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Kleinerova J, McKenna MC, Finnegan M, Tacheva A, Garcia-Gallardo A, Mohammed R, Tan EL, Christidi F, Hardiman O, Hutchinson S, Bede P. Clinical, Cortical, Subcortical, and White Matter Features of Right Temporal Variant FTD. Brain Sci 2024; 14:806. [PMID: 39199498 PMCID: PMC11352857 DOI: 10.3390/brainsci14080806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Revised: 08/05/2024] [Accepted: 08/09/2024] [Indexed: 09/01/2024] Open
Abstract
The distinct clinical and radiological characteristics of right temporal variant FTD have only been recently recognized. METHODS Eight patients with right temporal variant FTD were prospectively recruited and underwent a standardised neuropsychological assessment, clinical MRI, and quantitative neuroimaging. RESULTS Our voxelwise grey analyses captured bilateral anterior and mesial temporal grey matter atrophy with a clear right-sided predominance. Bilateral hippocampal involvement was also observed, as well as disease burden in the right insular and opercula regions. White matter integrity alterations were also bilateral in anterior temporal and sub-insular regions with a clear right-hemispheric predominance. Extra-temporal white matter alterations have also been observed in orbitofrontal and parietal regions. Significant bilateral but right-predominant thalamus, putamen, hippocampus, and amygdala atrophy was identified based on subcortical segmentation. The clinical profile of our patients was dominated by progressive indifference, decline in motivation, loss of interest in previously cherished activities, incremental social withdrawal, difficulty recognising people, progressive language deficits, increasingly rigid routines, and repetitive behaviours. CONCLUSIONS Right temporal variant FTD has an insidious onset and may be mistaken for depression at symptom onset. It manifests in a combination of apathy, language, and behavioural features. Quantitative MR imaging captures a characteristic bilateral but right-predominant temporal imaging signature with extra-temporal frontal and parietal involvement.
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Affiliation(s)
- Jana Kleinerova
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Mary Clare McKenna
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
| | - Martha Finnegan
- Department of Psychiatry, Tallaght University Hospital, D24 NR0A Dublin, Ireland
| | - Asya Tacheva
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | | | - Rayan Mohammed
- Department of Neurology, St James’s Hospital, D08 KC95 Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Foteini Christidi
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, 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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Kleinerova J, Tahedl M, Tan EL, Delaney S, Hengeveld JC, Doherty MA, McLaughlin RL, Hardiman O, Chang KM, Finegan E, Bede P. Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study. J Neurol 2024; 271:3239-3255. [PMID: 38438819 PMCID: PMC11136747 DOI: 10.1007/s00415-024-12261-z] [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: 12/21/2023] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 03/06/2024]
Abstract
BACKGROUND Primary lateral sclerosis (PLS) is traditionally solely associated with progressive upper motor neuron dysfunction manifesting in limb spasticity, gait impairment, bulbar symptoms and pseudobulbar affect. Recent studies have described frontotemporal dysfunction in some patients resulting in cognitive manifestations. Cerebellar pathology is much less well characterised despite sporadic reports of cerebellar disease. METHODS A multi-timepoint, longitudinal neuroimaging study was conducted to characterise the evolution of both intra-cerebellar disease burden and cerebro-cerebellar connectivity. The volumes of deep cerebellar nuclei, cerebellar cortical volumes, cerebro-cerebellar structural and functional connectivity were assessed longitudinally in a cohort of 43 individuals with PLS. RESULTS Cerebello-frontal, -temporal, -parietal, -occipital and cerebello-thalamic structural disconnection was detected at baseline based on radial diffusivity (RD) and cerebello-frontal decoupling was also evident based on fractional anisotropy (FA) alterations. Functional connectivity changes were also detected in cerebello-frontal, parietal and occipital projections. Volume reductions were identified in the vermis, anterior lobe, posterior lobe, and crura. Among the deep cerebellar nuclei, the dorsal dentate was atrophic. Longitudinal follow-up did not capture statistically significant progressive changes. Significant primary motor cortex atrophy and inter-hemispheric transcallosal degeneration were also captured. CONCLUSIONS PLS is not only associated with upper motor neuron dysfunction, but cerebellar cortical volume loss and deep cerebellar nuclear atrophy can also be readily detected. In addition to intra-cerebellar disease burden, cerebro-cerebellar connectivity alterations also take place. Our data add to the evolving evidence of widespread neurodegeneration in PLS beyond the primary motor regions. Cerebellar dysfunction in PLS is likely to exacerbate bulbar, gait and dexterity impairment and contribute to pseudobulbar affect.
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Affiliation(s)
- Jana Kleinerova
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Marlene Tahedl
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Siobhan Delaney
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | | | - Mark A Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland.
- Department of Neurology, St James's Hospital, Dublin, Ireland.
