Clinical validity of the Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB) in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

The identification and staging of Alzheimer's Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC). Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD.

METHODS

One hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses.

RESULTS

Two episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI.

CONCLUSIONS

Our findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.

Virtual Reality for the Rehabilitation of Acquired Cognitive Disorders: A Narrative Review

This review article explores the use of Virtual Reality (VR) technology in cognitive rehabilitation for individuals with neurological conditions, such as stroke, traumatic brain injury, and neurodegenerative diseases. The introduction highlights the challenges posed by cognitive impairments and the limitations of traditional rehabilitation methods. VR is presented as a transformative tool that immerses individuals in interactive environments, offering promising opportunities for enhancing cognitive functions and improving quality of life. This article covers the foundational principles of VR, its applications across different clinical conditions and cognitive domains, and evaluates empirical evidence supporting its efficacy. It also discusses the advantages, limitations, challenges, and ethical considerations in the use of VR for cognitive rehabilitation. This review concludes by exploring future developments, including advancements in VR technology, the integration of Augmented Reality (AR) and artificial intelligence (AI), and the importance of standardized assessment tools for the objective evaluation of rehabilitation outcomes.

Functional Living Skills in Patients with Major Neurocognitive Disorder Due to Degenerative or Non-Degenerative Conditions: Effectiveness of a Non-Immersive Virtual Reality Training

Virtual reality has gained attention as an effective tool for cognitive, motor, and daily activity rehabilitation in patients with major neurocognitive disorder (M-NCD). The first objective of this study was to check for differences between M-NCD caused by degenerative and non-degenerative conditions (DC and NDC, respectively) in terms of relearning four functional living skills (FLSs), by means of a non-immersive virtual reality training (VRT). The second purpose was to verify whether spontaneous transfer from the virtual environment to the real environment occurred. Four FLS apps were developed in our institute (Information, Suitcase, Medicine, and Supermarket). A nonrandomized interventional study was carried out, comparing experimental and control groups (EG and CG, respectively). The study included three phases: in vivo test at T1; VRT at T2 only for EG; in vivo test at T3. During the in vivo test, the four FLSs were assessed in their natural environments. Both EG-DC and EG-NDC significantly improved in all of the VRT variable scores (the EG-NDC group seemed to show better outcomes than the EG-DC group). Moderate-to-high satisfaction with the VRT was reported. EG-DC and EG-NDC also enhanced their performances in the in vivo test. No statistically significant differences between them were found. CG-DC and CG-NDC improved only in the execution time of Information in the in vivo test. These findings confirm the ecological validity of VRT for FLSs.

Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB 1.0): development and normative data

BACKGROUND

Neuropsychological testing plays a cardinal role in the diagnosis and monitoring of Alzheimer's disease. A major concern is represented by the heterogeneity of the neuropsychological batteries currently adopted in memory clinics and healthcare centers. The current study aimed to solve this issue.

METHODS

Following the initiative of the University of Washington's National Alzheimer's Coordinating Center (NACC), we presented the Italian adaptation of the Neuropsychological Test Battery of the Uniform Data Set (I-UDSNB). We collected data from 433 healthy Italian individuals and employed regression models to evaluate the impact of demographic variables on the performance, deriving the reference norms.

RESULTS

Higher education and lower age were associated with a better performance in the majority of tests, while sex affected only fluency tests and Digit Span Forward.

CONCLUSIONS

The I-UDSNB offers a valuable and harmonized tool for neuropsychological testing in Italy, to be used in clinical and research settings.

Advanced eNose-Driven Pedestrian Tracking Pipeline for Intelligent Car Driver Assisting System: Preliminary Results

From a biological point of view, alcohol human attentional impairment occurs before reaching a Blood Alcohol Content (BAC index) of 0.08% (0.05% under the Italian legislation), thus generating a significant impact on driving safety if the drinker subject is driving a car. Car drivers must keep a safe driving dynamic, having an unaltered physiological status while processing the surrounding information coming from the driving scenario (e.g., traffic signs, other vehicles and pedestrians). Specifically, the identification and tracking of pedestrians in the driving scene is a widely investigated problem in the scientific community. The authors propose a full, deep pipeline for the identification, monitoring and tracking of the salient pedestrians, combined with an intelligent electronic alcohol sensing system to properly assess the physiological status of the driver. More in detail, the authors propose an intelligent sensing system that makes a common air quality sensor selective to alcohol. A downstream Deep 1D Temporal Residual Convolutional Neural Network architecture will be able to learn specific embedded alcohol-dynamic features in the collected sensing data coming from the GHT25S air-quality sensor of STMicroelectronics. A parallel deep attention-augmented architecture identifies and tracks the salient pedestrians in the driving scenario. A risk assessment system evaluates the sobriety of the driver in case of the presence of salient pedestrians in the driving scene. The collected preliminary results confirmed the effectiveness of the proposed approach.

Functional Living Skills: A Non-Immersive Virtual Reality Training for Individuals with Major Neurocognitive Disorders

The loss of functional living skills (FLS) is an essential feature of major neurocognitive disorders (M-NCD); virtual reality training (VRT) offers many possibilities for improving FLS in people with M-NCD. The aim of our study was to verify the effectiveness of a non-immersive VRT on FLS for patients with M-NCD. VRT was carried out for 10 to 20 sessions, by means of four 3D apps developed in our institute and installed on a large touch screen. The experimental group (EG) and the control group (CG) included 24 and 18 patients with M-NCD, respectively. They were administered the in vivo test (in specific hospital places reproducing the natural environments) at T1 (pre-training) and T3 (post-training); at T2, only EG was administered VRT. Statistically significant differences between EG and CG in all the in vivo tests were found in the number of correct responses; during VRT, the number of correct responses increased, while the execution times and the number of clues decreased. The improvement in the in vivo tests appeared to be related to the specific VRT applied. The satisfaction of participants with the VRT was moderate to high.

