IGE-MRC is a minimally invasive and highly sensitive imaging technique. No adverse side effect during our long-term follow-up might strengthen and support the safety of IGE-MRC.
Objective
In the diagnosis of superior semicircular canal dehiscence (SSCD), computed tomography (CT) is the only imaging method. The aims of the study were to show that reformat images are more accurate than standard planes for diagnosis of SSCD and to determine the prevalence of SSCD.
Methods
The retrospective review yielded 1309 temporal CTs performed in our radiology department for any reason. Two radiologist interpreted CTs in standard planes collaboratively. Patients with SSCD were reinterpreted in Pöschl and Stenvers planes by 2 radiologists separately.
Results
Statistical analysis was made by accepting that 2 radiologists diagnosis were accurate in Pöschl plane. Coronal plane sensitivity 86%, specificity 64%, Stenvers plane sensitivity 96%, and specificity 52% have been found in the mean result of 2 observers (P < 0.001).
Conclusions
In the diagnosis of SSCD, standard and Stenvers planes can cause false-negative and false-positive diagnoses. Interpretation in Pöschl plane can significantly increase sensitivity, specificity, negative, and positive predictive values for diagnosing dehiscence.
To investigate the performance of a joint convolutional neural networks-recurrent neural networks (CNN-RNN) using an attention mechanism in identifying and classifying intracranial hemorrhage (ICH) on a large multi-center dataset; to test its performance in a prospective independent sample consisting of consecutive real-world patients. All consecutive patients who underwent emergency non-contrast-enhanced head CT in five different centers were retrospectively gathered. Five neuroradiologists created the ground-truth labels. The development dataset was divided into the training and validation set. After the development phase, we integrated the deep learning model into an independent center’s PACS environment for over six months for assessing the performance in a real clinical setting. Three radiologists created the ground-truth labels of the testing set with a majority voting. A total of 55,179 head CT scans of 48,070 patients, 28,253 men (58.77%), with a mean age of 53.84 ± 17.64 years (range 18–89) were enrolled in the study. The validation sample comprised 5211 head CT scans, with 991 being annotated as ICH-positive. The model's binary accuracy, sensitivity, and specificity on the validation set were 99.41%, 99.70%, and 98.91, respectively. During the prospective implementation, the model yielded an accuracy of 96.02% on 452 head CT scans with an average prediction time of 45 ± 8 s. The joint CNN-RNN model with an attention mechanism yielded excellent diagnostic accuracy in assessing ICH and its subtypes on a large-scale sample. The model was seamlessly integrated into the radiology workflow. Though slightly decreased performance, it provided decisions on the sample of consecutive real-world patients within a minute.
BackgroundAnterior falcotentorial junction dural arteriovenous fistulas (AFDAVFs) are the most deeply located and most complex type of tentorial fistula due to their location and vascular anatomy. We aimed to make new angiographic definitions of AFDAVF nidus and functionality of the deep venous system of the brain and thereby provide a safer approach for endovascular treatment.MethodsWe retrospectively examined 18 patients with AFDAVF who received endovascular treatment at our neuroradiology department between June 2002 and May 2019. Pre- and post-treatment clinical assessments were performed using the modified Rankin Scale. AFDAVF niduses were defined as mixed-type or pure-dural-type on the basis of whether choroidal arteriovenous malformation was coexisting or not, respectively. The deep venous system was denoted as functional or nonfunctional.ResultsWe included 13 men and 5 women (mean (range) age, 47.2 (31–62) years). We evaluated 15 patients with pure-dural-type AFDAVFs and three with mixed-type AFDAVFs. Complete occlusion of the fistula was achieved in 15/18 patients. Three patients had transient neurologic symptoms. In two patients these were due to mild thalamic ischemia and in the third patient was due to tectal venous ischemia, all in mixed-type AFDAVF. One patient also developed Parinaud syndrome due to compression of the tectal plate by a thrombosed large vein of Galen. No patients died or developed permanent morbidity.ConclusionEvaluating AFDAVFs as described here using our new subtyping model will help improve analysis of the malformation and development of a safer endovascular strategy, and hence may prevent periprocedural complications and improve treatment safety.
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