hypertension or pulsatile tinnitus.

In this cohort, most patients with idiopathic intracranial hypertension had extrinsic stenosis, and most patients with pulsatile tinnitus had intrinsic stenosis. Awareness and reporting of these subtypes may reduce the underrecognition of potential contributory stenoses in a given patient’s idiopathic intracranial hypertension or pulsatile tinnitus.

Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on the basis of machine learning algorithms for patients with acute ischemic stroke and to compare the performance between multiple models and the Stroke Prognostication Using Age and National Institutes of Health Stroke Scale (SPAN-100) index model.

A retrospective multicenter cohort of 1431 patients with acute ischemic stroke was subdivided into recanalized and nonrecanalized patients. Extreme Gradient Boosting machine learning models were built to predict the mRS score at 90 days using clinical, imaging, combined, and best-performing features. Feature selection was performed using the relative weight and frequency of occurrence in the models. The model with the best performance was compared with the SPAN-100 index model using area under the receiver operating curve analysis.

In 3 Machine learning models with the best-performing features, especially advanced CTP data, had superior performance of the recovery outcome prediction for patients with stroke at admission in comparison with SPAN-100.

Cone-beam CT is being increasingly used in head and neck imaging. We compared cone-beam CT with multidetector CT to assess postoperative implant placement and delineate finer anatomic structures, image quality, and radiation dose used.

This retrospective multicenter study included 51 patients with cochlear implants and postoperative imaging via temporal bone cone-beam CT (

=

32 ears) or multidetector CT (

=

19 ears) between 2012 and 2017. read more We evaluated the visualization quality of single electrode contacts, the scalar position of the electrodes, cochlear walls, mastoid facial canal, metallic artifacts (using a 4-level visual score), and the ability to measure the insertion angle of the electrodes. The signal-to-noise ratio and radiation dose were also evaluated.

Cone-beam CT was more sensitive for visualizing the scalar position of the electrodes (

= .046), cochlear outer wall (

= .001), single electrode contacts (

< .001), and osseous spiral lamina (

= .004) and had fewer metallic artifacts (

< .001). However, there were no significant differences between both methods in visualization of the modiolus (

= .37), cochlear inner wall (

> .99), and mastoid facial canal wall (

= .07) and the ability to measure the insertion angle of the electrodes (

> .99). The conebeam CT group had significantly lower dose-length product (

< .001), but multidetector CT showed a higher signal-to-noise ratio in both bone and air (

= .22 and

= .001).

Cone-beam CT in patients with cochlear implants provides images with higher spatial resolution and fewer metallic artifacts than multidetector CT at a relatively lower radiation dose.

Cone-beam CT in patients with cochlear implants provides images with higher spatial resolution and fewer metallic artifacts than multidetector CT at a relatively lower radiation dose.

Studies consistently report lower ADC values in

(

) wild-type gliomas than in

mutant tumors, but their methods and thresholds vary. This research aimed to compare volumetric and regional ADC measurement techniques for glioma genotyping, with a focus on

status prediction.

Treatment-naïve World Health Organization grade II and III gliomas were analyzed by 3 neuroradiologist readers blinded to tissue results. ADC minimum and mean ROIs were defined in tumor and in normal-appearing white matter to calculate normalized values. T2-weighted tumor VOIs were registered to ADC maps with histogram parameters (mean, 2nd and 5th percentiles) extracted. Nonparametric testing (eta

and ANOVA) was performed to identify associations between ADC metrics and glioma genotypes. Logistic regression was used to probe the ability of VOI and ROI metrics to predict

status.

The study included 283 patients with 79

wild-type and 204

mutant gliomas. Across the study population,

status was most accurately predicted by ROI mean normalized ADC and VOI mean normalized ADC, with areas under the curve of 0.83 and 0.82, respectively

The results for ROI-based genotyping of nonenhancing and solid-patchy enhancing gliomas were comparable with volumetric parameters (area under the curve = 0.81-0.84). In rim-enhancing, centrally necrotic tumors (

= 23), only volumetric measurements were predictive (0.90).

Regional normalized mean ADC measurements are noninferior to volumetric segmentation for defining solid glioma

status. Partially necrotic, rim-enhancing tumors are unsuitable for ROI assessment and may benefit from volumetric ADC quantification.

Regional normalized mean ADC measurements are noninferior to volumetric segmentation for defining solid glioma IDH status. Partially necrotic, rim-enhancing tumors are unsuitable for ROI assessment and may benefit from volumetric ADC quantification.

Patients infected with the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) can develop a spectrum of neurological disorders, including a leukoencephalopathy of variable severity. Our aim was to characterize imaging, lab, and clinical correlates of severe coronavirus disease 2019 (COVID-19) leukoencephalopathy, which may provide insight into the SARS-CoV-2 pathophysiology.

Twenty-seven consecutive patients positive for SARS-CoV-2 who had brain MR imaging following intensive care unit admission were included. Seven (7/27, 26%) developed an unusual pattern of “leukoencephalopathy with reduced diffusivity” on diffusion-weighted MR imaging. The remaining patients did not exhibit this pattern. Clinical and laboratory indices, as well as neuroimaging findings, were compared between groups.

The reduced-diffusivity group had a significantly higher body mass index (36 versus 28 kg/m

,

< .01). Patients with reduced diffusivity trended toward more frequent acute renal failure (7/7, 100% versus 9/20, 45%;

= .