Surto-remissão: caracterização deste tipo específico de esclerose múltipla

A Esclerose Múltipla é uma doença desmielinizante do Sistema Nervoso Central que assume particular importância por afectar e incapacitar indivíduos jovens. Afecta em maior proporção mulheres e apresenta uma predisposição genética. A clínica apresentada é reflexo de lesões desmielinizantes encontradas na substância branca do SNC, em vários locais, daí esta ser uma patologia que apresente inúmeras formas clínicas. A forma clínica mais comum é a surto-remissão. Etiologicamente aponta-se para um fundo auto-imune e/ou infeccioso. O diagnóstico assenta nos critérios de McDonald, suportado por exames de imagem (RMN), análise do líquido cefalorraquidiano, potenciais evocados e clínica. O tratamento actualmente passa pelo uso de imunomoduladores e imunosupressores. A incapacidade clínica classifica-se através do EDSS, que varia de 0 (normalidade) até o grau máximo de 10 (morte por Esclerose Múltipla). Quanto ao prognóstico, este é mais favorável para o sexo feminino, doença com início em idade mais jovem e doença que se inicie com sintomas sensitivos e disfunções dos nervos cranianos. Neste trabalho efectuou-se um estudo retrospectivo documental numa amostra de 40 doentes com Esclerose Múltipla do tipo surto-remissão e com diagnóstico há pelo menos três anos, seguidos na Consulta de Doenças Desmielinizantes do Serviço de Neurologia do Centro Hospitalar Cova da Beira, com o objectivo de efectuar o seu estudo descritivo. Verificou-se nesta amostra que havia um predomínio de indivíduos do sexo feminino (80%); que a média da idade no diagnóstico era, no geral, 32 anos, apresentando os homens uma idade média inferior à das mulheres na amostra estudada; as formas de apresentação clínica mais comummente encontradas neste estudo foram as alterações sensitivas, seguidas de neurite óptica e alterações do tronco cerebral e cerebelo; esta amostra encontra-se actualmente com um grau de disfunção ligeira ao apresentar um EDSS médio de 1,78 e a medicação que foi prescrita no momento do diagnóstico com maior frequência nestes casos foi o interferão β (1A e 1B). Concluiu-se com este trabalho que na Esclerose Múltipla há relação entre o número de anos de evolução da doença e o estado funcional do doente; foi no entanto excluída qualquer relação entre o estado funcional dos pacientes e a sua forma de apresentação clínica no momento do diagnóstico, o seu sexo e a idade com que a doença é diagnosticada.Multiple Sclerosis is a demyelinating disease of the Central Nervous System that assumes a particular role by affecting and disabling young people. It affects females in a larger proportion and presents a genetic predisposition. The clinical symptoms reflects the demyelinating lesions that are found in several locations of the white matter, of the Central Nervous System, therefore, it is a disease that can present itself in a variety of clinical forms. The commonest clinical form is relapsing-remitting Multiple Sclerosis. Auto-immune diseases and/or infections are possible etiological agents. The bases of the diagnosis are the McDonald criteria, supported by medical imaging test (Magnetic Resonance), liquor analysis, evoked potentials and clinical symptoms. Nowadays, imunomodulators and imunosupressors are the main treatment strategy. Disability can be classified through EDSS, that varies from 0 (normal exam) to 10 (death by Multiple Sclerosis). The prognosis is more favorable when the disease affects females and patients of a younger age, when there are initial sensitive symptoms and when the cranial nerves are affected at the diagnosis time. This research involved a retrospective study with a sample of 40 Relapsing-Remitting type of Multiple Sclerosis patients, with at least 3 years of diagnosis followed in the demyelinating diseases consultations in the Neurology Service of the Centro Hospitalar Cova da Beira. The aim of this study was to build a descriptive analysis. In this sample we found a predominance of females (80%); in general, the mean age of diagnosis was 32 years of age, being the men’s mean age of diagnosis inferior to the females; the most common presenting clinical forms found in this study were sensitive dysfunctions, followed by optical neuritis and brainstem and cerebelar dysfunctions. Having a medial EDSS of 1,78, this sample had a slight grade of dysfunction. When diagnosed, the most prescribed therapy was β Interferon (1A e 1B). In conclusion, Multiple Sclerosis is a disease with a relationship between the number of years of the evolution of the disease and the patient’s functional state. There was no relationship verified between the patient’s functional state with his clinical presentation at the time of diagnosis, or with their sex, or with their age of diagnosis

Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine.