An explainable AI system for automated COVID-19 assessment and lesion categorization from CT-scans

COVID-19 infection caused by SARS-CoV-2 pathogen has been a catastrophic pandemic outbreak all over the world, with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. We first propose a new segmentation module aimed at automatically identifying lung parenchyma and lobes. Next, we combine the segmentation network with classification networks for COVID-19 identification and lesion categorization. We compare the model's classification results with those obtained by three expert radiologists on a dataset of 166 CT scans. Results showed a sensitivity of 90.3% and a specificity of 93.5% for COVID-19 detection, at least on par with those yielded by the expert radiologists, and an average lesion categorization accuracy of about 84%. Moreover, a significant role is played by prior lung and lobe segmentation, that allowed us to enhance classification performance by over 6 percent points. The interpretation of the trained AI models reveals that the most significant areas for supporting the decision on COVID-19 identification are consistent with the lesions clinically associated to the virus, i.e., crazy paving, consolidation and ground glass. This means that the artificial models are able to discriminate a positive patient from a negative one (both controls and patients with interstitial pneumonia tested negative to COVID) by evaluating the presence of those lesions into CT scans. Finally, the AI models are integrated into a user-friendly GUI to support AI explainability for radiologists, which is publicly available at http://perceivelab.com/covid-ai. The whole AI system is unique since, to the best of our knowledge, it is the first AI-based software, publicly available, that attempts to explain to radiologists what information is used by AI methods for making decisions and that proactively involves them in the decision loop to further improve the COVID-19 understanding.

Deep Neuro-Vision Embedded Architecture for Safety Assessment in Perceptive Advanced Driver Assistance Systems: The Pedestrian Tracking System Use-Case

In recent years, the automotive field has been changed by the accelerated rise of new technologies. Specifically, autonomous driving has revolutionized the car manufacturer's approach to design the advanced systems compliant to vehicle environments. As a result, there is a growing demand for the development of intelligent technology in order to make modern vehicles safer and smarter. The impact of such technologies has led to the development of the so-called Advanced Driver Assistance Systems (ADAS), suitable to maintain control of the vehicle in order to avoid potentially dangerous situations while driving. Several studies confirmed that an inadequate driver's physiological condition could compromise the ability to drive safely. For this reason, assessing the car driver's physiological status has become one of the primary targets of the automotive research and development. Although a large number of efforts has been made by researchers to design safety-assessment applications based on the detection of physiological signals, embedding them into a car environment represents a challenging task. These mentioned implications triggered the development of this study in which we proposed an innovative pipeline, that through a combined less invasive Neuro-Visual approach, is able to reconstruct the car driver's physiological status. Specifically, the proposed contribution refers to the sampling and processing of the driver PhotoPlethysmoGraphic (PPG) signal. A parallel enhanced low frame-rate motion magnification algorithm is used to reconstruct such features of the driver's PhotoPlethysmoGraphic (PPG) data when that signal is no longer available from the native embedded sensor platform. A parallel monitoring of the driver's blood pressure levels from the PPG signal as well as the driver's eyes dynamics completes the reconstruction of the driver's physiological status. The proposed pipeline has been tested in one of the major investigated automotive scenarios i.e., the detection and monitoring of pedestrians while driving (pedestrian tracking). The collected performance results confirmed the effectiveness of the proposed approach.

Heart rate changes associated with the different types of leg movements during sleep in children, adolescents and adults with restless legs syndrome

The objective of this study was to describe in detail the heart rate changes accompanying short-interval leg movements during sleep, periodic leg movements during sleep, and isolated leg movements during sleep in children and adolescents with restless legs syndrome, and to compare them with the same findings in adults with restless legs syndrome. We analysed time series of R-R intervals synchronized to the onset of short-interval leg movements during sleep, periodic leg movements during sleep or isolated leg movements during sleep that entailed an arousal during non-rapid-eye-movement sleep. We assessed cardiac activation based on the heart rate changes with respect to baseline during non-rapid-eye-movement sleep without leg movements. All types of leg movements recorded during sleep were accompanied by important heart rate changes also in children, with an overall impact similar to that observed in adults. In all age groups, heart rate changes accompanying short-interval leg movements during sleep were constituted by a tachycardia, without a subsequent relative bradycardia, that was instead evident for periodic leg movements during sleep and isolated leg movements during sleep. Moreover, an age-related decline of the relative bradycardia following the heart rate increase, in association with periodic leg movements during sleep and isolated leg movements during sleep, was observed. Our findings show that important heart rate changes accompany all leg movements during sleep at all ages in restless legs syndrome, with significant age-related differences. This information represents an important contribution to the ongoing scientific debate on the possibility and opportunity to treat periodic leg movements during sleep.

Three-Dimensional Deep Noninvasive Radiomics for the Prediction of Disease Control in Patients With Metastatic Urothelial Carcinoma treated With Immunotherapy

INTRODUCTION

Immunotherapy is effective in a small percentage of patients with cancer and no reliable predictive biomarkers are currently available. Artificial Intelligence algorithms may automatically quantify radiologic characteristics associated with disease response to medical treatments.

