Artificial intelligence for screening and diagnosis of amyotrophic lateral sclerosis: a systematic review and meta-analysis.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS) is a rare and fatal neurological disease that leads to progressive motor function degeneration. Diagnosing ALS is challenging due to the absence of a specific detection test. The use of artificial intelligence (AI) can assist in the investigation and treatment of ALS. METHODS: We searched seven databases for literature on the application of AI in the early diagnosis and screening of ALS in humans. The findings were summarized using random-effects summary receiver operating characteristic curve. The risk of bias (RoB) analysis was carried out using QUADAS-2 or QUADAS-C tools. RESULTS: In the 34 analyzed studies, a meta-prevalence of 47% for ALS was noted. For ALS detection, the pooled sensitivity of AI models was 94.3% (95% CI - 63.2% to 99.4%) with a pooled specificity of 98.9% (95% CI - 92.4% to 99.9%). For ALS classification, the pooled sensitivity of AI models was 90.9% (95% CI - 86.5% to 93.9%) with a pooled specificity of 92.3% (95% CI - 84.8% to 96.3%). Based on type of input for classification, the pooled sensitivity of AI models for gait, electromyography, and magnetic resonance signals was 91.2%, 92.6%, and 82.2%, respectively. The pooled specificity for gait, electromyography, and magnetic resonance signals was 94.1%, 96.5%, and 77.3%, respectively. CONCLUSIONS: Although AI can play a significant role in the screening and diagnosis of ALS due to its high sensitivities and specificities, concerns remain regarding quality of evidence reported in the literature.

Brodmann Areas, V1 Atlas and Cognitive Impairment: Assessing Cortical Thickness for Cognitive Impairment Diagnostics.

Background and Objectives: Magnetic resonance imaging is vital for diagnosing cognitive decline. Brodmann areas (BA), distinct regions of the cerebral cortex categorized by cytoarchitectural variances, provide insights into cognitive function. This study aims to compare cortical thickness measurements across brain areas identified by BA mapping. We assessed these measurements among patients with and without cognitive impairment, and across groups categorized by cognitive performance levels using the Montreal Cognitive Assessment (MoCA) test. Materials and Methods: In this cross-sectional study, we included 64 patients who were divided in two ways: in two groups with (CI) or without (NCI) impaired cognitive function and in three groups with normal (NC), moderate (MPG) and low (LPG) cognitive performance according to MoCA scores. Scans with a 3T MRI scanner were carried out, and cortical thickness data was acquired using Freesurfer 7.2.0 software. Results: By analyzing differences between the NCI and CI groups cortical thickness of BA3a in left hemisphere (U = 241.000, p = 0.016), BA4a in right hemisphere (U = 269.000, p = 0.048) and BA28 in left hemisphere (U = 584.000, p = 0.005) showed significant differences. In the LPG, MPG and NC cortical thickness in BA3a in left hemisphere (H (2) = 6.268, p = 0.044), in V2 in right hemisphere (H (2) = 6.339, p = 0.042), in BA28 in left hemisphere (H (2) = 23.195, p < 0.001) and in BA28 in right hemisphere (H (2) = 10.015, p = 0.007) showed significant differences. Conclusions: Our study found that cortical thickness in specific Brodmann Areas-BA3a and BA28 in the left hemisphere, and BA4a in the right-differ significantly between NCI and CI groups. Significant differences were also observed in BA3a (left), V2 (right), and BA28 (both hemispheres) across LPG, MPG, NC groups. Despite a small sample size, these findings suggest cortical thickness measurements can serve as effective biomarkers for cognitive impairment diagnosis, warranting further validation with a larger cohort.

Protective role of Bacillus Calmette-Guérin vaccine in Alzheimer's disease progression: A systematic review and meta-analysis.

