Brain volumetric correlates of dysarthria in multiple sclerosis

Adaptation and validation of the Greek version of the Communication and Language Assessment questionnaire for persons with Multiple Sclerosis (CLAMS)

OBJECTIVE

The aim of the present study was to validate the Communication and Language Assessment questionnaire for persons with Multiple Sclerosis (CLAMS) into the Greek language.

METHOD

106 Persons with Multiple Sclerosis (PwMS) and 51 healthy controls (HCs) participated in this study. We evaluated patients' cognitive abilities with the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). All PwMS completed the CLAMS and three additional questionnaires (Speech Pathology-Specific Questionnaire for persons with Multiple Sclerosis, SMS; Stroke and Aphasia Quality of Life Scale-39, SAQOL-39; the Beck Depression Inventory Fast Screen, BDI-FS), and all HCs filled in the CLAMS.

RESULTS

The internal consistency of the CLAMS was excellent (a = 0.933) for the PwMS and a significant difference was found between PwMS and HCs for the total CLAMS score. Statistical analyses showed a significant positive correlation between the CLAMS and the other questionnaires (SMS, BDI, and SAQOL-39) and a statistically significant negative correlation between the CLAMS and the three subtests of the BICAMS (Symbol Digit Modalities Test, Greek Verbal Learning Test-II, and Brief Visuospatial Memory Test-Revised). There was no correlation between the CLAMS and participants' age, disease duration, and disease type.

CONCLUSION

The Greek version of the CLAMS is a valid self-reported questionnaire for the evaluation of language and communication symptoms in PwMS.

Functional and structural abnormalities of the speech disorders: a multimodal activation likelihood estimation meta-analysis

Speech disorders are associated with different degrees of functional and structural abnormalities. However, the abnormalities associated with specific disorders, and the common abnormalities shown by all disorders, remain unclear. Herein, a meta-analysis was conducted to integrate the results of 70 studies that compared 1843 speech disorder patients (dysarthria, dysphonia, stuttering, and aphasia) to 1950 healthy controls in terms of brain activity, functional connectivity, gray matter, and white matter fractional anisotropy. The analysis revealed that compared to controls, the dysarthria group showed higher activity in the left superior temporal gyrus and lower activity in the left postcentral gyrus. The dysphonia group had higher activity in the right precentral and postcentral gyrus. The stuttering group had higher activity in the right inferior frontal gyrus and lower activity in the left inferior frontal gyrus. The aphasia group showed lower activity in the bilateral anterior cingulate gyrus and left superior frontal gyrus. Across the four disorders, there were concurrent lower activity, gray matter, and fractional anisotropy in motor and auditory cortices, and stronger connectivity between the default mode network and frontoparietal network. These findings enhance our understanding of the neural basis of speech disorders, potentially aiding clinical diagnosis and intervention.

Speech deficits in multiple sclerosis: a narrative review of the existing literature

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating autoimmune disease. MS patients deal with motor and sensory impairments, visual disabilities, cognitive disorders, and speech and language deficits. The study aimed to record, enhance, update, and delve into our present comprehension of speech deficits observed in patients with MS and the methodology (assessment tools) studies followed. The method used was a search of the literature through the databases for May 2015 until June 2022. The reviewed studies offer insight into speech impairments most exhibited by MS patients. Patients with MS face numerous communication changes concerning the phonation system (changes observed concerning speech rate, long pause duration) and lower volume. Moreover, the articulation system was affected by the lack of muscle synchronization and inaccurate pronunciations, mainly of vowels. Finally, there are changes regarding prosody (MS patients exhibited monotonous speech). Findings indicated that MS patients experience communication changes across various domains. Based on the reviewed studies, we concluded that the speech system of MS patients is impaired to some extent, and the patients face many changes that impact their conversational ability and the production of slower and inaccurate speech. These changes can affect MS patients' quality of life.

Articulatory speech measures can be related to the severity of multiple sclerosis

Background

Dysarthria is one of the most frequent communication disorders in patients with Multiple Sclerosis (MS), with an estimated prevalence of around 50%. However, it is unclear if there is a relationship between dysarthria and the severity or duration of the disease.

Objective

Describe the speech pattern in MS, correlate with clinical data, and compare with controls.

Methods

A group of MS patients (n = 73) matched to healthy controls (n = 37) by sex and age. Individuals with neurological and/or systemic conditions that could interfere with speech were excluded. MS group clinical data were obtained through the analysis of medical records. The speech assessment consisted of auditory-perceptual and speech acoustic analysis, from recording the following speech tasks: phonation and breathing (sustained vowel/a/); prosody (sentences with different intonation patterns) and articulation (diadochokinesis; spontaneous speech; diphthong/iu/repeatedly).

