Two decades of advances in muscle imaging in children: from pattern recognition of muscle diseases to quantification and machine learning approaches

Gómez‐Andrés, David; Oulhissane, A.; Quijano‐Roy, Susana

doi:10.1016/j.nmd.2021.08.006

Cited by 3 publications

(4 citation statements)

References 84 publications

(73 reference statements)

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“…The muscle involvement patterns generated from our patient cohort appear distinct from those generated from the literature of other NM genotypes (Figs. 3 and 4) and those commonly associated with other congenital myopathies and muscular dystrophies 7,45 . One exception is the isolated distal lower limb involvement, predominantly of the anterior compartment, seen in around 12% of patients with Laing distal myopathy due to pathogenic MYH7 gene variants, which may mimic the imaging findings seen in NEB ‐NM 46 .…”

Section: Discussionmentioning

confidence: 99%

“…3 and 4 ) and those commonly associated with other congenital myopathies and muscular dystrophies. 7 , 45 One exception is the isolated distal lower limb involvement, predominantly of the anterior compartment, seen in around 12% of patients with Laing distal myopathy due to pathogenic MYH7 gene variants, which may mimic the imaging findings seen in NEB ‐NM. 46 However, Laing myopathy patients may also demonstrate an inverted or true collagen VI sign which is absent in NEB ‐NM and was not seen in any of our patients.…”

Section: Discussionmentioning

confidence: 99%

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Muscle magnetic resonance imaging involvement patterns in nemaline myopathies

Perry

Stimpson

Singh

et al. 2023

Ann Clin Transl Neurol

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Objective: Characterise the diagnostic and prognostic value of muscle MRI patterns as biomarkers in a genetically heterogeneous nemaline myopathy (NM) patient cohort. Methods: Modified Mercuri scoring of lower limb MRI in genetically characterised NM patients referred to the highly specialised service for congenital myopathies at Great Ormond Street Hospital. Findings were compared to clinical data and MRI patterns derived from collated published data. Results: Twenty-seven patients with MRI were identified (8 NEB-NM, 13 ACTA1-NM, 6 TPM3-NM). NEB-NM demonstrated sparing of the thigh. ACTA1-NM demonstrated diffuse thigh involvement, notable in the vasti, sartorius and biceps-femoris, with relative adductor and gracilis sparing. TPM3-NM demonstrated diffuse thigh involvement notable in biceps-femoris and adductor magnus with relative rectus femoris, adductor longus and gracilis sparing. In the lower leg, the soleus and tibialis anterior are notably involved in all three genotypes. NEB-NM and ACTA1-NM demonstrated relative gastrocnemii and tibialis posterior sparing, while TPM3-NM showed significantly more tibialis posterior involvement (P =< 0.05). Comparison of involvement patterns with literature datasets highlighted preferential adductor and gracilis sparing in our ACTA1-NM cohort, consistent tibialis posterior involvement in our TPM3-NM cohort and a distinct MRI pattern from those derived from other NM genotypes and congenital myopathies. Greater tibialis anterior involvement correlated with foot drop (P = 0.02). Greater tibialis anterior and extensor hallucis longus involvement correlated with worse mobility (P =< 0.04). Interpretation: This is the widest NM MRI data set described to date; we describe distinct muscle involvement patterns for NEB-NM, ACTA1-NM and TPM3-NM which may have utility as diagnostic and prognostic biomarkers and aid in genetic variant interpretation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Muscle magnetic resonance imaging involvement patterns in nemaline myopathies

Perry

Stimpson

Singh

et al. 2023

Ann Clin Transl Neurol

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“…To characterize patterns of performance across participants, we employed a hierarchical heat map—a visualization technique renowned for its efficacy in discerning clusters of participants and distinct clinical features, especially within the realm of heterogeneous diseases. 50 This heat map displays a colour-coded matrix representing individual data juxtaposed with clinical features. The participants and the clinical features are organized using hierarchical clustering, ensuring closely related entities are juxtaposed for clearer pattern recognition.…”

Section: Methodsmentioning

confidence: 99%

Clinical dimensions along the non-fluent variant primary progressive aphasia spectrum

