Notes

Evaluating Link between Wise-Pattern, Two-Stage Chest Reduction-Reconstruction along with and without Acellular Skin Matrix.
Klippel-Feil syndrome is an entity presenting with short neck, low hairline and reduced range of motion of cervical spine. Neurenteric cyst is a congenital abnormality, in which mucus-secreting epithelium of the gastrointestinal tract is seen in the spinal axis. The association of a neurenteric cyst with Klippel-Feil syndrome has been reported very rarely. We report the case of a young man, affected by Klippel-Feil syndrome, who presented with bilateral paraplegia. Imaging of the spine revealed features suggestive of cervico-dorsal neurenteric cyst. Subsequently, surgical resection of the cysts was done, which resulted in resolution of the symptoms.
Despite high interest in machine-learning algorithms for automated segmentation of MRIs of patients with brain tumors, there are few reports on the variability of segmentation results. The purpose of this study was to obtain benchmark measures of repeatability for a widely accessible software program, BraTumIA (Versions 1.2 and 2.0), which uses a machine-learning algorithm to segment tumor features on contrast-enhanced brain MR imaging.

Automatic segmentation of enhancing tumor, tumor edema, nonenhancing tumor, and necrosis was performed on repeat MR imaging scans obtained approximately 2 days apart in 20 patients with recurrent glioblastoma. Measures of repeatability and spatial overlap, including repeatability and Dice coefficients, are reported.

Larger volumes of enhancing tumor were obtained on later compared with earlier scans (mean, 26.3 versus 24.2 mL for BraTumIA 1.2;
< .05; and 24.9 versus 22.9 mL for BraTumIA 2.0,
< .01). In terms of percentage change, repeatability coefficients ranged from 31% to 46% for enhancing tumor and edema components and from 87% to 116% for nonenhancing tumor and necrosis. Dice coefficients were highest (>0.7) for enhancing tumor and edema components, intermediate for necrosis, and lowest for nonenhancing tumor and did not differ between software versions. Enhancing tumor and tumor edema were smaller, and necrotic tumor larger using BraTumIA 2.0 rather than 1.2.

Repeatability and overlap metrics varied by segmentation type, with better performance for segmentations of enhancing tumor and tumor edema compared with other components. Incomplete washout of gadolinium contrast agents could account for increasing enhancing tumor volumes on later scans.
Repeatability and overlap metrics varied by segmentation type, with better performance for segmentations of enhancing tumor and tumor edema compared with other components. Incomplete washout of gadolinium contrast agents could account for increasing enhancing tumor volumes on later scans.In the first part of this 2-part series, we described how to implement microscopy coil MR imaging of the orbits. Beyond being a useful anatomic educational tool, microscopy coil MR imaging has valuable applications in clinical practice. By depicting deep tissue tumor extension, which cannot be evaluated clinically, ophthalmic surgeons can minimize the surgical field, preserve normal anatomy when possible, and maximize the accuracy of resection margins. Here we demonstrate common and uncommon pathologies that may be encountered in orbital microscopy coil MR imaging practice and discuss the imaging appearance, the underlying pathologic processes, and the clinical relevance of the microscopy coil MR imaging findings.
Differentiating glioblastoma from solitary brain metastasis preoperatively using conventional MR images is challenging. Deep learning models have shown promise in performing classification tasks. The diagnostic performance of a deep learning-based model in discriminating glioblastoma from solitary brain metastasis using preoperative conventional MR images was evaluated.

Records of 598 patients with histologically confirmed glioblastoma or solitary brain metastasis at our institution between February 2006 and December 2017 were retrospectively reviewed. Preoperative contrast-enhanced T1WI and T2WI were preprocessed and roughly segmented with rectangular regions of interest. A deep neural network was trained and validated using MR images from 498 patients. The MR images of the remaining 100 were used as an internal test set. An additional 143 patients from another tertiary hospital were used as an external test set. The classifications of ResNet-50 and 2 neuroradiologists were compared for their accuracy, precision, recall, F1 score, and area under the curve.

The areas under the curve of ResNet-50 were 0.889 and 0.835 in the internal and external test sets, respectively. The area under the curve of neuroradiologists 1 and 2 were 0.889 and 0.768 in the internal test set and 0.857 and 0.708 in the external test set, respectively.

A deep learning-based model may be a supportive tool for preoperative discrimination between glioblastoma and solitary brain metastasis using conventional MR images.
A deep learning-based model may be a supportive tool for preoperative discrimination between glioblastoma and solitary brain metastasis using conventional MR images.
Predicting malignant cerebral edema can help identify patients who may benefit from appropriate evidence-based interventions. We investigated whether absent cortical venous filling is associated with more pronounced early brain edema, which leads to malignant cerebral edema.

Patients with acute ischemic stroke caused by large-vessel occlusion in the MCA territory who presented between July 2017 and September 2019 to our hospital were included. Collateral filling was rated using the modified Tan scale on CTA, and good collaterals were defined as a score of 2-3. The Cortical Vein Opacification Score (COVES) was calculated, and absent cortical venous filling was defined as a score of 0. AD80 Early brain edema was determined using net water uptake on baseline CT images. Malignant cerebral edema was defined as a midline shift of ≥5 mm on follow-up imaging or a massive cerebral swelling leading to decompressive hemicraniectomy or death. Multivariate linear and logistic regression models were performed to analyze datimized adjuvant antiedematous treatment.
Cerebral amyloid angiopathy (CAA) is a known risk factor for ischemic stroke though angiographic imaging is often negative. Our goal was to determine the relationship between vessel wall enhancement (VWE) in acute and future ischemic stroke in CAA patients.

