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.
Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive neurodegenerative disease of motor neurons, resulting in worsening weakness of voluntary muscles until death from respiratory failure ...occurs after about 3 years. Although great advances have been made in our understanding of the genetic causes of ALS, the contribution of environmental factors has been more difficult to assess. Large-scale studies of the clinical patterns of ALS, individual histories preceding the onset of ALS, and the rates of ALS in different populations and groups have led to improved patient care, but have not yet revealed a replicable, definitive environmental risk factor. In this Review, we outline what is currently known of the environmental and genetic epidemiology of ALS, describe the current state of the art with respect to the different types of ALS, and explore whether ALS should be considered a single disease or a syndrome. We examine the relationship between genetic and environmental risk factors, and propose a disease model in which ALS is considered to be the result of environmental risks and time acting on a pre-existing genetic load, followed by an automatic, self-perpetuating decline to death.
Summary Amyotrophic lateral sclerosis is a progressive adult-onset neurodegenerative disease that primarily affects upper and lower motor neurons, but also frontotemporal and other regions of the ...brain. The extent to which each neuronal population is affected varies between individuals. The subsequent patterns of disease progression form the basis of diagnostic criteria and phenotypic classification systems, with considerable overlap in the clinical terms used. This overlap can lead to confusion between diagnosis and phenotype. Formal classification systems such as the El Escorial criteria and the International Classification of Diseases are systematic approaches but they omit features that are important in clinical management, such as rate of progression, genetic basis, or functional effect. Therefore, many neurologists use informal classification approaches that might not be systematic, and could include, for example, anatomical descriptions such as flail-arm syndrome. A new strategy is needed to combine the benefits of a systematic approach to classification with the rich and varied phenotypic descriptions used in clinical practice.
Summary Most health-care professionals are trained to promote and maintain life and often have difficulty when faced with the often rapid decline and death of people with terminal illnesses such as ...amyotrophic lateral sclerosis (ALS). By contrast, data suggest that early and open discussion of end-of-life issues with patients and families allows time for reflection and planning, can obviate the introduction of unwanted interventions or procedures, can provide reassurance, and can alleviate fear. Patients' perspectives regarding end-of-life interventions and use of technologies might differ from those of the health professionals involved in their care, and health-care professionals should recognise this and respect the patient's autonomy. Advance care directives can preserve autonomy, but their legal validity and use varies between countries. Clinical management of the end of life should aim to maximise quality of life of both the patient and caregiver and, when possible, incorporate appropriate palliation of distressing physical, psychosocial, and existential distress. Training of health-care professionals should include the development of communication skills that help to sensitively manage the inevitability of death. The emotional burden for health-care professionals caring for people with terminal neurological disease should be recognised, with structures and procedures developed to address compassion, fatigue, and the moral and ethical challenges related to providing end-of-life care.
Despite significant advances in quantitative neuroimaging, the diagnosis of ALS remains clinical and MRI-based biomarkers are not currently used to aid the diagnosis. The objective of this study is ...to develop a robust, disease-specific, multimodal classification protocol and validate its diagnostic accuracy in independent, early-stage and follow-up data sets.
147 participants (81 ALS patients and 66 healthy controls) were divided into a training sample and a validation sample. Patients in the validation sample underwent follow-up imaging longitudinally. After removing age-related variability, indices of grey and white matter integrity in ALS-specific pathognomonic brain regions were included in a cross-validated binary logistic regression model to determine the probability of individual scans indicating ALS. The following anatomical regions were assessed for diagnostic classification: average grey matter density of the left and right precentral gyrus, the average fractional anisotropy and radial diffusivity of the left and right superior corona radiata, inferior corona radiata, internal capsule, mesencephalic crus of the cerebral peduncles, pontine segment of the corticospinal tract, and the average diffusivity values of the genu, corpus and splenium of the corpus callosum.
Using a 50% probability cut-off value of suffering from ALS, the model was able to discriminate ALS patients and HC with good sensitivity (80.0%) and moderate accuracy (70.0%) in the training sample and superior sensitivity (85.7%) and accuracy (78.4%) in the independent validation sample.
This diagnostic classification study endeavours to advance ALS biomarker research towards pragmatic clinical applications by providing an approach of automated individual-data interpretation based on group-level observations.
To estimate the prevalence rates (PRs) of acquired and inherited neuromuscular diseases (NMD) in the adult Irish population, reflecting the burden of these conditions in a single country.
This ...population-based study was performed in the Republic of Ireland (RoI), with a PR estimated for December 2013. Multiple case ascertainment sources were utilized. Demographic and clinical information and relevant diagnostic results were registered.
