Classification of Radiologically Isolated Syndrome and Clinically Isolated Syndrome with Machine-Learning Techniques

Background and purpose: The unanticipated detection by magnetic resonance imaging (MRI) in the brain of asymptomatic subjects of white matter lesions suggestive of multiple sclerosis (MS) has been named radiologically isolated syndrome (RIS). As the difference between early MS [i.e. clinically isolated syndrome (CIS)] and RIS is the occurrence of a clinical event, it is logical to improve detection of the subclinical form without interfering with MRI as there are radiological diagnostic criteria for that. Our objective was to use machine-learning classification methods to identify morphometric measures that help to discriminate patients with RIS from those with CIS. Methods: We used a multimodal 3-T MRI approach by combining MRI biomarkers (cortical thickness, cortical and subcortical grey matter volume, and white matter integrity) of a cohort of 17 patients with RIS and 17 patients with CIS for single-subject level classification. Results: The best proposed models to predict the diagnosis of CIS and RIS were based on the Naive Bayes, Bagging and Multilayer Perceptron classifiers using only three features: the left rostral middle frontal gyrus volume and the fractional anisotropy values in the right amygdala and right lingual gyrus. The Naive Bayes obtained the highest accuracy [overall classification, 0.765; area under the receiver operating characteristic (AUROC), 0.782]. Conclusions: A machine-learning approach applied to multimodal MRI data may differentiate between the earliest clinical expressions of MS (CIS and RIS) with an accuracy of 78%. Keywords: Bagging; Multilayer Perceptron; Naive Bayes classifier; clinically isolated syndrome; diffusion tensor imaging; machine-learning; magnetic resonance imaging; multiple sclerosis; radiologically isolated syndrome.Comment: 24 pages, 2 table

Impact of a specific consultation for patients with progressive forms of multiple sclerosis on the response to their unmet care needs: a cross-sectional study.

20.500.12530/87852As their disease evolves, most patients with progressive forms of multiple sclerosis (MS) develop particular healthcare needs that are not always addressed with usual follow-up. To adapt neurological care to these patients, we created a specific consultation for patients with progressive MS in our centre in 2019. To explore the main unmet care needs of patients with progressive MS in our setting, and to establish the usefulness of the specific consultation to address them. Literature review and interviews with patients and healthcare professionals were conducted to identify the main unmet needs in routine follow-up. Two questionnaires were developed, assessing the importance of the unmet needs identified and the usefulness of the consultation to meet them, for patients under follow-up in the specific consultation and their informal caregivers. Forty-one patients and nineteen informal caregivers participated. The most important unmet needs were the information about the disease, access to social services and coordination between specialists. A positive correlation was found between the importance of these unmet needs and the responsiveness to each of them in the specific consultation. The creation of a specific consultation may improve attention to the healthcare needs of patients with progressive MS

Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study

Background: Radiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. Objective: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). Methods: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. Results: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients’ cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus ( pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. Conclusion: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an “incidental finding” but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.National Institutes of Health (EEUU)European CommissionMinisterio de Economía y Competitividad (España)Ministerio de Ciencia e Innovación (España)Depto. de Psicobiología y Metodología en Ciencias del ComportamientoDepto. de Psicología Experimental, Procesos Cognitivos y LogopediaDepto. de MedicinaFac. de PsicologíaFac. de MedicinaTRUEpu

Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study

Radiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. Objective: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). Methods: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. Results: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients’ cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus (pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. Conclusion: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an “incidental finding” but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de PsicologíaTRUEpu

sj-docx-1-msj-10.1177_13524585231195851 – Supplemental material for Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study

Supplemental material, sj-docx-1-msj-10.1177_13524585231195851 for Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study by Julián Benito-León, Ana Belén del Pino, Yolanda Aladro, Constanza Cuevas, ángela Domingo-Santos, Victoria Galán Sánchez-Seco, Andrés Labiano-Fontcuberta, Ana Gómez-López, Paula Salgado-Cámara, Lucienne Costa-Frossard, Enrique Monreal, Susana Sainz de la Maza, Jordi A Matías-Guiu, Jorge Matías-Guiu, Alfonso Delgado-álvarez, Paloma Montero-Escribano, María Luisa Martínez-Ginés, Yolanda Higueras, Lucía Ayuso-Peralta, Norberto Malpica and Helena Melero in Multiple Sclerosis Journal</p