Patterns of structure-function association in normal aging and in Alzheimer's disease: Screening for mild cognitive impairment and dementia with ML regression and classification models.

Background: The combined analysis of imaging and functional modalities is supposed to improve diagnostics of neurodegenerative diseases with advanced data science techniques. Objective: To get an insight into normal and accelerated brain aging by developing the machine learning models that predict individual performance in neuropsychological and cognitive tests from brain MRI. With these models we endeavor to look for patterns of brain structure-function association (SFA) indicative of mild cognitive impairment (MCI) and Alzheimer's dementia. Materials and methods: We explored the age-related variability of cognitive and neuropsychological test scores in normal and accelerated aging and constructed regression models predicting functional performance in cognitive tests from brain radiomics data. The models were trained on the three study cohorts from ADNI dataset-cognitively normal individuals, patients with MCI or dementia-separately. We also looked for significant correlations between cortical parcellation volumes and test scores in the cohorts to investigate neuroanatomical differences in relation to cognitive status. Finally, we worked out an approach for the classification of the examinees according to the pattern of structure-function associations into the cohorts of the cognitively normal elderly and patients with MCI or dementia. Results: In the healthy population, the global cognitive functioning slightly changes with age. It also remains stable across the disease course in the majority of cases. In healthy adults and patients with MCI or dementia, the trendlines of performance in digit symbol substitution test and trail making test converge at the approximated point of 100 years of age. According to the SFA pattern, we distinguish three cohorts: the cognitively normal elderly, patients with MCI, and dementia. The highest accuracy is achieved with the model trained to predict the mini-mental state examination score from voxel-based morphometry data. The application of the majority voting technique to models predicting results in cognitive tests improved the classification performance up to 91.95% true positive rate for healthy participants, 86.21%-for MCI and 80.18%-for dementia cases. Conclusion: The machine learning model, when trained on the cases of this of that group, describes a disease-specific SFA pattern. The pattern serves as a "stamp" of the disease reflected by the model.

A modality-specific somatosensory evoked potential test protocol for clinical evaluation: A feasibility study.

OBJECTIVE: We aimed to establish an objective neurophysiological test protocol that can be used to assess the somatosensory nervous system. METHODS: In order to assess most fiber subtypes of the somatosensory nervous system, repetitive stimuli of seven different modalities (touch, vibration, pinprick, cold, contact heat, laser, and warmth) were synchronized with the electroencephalogram (EEG) and applied on the cheek and dorsum of the hand and dorsum of the foot in 21 healthy subjects and three polyneuropathy (PNP) patients. Latencies and amplitudes of the modalities were assessed and compared. Patients received quantitative sensory testing (QST) as reference. RESULTS: We found reproducible evoked potentials recordings for touch, vibration, pinprick, contact-heat, and laser stimuli. The recording of warm-evoked potentials was challenging in young healthy subjects and not applicable in patients. Latencies were shortest within Aß-fiber-mediated signals and longest within C-fibers. The test protocol detected function loss within the Aß-fiber and Aδ-fiber-range in PNP patients. This function loss corresponded with QST findings. CONCLUSION: In this pilot study, we developed a neurophysiological test protocol that can specifically assess most of the somatosensory modalities. Despite technical challenges, initial patient data appear promising regarding a possible future clinical application. SIGNIFICANCE: Established and custom-made stimulators were combined to assess different fiber subtypes of the somatosensory nervous system using modality-specific evoked potentials.

Minimal hepatic encephalopathy - diagnosis and treatment.

Hepatic encephalopathy is a dysfunction of the central nervous system caused by chronic and acute liver disease. It presents a wide spectrum of symptoms from undetectable in a standard clinical examination to hepatic coma. The mildest form of hepatic encephalopathy is minimal hepatic encephalopathy. It significantly influences the quality of life, prognosis, and the incidence of complications. A wide range of psychometric and neurophysiological tests are used in the diagnostics. Treatment is based on the same principles as in overt encephalopathy. The most commonly used drugs include rifaximin, ornithine aspartate, and LOLA.

Guidance for clinical neurophysiology examination throughout the COVID-19 pandemic. Latin American chapter of the IFCN task force - COVID-19.

