Indexed: 01/26/2023]
Abstract
Background and aim Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the degeneration of both upper and lower motoneurons in the brain and spinal cord leading to motor and extra-motor symptoms. Although traditionally considered a pure motor disease, recent evidences suggest that ALS is a multisystem disorder. Neuropsychological alterations, in fact, are observed in more than 50% of patients: while executive dysfunctions have been firstly identified, alterations in verbal fluency, behavior, and pragmatic and social cognition have also been described. Detecting and monitoring ALS cognitive and behavioral impairment even at early disease stages is likely to have staging and prognostic implications, and it may impact the enrollment in future clinical trials. During the last 10 years, humoral, radiological, neurophysiological, and genetic biomarkers have been reported in ALS, and some of them seem to potentially correlate to cognitive and behavioral impairment of patients. In this review, we sought to give an up-to-date state of the art of neuropsychological alterations in ALS: we will describe tests used to detect cognitive and behavioral impairment, and we will focus on promising non-invasive biomarkers to detect pre-clinical cognitive decline. Conclusions To date, the research on humoral, radiological, neurophysiological, and genetic correlates of neuropsychological alterations is at the early stage, and no conclusive longitudinal data have been published. Further and longitudinal studies on easily accessible and quantifiable biomarkers are needed to clarify the time course and the evolution of cognitive and behavioral impairments of ALS patients.
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