Introduction: Alzheimer's disease (AD) represents a significant societal challenge, highlighting the need to explore effective prevention and treatment approaches. Recent literature has suggested that Bacillus Calmette-Guérin (BCG) vaccine may be a viable therapeutic option for immune disorders associated with AD due to its immunomodulatory properties and protection against various diseases. Methods: This systematic review aimed to evaluate the association of BCG vaccine in the prevention of AD using six medical-scientific databases. A meta-analytical approach was undertaken to estimate the risk of AD incidence in patients with and without BCG vaccine exposure, followed by subgroup analyses. A risk of bias (RoB) assessment was performed using the Newcastle-Ottawa Scale (NOS). Results: Six cohort studies meeting our inclusion criteria were included (47,947 participants) in the study. From our meta-analysis, intravesical BCG vaccine administration lowered the risk of incidence of AD by 26% in non-muscle-invasive bladder cancer (p < 0.00001). Subgroup analyses showed that BCG vaccination showed a potentially notable preventive effect on AD in older adults (>75 years) and female participants. Conversely, significant heterogeneity in results was observed among male participants and those aged <75 years. The RoB was low in three studies and unclear in the remaining studies. Conclusions: Although our results support the potential benefits of BCG vaccine in preventing AD in specific demographics, we remain cautious about interpreting such results. Further research examining the implications of BCG vaccination for prevention and possible treatment of AD should be undertaken in the future.

Whole Brain and Corpus Callosum Fractional Anisotropy Differences in Patients with Cognitive Impairment.

Diffusion tensor imaging (DTI) is an MRI analysis method that could help assess cognitive impairment (CI) in the ageing population more accurately. In this research, we evaluated fractional anisotropy (FA) of whole brain (WB) and corpus callosum (CC) in patients with normal cognition (NC), mild cognitive impairment (MCI), and moderate/severe cognitive impairment (SCI). In total, 41 participants were included in a cross-sectional study and divided into groups based on Montreal Cognitive Assessment (MoCA) scores (NC group, nine participants, MCI group, sixteen participants, and SCI group, sixteen participants). All participants underwent an MRI examination that included a DTI sequence. FA values between the groups were assessed by analysing FA value and age normative percentile. We did not find statistically significant differences between the groups when analysing CC FA values. Both approaches showed statistically significant differences in WB FA values between the MCI-SCI and MCI-NC groups, where the MCI group participants showed the highest mean FA and highest mean FA normative percentile results in WB.

Combined Score of Perivascular Space Dilatation and White Matter Hyperintensities in Patients with Normal Cognition, Mild Cognitive Impairment, and Dementia.

Background and Objectives: Cerebral perivascular spaces (PVS) are part of the cerebral microvascular structure and play a role in lymphatic drainage and the removal of waste products from the brain. White matter hyperintensities (WMH) are hyperintense lesions on magnetic resonance imaging that are associated with cognitive impairment, dementia, and cerebral vascular disease. WMH and PVS are direct and indirect imaging biomarkers of cerebral microvascular integrity and health. In our research, we evaluated WMH and PVS enlargement in patients with normal cognition (NC), mild cognitive impairment (MCI), and dementia (D). Materials and Methods: In total, 57 participants were included in the study and divided into groups based on neurological evaluation and Montreal Cognitive Assessment results (NC group 16 participants, MCI group 29 participants, D group 12 participants). All participants underwent 3T magnetic resonance imaging. PVS were evaluated in the basal ganglia, centrum semiovale, and midbrain. WMHs were evaluated based on the Fazekas scale and the division between deep white matter (DWM) and periventricular white matter (PVWM). The combined score based on PVS and WMH was evaluated and correlated with the results of the MoCA. Results: We found statistically significant differences between groups on several measures. Centrum semiovale PVS dilatation was more severe in MCI and dementia group and statistically significant differences were found between D-MCI and D-NC pairs. PVWM was more severe in patients with MCI and dementia group, and statistically significant differences were found between D-MCI and D-NC pairs. Furthermore, we found statistically significant differences between the groups by analyzing the combined score of PVS dilatation and WMH. We did not find statistically significant differences between the groups in PVS dilation of the basal ganglia and midbrain and DWM hyperintensities. Conclusions: PVS assessment could become one of neuroimaging biomarkers for patients with cognitive decline. Furthermore, the combined score of WMH and PVS dilatation could facilitate diagnostics of cognitive impairment, but more research is needed with a larger cohort to determine the use of PVS dilatation and the combined score.

War Psychiatry: Identifying and Managing the Neuropsychiatric Consequences of Armed Conflicts.

