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Machine Learning-Enabled Determination of Diffuseness of Brain Arteriovenous Malformations from Magnetic Resonance Angiography
AbstractThe diffuseness of brain arteriovenous malformations (bAVMs) is a significant factor in surgical outcome evaluation and hemorrhagic risk prediction. However, there are still predicaments in identifying diffuseness, such as the judging variety resulting from different experience and difficulties in quantification. The purpose of this study was to develop a machine learning (ML) model to automatically identify the diffuseness of bAVM niduses using three-dimensional (3D) time-of-flight magnetic resonance angiography (TOF-MRA) images. A total of 635 patients with bAVMs who underwent TOF-MRA imaging were enrolled. Three...
Source: Translational Stroke Research - August 12, 2021 Category: Neurology Source Type: research

Behavioral Assessment of Sensory, Motor, Emotion, and Cognition in Rodent Models of Intracerebral Hemorrhage
Intracerebral hemorrhage (ICH) is the second most common type of stroke and has one of the highest fatality rates of any disease. There are many clinical signs and symptoms after ICH due to brain cell injury and network disruption resulted from the rupture of a tiny artery and activation of inflammatory cells, such as motor dysfunction, sensory impairment, cognitive impairment, and emotional disturbance, etc. Thus, researchers have established many tests to evaluate behavioral changes in rodent ICH models, in order to achieve a better understanding and thus improvements in the prognosis for the clinical treatment of stroke...
Source: Frontiers in Neurology - June 17, 2021 Category: Neurology Source Type: research

Predictors of Function, Activity, and Participation of Stroke Patients Undergoing Intensive Rehabilitation: A Multicenter Prospective Observational Study Protocol
Discussion: By identifying data-driven prognosis prediction models in stroke rehabilitation, this study might contribute to the development of patient-oriented therapy and to optimize rehabilitation outcomes.Clinical Trial Registration:ClinicalTrials.gov, NCT03968627. https://www.clinicaltrials.gov/ct2/show/NCT03968627?term=Cecchi&cond=Stroke&draw=2&rank=2.
Source: Frontiers in Neurology - April 8, 2021 Category: Neurology Source Type: research

One-Third of COVID-19 Survivors May Develop a Neuropsychiatric Disorder Within Months of Infection
One-third of individuals diagnosed with COVID-19 developed a psychiatric or neurological problem within six months of their diagnosis, according to astudy published Tuesday inThe Lancet Psychiatry. The prevalence of a post-COVID neurologic or psychiatric diagnosis was even greater among individuals with severe illness who had required hospitalization.“Given the size of the pandemic and the chronicity of many of the diagnoses and their consequences (for example, dementia, stroke, and intracranial hemorrhage), substantial effects on health and social care systems are likely to occur,” wrote Maxime Taque, Ph.D., of the Un...
Source: Psychiatr News - April 7, 2021 Category: Psychiatry Tags: anxiety COVID-19 electronic health records hospitalizations mood disorders neuropsychiatric disorders The Lancet Psychiatry Source Type: research

A journey through clinic and research
I started to study Medicine at the University of Genoa, Italy more than 20 years ago and I now realize that I was quite far from understanding what ‘Medicine’ really means. After weeks and weeks spent on books during the first year, I understood that becoming a MD not only requires the willingness to help people with health problems, but also strong motivation and dedication to learn a huge amount of notions. In Italy, as it is the case for several other countries, the University courses last 6 years, during which the MD student is fully engaged by individual study, lessons and seminars, exercises, and internships. Wit...
Source: European Heart Journal - March 29, 2021 Category: Cardiology Source Type: research

Strategies adopted to manage physical and psychosocial challenges after returning home among people with stroke: A qualitative study
This study was conducted to explore how stroke survivors manage their life after returning home from the hospital. This was a qualitative study with individual, semi-structured interviews. We recruited a purposive sample of adults who had a first or recurrent ischemic or hemorrhagic stroke and currently lived at home. Participants were asked about their post-stroke experiences, challenges encountered, and strategies adopted for managing post-stroke conditions. Data were transcribed verbatim and analyzed using thematic analysis. A total of 30 stroke survivors (mean age = 61.97 years, SD = 10.20) were interviewed. ...
Source: Medicine - March 12, 2021 Category: Internal Medicine Tags: Research Article: Quality Improvement Study Source Type: research

Ifenprodil Improves Long-Term Neurologic Deficits Through Antagonizing Glutamate-Induced Excitotoxicity After Experimental Subarachnoid Hemorrhage
AbstractExcessive glutamate leading to excitotoxicity worsens brain damage after SAH and contributes to long-term neurological deficits. The drug ifenprodil is a non-competitive antagonist of GluN1-GluN2B N-methyl-d-aspartate (NMDA) receptor, which mediates excitotoxic damage in vitro and in vivo. Here, we show that cerebrospinal fluid (CSF) glutamate level within 48  h was significantly elevated in aSAH patients who later developed poor outcome. In rat SAH model, ifenprodil can improve long-term sensorimotor and spatial learning deficits. Ifenprodil attenuates experimental SAH-induced neuronal death of basal cortex and h...
Source: Translational Stroke Research - March 12, 2021 Category: Neurology Source Type: research