METHODS

We investigated an innovative approach based on a 3-dimensional (3D) deep radiomics pipeline to classify visual features of chest-abdomen computed tomography (CT) scans with the aim of distinguishing disease control from progressive disease to immune checkpoint inhibitors (ICIs). Forty-two consecutive patients with metastatic urothelial cancer had progressed on first-line platinum-based chemotherapy and had baseline CT scans at immunotherapy initiation. The 3D-pipeline included self-learned visual features and a deep self-attention mechanism. According to the outcome to the ICIs, a 3D deep classifier semiautomatically categorized the most discriminative region of interest on the CT scans.

RESULTS

With a median follow-up of 13.3 months (95% CI, 11.1-15.6), the median overall survival was 8.5 months (95% CI, 3.1-13.8). According to disease response to immunotherapy, the median overall survival was 3.6 months (95% CI, 2.0-5.2) for patients with progressive disease; it was not yet reached for those with disease control. The predictive accuracy of the 3D-pipeline was 82.5% (sensitivity 96%; specificity, 60%). The addition of baseline clinical factors increased the accuracy to 92.5% by improving specificity to 87%; the accuracy of other architectures ranged from 72.5% to 90%.

CONCLUSION

Artificial Intelligence by 3D deep radiomics is a potential noninvasive biomarker for the prediction of disease control to ICIs in metastatic urothelial cancer and deserves validation in larger series.

MASK-RL: Multiagent Video Object Segmentation Framework Through Reinforcement Learning

Integrating human-provided location priors into video object segmentation has been shown to be an effective strategy to enhance performance, but their application at large scale is unfeasible. Gamification can help reduce the annotation burden, but it still requires user involvement. We propose a video object segmentation framework that leverages the combined advantages of user feedback for segmentation and gamification strategy by simulating multiple game players through a reinforcement learning (RL) model that reproduces human ability to pinpoint moving objects and using the simulated feedback to drive the decisions of a fully convolutional deep segmentation network. Experimental results on the DAVIS-17 benchmark show that: 1) including user-provided prior, even if not precise, yields high performance; 2) our RL agent replicates satisfactorily the same variability of humans in identifying spatiotemporal salient objects; and 3) employing artificially generated priors in an unsupervised video object segmentation model reaches state-of-the-art performance.

[Vinflunine: still an option for patients with advanced urothelial carcinoma following immune-checkpoint inhibitors?]

INTRODUCTION

The treatment of metastatic urothelial cancer (mUC) following first-line standard platinum-based chemotherapy and immune checkpoint inhibitors (ICIs) is not yet established.

MATERIAL AND METHODS

We investigated the activity and toxicity of vinflunine at the dose, due to previous treatments, of 280 mg i.v. every 21 days until disease progression or limiting toxicity, with instrumental disease reassessment every 3 cycles, in 6 patients aged ≥18 years, with metastatic urothelial carcinoma of the upper or lower urinary tract, with performance status (PS) according to the Eastern Cooperative Oncology Group (ECOG) of 0-2, adequate hematologic function and progressive disease (PD) following first-line platinum-based chemotherapy and second-line ICI.

RESULTS

The median age of the 6 patients was 67.5 years (range 63-77) and median PS 1 (range, 0-2). Four patients (67%) had a disease partial response (PR). With a median follow-up of 4.5 months (range, 3-9), 3 patients are alive (50%). The median progression-free survival following vinflunine (PFS-3) was 4 months (range, 1-8), as compared to the PFS-2 (following ICI) of 4 months (range, 2-9) and the PFS-1 (after platinum-based chemotherapy) of 6 months (range, 2-13). The PRs were not associated with the length of PFS-2 of PFS-1, the histologic subtype, primary and metastatic site of the tumour. No grade 3-4 toxicity has been observed; grade 2 asthenia occurred in 3 patients (50%), grade 1 nausea and constipation were observed in one patient (17%), respectively.

CONCLUSION

Despite the low number of patients treated, the activity of vinflunine was substantial and suggests its role as chemotherapy line following previous chemotherapy and immunotherapy, deserving further retrospective or prospective investigations in this setting.

Neutrophil-to-lymphocyte ratio and lactate dehydrogenase as biomarkers for urothelial cancer treated with immunotherapy

PURPOSE

To identify patients with metastatic urothelial cancer (mUC) unlikely to benefit from immune-checkpoint inhibitors (ICIs).

METHODS/PATIENTS

We explored the predictive and prognostic values of baseline neutrophil-to-lymphocyte ratio (NLR), with cut-offs ≥ 3 and ≥ 5, and of a urothelial immune prognostic index (UIPI, based on increased NLR and LDH), on 146 patients.

RESULTS

NLR and UIPI significantly predicted progressive disease and progression-free survival with both cut-offs (p = 0.0069, p = 0.0034, p = 0.0160, p = 0.0063; p < 0.001, p = 0.021, p = 0.014, p = 0.026; for NLR-3, NLR-5, UIPI-3, UIPI-5, respectively) and overall survival when NLR cut-off was ≥ 5 (p = 0.03 and p = 0.024, for NLR-5 and UIPI-5, respectively).

CONCLUSIONS

NLR-5 deserves prospective validation to identify mUC patients with poor prognosis following ICIs.

Adherence to abiraterone or enzalutamide in elderly metastatic castration-resistant prostate cancer

PURPOSE

To evaluate adherence to abiraterone or enzalutamide for the treatment of metastatic castration-resistant prostate cancer (mCRPC).