Results

In MS, 72.6% of the individuals presented mild dysarthria, with alterations in speech subsystems: phonation, breathing, resonance, and articulation. In the acoustic analysis, individuals with MS were significantly worse than the control group (CG) in the variables: standard deviation of the fundamental frequency (p = 0.001) and maximum phonation time (p = 0.041). In diadochokinesis, individuals with MS had a lower number of syllables, duration, and phonation time, but larger pauses per seconds, and in spontaneous speech, a high number of pauses were evidenced as compared to CG. Correlations were found between phonation time in spontaneous speech and the Expanded Disability Status Scale (EDSS) (r = - 0.238, p = 0.043) and phonation ratio in spontaneous speech and EDSS (r = -0.265, p = 0.023), which indicates a correlation between the number of pauses during spontaneous speech and the severity of the disease.

Conclusion

The speech profile in MS patients was mild dysarthria, with a decline in the phonatory, respiratory, resonant, and articulatory subsystems of speech, respectively, in order of prevalence. The increased number of pauses during speech and lower rates of phonation ratio can reflect the severity of MS.

Speech and gait abnormalities in motor subtypes of de-novo Parkinson's disease

AIM

To investigate the presence and relationship of temporal speech and gait parameters in patients with postural instability/gait disorder (PIGD) and tremor-dominant (TD) motor subtypes of Parkinson's disease (PD).

METHODS

Speech samples and instrumented walkway system assessments were acquired from a total of 60 de-novo PD patients (40 in TD and 20 in PIGD subtype) and 40 matched healthy controls. Objective acoustic vocal assessment of seven distinct speech timing dimensions was related to instrumental gait measures including velocity, cadence, and stride length.

RESULTS

Compared to controls, PIGD subtype showed greater consonant timing abnormalities by prolonged voice onset time (VOT) while also shorter stride length during both normal walking and dual task, while decreased velocity and cadence only during dual task. Speaking rate was faster in PIGD than TD subtype. In PIGD subtype, prolonged VOT correlated with slower gait velocity (r = -0.56, p = 0.01) and shorter stride length (r = -0.59, p = 0.008) during normal walking, whereas relationships were also found between decreased cadence in dual task and irregular alternating motion rates (r = -0.48, p = 0.04) and prolonged pauses (r = -0.50, p = 0.03). No correlation between speech and gait was detected in TD subtype.

CONCLUSION

Our findings suggest that speech and gait rhythm disorder share similar underlying pathomechanisms specific for PIGD subtype.

Speech biomarkers in Huntington's disease: A cross-sectional study in pre-symptomatic, prodromal and early manifest stages

BACKGROUND AND PURPOSE

Motor speech alterations are a prominent feature of clinically manifest Huntington's disease (HD). Objective acoustic analysis of speech can quantify speech alterations. It is currently unknown, however, at what stage of HD speech alterations can be reliably detected. We aimed to explore the patterns and extent of speech alterations using objective acoustic analysis in HD and to assess correlations with both rater-assessed phenotypical features and biological determinants of HD.

METHODS

Speech samples were acquired from 44 premanifest (29 pre-symptomatic and 15 prodromal) and 25 manifest HD gene expansion carriers, and 25 matched healthy controls. A quantitative automated acoustic analysis of 10 speech dimensions was performed.

RESULTS

Automated speech analysis allowed us to differentiate between participants with HD and controls, with areas under the curve of 0.74 for pre-symptomatic, 0.92 for prodromal, and 0.97 for manifest stages. In addition to irregular alternating motion rates and prolonged pauses seen only in manifest HD, both prodromal and manifest HD displayed slowed articulation rate, slowed alternating motion rates, increased loudness variability, and unstable steady-state position of articulators. In participants with premanifest HD, speech alteration severity was associated with cognitive slowing (r = -0.52, p < 0.001) and the extent of bradykinesia (r = 0.43, p = 0.004). Speech alterations correlated with a measure of exposure to mutant gene products (CAG-age-product score; r = 0.60, p < 0.001).

CONCLUSION

Speech abnormalities in HD are associated with other motor and cognitive deficits and are measurable already in premanifest stages of HD. Therefore, automated speech analysis might represent a quantitative HD biomarker with potential for assessing disease progression.

Speech acoustic indices for differential diagnosis between Parkinson's disease, multiple system atrophy and progressive supranuclear palsy

While speech disorder represents an early and prominent clinical feature of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), little is known about the sensitivity of speech assessment as a potential diagnostic tool. Speech samples were acquired from 215 subjects, including 25 MSA, 20 PSP, 20 Parkinson's disease participants, and 150 healthy controls. The accurate differential diagnosis of dysarthria subtypes was based on the quantitative acoustic analysis of 26 speech dimensions related to phonation, articulation, prosody, and timing. A semi-supervised weighting-based approach was then applied to find the best feature combinations for separation between PSP and MSA. Dysarthria was perceptible in all PSP and MSA patients and consisted of a combination of hypokinetic, spastic, and ataxic components. Speech features related to respiratory dysfunction, imprecise consonants, monopitch, slow speaking rate, and subharmonics contributed to worse performance in PSP than MSA, whereas phonatory instability, timing abnormalities, and articulatory decay were more distinctive for MSA compared to PSP. The combination of distinct speech patterns via objective acoustic evaluation was able to discriminate between PSP and MSA with very high accuracy of up to 89% as well as between PSP/MSA and PD with up to 87%. Dysarthria severity in MSA/PSP was related to overall disease severity. Speech disorders reflect the differing underlying pathophysiology of tauopathy in PSP and α-synucleinopathy in MSA. Vocal assessment may provide a low-cost alternative screening method to existing subjective clinical assessment and imaging diagnostic approaches.

Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS.

Assessing clinical utility of machine learning and artificial intelligence approaches to analyze speech recordings in multiple sclerosis: A pilot study

BACKGROUND

An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria.

METHOD

The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve.

RESULTS

The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant.

CONCLUSION

Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations.

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

Assessment of non-progressive dysarthria: practice and attitude of speech and language therapists in Lebanon

BACKGROUND

Non-progressive dysarthria is an acquired motor speech disorder resulting from neurological diseases such as stroke and traumatic brain injury. The evidence base for the assessment of non-progressive dysarthria remains limited with professional practices relying mainly on therapists' clinical experience. Limited information on the assessment practices of Lebanese speech and language therapists (SLTs) is available. Such information is crucial for the development of adequate therapy services for clients with non-progressive dysarthria. This study aims to explore the assessment practices and attitudes of Lebanese SLTs working with adults with non-progressive dysarthria and to investigate their adherence to the framework of the World Health Organization's International Classification of Functioning, Disability and Health (ICF).

METHODS

A cross-sectional study was conducted in Lebanon between March and May 2021. Data was collected through an online survey that included information on socio-demographic characteristics, practices, and attitudes of SLTs who assess adults with non-progressive dysarthria.

RESULTS

A total of 50 Lebanese SLTs responded to the survey. The majority of SLTs (78%) assessed clients with non-progressive dysarthria across all ICF domains. SLTs reported dissatisfaction with the available assessment tools (64%) and reliance on informal tools (84%). In addition, 68% of the SLTs suggested the crucial need for the development of Arabic formal assessments that can quantitatively evaluate dysarthria and determine severity. The survey also showed that the respondents demonstrated a preference for the use of impairment-based tools.

CONCLUSION

It can be concluded that the assessment practices of Lebanese SLTs, generally, follow the international trend and the recommended professional guidelines. Further research initiatives should be held to develop Arabic formal assessment tools for non-progressive dysarthria.

Outcome measures assisting treatment optimization in multiple sclerosis

Objective

To review instruments used to assess disease stability or progression in persons with multiple sclerosis (pwMS) that can guide clinicians in optimizing therapy.

Methods

A non-systematic review of scientific literature was undertaken to explore modalities of monitoring symptoms and the disease evolution of MS.

Results

Multiple outcome measures, or tools, have been developed for use in MS research as well as for the clinical management of pwMS. Beginning with the Expanded Disability Status Scale, introduced in 1983, clinicians and researchers have developed monitoring modalities to assess all aspects of MS and the neurological impairment it causes.

Conclusions

Much progress has been made in recent decades for the management of MS and for the evaluation of disease progression. New technology, such as wearable sensors, will provide new opportunities to better understand changes in function, dexterity, and cognition. Essential work over the decades since EDSS was introduced continues to improve our ability to treat this debilitating disease.

Update on Recent Developments in Communication and Swallowing in Multiple Sclerosis

Swallowing and communication disorders are common in persons with multiple sclerosis (MS). Both disorders are extremely variable and can have a major effect on health status and quality of life. This is why it is important to provide health care professionals who are working with persons with MS with tools to signal, assess, and treat swallowing and communication disorders. This synthesis gives an update on relevant and recent literature on swallowing and communication disorders, supplemented with current practice-based evidence. Studies on swallowing and communication disorders in MS are scarce: more and higher-quality research is needed. It should be emphasized that therapists need to focus on the patient's acquisition of skills to participate in daily life. This means that each patient requires an individual approach based on their own needs.

Speech metrics, general disability, brain imaging and quality of life in multiple sclerosis

BACKGROUND AND PURPOSE

Objective measurement of speech has shown promising results to monitor disease state in multiple sclerosis. In this study, we characterize the relationship between disease severity and speech metrics through perceptual (listener based) and objective acoustic analysis. We further look at deviations of acoustic metrics in people with no perceivable dysarthria.

METHODS

Correlations and regression were calculated between speech measurements and disability scores, brain volume, lesion load and quality of life. Speech measurements were further compared between three subgroups of increasing overall neurological disability: mild (as rated by the Expanded Disability Status Scale ≤2.5), moderate (≥3 and ≤5.5) and severe (≥6).

RESULTS

Clinical speech impairment occurred majorly in people with severe disability. An experimental acoustic composite score differentiated mild from moderate (P < 0.001) and moderate from severe subgroups (P = 0.003), and correlated with overall neurological disability (r = 0.6, P < 0.001), quality of life (r = 0.5, P < 0.001), white matter volume (r = 0.3, P = 0.007) and lesion load (r = 0.3, P = 0.008). Acoustic metrics also correlated with disability scores in people with no perceivable dysarthria.

CONCLUSIONS

Acoustic analysis offers a valuable insight into the development of speech impairment in multiple sclerosis. These results highlight the potential of automated analysis of speech to assist in monitoring disease progression and treatment response.