Caracterización de la morfología foveal: parametrización, diferencias de sexo y efectos de la edad

Frente a los análisis convencionales de grosores de la retina, el análisis morfológico de la fóvea presenta una metodología alternativa de gran potencial pero poco explorada. En este estudio se implementa un pipeline completo de análisis morfológico basado en imágenes OCT (Optical Coherence Tomography), comparando los modelos matemáticos existentes para estudiar la fóvea y demostrando su capacidad de ajuste y mejora de la fiabilidad test-retest. Asimismo, se analiza la influencia de la edad y el sexo en parámetros morfológicos como la altura, anchura, pendiente o área de la fóvea en una cohorte de 272 sujetos sanos. Los resultados muestran un claro dimorfismo sexual en la fóvea junto con relevantes cambios experimentados durante el envejecimiento

Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps

Disentangling the cellular anatomy that gives rise to human visual perception is one of the main challenges of ophthalmology. Of particular interest is the foveal pit, a concave depression located at the center of the retina that captures light from the gaze center. In recent years, there has been a growing interest in studying the morphology of the foveal pit by extracting geometrical features from optical coherence tomography (OCT) images. Despite this, research has devoted little attention to comparing existing approaches for two key methodological steps: the location of the foveal center and the mathematical modelling of the foveal pit. Building upon a dataset of 185 healthy subjects imaged twice, in the present paper the image alignment accuracy of four different foveal center location methods is studied in the first place. Secondly, state-of-the-art foveal pit mathematical models are compared in terms of fitting error, repeatability, and bias. The results indicate the importance of using a robust foveal center location method to align images. Moreover, we show that foveal pit models can improve the agreement between different acquisition protocols. Nevertheless, they can also introduce important biases in the parameter estimates that should be considered.This research was funded by the Department of Health of the Basque Government through the projects 2019111100 and 2020333033, Instituto de Salud Carlos III through the project PI16/00005 (Co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”/”Investing in your future”) and the Basque Foundation for Health Innovation and Research (BIOEF) through the 2017 EITB Telemaratoia call (BIO17/ND/010)

Machine Learning for Prediction of Cognitive Deterioration in Patients with Early Parkinson’s Disease

Parkinson’s disease (PD) is a neurodegenerative disorder marked by motor and cognitive impairments. The early prediction of cognitive deterioration in PD is crucial. This work aims to predict the change in the Montreal Cognitive Assessment (MoCA) at years 4 and 5 from baseline in the Parkinson’s Progression Markers Initiative database. The predictors included demographic and clinical variables: motor and non-motor symptoms from the baseline visit and change scores from baseline to the first-year follow-up. Various regression models were compared, and SHAP (SHapley Additive exPlanations) values were used to assess domain importance, while model coefficients evaluated variable importance. The LASSOLARS algorithm outperforms other models, achieving lowest the MAE, 1.55±0.23 and 1.56±0.19, for the fourth- and fifth-year predictions, respectively. Moreover, when trained to predict the average MoCA score change across both time points, its performance improved, reducing its MAE by 19%. Baseline MoCA scores and MoCA deterioration over the first-year were the most influential predictors of PD (highest model coefficients). However, the cumulative effect of other cognitive variables also contributed significantly. This study demonstrates that mid-term cognitive deterioration in PD can be accurately predicted from patients’ baseline cognitive performance and short-term cognitive deterioration, along with a few easily measurable clinical measurements.Maitane Martinez-Eguiluz is the recipient of a predoctoral fellowship from the Basque Government (Grant PRE-2022-1-0204). This work was funded by Grant PID2021-123087OB-I00, MICIU/AEI/10.13039/501100011033, and FEDER, UE (Grant Recipient: Olatz Arbelaitz and Javier Muguerza), as well as the Department of Economic Development and Competitiveness (ADIAN, IT1437-22) of the Basque Government (Grant Recipient: Javier Muguerza)