METHODS

In an observational prospective cohort study, we monitored patients with mCRPC for their adherence to abiraterone or enzalutamide in the pre- or post-chemotherapy setting.

RESULTS

Fifty-eight patients with median age of 76 years (range 56-94), age-adjusted Charlson comorbidity score of 10 (range, 4-15), and geriatric G8 score of 14 (range, 6-17) were enrolled. Twenty-two (38%) patients were treated with abiraterone and 36 (62%) with enzalutamide, while forty-two (72%) were in the pre-chemotherapy setting. Forty-seven patients (81%) had a caregiver. Based on the pill counting, a non-adherence rate of 4.8% and 6.2% was observed for the whole period and the first 3 months, respectively, without a statistically significant difference between abiraterone and enzalutamide cohorts. A lower non-adherence rate (1.3%) was reported by patients during the whole period, mainly due to a misperception (77%) and forgetfulness (19%). Non-adherence rate to the fulfilling of the clinical diary was 38% for the whole period. Non-adherence in the whole period was related to the radiological response (p = 0.03) and geriatric G8 score (p = 0.005). By the receiver operating characteristic (ROC) curve based on the radiological response, non-adherence cut-off was 1.87% (p = 0.04). By this non-adherence cut-off, the G8 cut-off was 14.75 (p = 0.0003).

CONCLUSION

Non-adherence to abiraterone or enzalutamide for mCRPC may have an impact on disease response and be related to patients' frailty, suggesting their geriatric assessment and clinical interventions to monitor and increase their adherence.

The Promise of Digital Biopsy for the Prediction of Tumor Molecular Features and Clinical Outcomes Associated With Immunotherapy

Immunotherapy by immune checkpoint inhibitors has emerged as an effective treatment for a slight proportion of patients with aggressive tumors. Currently, some molecular determinants, such as the expression of the programmed cell death ligand-1 (PD-L1) or the tumor mutational burden (TMB) have been used in the clinical practice as predictive biomarkers, although they fail in consistency, applicability, or reliability to precisely identify the responding patients mainly because of their spatial intratumoral heterogeneity. Therefore, new biomarkers for early prediction of patient response to immunotherapy, that could integrate several approaches, are eagerly sought. Novel methods of quantitative image analysis (such as radiomics or pathomics) might offer a comprehensive approach providing spatial and temporal information from macroscopic imaging features potentially predictive of underlying molecular drivers, tumor-immune microenvironment, tumor-related prognosis, and clinical outcome (in terms of response or toxicity) following immunotherapy. Preliminary results from radiomics and pathomics analysis have demonstrated their ability to correlate image features with PD-L1 tumor expression, high CD3 cell infiltration or CD8 cell expression, or to produce an image signature concordant with gene expression. Furthermore, the predictive power of radiomics and pathomics can be improved by combining information from other modalities, such as blood values or molecular features, leading to increase the accuracy of these models. Thus, “digital biopsy,” which could be defined by non-invasive and non-consuming digital techniques provided by radiomics and pathomics, may have the potential to allow for personalized approach for cancer patients treated with immunotherapy.

Remote Home-Based Virtual Training of Functional Living Skills for Adolescents and Young Adults With Intellectual Disability: Feasibility and Preliminary Results

Background: Virtual Reality (VR) is acquiring increasing credibility as a tool for teaching independent living skills to people with Intellectual Disability (ID). Generalization of skills acquired during VR training into real environment seems to be feasible.

Objective: To assess feasibility and verify effectiveness of a remote home-based rehabilitation, focused on functional living skills, for adolescents and young adults with ID, by using virtual apps installed on tablets. In particular, to assess if this tool can be managed independently, if it is enjoyable and simple to be used, and if the acquired skills can be generalized to the real environment of everyday life.

Subjects and method: A single group, pre- and post-test research design was used. Sixteen participants with ID were included. A digital system was arranged, with a server managing communication between the database and the apps installed on tablets. In vivo tests were performed before and after the eleven sessions of VR training. Satisfaction questionnaires were also administered.

Results: Statistically significant improvements were found between the pre- and post-in vivo tests, as well as between the VR training sessions, in almost all the parameters taken into account, for each app. Final questionnaires showed a good satisfaction level for both the participants and their families.

Conclusion: The highly technological system was managed independently by participants with ID, who found it simple to be used, useful and even fun; generalization across settings was obtained. Results obtained require to be confirmed by future controlled studies, with larger samples.

Oral Metronomic Vinorelbine in Advanced Non-small Cell Lung Cancer Patients Unfit for Chemotherapy

AIM

To explore the feasibility and activity of oral metronomic vinorelbine patients with advanced NSCLC not eligible to standard chemotherapy because of old age (≥70 years), and/or poor Eastern Cooperative Oncology Group performance status (≥2), and/or extensive brain or bone disease, and/or active comorbidities (≥2) requiring for pharmacological treatment.

PATIENTS AND METHODS

In a prospective phase II not randomized study, patients with stage IV NSCLC unfit to chemotherapy were treated with oral metronomic vinorelbine at 30 mg fixed dose three times a week until disease progression.

RESULTS

Fifty patients were treated, 19 (38%) in the first-line setting. Five patients (11%) experienced a grade 3 toxicity; no grade 4 toxicity occurred. Overall disease control rate was 32%, 44% and 26% in first and subsequent lines, respectively (p=0.39). Median OS and PFS were 7.3 months (95% confidence interval [CI]=4.7-10.0) and 2.7 months (95%CI=2.0-3.4), respectively.