Preliminary development of a prediction model for daily stroke occurrences based on meteorological and calendar information using deep learning framework (Prediction One; Sony Network Communications Inc., Japan).
Conclusion: Our preliminary results suggested a probability of the DL-based prediction models for stroke occurrence only by meteorological and calendar factors. In the future, by synchronizing a variety of medical information among the electronic medical records and personal smartphones as well as integrating the physical activities or meteorological conditions in real time, the prediction of stroke occurrence could be performed with high accuracy, to save medical resources, to have patients care for themselves, and to perform efficient medicine. PMID: 33598347 [PubMed]
Source: Surgical Neurology International - February 21, 2021 Category: Neurosurgery Tags: Surg Neurol Int Source Type: research

C-Reactive Protein Triggers Cell Death in Ischemic Cells
C-reactive protein (CRP) is the best-known acute phase protein. In humans, almost every type of inflammation is accompanied by an increase of CRP concentration. Until recently, the only known physiological function of CRP was the marking of cells to initiate their phagocytosis. This triggers the classical complement pathway up to C4, which helps to eliminate pathogens and dead cells. However, vital cells with reduced energy supply are also marked, which is useful in the case of a classical external wound because an important substrate for pathogens is disposed of, but is counterproductive at internal wounds (e.g., heart at...
Source: Frontiers in Immunology - February 10, 2021 Category: Allergy & Immunology Source Type: research

Imaging-Based Outcome Prediction of Acute Intracerebral Hemorrhage
AbstractWe hypothesized that imaging-only-based machine learning algorithms can analyze non-enhanced CT scans of patients with acute intracerebral hemorrhage (ICH). This retrospective multicenter cohort study analyzed 520 non-enhanced CT scans and clinical data of patients with acute spontaneous ICH. Clinical outcome at hospital discharge was dichotomized into good outcome and poor outcome using different modified Rankin Scale (mRS) cut-off values. Predictive performance of a random forest machine learning approach based on filter- and texture-derived high-end image features was evaluated for differentiation of functional ...
Source: Translational Stroke Research - February 6, 2021 Category: Neurology Source Type: research

Deep Learning-Based Screening Test for Cognitive Impairment Using Basic Blood Test Data for Health Examination
Conclusions: The DNN model could predict cognitive function accurately. The predicted MMSE scores were significantly lower than the ground truth scores in the Healthy and Health examination groups, while there was no significant difference in the Patient group. We suggest that the difference between the predicted and ground truth MMSE scores was caused by changes in atherosclerosis with aging, and that applying the DNN model to younger subjects may predict future cognitive impairment after the onset of atherosclerosis.
Source: Frontiers in Neurology - December 14, 2020 Category: Neurology Source Type: research

Neurologic Complications in Patients With Cancer
PURPOSE OF REVIEW Neurologic complications in patients with cancer can significantly impact morbidity and mortality. Although these complications can be seen in patients without cancer as well, the purpose of this review is to highlight how the presentation, etiology, and management of delirium, seizures, cerebrovascular disease, and central nervous system infections may be different in patients with cancer. RECENT FINDINGS Some of the newer anticancer therapies are associated with neurologic complications. Delirium and seizures have been described in patients receiving chimeric antigen receptor (CAR) T-cell the...
Source: CONTINUUM: Lifelong Learning in Neurology - December 1, 2020 Category: Neurology Tags: REVIEW ARTICLES Source Type: research

Machine learning boosts chest CT's performance
Machine learning-based CT texture analysis software improves reader accuracy...Read more on AuntMinnie.comRelated Reading: AI can quantify hematoma in hemorrhagic stroke patients Large study confirms value of CT lung cancer screening CT radiation doses for COVID-19 patients vary widely CT lung screening scans also work for bone density CT lung screening program falls short in China
Source: AuntMinnie.com Headlines - November 18, 2020 Category: Radiology Source Type: news

Deep Learning-Based Approach for the Diagnosis of Moyamoya Disease
Moyamoya disease is a unique cerebrovascular disorder that is characterized by chronic progressive bilateral stenosis of the terminal portion of the internal carotid arteries (ICAs), and it is associated with the formation of an abnormal vascular network at the base of the brain.1,2 For the diagnosis of the moyamoya disease, digital subtraction angiography (DSA), which helps evaluate collateral circulation from the view point of the hemorrhagic risk, is the gold standard.3,4 On the contrary, magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) can be used as alternatives to conventional angiography bec...
Source: Journal of Stroke and Cerebrovascular Diseases - September 25, 2020 Category: Neurology Authors: Yukinori Akiyama, Takeshi Mikami, Nobuhiro Mikuni Source Type: research

An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage
Publication date: Available online 17 September 2020Source: Neuroimaging Clinics of North AmericaAuthor(s): Rajiv Gupta, Sanjith Prahas Krishnam, Pamela W. Schaefer, Michael H. Lev, R. Gilberto Gonzalez
Source: Neuroimaging Clinics of North America - September 18, 2020 Category: Radiology Source Type: research

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