Diagnostic classification of Parkinson’s disease based on non-motor manifestations and machine learning strategies

Non-motor manifestations of Parkinson’s disease (PD) appear early and have a significant impact on the quality of life of patients, but few studies have evaluated their predictive potential with machine learning algorithms. We evaluated 9 algorithms for discriminating PD patients from controls using a wide collection of non-motor clinical PD features from two databases: Biocruces (96 subjects) and PPMI (687 subjects). In addition, we evaluated whether the combination of both databases could improve the individual results. For each database 2 versions with different granularity were created and a feature selection process was performed. We observed that most of the algorithms were able to detect PD patients with high accuracy (>80%). Support Vector Machine and Multi-Layer Perceptron obtained the best performance, with an accuracy of 86.3% and 84.7%, respectively. Likewise, feature selection led to a significant reduction in the number of variables and to better performance. Besides, the enrichment of Biocruces database with data from PPMI moderately benefited the performance of the classification algorithms, especially the recall and to a lesser extent the accuracy, while the precision worsened slightly. The use of interpretable rules obtained by the RIPPER algorithm showed that simply using two variables (autonomic manifestations and olfactory dysfunction), it was possible to achieve an accuracy of 84.4%. Our study demonstrates that the analysis of non-motor parameters of PD through machine learning techniques can detect PD patients with high accuracy and recall, and allows us to select the most discriminative non-motor variables to create potential tools for PD screening.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was partially funded by the Department of Education, Universities and Research of the Basque Government (ADIAN, IT-980-16); by the Spanish Ministry of Science, Innovation and Universities - National Research Agency and the European Regional Development Fund - ERDF (PhysComp, TIN2017-85409-P), and from the State Research Agency (AEI, Spain) under grant agreement No RED2018-102312-T (IA-Biomed); by Michael J. Fox Foundation [RRIA 2014 (Rapid Response Innovation Awards) Program (Grant ID: 10189)]; by the Instituto de Salud Carlos III through the project “PI14/00679” and “PI16/00005”, the Juan Rodes grant “JR15/00008” (IG) (Co-funded by European Regional Development Fund/European Social Fund - “Investing in your future”); and by the Department of Health of the Basque Government through the projects “2016111009” and “2019111100”

Impacto de la estimulación subtalámica a largo plazo sobre la situación cognitiva de los pacientes con enfermedad de Parkinson avanzada

Objetivo El objetivo es evaluar los efectos de la estimulación cerebral profunda del núcleo subtalámico bilateral (STN-DBS) sobre el estado cognitivo de los pacientes con enfermedad de Parkinson 5 años después de la cirugía. Materiales y métodos En este estudio prospectivo se incluyeron 50 pacientes con enfermedad de Parkinson (62,5% hombres, edad media 62,2 ± 8,2 años y duración de la enfermedad 14,1 ± 6,3 años) sometidos a STN-DBS. Todos los pacientes fueron evaluados preoperatoriamente y un año después de la cirugía, y 40 pacientes fueron seguidos hasta 5 años. En cada visita se realizaron las siguientes evaluaciones neuropsicológicas: Mini-Mental State Examination, Mattis Dementia Rating Scale (MDRS), test de secuencias números-letras de WAIS III-LN, Prueba de dibujo de reloj, Prueba de aprendizaje verbal auditivo Rey, la Prueba de retención visual de Benton, la Prueba de juicio de orientación de línea de Benton, la fluidez verbal fonética y semántica, la Prueba Stroop y la Escala de clasificación de depresión de Montgomery-Asberg. Resultados Anualmente se observaron reducciones en la puntación de Mini-Mental State Examination (–0,89%), Prueba del dibujo de reloj (–2,61%) y MDRS (–1,72%), fueron más marcados tanto para la fluidez verbal fonética (–13,28%) como semántica (–12,40%). Para la Prueba de aprendizaje verbal auditivo Rey observamos un deterioro en la capacidad de recuerdo diferido (–10,12%) un año después de la cirugía. A los 5 años la mayor parte del deterioro se produjo en la fluidez verbal, con reducciones adicionales de 16,10% y 16,60% para la fluidez verbal semántica y fonética, respectivamente. Se observó un empeoramiento más moderado del recuerdo inmediato (–16,87%), WAIS III-LN (–16,67%) y de la prueba de orientación lineal de Benton (–11,56%). Discusión La STN-DBS no condujo a deterioro cognitivo global a los 5 años de la cirugía. Hubo un deterioro significativo en la función verbal desde el primer año de la cirugía. El deterioro de la capacidad de aprendizaje y de las funciones visuoespaciales podría atribuirse al propio proceso degenerativo de la enfermedad.This study was partially funded by research grant INT-BC2016-1 from Biocruces Bizkaia Health Research Institute

