IMPORTANCEA carotid web (CW) is a shelf-like lesion along the posterior wall of the internal carotid artery bulb and an underrecognized cause of young stroke. Several studies suggest that patients with symptomatic CW have a high risk of recurrent stroke, but high-quality data are lacking.OBJECTIVE To assess the 2-year risk of recurrent stroke in patients with a symptomatic CW.

<b><i>Introduction:</i></b> Radiomics now has significant momentum in the era of precision medicine. Glioma is one of the pathologies that has been extensively evaluated by radiomics. However, this technique has not been incorporated into clinical practice. In this systematic review, we selected and reviewed the published studies about glioma grading by radiomics to evaluate this technique’s feasibility and its challenges. <b><i>Material and Methods:</i></b> Using seven different search strings, we considered all published English manuscripts from 2015 to September 2020 in PubMed, Embase, and Scopus databases. After implementing the exclusion and inclusion criteria, the final papers were selected for the methodological quality assessment based on our in-house Modified Radiomics Standard Scoring (RQS) containing 43 items (minimum score of 0, maximum score of 44). Finally, we offered our opinion about the challenges and weaknesses of the selected papers. <b><i>Results:</i></b> By our search, 1,177 manuscripts were found (485 in PubMed, 343 in Embase, and 349 in Scopus). After the implementation of inclusion and exclusion criteria, 18 papers remained for the final analysis by RQS. The total RQS score ranged from 26 (59% of maximum possible score) to 43 (97% of maximum possible score) with a mean of 33.5 (76% of maximum possible score). <b><i>Conclusion:</i></b> The current studies are promising but very heterogeneous in design with high variation in the radiomics software, the number of extracted features, the number of selected features, and machine learning models. All of the studies were retrospective in design; many are based on small datasets and/or suffer from class imbalance and lack of external validation data­sets.

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As human life expectancy increases, there is an increased prevalence of neurodegenerative disorders and dementia. There are many ongoing research trials for early diagnosis and management of dementia, and neuroimaging is a critical part of such studies. However, conventional neuroimaging often fails to provide enough diagnostic findings in patients with neurodegenerative disorders. In this context, different MRI sequences are currently under investigation to facilitate the accurate diagnosis of such disorders. Susceptibility‐weighted imaging (SWI) is an innovative MRI technique that utilizes “magnitude” and “phase” images to produce an image contrast that is sensitive for the detection of susceptibility differences of the tissues. As many neurodegenerative disorders are associated with accelerated iron deposition and/or microhemorrhages in different parts of the brain, SWI can be applied to detect these diagnostic clues. For instance, in cerebral amyloid angiopathy, SWI can demonstrate cortical microhemorrhages, which are predominantly in the frontal and parietal regions. Or in Parkinson disease, abnormal swallow‐tail sign on high‐resolution SWI is highly diagnostic. Also, SWI is a useful sequence to detect the low signal intensity of precentral cortices in patients with amyotrophic lateral sclerosis. Being familiar with SWI findings in neurodegenerative disorders is critical for an accurate diagnosis. In this paper, the authors review the technical parameters of SWI, physiologic, and pathologic iron deposition in the brain, and the role of SWI in the evaluation of neurodegenerative disorders in daily practice.

Diffusion-weighted imaging (DWI) is a well-established MRI sequence for diagnosing early stroke and provides therapeutic implications. However, DWI yields pertinent information in various other brain pathologies and helps establish a specific diagnosis and management of other central nervous system disorders. Some of these conditions can present with acute changes in neurological status and mimic stroke. This review will focus briefly on diffusion imaging techniques, followed by a more comprehensive description of the utility of DWI in common neurological entities beyond stroke.

Background:Computed tomography-guided percutaneous core needle biopsy (PCNB) is a diagnostic technique for initial assessment of mediastinal mass lesions. This study was conducted to evaluate its diagnostic yield and its complication rate.Materials and Methods:We reviewed the records of CT-guided PCNB in 110 patients with mediastinal mass lesions performed in Kashani and Alzahra Hospitals, Isfahan, from 2006 to 2012. Gender, age at biopsy, size, and anatomic location of the lesion, number of passes, site of approach, complications, and final diagnosis were extracted.Results:Our series encompasses 52 (47.2%) females and 58 (52/7%) males with mean age of 41 ± 8 years. The most common site of involvement was the anterior mediastinum (91.8% of cases). An average of 3/5 passes per patient has been taken for tissue sampling. Parasternal site was the most frequent approach taken for PCNB (in 78.1% of cases). Diagnostic tissue was obtained in 99 (90%) biopsies while, in 11 (10%) cases, specimen materials were inadequate. Lymphoma (49.5%) and bronchogenic carcinoma (33.3%) were the most frequent lesions in our series. The overall complication rate was 17.2% from which 10.9% was pneumothorax, 5.4% was hemoptysis, and 0.9% was vasovagal reflex.Conclusion:CT-guided PCNB is a safe and reliable procedure that can provide a precise diagnosis for patients with both benign and malignant mediastinal masses, and it is considered the preferred first diagnostic procedure use for this purpose.

The development of cognitive dysfunction and dementia is a complex, multifactorial process. One of the contributors to various types of cognitive dysfunction is carotid atherosclerosis which can frequently be seen in asymptomatic individuals. There are a number of different manifestations of asymptomatic carotid atherosclerosis including arterial stiffness, carotid intima-media thickening, flow-limiting stenosis, and complex, atherosclerotic plaque. Each of these forms of atherosclerosis may contribute to cerebral parenchymal damage, contributing to cognitive dysfunction. In this review article, we will discuss each of these forms of carotid atherosclerosis, present the potential mechanistic underpinnings behind an association, and then review the scientific evidence supporting potential associations to cognitive dysfunction and dementia.

This study aimed to develop a predictive model to predict patients' mortality with coronavirus disease 2019 from the basic medical data on the first day of admission. MethodsThe medical data including the demographic, clinical, and laboratory features on the first day of admission of clinically diagnosed COVID-19 patients were documented. The outcome of patients was also recorded as discharge or death. Feature selection models were then implemented and different machine learning models were developed on top of the selected features to predict discharge or death. The trained models were then tested on the test dataset. ResultsA total of 520 patients were included in the training dataset. The feature selection demonstrated 22 features as the most powerful predictive features. Among different machine learning models, the naive Bayes demonstrated the best performance with an area under the curve of 0.85. The ensemble model of the naive Bayes and neural network combination had slightly better performance with an area under the curve of 0.86. The models had relatively the same performance on the test dataset. ConclusionDeveloping a predictive machine learning model based on the basic medical features on the first day of admission in COVID-19 infection is feasible with acceptable performance.