This was a retrospective study of patients with new-onset neurologic symptoms undergoing 3T vessel wall MR imaging from 2015 to 2019. Vessel wall enhancement was detected on pre- and postcontrast flow-suppressed 3D T1WI. Interrater agreement was evaluated in cerebral amyloid angiopathy-positive and age-matched negative participants using a prevalence- and bias-adjusted kappa analysis. In patients with cerebral amyloid angiopathy, multivariable Poisson and Cox regression were used to determine the association of vessel wall enhancement with acute and future ischemic stroke, respectively, using backward elimination of confounders to
 < .20.

Fifty patients with cerebral amyloid angiopathy underwent vessel wall MR imaging, including 35/50 (70.0%) wiluded initial ischemic stroke (hazard ratio = 3.4; 95% CI, 1.0-12.0;
= .053) and vessel wall enhancement (hazard ratio = 2.5; 95% CI, 0.9-7.0;
= .080).

Vessel wall enhancement is associated with both acute and future stroke in patients with cerebral amyloid angiopathy.
Vessel wall enhancement is associated with both acute and future stroke in patients with cerebral amyloid angiopathy.
In certain cases of pediatric patients with Moyamoya disease undergoing encephaloduroarteriosynangiosis (EDAS) treatment, the posterior auricular artery can be used as an alternative when the parietal branch of the superficial temporal artery is unavailable. In this study, anatomic variations of the superficial temporal and posterior auricular arteries in pediatric patients with Moyamoya disease and postoperative outcomes of posterior auricular artery-EDAS are explored.

Medical records of 572 patients with Moyamoya disease who underwent surgical procedures from 2007 to 2017 at the Seoul National University Children's Hospital were reviewed. Anatomic classifications of the superficial temporal and posterior auricular arteries were based on previous classifications. Postoperative hemodynamic changes of posterior auricular artery-EDAS were analyzed using the Matsushima grade. Also, Karnofsky Performance Scale and mRS scores of posterior auricular artery-EDAS cases were reviewed to identify postoperative clin is unavailable.
In approximately 2% of pediatric patients with Moyamoya disease for whom the superficial temporal artery is unavailable as the EDAS donor, the posterior auricular artery can be considered an alternative. On the basis of the results, the clinical outcome of posterior auricular artery-EDAS was not inferior to that of superficial temporal artery-EDAS. Hence, we suggest an in-depth consideration of the posterior auricular artery as the donor artery if the superficial temporal artery parietal branch is unavailable.
At times, there is a clinical need for using routine brain MR imaging performed close to the time of onset of patients' visual symptoms to firmly establish the diagnosis of optic neuritis. Our aim was to assess the diagnostic performance of radiologists in detecting optic neuritis on routine brain MR images and whether this performance could be enhanced using a postprocessing algorithm.

In this retrospective case-control study of 60 patients (37 women, 23 men; mean age, 47.2 [SD, 17.9] years), 2 blinded neuroradiologists evaluated T2-weighted FLAIR and contrast-enhanced T1WI from brain MR imaging for the presence of imaging evidence of optic neuritis. Images were processed using an image-processing algorithm that aimed to selectively accentuate the signal intensity of diseased optic nerves. We assessed the effect of image processing on the contrast-to-noise ratio between the optic nerves and normal-appearing white matter and on the diagnostic performance of the neuroradiologists, including the interobserver reliability.

The average sensitivity of readers was 55%, 56.5%, and 30.0% on FLAIR, coronal contrast-enhanced T1WI, and axial contrast-enhanced T1WI, respectively. Sensitivities were lower in the absence of fat saturation on FLAIR (
= .001) and coronal contrast-enhanced T1WI (
= .04). Processing increased the contrast-to-noise ratio of diseased (
value range = .03 to <.001) but not of control optic nerves. Processing did not improve the sensitivity but improved the specificity and positive predictive value. Interobserver agreement improved from slight to good.

Detection of optic neuritis on routine brain MR imaging is challenging. Specificity, positive predictive value, and interobserver agreement can be improved by postprocessing of MR images.
Detection of optic neuritis on routine brain MR imaging is challenging. Specificity, positive predictive value, and interobserver agreement can be improved by postprocessing of MR images.
In 2019, with the COVID-19 pandemic sweeping across the globe, public health systems worldwide faced severe challenges. Amid the pandemic, one simulation game, Plague Inc., has received substantial attention. This game has indirectly drawn greater public attention to public health issues by simulating pathogen transmission and disease symptoms.

Against this backdrop, this research investigates whether the gameful experience of Plague Inc. has indirectly affected public knowledge, attitudes, and practices (KAP) regarding COVID-19.

An online survey was conducted through social networking services in Taiwan from May 6-28, 2020.

A total of 486 subjects participated in this study, of which 276 (56.8%) had played Plague Inc. This study had several findings. First, participants who had played Plague Inc. demonstrated higher levels of knowledge (P=.03, median 7, IQR 7-8) and attitudes (P=.007, median 8, IQR 7-8) than participants who had not played Plague Inc. (knowledge median 7, IQR 6-8; attitude median 7, IQR 6-8).
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