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CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study
This study aimed to develop a machine learning model for predicting brain arteriovenous malformation (bAVM) rupture using a combination of traditional risk factors and radiomics features. This multicenter retrospective study enrolled 586 patients with unruptured bAVMs from 2010 to 2020. All patients were grouped into the hemorrhage (n = 368) and non-hemorrhage (n = 218) groups. The bAVM nidus were segmented on CT angiography images using Slicer software, and radiomic features were extracted using Pyradiomics. The dataset included a training set and an independent testing set. The machine learning model was developed on the...
Source: Translational Stroke Research - June 13, 2023 Category: Neurology Source Type: research

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

CTA lowers costs, improves outcomes for minor stroke
Integrating CT angiography (CTA) into the routine clinical evaluation of patients...Read more on AuntMinnie.comRelated Reading: Are clinicians overusing CTA for carotid stenosis? SIR: Stroke treatment training program improves outcomes CT matches MRI for late-window stroke evaluation 3 CTA signs show which stroke patients can skip surgery 5 risk factors help predict brain hemorrhage on CT
Source: AuntMinnie.com Headlines - January 16, 2020 Category: Radiology Source Type: news

Ctbrain machine learning predicts stroke thrombolysis result
Conclusions This proof-of-concept study shows that machine learning methods applied to acute stroke CT-scans potentially offers automation, and improved performance in SICH prediction following thrombolysis. Larger-scale cohorts, and incorporation of CT perfusion/angiography data, should be tested with such methods.
Source: Journal of Neurology, Neurosurgery and Psychiatry - September 9, 2014 Category: Neurosurgery Authors: Epton, S., Bentley, P., Ganesalingam, J., Dias, A., Mahady, K., Rinne, P., Sharma, P., Halse, O., Mehta, A., Rueckert, D. Tags: Abstracts Source Type: research

Multicenter Accuracy and Interobserver Agreement of Spot Sign Identification in Acute Intracerebral Hemorrhage Clinical Sciences
Conclusions— Accuracy for spot identification is high with opportunity for improvement in spot interpretation sensitivity and interobserver agreement particularly through greater reliance on computed tomography angiography source data and awareness of limitations of multiplanar images. Further prospective study is needed.
Source: Stroke - December 23, 2013 Category: Neurology Authors: Huynh, T. J., Flaherty, M. L., Gladstone, D. J., Broderick, J. P., Demchuk, A. M., Dowlatshahi, D., Meretoja, A., Davis, S. M., Mitchell, P. J., Tomlinson, G. A., Chenkin, J., Chia, T. L., Symons, S. P., Aviv, R. I. Tags: Acute Cerebral Hemorrhage, Angiography, Computerized tomography and Magnetic Resonance Imaging, Intracerebral Hemorrhage Clinical Sciences Source Type: research

The Impact of Comprehensive Stroke Care Capacity on the Hospital Volume of Stroke Interventions: A Nationwide Study in Japan: J-ASPECT Study
We examined the effect of hospital characteristics, having a t-PA protocol, and the number of fulfilled CSC items (total CSC score) on the hospital volume of t-PA infusion, removal of intracerebral hemorrhage, and coiling and clipping of intracranial aneurysms performed in 2009.Results: Approximately 55% of hospitals responded to the survey. Facilities with t-PA protocols (85%) had a significantly higher likelihood of having 23 CSC items, for example, personnel (eg, neurosurgeons: 97.3% versus 66.1% and neurologists: 51.3% versus 27.7%), diagnostic (eg, digital cerebral angiography: 87.4% versus 43.2%), specific expertise...
Source: Journal of Stroke and Cerebrovascular Diseases - October 7, 2013 Category: Neurology Authors: Koji Iihara, Kunihiro Nishimura, Akiko Kada, Jyoji Nakagawara, Kazunori Toyoda, Kuniaki Ogasawara, Junichi Ono, Yoshiaki Shiokawa, Toru Aruga, Shigeru Miyachi, Izumi Nagata, Shinya Matsuda, Koichi B. Ishikawa, Akifumi Suzuki, Hisae Mori, Fumiaki Nakamura, Tags: Original Articles Source Type: research