Illán-Gala,

Lorca-Puls,

Tee

et al. 2023

Brain

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It is debated whether primary progressive apraxia of speech (PPAOS) and progressive agrammatic aphasia (PAA) belong to the same clinical spectrum traditionally termed nonfluent/agrammatic variant primary progressive aphasia (nfvPPA) or exist as two completely distinct syndromic entities with specific pathologic/prognostic correlates. We analyzed speech, language, and disease severity features in a comprehensive cohort of patients with progressive motor speech impairment and/or agrammatism to ascertain evidence of naturally occurring, clinically meaningful non-overlapping syndromic entities (e.g., PPAOS and PAA) in our data. We also assessed if data-driven latent clinical dimensions with etiologic/prognostic value could be identified. We included 98 participants, 43 of whom had an autopsy-confirmed neuropathological diagnosis. Speech pathologists assessed motor speech features indicative of dysarthria and apraxia of speech (AOS). Quantitative expressive/receptive agrammatism measures were obtained and compared with healthy controls. Baseline and longitudinal disease severity was evaluated using the Clinical Dementia Rating sum-of-boxes (CDR-SB). We investigated the data's clustering tendency and cluster stability to form robust symptom clusters and employed principal component analysis to extract data-driven latent clinical dimensions (LCD). The longitudinal CDR-SB change was estimated utilizing linear mixed-effects models. Of the participants included in this study, 93 conformed to previously reported clinical profiles (75 with AOS and agrammatism, 12 PPAOS, and 6 PAA). The remaining five participants were characterized by nonfluent speech, executive dysfunction, and dysarthria without apraxia of speech or frank agrammatism. No baseline clinical features differentiated between FTLD neuropathological subgroups. The Hopkins statistic demonstrated a low cluster tendency in the entire sample (.45 with values near 0.5 indicating random data). Cluster stability analyses showed that only two robust subgroups (differing in agrammatism, executive dysfunction and overall disease severity) could be identified. Three data-driven components accounted for 71% of the variance ([i] severity-agrammatism, [ii] prominent AOS, and [iii] prominent dysarthria). None of these data-driven LCD allowed an accurate prediction of neuropathology. The severity-agrammatism component was an independent predictor of a faster CDR-SB increase in all the participants. Higher dysarthria severity, reduced words per minute, and expressive and receptive agrammatism severity at baseline independently predicted accelerated disease progression. Our findings indicate that PPAOS and PAA, rather than exist as completely distinct syndromic entities, constitute a clinical continuum. In our cohort, splitting the nfvPPA spectrum into separate clinical phenotypes did not improve clinical-pathological correlations, stressing the need for new biological markers and consensus regarding updated terminology and clinical classification.

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“…Hierarchical heatmaps have proven useful in identifying clusters of participants and clinical features within heterogeneous diseases. 47 They consist of a colored matrix including individual data and clinical features, with the participants and the clinical features ordered by hierarchical clustering.…”

Section: Assessing Clustering Tendency Of Raw Datamentioning

confidence: 99%

Clinical dimensions along the progressive nonfluent variant primary progressive aphasia spectrum

Illán-Gala

Lorca-Puls

Ezzes

et al. 2023

Preprint

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It is debated whether primary progressive apraxia of speech (PPAOS) and progressive agrammatic aphasia (PAA) belong to the same clinical spectrum traditionally termed nonfluent/agrammatic variant primary progressive aphasia (nfvPPA) or exist as two completely distinct syndromic entities with specific pathologic/prognostic correlates. We analyzed speech, language, and disease severity features in a comprehensive cohort of patients with a progressive motor speech impairment and/or agrammatism to ascertain any evidence of the existence of naturally occurring, non-overlapping syndromic entities (e.g., PPAOS and PAA) in our data. We also assessed if data-driven latent clinical dimensions with etiologic/prognostic value could be identified. We included 98 participants with progressive motor speech impairment and/or agrammatism, with 43 having an autopsy-confirmed neuropathological diagnosis. Speech pathologists assessed motor speech features indicative of dysarthria and apraxia of speech (AOS). Quantitative expressive/receptive agrammatism measures were obtained and compared with healthy controls. Baseline and longitudinal disease severity was evaluated using the Clinical Dementia Rating sum-of-boxes (CDR-SB). We investigated the data's clustering tendency to form robust symptom clusters and employed principal component analysis to extract data-driven latent clinical dimensions (LCD). The longitudinal CDR-SB change was estimated utilizing linear mixed-effects models. Of the participants included in this study, 91 conformed to previously reported clinical profiles (69 with AOS and agrammatism, 18 PPAOS, and 4 PAA). The remaining seven participants were characterized by nonfluent speech and dysarthria without apraxia of speech or agrammatism. No baseline clinical features differentiated between FTLD neuropathological subgroups. Critically, the Hopkins statistic dismissed the presence of non-overlapping syndromic clusters in the entire sample (.45 with values near 0.5 indicating random data). Three data-driven components accounted for 71% of the variance ([i] severity-agrammatism, [ii] prominent AOS, and [iii] prominent dysarthria). The component typified by prominent dysarthria was more specific to patients with Progressive Supranuclear Palsy (4/5 [80%] participants with autopsy in this group had PSP), while the severity-agrammatism component predicted a faster CDR-SB increase. Higher dysarthria severity, reduced words per minute, and expressive and receptive agrammatism severity at baseline independently predicted accelerated disease progression (as measured by the CDR-SB score). Our findings indicate that PPAOS and PAA, rather than exist as completely distinct syndromic entities, constitute a clinical continuum strongly predictive of underlying Frontotemporal Lobar Degeneration (FTLD, 66% 4R tauopathy, 16% Pick's disease, 9.3% FTLD TDP type A, and 12% other pathologies). While highlighting the graded distinctions (rather than sharp boundaries) that characterize the nfvPPA spectrum may be useful for establishing early clinical rehabilitation strategies, novel clinical and biological markers are needed to improve clinical-pathological correlations.

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Two decades of advances in muscle imaging in children: from pattern recognition of muscle diseases to quantification and machine learning approaches

Cited by 3 publications

References 84 publications

Muscle magnetic resonance imaging involvement patterns in nemaline myopathies

Muscle magnetic resonance imaging involvement patterns in nemaline myopathies

Clinical dimensions along the non-fluent variant primary progressive aphasia spectrum

Clinical dimensions along the progressive nonfluent variant primary progressive aphasia spectrum

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