On 31st December 2019, China notified the World Health Organization of an outbreak of atypical pneumonia from patients at a local seafood market in Wuhan, Hubei, China, responsible for a new coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that caused COVID-19 disease, which spread rapidly around the world. WHO declared a state of pandemic (11th March, 2020), which has caused more than 1 million infected and more than 110,000 deaths; it was observed that up to 29% of those infected were health care personnel. The main route of transmission of SARS-CoV2 is through respiratory secretions and direct contact with contaminated surfaces and material. The pandemic induced an international saturation of health care services and a rupture in the supply chain of protective equipment for healthcare personnel, which poses a high occupational risk to all. Based on the different healthcare systems, human resources, infrastructure and medical emergencies that will warrant the conduct of clinical neurophysiology studies and the lack of a guide for the management of the situation, it was decided by an expert task force of the Latin American Chapter of the International Federation of Clinical Neurophysiology to carry out these guidelines for the protection of patient and healthcare professionals conducting clinical neurophysiological studies.

Diagnosis of covert hepatic encephalopathy: a multi-center study testing the utility of single versus combined testing.

Covert hepatic encephalopathy (CHE) affects cognition in a multidimensional fashion. Current guidelines recommend performing Psychometric Hepatic Encephalopathy Score (PHES) and a second test to diagnose CHE for multi-center trials. We aimed to determine if a two-test combination strategy improved CHE diagnosis agreement, and accuracy to predict overt hepatic encephalopathy (OHE), compared to single testing. Cirrhotic outpatients without baseline OHE performed PHES, Inhibitory Control Test (ICT), and Stroop EncephAlapp (StE) at three centers. Patients were followed for OHE development. Areas under the receiver operation characteristic curve (AUROC) were calculated. We included 437 patients (399 with follow-up data). CHE prevalence varied with testing strategy: PHES+ICT 18%, ICT + StE 25%, PHES+StE 29%, ICT 35%, PHES 37%, and StE 54%. Combination with best test agreement was PHES+StE (k = 0.34). Sixty patients (15%) developed OHE. Although CHE by StE showed the highest sensitivity to predict OHE, PHES and PHES+StE were more accurate at the expense of a lower sensitivity (55%, AUROC: 0.587; 36%, AUROC: 0.629; and 29%, AUROC: 0.623; respectively). PHES+ICT was the most specific (85%) but all strategies including ICT showed sensitivities in the 33-45% range. CHE diagnosis by PHES (HR = 1.79, p = 0.04), StE (HR = 1.69, p = 0.04), and PHES+StE (HR = 1.72, p = 0.04), were significant OHE predictors even when adjusted for prior OHE and MELD. Our results demonstrate that combined testing decreases CHE prevalence without improving the accuracy of OHE prediction. Testing with PHES or StE alone, or a PHES+StE combination, is equivalent to diagnose CHE and predict OHE development in a multi-center setting.

Critical flicker frequency test predicts overt hepatic encephalopathy and survival in patients with liver cirrhosis.

BACKGROUND: A critical flicker frequency (CFF) ≤39 Hz identifies cirrhotic patients with minimal hepatic encephalopathy (mHE) and predicts the risk of both overt hepatic encephalopathy (oHE) and mortality in patients with previous episodes of decompensation and/or oHE. AIMS: Herein, we evaluated the effectiveness of CFF in predicting the first episode of oHE and survival in cirrhotics who had never experienced an episode of oHE. METHODS: Our cohort study of 134 patients and 150 healthy subjects were examined. A CFF > 39 Hz was considered normal and pathological when ≤39 Hz. The median follow up was 36 months. RESULTS: At baseline, all controls had CFF > 39 Hz. Ninety-three patients had a CFF > 39 Hz and 41 had a CFF ≤ 39 Hz. The prevalence of CFF ≤ 39 Hz significantly increased with the progression of the Child-Pugh class (p = 0.003). Moreover, the risk of oHE was increased by CFF ≤ 39 (p < 0.001, by log-rank test) [HR = 7.57; CI(3.27-17.50); p < 0.0001, by Cox model] and ammonia [HR = 1.02 CI(1.01-1.03), p = 0.0009]. Both a CFF value ≤ 39 Hz and Child-Pugh class were independent predictors of mortality by Cox model [HR = 1.97; CI(1.01-3.95), p = 0.049; HR = 3.85 CI(1.68-8.83), p = 0.003]. CONCLUSIONS: CFF predicts the first episode of oHE in cirrhotics that had never experienced oHE, and predicts mortality risk. These findings suggest that cirrhotic patients should be routinely screened by CFF.

Serum level of taurine would be associated with the amelioration of minimal hepatic encephalopathy in cirrhotic patients.

