Transcranial focused ultrasound is an emerging technique for non-invasive neurostimulation. Compared to magnetic or electric non-invasive brain stimulation, this technique has a higher spatial ...resolution and can reach deep structures. In addition, both animal and human studies suggest that, potentially, different sites of the central and peripheral nervous system can be targeted by this technique. Depending on stimulation parameters, transcranial focused ultrasound is able to determine a wide spectrum of effects, ranging from suppression or facilitation of neural activity to tissue ablation. The aim is to review the state of the art of the human transcranial focused ultrasound neuromodulation literature, including the theoretical principles which underlie the explanation of the bioeffects on neural tissues, and showing the stimulation techniques and parameters used and their outcomes in terms of clinical, neurophysiological or neuroimaging results and safety.
The aim of this review is to summarize that most relevant technologies used to evaluate gait features and the associated algorithms that have shown promise to aid diagnosis and symptom monitoring in ...Parkinson's disease (PD) patients. We searched PubMed for studies published between 1 January 2005, and 30 August 2019 on gait analysis in PD. We selected studies that have either used technologies to distinguish PD patients from healthy subjects or stratified PD patients according to motor status or disease stages. Only those studies that reported at least 80% sensitivity and specificity were included. Gait analysis algorithms used for diagnosis showed a balanced accuracy range of 83.5-100%, sensitivity of 83.3-100% and specificity of 82-100%. For motor status discrimination the gait analysis algorithms showed a balanced accuracy range of 90.8-100%, sensitivity of 92.5-100% and specificity of 88-100%. Despite a large number of studies on the topic of objective gait analysis in PD, only a limited number of studies reported algorithms that were accurate enough deemed to be useful for diagnosis and symptoms monitoring. In addition, none of the reported algorithms and technologies has been validated in large scale, independent studies.
Gait features differ between Parkinson's disease (PD) and healthy subjects (HS). Kinematic alterations of gait include reduced gait speed, swing time, and stride length between PD patients and HS. ...Stride time and swing time variability are increased in PD patients with respect to HS. Additionally, dynamic parameters of asymmetry of gait are significantly different among the two groups. The aim of the present study is to evaluate which kind of gait analysis (dynamic or kinematic) is more informative to discriminate PD and HS gait features.
In the present study, we analyzed gait dynamic and kinematic features of 108 PD patients and 88 HS from four cohorts of two datasets.
Kinematic features showed statistically significant differences among PD patients and HS for gait speed and time Up and Go test and for selected kinematic dispersion indices (standard deviation and interquartile range of swing, stance, and double support time). Dynamic features did not show any statistically significant difference between PD patients and HS.
Despite kinematics features like acceleration being directly proportional to dynamic features like ground reaction force, the results of this study showed the so-called force/rhythm dichotomy since kinematic features were more informative than dynamic ones.
Quantitative indoor monitoring, in a low-invasive and accurate way, is still an unmet need in clinical practice. Indoor environments are more challenging than outdoor environments, and are where ...patients experience difficulty in performing activities of daily living (ADLs). In line with the recent trends of telemedicine, there is an ongoing positive impulse in moving medical assistance and management from hospitals to home settings. Different technologies have been proposed for indoor monitoring over the past decades, with different degrees of invasiveness, complexity, and capabilities in full-body monitoring. The major classes of devices proposed are inertial-based sensors (IMU), vision-based devices, and geomagnetic and radiofrequency (RF) based sensors. In recent years, among all available technologies, there has been an increasing interest in using RF-based technology because it can provide a more accurate and reliable method of tracking patients’ movements compared to other methods, such as camera-based systems or wearable sensors. Indeed, RF technology compared to the other two techniques has higher compliance, low energy consumption, does not need to be worn, is less susceptible to noise, is not affected by lighting or other physical obstacles, has a high temporal resolution without a limited angle of view, and fewer privacy issues. The aim of the present narrative review was to describe the potential applications of RF-based indoor monitoring techniques and highlight their differences compared to other monitoring technologies.
