RESUMEN
Spinal cord enlargement (SCE) includes conditions such as Syringomyelia, tumors, and tumor-like cases of demyelination, edema, or inflammation. These conditions involve fluid-filled cysts, known as syrinx, or masses of tissue, referred to as tumors, which cause increased pressure within the spinal cord (SC) and obstruct cerebrospinal fluid (CSF) circulation. To assess the impact of SCE location and diameter, we constructed fifteen computational SC models, each featuring a SCE placed in one of five probable locations with 20 %, 40 %, and 60 % stenosis. Our objective was to investigate how the location, diameter, and length of the SCE influence CSF velocity pattern and to identify the most critical location in the SC associated with this condition. The results indicated a velocity increase of 0.5 cm/(s) near models with 60 % stenosis. Importantly, SCE located from T1 to T5 exhibit a more pronounced reduction, exceeding 6.5, in the Womersley number. Our finding suggests that this region is the most vulnerable for SCE formation due to its significant impact on fluid circulation. The identification of specific locations within the SC associated with heightened risk can contribute to an improved understanding, treatment and management of SCE.
RESUMEN
Coronary artery disease is the leading global cause of mortality and Fractional Flow Reserve (FFR) is widely regarded as the gold standard for assessing coronary artery stenosis severity. However, due to the limitations of invasive FFR measurements, there is a pressing need for a highly accurate virtual FFR calculation framework. Additionally, it's essential to consider local haemodynamic factors such as time-averaged wall shear stress (TAWSS), which play a critical role in advancement of atherosclerosis. This study introduces an innovative FFR computation method that involves creating five patient-specific geometries from two-dimensional coronary angiography images and conducting numerical simulations using computational fluid dynamics with a three-element Windkessel model boundary condition at the outlet to predict haemodynamic distribution. Furthermore, four distinct boundary condition methodologies are applied to each geometry for comprehensive analysis. Several haemodynamic features, including velocity, pressure, TAWSS, and oscillatory shear index are investigated and compared for each case. Results show that models with average boundary conditions can predict FFR values accurately and observed errors between invasive FFR and virtual FFR are found to be less than 5%.