AIM: A variety of treatment modalities including L-carnitine have been tried for cirrhotic patients with minimal hepatic encephalopathy (MHE), which improved MHE for some patients, but were not effective for the other patients. We aimed to identify pre-therapeutic independent factors to predict the amelioration of MHE after L-carnitine treatment. METHODS: We performed a prospective cohort study on a total of 64 consecutive outpatients of cirrhotic patients who underwent blood biochemical examinations and neuropsychiatric (NP) test at Kobe University Hospital. MHE patients diagnosed by the NP test were p.o. administrated L-carnitine for 3 months. The patients with and without MHE amelioration were compared, and the independent factors were statistically examined. Predictive scoring systems of the amelioration of MHE were established using multivariate logistic regression. RESULTS: The amelioration of MHE was found in 45.8% of MHE patients. Serum taurine before the treatment was the best predictive factor of the amelioration of MHE (P = 0.046). The predictive model using serum taurine discriminated well between patients with and without the amelioration of MHE (area under the receiver-operator curve, 0.748; 95% confidence interval, 0.531-0.901). The predictive scores of the amelioration of MHE enable the patient-specific probability to be easily looked up. CONCLUSION: Serum taurine before L-carnitine treatment was shown to be an independent factor associated with the amelioration of MHE 3 months after the treatment. The easy pre-therapeutic prediction of MHE amelioration after L-carnitine treatment would help in improving awareness of the selection of MHE patients with good response to L-carnitine, thus being beneficial from a financial perspective.

Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study.

Diffusion tensor imaging (DTI) allows in vivo structural brain mapping and detection of microstructural disruption of white matter (WM). One of the commonly used parameters for grading the anisotropic diffusivity in WM is fractional anisotropy (FA). FA value helps to quantify the directionality of the local tract bundle. Therefore, FA images are being used in voxelwise statistical analyses (VSA). The present study used Tract-Based Spatial Statistics (TBSS) of FA images across subjects, and computes the mean skeleton map to detect voxelwise knowledge of the tracts yielding to groupwise comparison. The skeleton image illustrates WM structure and shows any changes caused by brain damage. The microstructure of WM in thalamic stroke is investigated, and the VSA results of healthy control and thalamic stroke patients are reported. It has been shown that several skeleton regions were affected subject to the presence of thalamic stroke (FWE, p < 0.05). Furthermore the correlation of quantitative EEG (qEEG) scores and neurophysiological tests with the FA skeleton for the entire test group is also investigated. We compared measurements that are related to the same fibers across subjects, and discussed implications for VSA of WM in thalamic stroke cases, for the relationship between behavioral tests and FA skeletons, and for the correlation between the FA maps and qEEG scores.Results obtained through the regression analyses did not exceed the corrected statistical threshold values for multiple comparisons (uncorrected, p < 0.05). However, in the regression analysis of FA values and the theta band activity of EEG, cingulum bundle and corpus callosum were found to be related. These areas are parts of the Default Mode Network (DMN) where DMN is known to be involved in resting state EEG theta activity. The relation between the EEG alpha band power values and FA values of the skeleton was found to support the cortico-thalamocortical cycles for both subject groups. Further, the neurophysiological tests including Benton Face Recognition (BFR), Digit Span test (DST), Warrington Topographic Memory test (WTMT), California Verbal Learning test (CVLT) has been regressed with the FA skeleton maps for both subject groups. Our results corresponding to DST task were found to be similar with previously reported findings for working memory and episodic memory tasks. For the WTMT, FA values of the cingulum (right) that plays a role in memory process was found to be related with the behavioral responses. Splenium of corpus callosum was found to be correlated for both subject groups for the BFR.

Chronic Liver Disease Questionnaire would be a primary screening tool of neuropsychiatric test detecting minimal hepatic encephalopathy of cirrhotic patients.

AIM: The neuropsychiatric test (NP test) is a clinically available modality to confirm minimal hepatic encephalopathy (MHE), but it takes at least 30 min for outpatients to complete. An easier primary screening tool of the NP test would be helpful to predict MHE in routine testing on the public. METHODS: We performed a prospective cohort study on 59 cirrhotic outpatients at Kobe University Hospital. Laboratory measurements, the NP test and the Chronic Liver Disease Questionnaire (CLDQ) were performed. As an indicator of MHE, cases with and without two abnormal subsets or more in the NP test were compared, and the independent risk factors were statistically examined. Predictive scoring systems of the risk of MHE were established using multivariate logistic regression. RESULTS: CLDQ worry (WO) was the best predictive factor of MHE diagnosed by the NP test (P = 0.006). The predictive model using CLDQ WO discriminated well between patients with and without MHE (area under the curve, 0.714; 95% confidence interval, 0.582-0.824). The predictive scores of MHE enable the patient-specific probability to be easily looked up. CONCLUSION: CLDQ WO was shown to be an independent factor associated with the NP test to diagnose MHE in cirrhotic patients. The easy predictive scoring system of the risk of MHE using CLDQ WO could become a primary screening tool before performing the NP test in a social setting.