See Vidailhet et al. (doi:10.1093/brain/awx140) for a scientific commentary on this article. Misdiagnosis among tremor syndromes is common, and can impact on both clinical care and research. To date ...no validated neurophysiological technique is available that has proven to have good classification performance, and the diagnostic gold standard is the clinical evaluation made by a movement disorders expert. We present a robust new neurophysiological measure, the tremor stability index, which can discriminate Parkinson’s disease tremor and essential tremor with high diagnostic accuracy. The tremor stability index is derived from kinematic measurements of tremulous activity. It was assessed in a test cohort comprising 16 rest tremor recordings in tremor-dominant Parkinson’s disease and 20 postural tremor recordings in essential tremor, and validated on a second, independent cohort comprising a further 55 tremulous Parkinson’s disease and essential tremor recordings. Clinical diagnosis was used as gold standard. One hundred seconds of tremor recording were selected for analysis in each patient. The classification accuracy of the new index was assessed by binary logistic regression and by receiver operating characteristic analysis. The diagnostic performance was examined by calculating the sensitivity, specificity, accuracy, likelihood ratio positive, likelihood ratio negative, area under the receiver operating characteristic curve, and by cross-validation. Tremor stability index with a cut-off of 1.05 gave good classification performance for Parkinson’s disease tremor and essential tremor, in both test and validation datasets. Tremor stability index maximum sensitivity, specificity and accuracy were 95%, 95% and 92%, respectively. Receiver operating characteristic analysis showed an area under the curve of 0.916 (95% confidence interval 0.797–1.000) for the test dataset and a value of 0.855 (95% confidence interval 0.754–0.957) for the validation dataset. Classification accuracy proved independent of recording device and posture. The tremor stability index can aid in the differential diagnosis of the two most common tremor types. It has a high diagnostic accuracy, can be derived from short, cheap, widely available and non-invasive tremor recordings, and is independent of operator or postural context in its interpretation.
Stroke, a complex and heterogeneous disease, is a leading cause of morbidity and mortality worldwide. The timely therapeutic intervention significantly impacts patient outcomes, but early stroke ...diagnosis is challenging due to the lack of specific diagnostic biomarkers. This review critically examines the literature for potential biomarkers that may aid in early diagnosis, differentiation between ischemic and hemorrhagic stroke, and prediction of hemorrhagic transformation in ischemic stroke. After a thorough analysis, four promising biomarkers were identified: Antithrombin III (ATIII), fibrinogen, and ischemia-modified albumin (IMA) for diagnostic purposes; glial fibrillary acidic protein (GFAP), micro RNA 124-3p, and a panel of 11 metabolites for distinguishing between ischemic and hemorrhagic stroke; and matrix metalloproteinase-9 (MMP-9), s100b, and interleukin 33 for predicting hemorrhagic transformation. We propose a biomarker panel integrating these markers, each reflecting different pathophysiological stages of stroke, that could significantly improve stroke patients' early detection and treatment. Despite promising results, further research and validation are needed to demonstrate the clinical utility of this proposed panel for routine stroke treatment.
Reperfusion therapy administration timing in acute ischaemic stroke is the main determinant of patients' mortality and long-term disability. Indeed, the first hour from the stroke onset is defined ...the "golden hour", in which the treatment has the highest efficacy and lowest side effects. Delayed ambulance transport, inappropriate triage and difficulty in accessing CT scans lead to delayed onset to treatment time (OTT) in clinical practice. To date brain CT scan is needed to rule out intracranial haemorrhage, which is a major contraindication to thrombolytic therapy. The availability, dimension and portability make CT suitable mainly for intrahospital use, determining further delays in the therapies administration. This review aims at evaluating portable neurophysiology technologies developed with the scope of speeding up the diagnostic phase of acute stroke and, therefore, the initiation of intravenous thrombolysis. Medline databases were explored for studies concerning near infrared spectroscopy (NIRS), bioelectrical impedance spectroscopy (BIS) and Microwave imaging (MWI) as methods for stroke diagnosis. A total of 1368 articles were found, and 12 of these fit with our criteria and were included in the review. For each technology, the following parameters were evaluated: diagnostic accuracy, ability to differentiate ischaemic and haemorrhagic stroke, diagnosis time from stroke onset, portability and technology readiness level (TRL). All the described methods seem to be able to identify acute stroke even though the number of studies is very limited. Low cost and portability make them potentially usable during ambulance transport, possibly leading to a reduction of stroke OTT along with the related huge benefits in terms of patients outcome and health care costs. In addition, unlike standard imaging techniques, neurophysiological techniques could allow continuous monitoring of patients for timely intrahospital stroke diagnosis.
KEY MESSAGES
First hour from the stroke onset is defined the "golden hour", in which the treatment has the highest efficacy and lowest side effects.
The delay for stroke onset to brain imaging time is one of the major reasons why only a minority of patients with acute ischaemic stroke are eligible to reperfusion therapies.
Neurophysiology techniques (NIRS, BIS and MWI) could have a potential high impact in reducing the time to treatment in stroke patients.
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