A total of 2,641 adults were identified, giving a PR of 62.6/100,000 (95% confidence interval CI 59.95-65.24) for all NMD in RoI. Disease-specific PR include chronic inflammatory demyelinating polyradiculoneuropathy 5.87/100,000 (95% CI 5.06-6.68), Charcot-Marie-Tooth 10.52/100,000 (95% CI 9.44-11.61), hereditary neuropathy with liability to pressure palsies 0.84/100,000 (95% CI 0.54-1.15), myotonic dystrophy type I 6.75/100,000 (95% CI 5.88-7.61), Duchenne muscular dystrophy 3.0/100,000 (95% CI 2.33-3.70), Becker muscular dystrophy 2.2/100,000 (95% CI 1.64-2.88), facioscapulohumeral dystrophy 2.59/100,000 (95% CI 2.05-3.13), limb-girdle muscular dystrophy 2.88/100,000 (95% CI 2.31-3.45), periodic paralysis 1.72/100,000 (95% CI 1.28-2.15), myotonia congenita 0.32/100,000 (95% CI 0.18-0.56), paramyotonia congenita 0.15/100,000 (95% CI 0.06-0.34), Kennedy disease 0.83/100,000 (95% CI 0.40-1.27), Lambert-Eaton myasthenic syndrome 0.29/100,000 (95% CI 0.11-0.47), myasthenia gravis 15.12/100,000 (95% CI 13.82-16.42), and sporadic inclusion body myositis 11.7/100,000 (95% CI 9.82-13.58). PR for amyotrophic lateral sclerosis was established from an existing Register as 7.20/100,000 (95% CI 6.34-8.15).
The PR of all adult NMD in RoI is relatively high when compared with other chronic neurologic disorders, although some figures may be an underestimate of the true prevalence. The data provide a framework for international comparison and service planning.
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a rare neurodegenerative, fatal and currently incurable disease. People with ALS need support from informal caregivers due to the motor and cognitive ...decline caused by the disease. This study aims to identify caregivers whose quality of life (QoL) may be impacted as a result of caring for a person with ALS. In this study, we worked towards the identification of the predictors of a caregiver’s QoL in addition to the development of a model for clinical use to alert clinicians when a caregiver is at risk of experiencing low QoL. The data were collected through the Irish ALS Registry and via interviews on several topics with 90 patient and caregiver pairs at three time-points. The McGill QoL questionnaire was used to assess caregiver QoL—the MQoL Single Item Score measures the overall QoL and was selected as the outcome of interest in this work. The caregiver’s existential QoL and burden, as well as the patient’s depression and employment before the onset of symptoms were the features that had the highest impact in predicting caregiver quality of life. A small subset of features that could be easy to collect was used to develop a second model to use it in a clinical setting. The most predictive features for that model were the weekly caregiving duties, age and health of the caregiver, as well as the patient’s physical functioning and age of onset.
Amyotrophic lateral sclerosis (ALS) a highly heterogeneous neurodegenerative condition. Accurate diagnostic, monitoring and prognostic biomarkers are urgently needed both for individualised patient ...care and clinical trials. A multimodal magnetic resonance imaging study is presented, where MRI measures of ALS-associated brain regions are utilised to predict 18-month survival.
A total of 60 ALS patients and 69 healthy controls were included in this study. 20% of the patient sample was utilised as an independent validation sample. Surface-based morphometry and diffusion tensor white matter parameters were used to identify anatomical patterns of neurodegeneration in 80% of the patient sample compared to healthy controls. Binary logistic ridge regressions were carried out to predict 18-month survival based on clinical measures alone, MRI features, and a combination of clinical and MRI data. Clinical indices included age at symptoms onset, site of disease onset, diagnostic delay from first symptom to diagnosis, and physical disability (ALSFRS-r). MRI features included the average cortical thickness of the precentral and paracentral gyri, the average fractional anisotropy, radial-, medial-, and axial diffusivity of the superior and inferior corona radiata, internal capsule, cerebral peduncles and the genu, body and splenium of the corpus callosum.
Clinical data alone had a survival prediction accuracy of 66.67%, with 62.50% sensitivity and 70.84% specificity. MRI data alone resulted in a prediction accuracy of 77.08%, with 79.16% sensitivity and 75% specificity. The combination of clinical and MRI measures led to a survival prediction accuracy of 79.17%, with 75% sensitivity and 83.34% specificity.
Quantitative MRI measures of ALS-specific brain regions enhance survival prediction in ALS and should be incorporated in future clinical trial designs.
Individuals who are diagnosed with amyotrophic lateral sclerosis (ALS) today face the same historically intransigent problem that has existed since the initial description of the disease in the 1860s ...- a lack of effective therapies. In part, the development of new treatments has been hampered by an imperfect understanding of the biological processes that trigger ALS and promote disease progression. Advances in our understanding of these biological processes, including the causative genetic mutations, and of the influence of environmental factors have deepened our appreciation of disease pathophysiology. The consequent identification of pathogenic targets means that the introduction of effective therapies is becoming a realistic prospect. Progress in precision medicine, including genetically targeted therapies, will undoubtedly change the natural history of ALS. The evolution of clinical trial designs combined with improved methods for patient stratification will facilitate the translation of novel therapies into the clinic. In addition, the refinement of emerging biomarkers of therapeutic benefits is critical to the streamlining of care for individuals. In this Review, we synthesize these developments in ALS and discuss the further developments and refinements needed to accelerate the introduction of effective therapeutic approaches.
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