CONCLUSION

These data support the activity and safety of metronomic vinorelbine in a relevant proportion of patients usually excluded from any specific treatment.

Isolated rapid eye movement sleep without atonia in amyotrophic lateral sclerosis

OBJECTIVE

The aim of this study was to quantitatively analyze, with the most recent and advanced tools, the presence of periodic leg movements during sleep (PLMS) and/or rapid eye movement (REM) sleep without atonia (RSWA), in a group of patients with amyotrophic lateral sclerosis (ALS), and to assess their eventual correlation with the clinical severity of the disease.

METHODS

Twenty-nine ALS patients were enrolled (mean age 63.6 years) along with 28 age-matched "normal" controls (mean age 63.8 years). Functional impairment due to ALS was evaluated using the ALS-Functional Rating Scale-Revised (ALS-FRS) and the ALS severity scale (ALSSS). Full video polysomnographic night recordings were obtained, and PLMS were analyzed by considering their number/hour of sleep and periodicity index, the distribution of intermovement intervals, and the distribution during the night. The characteristics of the chin electromyogram (EMG) amplitude during REM sleep were analyzed by means of the automatic atonia index and the number of chin EMG activations (movements).

RESULTS

The ALS patients showed longer sleep latency than the controls, together with an increase in number of stage shifts, increased sleep stage 1, and decreased sleep stage 2. None of the leg PLMS parameters were different between the ALS patients and controls. The REM atonia index was significantly decreased in the ALS patients, and the number of chin movements/hour tended to increase. Both REM atonia index and number of chin movements/hour correlated significantly with the ALS-FRS; REM atonia was higher and chin movements were less in ALS patients with more preserved function (higher scores on the ALS-FRS).

CONCLUSION

Abnormal REM sleep atonia seemed to be a genuine effect of ALS pathology per se and correlated with the clinical severity of the disease. It is unclear if this might constitute the basis of a possible risk for the development of REM sleep behavior disorder or represent a form of isolated RSWA in ALS.

A Data-Driven Analysis of the Rules Defining Bilateral Leg Movements during Sleep

STUDY OBJECTIVES

The aim of this study was to describe and analyze the association between bilateral leg movements (LMs) during sleep in subjects with restless legs syndrome (RLS), in order to eventually support or challenge the current scoring rules defining bilateral LMs.

METHODS

Polysomnographic recordings of 100 untreated patients with RLS (57 women and 43 males, mean age 57 y) were included. In each recording, we selected as reference all LMs that occurred during sleep and that were separated from another ipsilateral LM by at least 10 sec of EMG inactivity. For each reference LM and an evaluation interval from 5 sec before the onset to 5 sec after the offset of the reference LM, we evaluated (1) the presence or absence of contralateral leg movement activity and (2) the distribution of the onset-to-onset and (3) the offset-to-onset differences between bilateral LMs.

RESULTS

We selected a mean of 368 (± 222 standard deviation [SD]) reference LMs per subject. For 42% (± 22%) of the reference LMs no contralateral leg movement activity was observed within the evaluation interval. In 55% (± 22%) exactly one and in 3% (± 2%) more than one contralateral LM was observed. A further evaluation of events where exactly one contralateral LM was observed showed that in most (1) the two LMs were overlapping (93% ± 9% SD) and (2) were classified as bilateral according to the World Association of Sleep Medicine and the International Restless Legs Syndrome Study Group (WASM/ IRLSSG) (96% ± 6% SD) and (3) the American Academy of Sleep Medicine scoring rules (99% ± 2% SD). Although there was a systematic and statistically significant difference in standard LM indices during sleep based on the two different definitions of bilateral LMs, the size of the difference was not clinically meaningful (maximum individual, absolute difference in LM indices ± 2.5). In addition, we found that the duration of LMs within bilateral LM pairs was longer compared to monolateral LMs and that the duration of the single LMs in bilateral LM pairs tended to correlate.

CONCLUSIONS

The results of this study indicate that the two current standard scoring rules for the definition of bilateral LMs during sleep provide largely corresponding classifications in subjects with RLS and, in a clinical context, can be considered to be equivalent.

An Evidence-based Analysis of the Association between Periodic Leg Movements during Sleep and Arousals in Restless Legs Syndrome

STUDY OBJECTIVES

To analyze statistically the association between periodic leg movements during sleep (PLMS) and arousals, in order to eventually support or challenge the current scoring rules and to further understand their reciprocal influence.

SETTING

Sleep research center.

PATIENTS

Twenty untreated consecutive patients with restless legs syndrome (RLS) (13 women and 7 males, mean age 60.9 y).

METHODS

In each recording, we selected all PLMS/arousal pairs that met the following inclusion criteria: (a) PLMS events that were separated from another PLMS event (preceding or following) by at least 10 s of EMG inactivity; (b) arousal events separated from another arousal event (preceding or following) by at least 10 s of stable EEG baseline activity; (c) PLMS/arousal pairs were then selected among events identified according to the previous two criteria, when PLMS and arousals were separated (offset-to-onset) by no more than 10 s, regardless of which was first.

MEASUREMENTS AND RESULTS

We selected a mean of 46.1 (SD 25.55) PLMS/arousal pairs per subject; in these pairs, average PLMS duration was 3.2 s (0.65) and average arousal duration was 6.5 s (0.92). Within these event pairs, the great majority (on average 98.4%, SD 3.88) was separated by less than 0.5 s (i.e., between the end of one event and the onset of the other, regardless of which was first). Arousal onsets preceded PLMS onset in 41.2% of pairs, while the opposite was true for the remaining 58.8% of pairs. A significant correlation between PLMS duration and arousal duration was also found (r = 0.447, P < 0.000001).