War refugees and veterans have been known to frequently develop neuropsychiatric conditions including depression, post-traumatic stress disorder (PTSD), and anxiety disorders that tend to leave a long-lasting scar and impact their emotional response system. The shear stress, trauma, and mental breakdown from overnight displacement, family separation, and killing of friends and families cannot be described enough. Victims often require years of mental health support as they struggle with sleep difficulties, recurring memories, anxiety, grief, and anger. Everyone develops their coping mechanism which can involve dependence and long-term addiction to alcohol, drugs, violence, or gambling. The high prevalence of mental health disorders during and after the war indicates an undeniable necessity for screening those in need of treatment. For medical health professionals, it is crucial to identify such vulnerable groups who are prone to developing neuropsychiatric morbidities and associated risk factors. It is pivotal to develop and deploy effective and affordable multi-sectoral collaborative care models and therapy, which primarily depends upon family and primary care physicians in the conflict zones. Herein, we provide a brief overview regarding the identification and management of vulnerable populations, alongside discussing the challenges and possible solutions to the same.

Cerebellar Cortex and Cerebellar White Matter Volume in Normal Cognition, Mild Cognitive Impairment, and Dementia.

The cerebellum is commonly viewed as a structure that is primarily responsible for the coordination of voluntary movement, gait, posture, and speech. Recent research has shown evidence that the cerebellum is also responsible for cognition. We analyzed 28 participants divided into three groups (9 with normal cognition, 9 with mild cognitive impairment, and 10 with moderate/severe cognitive impairment) based on the Montreal Cognitive Assessment. We analyzed the cerebellar cortex and white matter volume and assessed differences between groups. Participants with normal cognition had higher average values in total cerebellar volume, cerebellar white matter volume, and cerebellar cortex volume in both hemispheres, but by performing the Kruskal-Wallis test, we did not find these values to be statistically significant.

Brain Structural Connectivity Differences in Patients with Normal Cognition and Cognitive Impairment.

Advances in magnetic resonance imaging, particularly diffusion imaging, have allowed researchers to analyze brain connectivity. Identification of structural connectivity differences between patients with normal cognition, cognitive impairment, and dementia could lead to new biomarker discoveries that could improve dementia diagnostics. In our study, we analyzed 22 patients (11 control group patients, 11 dementia group patients) that underwent 3T MRI diffusion tensor imaging (DTI) scans and the Montreal Cognitive Assessment (MoCA) test. We reconstructed DTI images and used the Desikan-Killiany-Tourville cortical parcellation atlas. The connectivity matrix was calculated, and graph theoretical analysis was conducted using DSI Studio. We found statistically significant differences between groups in the graph density, network characteristic path length, small-worldness, global efficiency, and rich club organization. We did not find statistically significant differences between groups in the average clustering coefficient and the assortativity coefficient. These statistically significant graph theory measures could potentially be used as quantitative biomarkers in cognitive impairment and dementia diagnostics.

Structural Analysis of Brain Hub Region Volume and Cortical Thickness in Patients with Mild Cognitive Impairment and Dementia.

Background and Objectives: A complex network of axonal pathways interlinks the human brain cortex. Brain networks are not distributed evenly, and brain regions making more connections with other parts are defined as brain hubs. Our objective was to analyze brain hub region volume and cortical thickness and determine the association with cognitive assessment scores in patients with mild cognitive impairment (MCI) and dementia. Materials and Methods: In this cross-sectional study, we included 11 patients (5 mild cognitive impairment; 6 dementia). All patients underwent neurological examination, and Montreal Cognitive Assessment (MoCA) test scores were recorded. Scans with a 3T MRI scanner were done, and cortical thickness and volumetric data were acquired using Freesurfer 7.1.0 software. Results: By analyzing differences between the MCI and dementia groups, MCI patients had higher hippocampal volumes (p < 0.05) and left entorhinal cortex thickness (p < 0.05). There was a significant positive correlation between MoCA test scores and left hippocampus volume (r = 0.767, p < 0.01), right hippocampus volume (r = 0.785, p < 0.01), right precuneus cortical thickness (r = 0.648, p < 0.05), left entorhinal cortex thickness (r = 0.767, p < 0.01), and right entorhinal cortex thickness (r = 0.612, p < 0.05). Conclusions: In our study, hippocampal volume and entorhinal cortex showed significant differences in the MCI and dementia patient groups. Additionally, we found a statistically significant positive correlation between MoCA scores, hippocampal volume, entorhinal cortex thickness, and right precuneus. Although other brain hub regions did not show statistically significant differences, there should be additional research to evaluate the brain hub region association with MCI and dementia.