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One aneurysm in the right cavernous segment of internal carotid artery in 40-year-old man. (a) Volume-rendered digital subtraction CT angiographic image shows the aneurysm in the right cavernous segment of internal carotid artery (arrow). (b) Volume-rendered image without bone subtraction shows part of the aneurysm covered by the adjacent skull (arrow). (c) Contrast-enhanced maximum intensity projection with bone subtraction shows the aneurysm in right internal carotid artery (arrow). (d) Three-dimensional DSA image of the aneurysm (arrow).  

One aneurysm in the right cavernous segment of internal carotid artery in 40-year-old man. (a) Volume-rendered digital subtraction CT angiographic image shows the aneurysm in the right cavernous segment of internal carotid artery (arrow). (b) Volume-rendered image without bone subtraction shows part of the aneurysm covered by the adjacent skull (arrow). (c) Contrast-enhanced maximum intensity projection with bone subtraction shows the aneurysm in right internal carotid artery (arrow). (d) Three-dimensional DSA image of the aneurysm (arrow).  

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To evaluate the diagnostic accuracy of digital subtraction computed tomographic (CT) angiography in the detection of intracranial aneurysms compared with three-dimensional (3D) rotational digital subtraction angiography (DSA), as reference standard, in a large cohort in a single center. The study was waived by the institutional review board because...

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... However, for aneurysms < 4-mm multidetector arrays are significantly better with a sensitivity of 92% compared 75% for a single array [30]. Other series looking at small aneurysms < 3 mm report a sensitivity falling to 86-92% [31][32][33]. While sub-3-mm aneurysms have a lower rupture risk and are unlikely to be treated, a false negative still has implications for decisions on further surveillance imaging for the patient. ...
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The treatment of intracranial aneurysms is dictated by its risk of rupture in the future. Several clinical and radiological risk factors for aneurysm rupture have been described and incorporated into prediction models. Despite the recent technological advancements in aneurysm imaging, linear length and visible irregularity with a bleb are the only radiological measure used in clinical prediction models. The purpose of this article is to summarize both the standard imaging techniques, including their limitations, and the advanced techniques being used experimentally to image aneurysms. It is expected that as our understanding of advanced techniques improves, and their ability to predict clinical events is demonstrated, they become an increasingly routine part of aneurysm assessment. It is important that neurovascular specialists understand the spectrum of imaging techniques available.
... Although it is well known that CT angiography is less sensitive than Digital Subtraction Angiography (DSA), which remains the gold standard, it is generally accepted that the CTA is highly accurate in the diagnosis of intracranial aneurysms. Comparison studies between CTA and DSA for the detection and evaluation of intracranial aneurysms find that CTA is highly sensitive, and specific and can be used as an alternative to DSA [11,12]. ...
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... 9 Lu et al found that digital subtraction angiogram had a sensitivity of 91.3% of detecting aneurysms less than 3 millimeters (mm); 94.0% for aneurysms between 3 mm but <5 mm; 98.4% for aneurysms between 5 mm and <10 mm; and 100% for aneurysms ≥10 mm. 10 This case highlights the importance of the above evaluation with regard to sentinel headaches. Sentinel headaches signify a particularly severe headache that precedes a second episode of a profound headache secondary to intracranial aneurysm rupture. ...
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... 8,9 The majority of data in the literature showed that CTA has a good diagnostic efficiency which is comparable to DSA with a high sensitivity, specificity and accuracy of 95% -98%, 90% -100% and 94% -98%, respectively. 10,11,12,13 Meta-analyses of up to 50 studies stated similar findings with pooled sensitivities and specificities of 97% -98% and 98% -100%, respectively. 8,9 A few studies demonstrated lower CTA diagnostic performance with overall sensitivity of 71% -89% and accuracy of 74% -90%. ...
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The study of cerebrovascular anatomy can be difficult and may take time due to its intrinsic complexity. However, it can also be difficult for the following reasons: the excessive description of neuroanatomy making articles hard to read, the unclear clinical application of what is written, the use of simplified or intricate schematic drawings that are not always appropriate for effective teaching, the poor quality of neuroanatomy dissections and the use of unusual views of figures that are not strictly related to the most frequent neuroimages to be interpreted in daily practice. Because of this, we designed an article that incorporates original and accurate anatomical dissections in an attempt to improve its comprehensibility. Five formalin-fixed adult cadaveric heads, whose vessels were injected with a colored silicone mixture (red for arteries and blue for veins), were dissected and examined under a microscope with magnifications from 3× to 40×. Special emphasis has been placed on correlating topographic anatomy with routine neuroimaging studies from computed tomographic angiography (CTA) and digital subtraction angiography (DSA). The essential surgical anatomy in a neurosurgeon’s daily practice is also described. The cadaveric dissections included in this study contribute to the understanding of the cerebrovascular anatomy necessary for the neurosurgeon’s daily practice.
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Auto-detection of cerebral aneurysms via convolutional neural network (CNN) is being increasingly reported. However, few studies to date have accurately predicted the risk, but not the diagnosis itself. We developed a multi-view CNN for the prediction of rupture risk involving small unruptured intracranial aneurysms (UIAs) based on three-dimensional (3D) digital subtraction angiography (DSA). The performance of a multi-view CNN-ResNet50 in accurately predicting the rupture risk (high vs. non-high) of UIAs in the anterior circulation measuring less than 7 mm in size was compared with various CNN architectures (AlexNet and VGG16), with similar type but different layers (ResNet101 and ResNet152), and single image-based CNN (single-view ResNet50). The sensitivity, specificity, and overall accuracy of risk prediction were estimated and compared according to CNN architecture. The study included 364 UIAs in training and 93 in test datasets. A multi-view CNN-ResNet50 exhibited a sensitivity of 81.82 (66.76–91.29)%, a specificity of 81.63 (67.50–90.76)%, and an overall accuracy of 81.72 (66.98–90.92)% for risk prediction. AlexNet, VGG16, ResNet101, ResNet152, and single-view CNN-ResNet50 showed similar specificity. However, the sensitivity and overall accuracy were decreased (AlexNet, 63.64% and 76.34%; VGG16, 68.18% and 74.19%; ResNet101, 68.18% and 73.12%; ResNet152, 54.55% and 72.04%; and single-view CNN-ResNet50, 50.00% and 64.52%) compared with multi-view CNN-ResNet50. Regarding F1 score, it was the highest in multi-view CNN-ResNet50 (80.90 (67.29–91.81)%). Our study suggests that multi-view CNN-ResNet50 may be feasible to assess the rupture risk in small-sized UIAs.