CONCLUSION

The results of this study support the current rule for the definition of the association between periodic leg movements during sleep (PLMS) and arousals. The tight time relationship between PLMS and arousals and their correlated durations seem to indicate that both events might be regulated by a complex mechanism, rather than being connected by a simple reciprocal cause/effect relationship.

Increased electroencephalographic high frequencies during the sleep onset period in patients with restless legs syndrome

STUDY OBJECTIVES

To analyze the electroencephalographic (EEG) spectral content in untreated patients with restless legs syndrome (RLS) during the sleep onset period (SOP) and during the quiet wakefulness preceding sleep, in order to test the hypothesis that a state of hyperarousal might be present during the SOP with RLS.

SETTING

Sleep Research Centre.

PATIENTS

Twenty-seven untreated consecutive patients with RLS (mean age = 53.6 y), 11 untreated consecutive patients with primary insomnia (mean age = 58.9 y), and 14 normal controls (mean age = 50.3 y).

METHODS

SOP was defined as the 10-min period centered with the occurrence of the first sleep spindle in the EEG, and then subdivided into SOP-1 (period of 5 min before the first spindle) and SOP-2 (period of 5 min following). Leg movements occurring during SOP were counted and used as a covariate in the statistical analysis. Also, one period of 1 min of artifact-free quiet wakefulness after lights off was identified. EEG spectral analysis was run during these periods using the C3/A2 or C4/A1 channel.

MEASUREMENTS AND RESULTS

Increased EEG alpha and beta bands and/or beta/delta ratio in RLS versus normal controls, during both wakefulness preceding sleep and SOP (both parts SOP-1 and SOP-2) were found, which were, however, smaller than the increases found in patients with insomnia.

CONCLUSION

The results of this study support the hypothesis of the presence of a state of hyperarousal in restless legs syndrome (RLS) during the sleep onset period. Treatment for RLS might need to take these findings into consideration.

CITATION

Ferri R, Cosentino FI, Manconi M, Rundo F, Bruni O, Zucconi M. Increased electroencephalographic high frequencies during the sleep onset period in patients with restless legs syndrome.

Comparison between an automatic and a visual scoring method of the chin muscle tone during rapid eye movement sleep

OBJECTIVE

To compare two different methods, one visual and the other automatic, for the quantification of rapid eye movement (REM) sleep without atonia (RSWA) in the diagnosis of REM sleep behavior disorder (RBD).

METHODS

Seventy-four RBD patients (mean age, 62.14±9.67 years) and 75 normal controls (mean age, 61.04±12.13 years) underwent one night video-polysomnographic recording. The chin electromyogram (EMG) during REM sleep was analyzed by means of a previously published visual method quantifying the percentage of 30s epochs scored as tonic (abnormal, > or =30%) and that of 2s mini-epochs containing phasic EMG events (abnormal, > or =15%). For the computer quantitative analysis we used the automatic scoring algorithm known as the atonia index (abnormal, <0.8). The percentage correct classification, sensitivity, specificity, and Cohen kappa were calculated.

RESULTS

The atonia index correctly classified 82.6% of subjects, similar to the percentage of correct classifications with individual components of the visual analysis (83.2% each for tonic and phasic), and the combined visual parameters (85.9%). The sensitivity and specificity of automatic analysis (84% and 81%) was similar to the combined visual analysis (89% and 83%). The correlation coefficient between the automatic atonia index and the percentage of visual tonic EMG was high (r = -0.886, P<0.00001), with moderately high correlation with the percentage of phasic EMG (r = -0.690, P<0.00001). The agreement between atonia index and the visual parameters (individual or combined) was approximately 85% with Cohen's kappa, ranging from 0.638 to 0.693.

CONCLUSION

Sensitivity, specificity, and correct classifications were high with both methods. Moreover, there was general agreement between methods, with Cohen's kappa values in the 'good' range. Given the considerable practical advantages of automatic quantification of REM atonia, automatic quantification may be a useful alternative to visual scoring methods in otherwise uncomplicated polysomnograms.

Stability of auditory discrimination and novelty processing in physiological aging

Complex higher-order cognitive functions and their possible changes with aging are mandatory objectives of cognitive neuroscience. Event-related potentials (ERPs) allow investigators to probe the earliest stages of information processing. N100, Mismatch negativity (MMN) and P3a are auditory ERP components that reflect automatic sensory discrimination. The aim of the present study was to determine if N100, MMN and P3a parameters are stable in healthy aged subjects, compared to those of normal young adults. Normal young adults and older participants were assessed using standardized cognitive functional instruments and their ERPs were obtained with an auditory stimulation at two different interstimulus intervals, during a passive paradigm. All individuals were within the normal range on cognitive tests. No significant differences were found for any ERP parameters obtained from the two age groups. This study shows that aging is characterized by a stability of the auditory discrimination and novelty processing. This is important for the arrangement of normative for the detection of subtle preclinical changes due to abnormal brain aging.

Night-to-night variability of automatic quantitative parameters of the chin EMG amplitude (Atonia Index) in REM sleep behavior disorder

STUDY OBJECTIVES

To analyze the night-to-night variability of REM sleep electromyographic (EMG) features of REM sleep behavior disorder (RBD) by using the automatic quantitative method known as atonia index (AI), and to evaluate the improvement in sensitivity and specificity of AI for the diagnosis of RBD when a second recording night is available.

SETTING

Sleep research center.