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Tahedl M, Tan EL, Siah WF, Hengeveld JC, Doherty MA, McLaughlin RL, Hardiman O, Finegan E, Bede P. Radiological correlates of pseudobulbar affect: Corticobulbar and cerebellar components in primary lateral sclerosis. J Neurol Sci 2023; 451:120726. [PMID: 37421883 DOI: 10.1016/j.jns.2023.120726] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/02/2023] [Accepted: 06/28/2023] [Indexed: 07/10/2023]
Abstract
INTRODUCTION Pseudobulbar affect (PBA) is a distressing symptom of a multitude of neurological conditions affecting patients with a rage of neuroinflammatory, neurovascular and neurodegenerative conditions. It manifests in disproportionate emotional responses to minimal or no contextual stimulus. It has considerable quality of life implications and treatment can be challenging. METHODS A prospective multimodal neuroimaging study was conducted to explore the neuroanatomical underpinnings of PBA in patients with primary lateral sclerosis (PLS). All participants underwent whole genome sequencing and screening for C9orf72 hexanucleotide repeat expansions, a comprehensive neurological assessment, neuropsychological screening (ECAS, HADS, FrSBe) and PBA was evaluated by the emotional lability questionnaire. Structural, diffusivity and functional MRI data were systematically evaluated in whole-brain (WB) data-driven and region of interest (ROI) hypothesis-driven analyses. In ROI analyses, functional and structural corticobulbar connectivity and cerebello-medullary connectivity alterations were evaluated separately. RESULTS Our data-driven whole-brain analyses revealed associations between PBA and white matter degeneration in descending corticobulbar as well as in commissural tracts. In our hypothesis-driven analyses, PBA was associated with increased right corticobulbar tract RD (p = 0.006) and decreased FA (p = 0.026). The left-hemispheric corticobulbar tract, as well as functional connectivity, showed similar tendencies. While uncorrected p-maps revealed both voxelwise and ROI trends for associations between PBA and cerebellar measures, these did not reach significance to unequivocally support the "cerebellar hypothesis". CONCLUSIONS Our data confirm associations between cortex-brainstem disconnection and the clinical severity of PBA. While our findings may be disease-specific, they are consistent with the classical cortico-medullary model of pseudobulbar affect.
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Affiliation(s)
- Marlene Tahedl
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Ireland
| | | | - Mark A Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Ireland; Department of Neurology, St James's Hospital, Dublin, Ireland.
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McKenna MC, Lope J, Bede P, Tan EL. Thalamic pathology in frontotemporal dementia: Predilection for specific nuclei, phenotype-specific signatures, clinical correlates, and practical relevance. Brain Behav 2023; 13:e2881. [PMID: 36609810 PMCID: PMC9927864 DOI: 10.1002/brb3.2881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 12/17/2022] [Accepted: 12/18/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Frontotemporal dementia (FTD) phenotypes are classically associated with distinctive cortical atrophy patterns and regional hypometabolism. However, the spectrum of cognitive and behavioral manifestations in FTD arises from multisynaptic network dysfunction. The thalamus is a key hub of several corticobasal and corticocortical circuits. The main circuits relayed via the thalamic nuclei include the dorsolateral prefrontal circuit, the anterior cingulate circuit, and the orbitofrontal circuit. METHODS In this paper, we have reviewed evidence for thalamic pathology in FTD based on radiological and postmortem studies. Original research papers were systematically reviewed for preferential involvement of specific thalamic regions, for phenotype-associated thalamic disease burden patterns, characteristic longitudinal changes, and genotype-associated thalamic signatures. Moreover, evidence for presymptomatic thalamic pathology was also reviewed. Identified papers were systematically scrutinized for imaging methods, cohort sizes, clinical profiles, clinicoradiological associations, and main anatomical findings. The findings of individual research papers were amalgamated for consensus observations and their study designs further evaluated for stereotyped shortcomings. Based on the limitations of existing studies and conflicting reports in low-incidence FTD variants, we sought to outline future research directions and pressing research priorities. RESULTS FTD is associated with focal thalamic degeneration. Phenotype-specific thalamic traits mirror established cortical vulnerability patterns. Thalamic nuclei mediating behavioral and language functions are preferentially involved. Given the compelling evidence for considerable thalamic disease burden early in the course of most FTD subtypes, we also reflect on the practical relevance, diagnostic role, prognostic significance, and monitoring potential of thalamic metrics in FTD. CONCLUSIONS Cardinal manifestations of FTD phenotypes are likely to stem from thalamocortical circuitry dysfunction and are not exclusively driven by focal cortical changes.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
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McKenna MC, Murad A, Huynh W, Lope J, Bede P. The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation. Expert Rev Neurother 2022; 22:179-207. [PMID: 35227146 DOI: 10.1080/14737175.2022.2048648] [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] [Indexed: 11/04/2022]
Abstract
INTRODUCTION While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterised based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorise individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories. AREAS COVERED This article reviews (1) the neuroimaging studies that propose single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) potential practical implications and (3) the limitations of current single-subject data interpretation models. EXPERT OPINION Classification studies in FTLD have demonstrated the feasibility of categorising individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.
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Affiliation(s)
| | - Aizuri Murad
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| | - William Huynh
- Brain and Mind Centre, University of Sydney, Australia
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, France
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