Costs and effects of telerehabilitation in neurological and cardiological diseases: A systematic review

Introduction: Telerehabilitation in neurological and cardiological diseases is an alternative rehabilitation that improves the quality of life and health conditions of patients and enhances the accessibility to health care. However, despite the reported benefits of telerehabilitation, it is necessary to study its impact on the healthcare system. Methods: The systematic review aims to investigate the costs and results of telerehabilitation in neurological and cardiological diseases. MEDLINE and EMBASE databases were searched from 2005 to 2021, for studies that assess the costs and results of telerehabilitation compared to traditional rehabilitation (center-based programs) in neurological and cardiological diseases. A narrative synthesis of results was carried out. Results: A total of 8 studies (865 participants) of 430 records were included. Three studies were related to the costs and results of telerehabilitation in neurological diseases (specifically in stroke). In total, five studies assessed telerehabilitation in cardiological diseases (chronic heart failure, coronary heart disease, acute coronary syndrome, and cardiovascular diseases). The duration of the telerehabilitation ranged from 6 to 48 weeks. The studies included cost-analysis, cost-benefit, cost-effectiveness, or cost-utility. In total, four studies found significant cost/savings per person between $565.66 and$2,352.00 (p < 0.05). In contrast, most studies found differences in costs and clinical effects between the telerehabilitation performed and the rehabilitation performed at the clinic. Just one study found quality-adjusted life years (QALY) significant differences between groups [Incremental cost-effectiveness ratio (ICER) per QALY ($-21,666.41/QALY). Discussion: Telerehabilitation is an excellent alternative to traditional center rehabilitation, which increases the accessibility to rehabilitation to more people, either due to the geographical situation of the patients or the limitations of the health systems. Telerehabilitation seems to be as clinical and cost-effective as traditional rehabilitation, even if, generally, telerehabilitation is less costly. More research is needed to evaluate health-related quality of life and cost-effectiveness in other neurological diseases.This project has received funding from the European Union's Horizon 2020 Research and Innovation Program under grant agreement no: 769807

Spatial characterization of the effect of age and sex on macular layer thicknesses and foveal pit morphology