INTERVENTIONS

N/A.

METHODS

A group of 17 idiopathic RBD patients was recruited for whom 2 all-night polysomnographic (PSG) recordings were available. Thirty normal controls were also recruited and subgrouped into Young (< 45 years of age) or Aged (> 45 years). Chin EMG analysis was run on all recordings; night-to-night variability of both AI and number of chin EMG activations/h during REM sleep was additionally quantified as the absolute difference between the 2 nights standardized as the percentage of their mean.

MEASUREMENTS AND RESULTS

Night-to-night variability of AI was higher in RBD patients (19.7%) than in the 2 groups of controls (Young 1.8% and Aged 2.8%). The values of variability of chin EMG activations were much higher than those of AI, especially in the Aged controls. Sensitivity of AI ≤ 0.9 for RBD was always higher than 82% and reached 88.9% for the combined-night analysis; specificity was also high, with a value of 92.3% for the combined-value analysis.

CONCLUSION

The night-to-night variability of AI seems to be very low in normal controls and remains under 20% in RBD patients; that of the number of EMG activations is higher. However, even a single PSG recording provides high values of sensitivity and specificity when a threshold value of AI ≤ 0.9 is used to define abnormal chin EMG levels during REM sleep that increase only moderately when a second night recording is available.

The functional connectivity of different EEG bands moves towards small-world network organization during sleep

OBJECTIVE

To analyze the functional connectivity patterns of the different EEG bands during wakefulness and sleep (different sleep stages and cyclic alternating pattern (CAP) conditions), using concepts derived from Graph Theory.

METHODS

We evaluated spatial patterns of EEG band synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during wakefulness and the different sleep stages/CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s).

RESULTS

We found values of Cp and Lp compatible with a small-world network organization in all sleep stages and for all EEG bands. All bands below 15Hz showed an increase of these features during sleep (and during CAP-A phases in particular), compared to wakefulness.

CONCLUSIONS

The results of this study seem to confirm our initial hypothesis that during sleep there exists a clear trend for the functional connectivity of the EEG to move forward to an organization more similar to that of a small-world network, at least for the frequency bands lower than 15Hz.

SIGNIFICANCE

Sleep network "reconfiguration" might be one of the key mechanisms for the understanding of the "global" and "local" neural plasticity taking place during sleep.

Self organizing motor maps for color-mapped image re-indexing

Palette re-ordering is an effective approach for improving the compression of color-indexed images. If the spatial distribution of the indexes in the image is smooth, greater compression ratios may be obtained. As is already known, obtaining an optimal re-indexing scheme is not a trivial task. In this paper, we provide a novel algorithm for palette re-ordering problem making use of a motor map neural network. Experimental results show the real effectiveness of the proposed method both in terms of compression ratio and zero-order entropy of local differences. Also, its computational complexity is competitive with previous works in the field.

Directionality of EEG synchronization in Alzheimer's disease subjects

Is directionality of electroencephalographic (EEG) synchronization abnormal in amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD)? EEG data were recorded in 64 normal elderly (Nold), 69 amnesic MCI, and 73 mild AD subjects at rest condition (closed eyes). Direction of information flux within EEG functional coupling at electrode pairs was performed by directed transfer function (DTF) at delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). Parietal to frontal direction of the information flux within EEG functional coupling was stronger in Nold than in MCI and/or AD subjects, namely for alpha and beta rhythms. In contrast, the directional flow within inter-hemispheric EEG functional coupling did not discriminate among the three groups. These results suggest that directionality of parieto-to-frontal EEG synchronization is abnormal not only in AD but also in amnesic MCI.

Small-world network organization of functional connectivity of EEG slow-wave activity during sleep

OBJECTIVE

To analyze the functional connectivity patterns of the EEG slow-wave activity during the different sleep stages and Cyclic Alternating Pattern (CAP) conditions, using concepts derived from Graph Theory.

METHODS

We evaluated spatial patterns of EEG slow-wave synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during the different sleep stages and CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s).

RESULTS

Cp and Cp/Cp-s increased significantly from wakefulness to sleep while Lp and Lp/Lp-s did not show changes. Cp/Cp-s was higher for A1 phases, compared to B phases of CAP.

CONCLUSIONS

The network organization of the EEG slow-wave synchronization during sleep shows features characteristic of small-world networks (high Cp combined with low Lp); this type of organization is slightly but significantly more evident during the CAP A1 subtypes.

SIGNIFICANCE

Our results show feasibility of using graph theoretical measures to characterize the complexity of brain networks during sleep and might indicate sleep, and the A1 phases of CAP in particular, as a period during which slow-wave synchronization shows optimal network organization for information processing.

Heart rate and spectral EEG changes accompanying periodic and non-periodic leg movements during sleep

OBJECTIVE

To evaluate the changes in heart rate (HR) and EEG spectra accompanying periodic (PLM) and non-periodic leg movements (NPLM) during sleep in patients with restless legs syndrome (RLS).

METHODS

Sixteen patients with RLS underwent one polysomnographic night recording; leg movements (LMs) during sleep were detected and classified as PLM or NPLM; up to 10 PLM and NPLM were chosen from NREM and REM sleep, for each patient and for each type (mono- or bilateral). EEG spectral analysis and HR were evaluated for 20s preceding and 30s following the onset of each LM.

RESULTS

EEG activation preceded LMs, particularly in the delta band which increased before the other frequency bands, in NREM sleep but not in REM sleep for PLM, and in both stages for NPLM. A similar difference was seen between mono- and bilateral LMs.