The ever-increasing amount of biomedical data is enabling new large-scale studies, even though ad hoc computational solutions are required. The most recent Machine Learning (ML) and Artificial Intelligence (AI) techniques have been achieving outstanding performance and an important impact in clinical research, aiming at precision medicine, as well as improving healthcare workflows. However, the inherent heterogeneity and uncertainty in the healthcare information sources pose new compelling challenges for clinicians in their decision-making tasks. Only the proper combination of AI and human intelligence capabilities, by explicitly taking into account effective and safe interaction paradigms, can permit the delivery of care that outperforms what either can do separately. Therefore, Human-Computer Interaction (HCI) plays a crucial role in the design of software oriented to decision-making in medicine. In this work, we systematically review and discuss several research fields strictly linked to HCI and clinical decision-making, by subdividing the articles into six themes, namely: Interfaces, Visualization, Electronic Health Records, Devices, Usability, and Clinical Decision Support Systems. However, these articles typically present overlaps among the themes, revealing that HCI inter-connects multiple topics. With the goal of focusing on HCI and design aspects, the articles under consideration were grouped into four clusters. The advances in AI can effectively support the physicians' cognitive processes, which certainly play a central role in decision-making tasks because the human mental behavior cannot be completely emulated and captured; the human mind might solve a complex problem even without a statistically significant amount of data by relying upon domain knowledge. For this reason, technology must focus on interactive solutions for supporting the physicians effectively in their daily activities, by exploiting their unique knowledge and evidence-based reasoning, as well as improving the various aspects highlighted in this review

Eye as a window to the brain: investigating the clinical utility of retinal imaging derived biomarkers in the phenotyping of neurodegenerative disease.

Background Neurodegenerative diseases, like multiple sclerosis, dementia and motor neurone disease, represent one of the major public health threats of our time. There is a clear persistent need for novel, affordable, and patient‐acceptable biomarkers of these diseases, to assist with diagnosis, prognosis and impact of interventions. And these biomarkers need to be sensitive, specific and precise. The retina is an attractive site for exploring this potential, as it is easily accessible to non‐invasive imaging. Remarkable technology revolutions in retinal imaging are enabling us to see the retina in microscopic level detail, and measure neuronal and vascular integrity. Aims and objectives I therefore propose that retinal imaging could provide reliable and accurate markers of these neurological diseases. In this project, I aimed to explore the clinical utility of retinal imaging derived measures of retinal neuronal and vessel size and morphology, and determine their candidacy for being reliable biomarkers in these diseases. I also aimed to detail the methods of retinal imaging acquisition, and processing, and the principles underlying all these stages, in relation to understanding of retinal structure and function. This provides an essential foundation to the application of retinal imaging analysis, highlighting both the strengths and potential weaknesses of retinal biomarkers and how they are interpreted. Methods After performing detailed systematic reviews and meta‐analyses of the existing work on retinal biomarkers of neurodegenerative disease, I carried out a prospective, controlled, cross‐sectional study of retinal image analysis, in patients with MS, dementia, and ALS. This involved developing new software for vessel analysis, to add value and maximise the data available from patient imaging episodes. Results From the systematic reviews, I identified key unanswered questions relating to the detailed analysis and utility of neuroretinal markers, and diseases with no studies yet performed of retinal biomarkers, such as non‐AD dementias. I recruited and imaged 961 participants over a two‐year period, and found clear patterns of significance in the phenotyping of MS, dementia and ALS. Detailed analysis has provided new insights into how the retina may yield important disease information for the individual patient, and also generate new hypotheses with relation to the disease pathophysiology itself. Conclusions Overall, the results show that retinal imaging derived biomarkers have an important and specific role in the phenotyping of neurodegenerative diseases, and support the hypothesis that the eye is an important window to neurological brain disease

