AJNR. American journal of neuroradiology
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Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to medical imaging. ⋯ This review article describes the reasons, outlines the basic methods used to train and test deep learning models, and presents a brief overview of current and potential clinical applications with an emphasis on how they are likely to change future neuroradiology practice. Facility with these methods among neuroimaging researchers and clinicians will be important to channel and harness the vast potential of this new method.
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AJNR Am J Neuroradiol · Oct 2018
Automated Integration of Multimodal MRI for the Probabilistic Detection of the Central Vein Sign in White Matter Lesions.
The central vein sign is a promising MR imaging diagnostic biomarker for multiple sclerosis. Recent studies have demonstrated that patients with MS have higher proportions of white matter lesions with the central vein sign compared with those with diseases that mimic MS on MR imaging. However, the clinical application of the central vein sign as a biomarker is limited by interrater differences in the adjudication of the central vein sign as well as the time burden required for the determination of the central vein sign for each lesion in a patient's full MR imaging scan. In this study, we present an automated technique for the detection of the central vein sign in white matter lesions. ⋯ The current study presents the first fully automated method for detecting the central vein sign in white matter lesions and demonstrates promising performance in a sample of patients with and without MS.
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AJNR Am J Neuroradiol · Oct 2018
Identification of Hostile Hemodynamics and Geometries of Cerebral Aneurysms: A Case-Control Study.
Hostile hemodynamic conditions and geometries are thought to predispose aneurysms for instability and rupture. This study compares stable, unstable, and ruptured aneurysms while controlling for location and patient characteristics. ⋯ Unstable and ruptured aneurysms have more complex flows with concentrated wall shear stress and are larger, more elongated, and irregular than stable aneurysms, independent of aneurysm location and patient sex and age.
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AJNR Am J Neuroradiol · Oct 2018
Dilated Vein of the Filum Terminale on MRI: A Marker for Deep Lumbar and Sacral Dural and Epidural Arteriovenous Fistulas.
Conventional MR imaging can provide important clues regarding the location of a spinal vascular malformation. We hypothesized that a dilated vein of the filum terminale, identified as a curvilinear flow void on T2WI, could be an imaging marker for a lower lumbar (L3-L5) or sacral fistula. ⋯ The presence of a dilated vein of the filum terminale can accurately localize a spinal dural arteriovenous fistula/spinal epidural arteriovenous fistula to the lower lumbar or sacral spine in patients being evaluated for such lesions. This finding can be used to facilitate both noninvasive and conventional spinal angiography.
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AJNR Am J Neuroradiol · Sep 2018
Longitudinal Microstructural Changes in Traumatic Brain Injury in Rats: A Diffusional Kurtosis Imaging, Histology, and Behavior Study.
Traumatic brain injury is a major public health problem worldwide. Accurately evaluating the brain microstructural changes in traumatic brain injury is crucial for the treatment and prognosis assessment. This study aimed to assess the longitudinal brain microstructural changes in traumatic brain injury in the rat using diffusional kurtosis imaging. ⋯ Our study indicated that there were longitudinal changes in diffusional kurtosis imaging parameters, accompanied by multiple pathologic changes at different time points following traumatic brain injury, and that mean kurtosis is more sensitive to detect microstructural changes, especially in gray matter, than mean diffusivity and fractional anisotropy.