Incidence rates of cranial<unk> s are estimated at between 0.4% and 3.6%. Those without risk factors have expected prevalence of 2–3%. In adults, females are more likely to have<unk> s. They are most prevalent in people ages 35 – 60 but can occur in children as well.<unk> s are rare in children with a reported prevalence of .5% to 4.6%. The most common incidence is among 50-year-olds, and there are typically no warning signs. Most<unk> s develop after the age of 40. Pediatric<unk> s Pediatric<unk> s have different incidences and features than adult<unk> s. Intracranial<unk> s are rare in childhood, with over 95% of all<unk> s occurring in adults. Risk factors Incidence rates are two to three times higher in males, while there are more large and giant<unk> s and fewer multiple<unk> s. Intracranial hemorrhages are 1.6 times more likely to be due to<unk> s than cerebral arteriovenous malformations in whites, but four times less in certain Asian populations. Most patients, particularly infants, present with subarachnoid hemorrhage and corresponding headaches or neurological deficits. The mortality rate for pediatric<unk> s is lower than in adults. Modeling Vortex formation inside an<unk> . 1- Blood flow inlet. 2- Vortex formation inside<unk> . Velocity at center is near zero. 3- Blood flow exit Modeling of<unk> s consists of creating a 3D model that mimics a particular<unk> . Using patient data for the blood velocity, and blood pressure, along with the geometry of the<unk> , researchers can apply computational fluid dynamics (CFD) to predict whether an<unk>  is benign or if it is at risk of complication. One risk is rupture. Analyzing the velocity and pressure profiles of the blood flow leads to obtaining the resulting wall shear stress on the vessel and<unk>  wall. The neck of the<unk>  is the most at risk due to the combination of a small wall thickness and high wall shear stress. When the wall shear stress reaches its limit, the<unk>  ruptures, leading to intracranial hemorrhage. Conversely, another risk of<unk> s is the creation of clots.<unk> s create a pocket which diverts blood flow. This diverted blood flow creates a vortex inside of the<unk> . This vortex can lead to areas inside of the<unk>  where the blood flow is stagnant, which promotes formations of clots. Blood clots can dislodge from the<unk> , which can then lead to an embolism when the clot gets stuck and disrupts blood flow. Model analysis allows these risky<unk> s to be identified and treated. In the past,<unk> s were modeled as rigid spheres with linear inlets and outlets. As technology advances, the ability to detect and analyze<unk> s becomes easier. Researchers are able to CT scan a patient's body to create a 3D computer model that possesses the correct geometry.<unk> s can now be modeled with their distinctive "balloon" shape. Nowadays researchers are optimizing the parameters required to accurately model a patient's<unk>  that will lead to a successful intervention. Current modeling is not able to take into account all variables though. For example, blood is considered to be a non-Newtonian fluid. Some researchers treat blood as a Newtonian fluid instead, as it sometimes has negligible effects to the analysis in large vessels. When analyzing small vessels though, such as those present in intracranial<unk> s. Similarly, sometimes it is difficult to model the varying wall thickness in small vessels, so researchers treat wall thickness as constant. Researchers make these assumptions to reduce computational time. Nonetheless, making erroneous assumptions could lead to a misdiagnosis that could put a patient's life at risk.
Aneurysm
Baker's cyst
Coma
Angioma
Hematoma
Vascular tumor
Gliosis
Pseudoaneurysm