Brain imaging biomarkers in Multiple Sclerosis

Background: Iron rim lesions (IRLs), white matter lesions (WMLs) accumulation and linear brain atrophy measurements have been suggested to be important imaging biomarkers in multiple sclerosis (MS). The extent to which these markers are related to MS diagnosis and predict disease prognosis remains unclear. Furthermore, research Magnetic Resonance Imaging (MRI) findings need validation in clinical settings before they can be incorporated into clinical practice. Methods: I conducted two reviews one was a mapping review on IRLs and the other was a meta-analysis on WMLs in MS. I then tested the diagnostic and prognostic usefulness of the IRL in two studies: (1) a large, cross-sectional, multi-centre study of patients with MS and mimicking disorders using 3T MRI, (2) a retrospective single-centre study of patients with first presentation of a clinically isolated syndrome (CIS) or at the early stage of the disease using 7T MRI. I also explored the utility of routine, non-standardised MRI scans measuring WMLs number, volume and linear measures of atrophy at the early stage of the disease and examined their role in predicting long-term disability. Results: The IRLs achieved high specificity (up to 99%) in diagnosing MS compared to MS-mimics but low sensitivity of 24%. All patients with IRLs showing a central vein sign (CVS) had MS or CIS, giving a diagnostic specificity of 100% but equally low sensitivity of 21%. Moreover, the presence of IRLs was also a predictor of long-term disability, especially in patients with ≥4 IRLs. IRLs had a greater impact on disability compared to the WMLs number and volume. Linear brain atrophy of Inter-Caudate Distance (ICD) and Third Ventricle Width (TVW) had a significant impact in predicting disability after 10 years. Conclusions: The perilesional IRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS. Also, the presence and number of IRLs hold prognostic value for long-term physical disability in MS. Simple and reliable assessment of brain atrophy remains challenging in clinical practice

Translation of quantitative MRI analysis tools for clinical neuroradiology application

Quantification of imaging features can assist radiologists by reducing subjectivity, aiding detection of subtle pathology, and increasing reporting consistency. Translation of quantitative image analysis techniques to clinical use is currently uncommon and challenging. This thesis explores translation of quantitative imaging support tools for clinical neuroradiology use. I have proposed a translational framework for development of quantitative imaging tools, using dementia as an exemplar application. This framework emphasises the importance of clinical validation, which is not currently prioritised. Aspects of the framework were then applied to four disease areas: hippocampal sclerosis (HS) as a cause of epilepsy; dementia; multiple sclerosis (MS) and gliomas. A clinical validation study for an HS quantitative report showed that when image interpreters used the report, they were more accurate and confident in their assessments, particularly for challenging bilateral cases. A similar clinical validation study for a dementia reporting tool found improved sensitivity for all image interpreters and increased assessment accuracy for consultant radiologists. These studies indicated benefits from quantitative reports that contextualise a patient’s results with appropriate normative reference data. For MS, I addressed a technical translational challenge by applying lesion and brain quantification tools to standard clinical image acquisitions which do not include a conventional T1-weighted sequence. Results were consistent with those from conventional sequence inputs and therefore I pursued this concept to establish a clinically applicable normative reference dataset for development of a quantitative reporting tool for clinical use. I focused on current radiology reporting of gliomas to establish which features are commonly missed and may be important for clinical management decisions. This informs both the potential utility of a quantitative report for gliomas and its design and content. I have identified numerous translational challenges for quantitative reporting and explored aspects of how to address these for several applications across clinical neuroradiology