Characterizing the effect of age and sex on macular retinal layer thicknesses and foveal pit morphology is crucial to differentiating between natural and disease-related changes. We applied advanced image analysis techniques to optical coherence tomography (OCT) to: 1) enhance the spatial description of age and sex effects, and 2) create a detailed open database of normative retinal layer thickness maps and foveal pit shapes. The maculae of 444 healthy subjects (age range 21–88) were imaged with OCT. Using computational spatial data analysis, thickness maps were obtained for retinal layers and averaged into 400 (20 x 20) sectors. Additionally, the geometry of the foveal pit was radially analyzed by computing the central foveal thickness, rim height, rim radius, and mean slope. The effect of age and sex on these parameters was analyzed with multiple regression mixed-effects models. We observed that the overall age-related decrease of the total retinal thickness (TRT) (-1.1% per 10 years) was mainly driven by the ganglion cell-inner plexiform layer (GCIPL) (-2.4% per 10 years). Both TRT and GCIPL thinning patterns were homogeneous across the macula when using percentual measurements. Although the male retina was 4.1 μm thicker on average, the greatest differences were mainly present for the inner retinal layers in the inner macular ring (up to 4% higher TRT than in the central macula). There was an age-related decrease in the rim height (1.0% per 10 years) and males had a higher rim height, shorter rim radius, and steeper mean slope. Importantly, the radial analysis revealed that these changes are present and relatively uniform across angular directions. These findings demonstrate the capacity of advanced analysis of OCT images to enhance the description of the macula. This, together with the created dataset, could aid the development of more accurate diagnosis models for macular pathologies.This study was partially co-funded by the Instituto de Salud Carlos III (https://www.isciii.es) through the projects PI14/00679 (IG) and PI16/00005 (IG), by the Basque Foundation for Health Innovation and Research (https://www.bioef.org) through the project BIO17/ND/010 (IG), and by the Department of Health of the Basque Government (https://www.euskadi.eus/gobierno-vasco/departamento-salud) through the projects 2019111100 (IG), 2020333033(IG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Foveal remodeling of retinal microvasculature in Parkinson’s disease

[EN] Background: Retinal microvascular alterations have been previously described in Parkinson’s disease (PD) patients using optical coherence tomography angiography (OCT-A). However, an extensive description of retinal vascular morphological features, their association with PD-related clinical variables and their potential use as diagnostic biomarkers has not been explored. Methods: We performed a cross-sectional study including 49 PD patients (87 eyes) and 40 controls (73 eyes). Retinal microvasculature was evaluated with Spectralis OCT-A and cognitive status with Montreal Cognitive Assessment. Unified PD Rating Scale and disease duration were recorded in patients. We extracted microvascular parameters from superficial and deep vascular plexuses of the macula, including the area and circularity of foveal avascular zone (FAZ), skeleton density, perfusion density, vessel perimeter index, vessel mean diameter, fractal dimension (FD) and lacunarity using Python and MATLAB. We compared the microvascular parameters between groups and explored their association with thickness of macular layers and clinical outcomes. Data were analyzed with General Estimating Equations (GEE) and adjusted for age, sex, and hypertension. Logistic regression GEE models were fitted to predict diagnosis of PD versus controls from microvascular, demographic, and clinical data. The discrimination ability of models was tested with receiver operating characteristic curves. Results: FAZ area was significantly smaller in patients compared to controls in superficial and deep plexuses, whereas perfusion density, skeleton density, FD and lacunarity of capillaries were increased in the foveal zone of PD. In the parafovea, microvascular parameters of superficial plexus were associated with ganglion cellinner plexiform layer thickness, but this was mainly driven by PD with mild cognitive impairment. No such associations were observed in controls. FAZ area was negatively associated with cognition in PD (non-adjusted models). Foveal lacunarity, combined with demographic and clinical confounding factors, yielded an outstanding diagnostic accuracy for discriminating PD patients from controls. Conclusion: Parkinson’s disease patients displayed foveal microvascular alterations causing an enlargement of the vascular bed surrounding FAZ. Parafoveal microvascular alterations were less pronounced but were related to inner retinal layer thinning. Retinal microvascular abnormalities helped discriminating PD from controls. All this supports OCT-A as a potential non-invasive biomarker to reveal vascular pathophysiology and improve diagnostic accuracy in PD.This study was partially co-funded by the Instituto de Salud Carlos III through the projects PI14/00679 and PI16/00005 (co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”/“Investing in your future”), and by the Department of Health of the Basque Government through the projects “2019111100” and “2020333033”

Brain connectivity and cognitive functioning in individuals six months after multiorgan failure