CONCLUSIONS

Sleep EEG, HR, and leg motor activity seems to be modulated by a complex dynamically interacting system of cortical and subcortical mechanisms, which influence each other.

SIGNIFICANCE

Future studies on the clinical significance of leg motor events during sleep need to take into account events classifiable as "isolated" and to integrate the autonomic and EEG changes accompanying them.

Regional scalp EEG slow-wave synchronization during sleep cyclic alternating pattern A1 subtypes

The levels of EEG synchronization, in the 0.25-2.5 Hz band, during the A1 subtypes of the sleep "cyclic alternating pattern" (CAP) were measured in five healthy subjects by means of the synchronization likelihood (SL) algorithm. SL was measured for seven electrode pairs (F4-F3, C4-C3, P4-P3 for the analysis of interhemispheric SL and F4-C4, C4-P4, F3-C3, and C3-P3, for the analysis of intrahemispheric SL). During the A1 CAP subtypes, SL tended to be highest between pairs of electrodes situated over different hemispheres; in particular, SL obtained from F4-F3 was the highest, followed by that of P4-P3. These results indicate that the transient high level of synchronization in the slow-wave EEG range, during the sleep A1 CAP subtypes, is a phenomenon involving mostly the anterior parts of the brain and is probably based on interhemispheric interactions, possibly mediated by transcallosal connections.

EEG synchronisation during sleep-related epileptic seizures as a new tool to discriminate confusional arousals from paroxysmal arousals: preliminary findings

Confusional arousals, paroxysmal arousals (as part of the nocturnal frontal lobe epilepsy) and normal arousals and awakenings from NREM sleep are frequently a challenge for differential diagnosis. In this article we describe the course of synchronisation between different EEG channels during nocturnal seizures in 3 patients with sleep-related epileptic seizures and in 1 patient with sleep terrors. The functional interactions between the different EEG channels during the nocturnal seizures were analysed by means of the so-called synchronisation likelihood (SL). SL is a measure of the dynamical (linear and nonlinear) interdependencies between a time series (EEG channel) and one or more other time series. The main results of our study are the confirmation of a significant increase in EEG synchronisation during sleep-related seizures and the indication that clinically similar ictal motor patterns might be generated by different neurophysiological mechanisms, characterised by different patterns of synchronisation involving multiple or single frequency bands. This new approach might be useful to differentiate motor seizures, emerging from NREM sleep, from parasomnias (arousal disorders) when both ictal and interictal EEGs are uninformative.

Dynamics of the EEG slow-wave synchronization during sleep

OBJECTIVE

To study the dynamics of spatial synchronization of the slow-wave activity recorded from different scalp electrodes during sleep in healthy normal controls.

METHODS

We characterized the different levels of EEG synchronization during sleep (in the 0.25-2.5 Hz band) of five healthy subjects by means of the synchronization likelihood (SL) algorithm and analyzed its long-range temporal correlations by means of the detrended fluctuation analysis (DFA).

RESULTS

We found higher levels of interregional synchronization during 'cyclic alternating pattern' (CAP) sleep than during nonCAP with a small but significant difference between its A and B phases. SL during CAP showed fluctuations probably corresponding to the single EEG slow-wave elements. DFA showed the presence of two linear scaling regions in the double-logarithmic plot of the fluctuations of SL level as a function of time scale. This indicates the presence of a characteristic time scale in the underlying dynamics which was very stable among the different subjects (1.23-1.33 s). We also computed the DFA exponent of the two scaling regions; the first, with values approximately 1.5, corresponded to fluctuations with period 0.09-0.75 s and the second, with values approximately 1, corresponded to fluctuations with period 1.5-24.0 s. Only the first exponent showed different values during the different sleep stages.

CONCLUSIONS

All these results indicate a different role for each sleep stage and CAP condition in the EEG synchronization processes of sleep which show a complex time structure correlated with its neurophysiological mechanisms.

SIGNIFICANCE

Very slow oscillations in spatial EEG synchronization might play a critical role in the long-range temporal EEG correlations during sleep which might be the chain of events responsible for the maintenance and correct complex development of sleep structure during the night.

Fronto-parietal coupling of brain rhythms in mild cognitive impairment: a multicentric EEG study

Electroencephalographic (EEG) data were recorded in 69 normal elderly (Nold), 88 mild cognitive impairment (MCI), and 109 mild Alzheimer's disease (AD) subjects at rest condition, to test whether the fronto-parietal coupling of EEG rhythms is in line with the hypothesis that MCI can be considered as a pre-clinical stage of the disease at group level. Functional coupling was estimated by synchronization likelihood of Laplacian-transformed EEG data at electrode pairs, which accounts for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz). Compared to the Nold subjects, the AD patients presented a marked reduction of the synchronization likelihood (delta to gamma) at both fronto-parietal and inter-hemispherical (delta to beta 2) electrodes. As a main result, alpha 1 synchronization likelihood progressively decreased across Nold, MCI, and mild AD subjects at midline (Fz-Pz) and right (F4-P4) fronto-parietal electrodes. The same was true for the delta synchronization likelihood at right fronto-parietal electrodes (F4-P4). For these EEG bands, the synchronization likelihood correlated with global cognitive status as measured by the Mini Mental State Evaluation. The present results suggest that at group level, fronto-parietal coupling of the delta and alpha rhythms progressively becomes abnormal though MCI and mild AD. Future longitudinal research should evaluate whether the present EEG approach is able to predict the cognitive decline in individual MCI subjects.