Brain imaging biomarkers in Multiple Sclerosis

Background: Iron rim lesions (IRLs), white matter lesions (WMLs) accumulation and linear brain atrophy measurements have been suggested to be important imaging biomarkers in multiple sclerosis (MS). The extent to which these markers are related to MS diagnosis and predict disease prognosis remains unclear. Furthermore, research Magnetic Resonance Imaging (MRI) findings need validation in clinical settings before they can be incorporated into clinical practice. Methods: I conducted two reviews one was a mapping review on IRLs and the other was a meta-analysis on WMLs in MS. I then tested the diagnostic and prognostic usefulness of the IRL in two studies: (1) a large, cross-sectional, multi-centre study of patients with MS and mimicking disorders using 3T MRI, (2) a retrospective single-centre study of patients with first presentation of a clinically isolated syndrome (CIS) or at the early stage of the disease using 7T MRI. I also explored the utility of routine, non-standardised MRI scans measuring WMLs number, volume and linear measures of atrophy at the early stage of the disease and examined their role in predicting long-term disability. Results: The IRLs achieved high specificity (up to 99%) in diagnosing MS compared to MS-mimics but low sensitivity of 24%. All patients with IRLs showing a central vein sign (CVS) had MS or CIS, giving a diagnostic specificity of 100% but equally low sensitivity of 21%. Moreover, the presence of IRLs was also a predictor of long-term disability, especially in patients with ≥4 IRLs. IRLs had a greater impact on disability compared to the WMLs number and volume. Linear brain atrophy of Inter-Caudate Distance (ICD) and Third Ventricle Width (TVW) had a significant impact in predicting disability after 10 years. Conclusions: The perilesional IRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS. Also, the presence and number of IRLs hold prognostic value for long-term physical disability in MS. Simple and reliable assessment of brain atrophy remains challenging in clinical practice

On Improving Generalization of CNN-Based Image Classification with Delineation Maps Using the CORF Push-Pull Inhibition Operator

Deployed image classification pipelines are typically dependent on the images captured in real-world environments. This means that images might be affected by different sources of perturbations (e.g. sensor noise in low-light environments). The main challenge arises by the fact that image quality directly impacts the reliability and consistency of classification tasks. This challenge has, hence, attracted wide interest within the computer vision communities. We propose a transformation step that attempts to enhance the generalization ability of CNN models in the presence of unseen noise in the test set. Concretely, the delineation maps of given images are determined using the CORF push-pull inhibition operator. Such an operation transforms an input image into a space that is more robust to noise before being processed by a CNN. We evaluated our approach on the Fashion MNIST data set with an AlexNet model. It turned out that the proposed CORF-augmented pipeline achieved comparable results on noise-free images to those of a conventional AlexNet classification model without CORF delineation maps, but it consistently achieved significantly superior performance on test images perturbed with different levels of Gaussian and uniform noise

THE EFFECTS OF PILATES BASED CORE STABILITY TRAINING IN PEOPLE WITH MS

Background: People with Multiple Sclerosis experience difficulties with balance and mobility. Pilates exercises are often used to address these difficulties. Design: This was a multi-centre, double blind, block randomised, controlled trial. Eligible participants were recruited from seven UK centres. Participants were randomly allocated to either: Pilates based core stability training (Pilates), Standardised Exercise (SE) or Relaxation (placebo). All received face-to-face training sessions over a 12 week period; together with a home exercise programme. Blinded assessments were taken before training, at the end of the 12 week programme and at 16 weeks (follow-up). The primary outcome measure was the 10metre timed walk (10mtw). Secondary outcome measures were the MS walking Scale (MSWS-12), Functional Reach Test (FRT ) (forwards and lateral), a 10 point Visual Analogue Scale (VAS) to determine “Difficulty in carrying a drink when walking”, and the Activities-specific Balance Confidence (ABC) Scale. Effects on deep abdominal muscles were measured with ultrasound imaging (USI) in a subgroup of patients. Independent t-tests were performed to compare groups. Sensitivity analyses were undertaken to confirm the results. A mixed factorial ANOVA analysed the effect of intervention over time upon TrAb and IO upon USI. Results: Of the 100 participants recruited, 13 relapsed leaving 94 for intention to treat analysis. At 12 weeks there were significant differences between: (1) Pilates and Relaxation for walking velocity (p=0.04), forward (p=0.04) and lateral (p=0.04) FRT. (2) SE and Relaxation for all measures (p<0.05) apart from the VAS. These remained at 16 weeks for 10mtw (p=0.04), LFR (p<0.01) MSWS-12 (p=0.03) and ABC (p= 0.03). There were no significant interactions (p>0.05) between groups or over time for TrAb and IO. Conclusions: Participants improved with both Pilates and SE in the short term; with broader and longer-lasting effects in the SE group. USI did not detect any effect of group over time.MS Trust, Plymouth Universit