Multiorgan failure (MOF) is a life-threating condition that affects two or more systems of organs not involved in the disorder that motivates admission to an Intensive Care Unit (ICU). Patients who survive MOF frequently present long-term functional, neurological, cognitive, and psychiatric sequelae. However, the changes to the brain that explain such symptoms remain unclear. Objective: To determine brain connectivity and cognitive functioning differences between a group of MOF patients six months after ICU discharge and healthy controls (HC). Methods: 22 MOF patients and 22 HC matched by age, sex, and years of education were recruited. Both groups were administered a 3T magnetic resonance imaging (MRI), including structural T1 and functional BOLD, as well as a comprehensive neuropsychological evaluation that included tests of learning and memory, speed of information processing and attention, executive function, visual constructional abilities, and language. Voxel-based morphometry was used to analyses T1 images. For the functional data at rest, functional connectivity (FC) analyses were performed. Results: There were no significant differences in structural imaging and neuropsychological performance between groups, even though patients with MOF performed worse in all the cognitive tests. Functional neuroimaging in the default mode network (DMN) showed hyper-connectivity towards sensory-motor, cerebellum, and visual networks. DMN connectivity had a significant association with the severity of MOF during ICU stay and with the neuropsychological scores in tests of attention and visual constructional abilities. Conclusions: In MOF patients without structural brain injury, DMN connectivity six months after ICU discharge is associated with MOF severity and neuropsychological impairment, which supports the use of resting-state functional MRI as a potential tool to predict the onset of long-term cognitive deficits in these patients. Similar to what occurs at the onset of other pathologies, the observed hyper-connectivity might suggest network re-adaptation following MOF.This research was founded by Ministerio Economia, Industria y Competitividad, Spain and FEDER (grant no. DPI2016-79874-R) to JC and JCAL. ID's time was founded by the Department of Education of the Basque Country, postdoctoral program. JR's time was founded by the Ministry of Education, Language Policy and Culture (Basque Government). JMC's time was founded by Ikerbasque and the Department of Economic Development and Infrastructure of the Basque Country, Elkartek Program (grant no. KK-2018/00032). JCAL's time was founded by Ikerbasque and Fundacion Mutua Madrileña (grant no. AP169812018). IG's time was founded by the Instituto de Salud Carlos III for a Juan Rodes (grant no. JR15/00008 ) co-funded by the European Regional Development Fund/European Social Fund ‘Investing in Your Future’. AJM's time was partly founded by Euskampus Fundazioa

Influence of corpus callosum damage on cognition and physical disability in multiple sclerosis: a multimodal study.

Background Corpus callosum (CC) is a common target for multiple sclerosis (MS) pathology. We investigated the influence of CC damage on physical disability and cognitive dysfunction using a multimodal approach. Methods Twenty-one relapsing-remitting MS patients and 13 healthy controls underwent structural MRI and diffusion tensor of the CC (fractional anisotropy; mean diffusivity, MD; radial diffusivity, RD; axial diffusivity). Interhemisferic transfer of motor inhibition was assessed by recording the ipsilateral silent period (iSP) to transcranial magnetic stimulation. We evaluated cognitive function using the Brief Repeatable Battery and physical disability using the Expanded Disability Status Scale (EDSS) and the MS Functional Composite (MSFC) z-score. Results The iSP latency correlated with physical disability scores (r ranged from 0.596 to 0.657, P values from 0.004 to 0.001), and with results of visual memory (r = −0.645, P = 0.002), processing speed (r = −0.51, P = 0.018) and executive cognitive domain tests (r = −0.452, P = 0.039). The area of the rostrum correlated with the EDSS (r = −0.442, P = 0.045). MD and RD correlated with cognitive performance, mainly with results of visual and verbal memory tests (r ranged from −0.446 to −0.546, P values from 0.048 to 0.011). The iSP latency correlated with CC area (r = −0.345, P = 0.049), volume (r = −0.401, P = 0.002), MD (r = 0.404, P = 0.002) and RD (r = 0.415, P = 0.016). Conclusions We found evidence for structural and microstructural CC abnormalities associated with impairment of motor callosal inhibitory conduction in MS. CC damage may contribute to cognitive dysfunction and in less extent to physical disability likely through a disconnection mechanism