A novel method for improving the accuracy of MR-derived patient-specific vascular models using X-ray angiography

MR imaging is a noninvasive imaging modality that is commonly used during clinical follow up and has been widely utilized to reconstruct realistic 3D vascular models for patient-specific analysis. In a recent work, we utilized patient-specific hemodynamic analysis of the circle of Willis to noninvasively assess stroke risk in pediatric Moyamoya disease (MMD)—a progressive steno-occlusive cerebrovascular disease that leads to recurrent stroke. The objective was to identify vascular regions with critically high wall shear rate (WSR), signifying elevated stroke risk. However, sources of error including insufficient resolution of MR images can negatively impact vascular model accuracy, especially in areas of severe pathological narrowing, and thus diminish clinical relevance of simulation results, as local hemodynamics are sensitive to vessel geometry. We have developed a novel method to improve the accuracy of MR-derived 3D vascular models utilizing 2D X-ray angiography (XA), which is considered the gold standard for clinically assessing vessel caliber. In this workflow, ″virtual angiographies″ (VA) of 3D MR-derived vascular models are conducted, producing 2D projections that are compared to corresponding XA images guiding the local adjustment of modeled vessels. This VA-comparison-adjustment loop is iterated until the two agree, as confirmed by an expert neuroradiologist. Using this method, we generated models of the circle of Willis of two patients with a history of unilateral stroke. Blood flow simulations were performed using a Navier-Stokes solver within an isogeoemtric analysis framework and WSR distributions were quantified. Results for one patient show as much as 45% underestimation of local WSR in the stenotic left anterior cerebral artery (LACA) and up to a 60% underestimation in the right anterior cerebral artery when using the initial MR-derived model compared to the XA-adjusted model, emphasizing the need for verifying improved accuracy of the adjusted model. To that end, vessel cross-sectional areas of the pre- and post-adjustment models were compared to those seen in 3D CTA images of the same patient. CTA has superior resolution and signal to noise ratio compared to MR imaging but is not commonly used in clinic due to radiation exposure concerns, especially in pediatric patients. While the vessels in the initial model had normalized root mean squared deviations (NRMSDs) ranging from 26% to 182% and 31% to 69% in two patients with respect to CTA, the adjusted vessel NRMSDs were comparatively smaller (32% to 53% and 11% to 42%). In the mildly stenotic LACA of patient 1, the NRMSDs for the pre- and post-adjusted models were 49% and 32%, respectively. These findings suggest that our XA-based adjustment method can considerably improve the accuracy of vascular models, and thus, stroke-risk prediction. An accurate individualized assessment of stroke risk would be of substantial clinical benefit because it would help guide the timing of preventative surgical interventions in pediatric MMD patients.

Moyamoya Syndrome in a Child with HbEβ-Thalassemia

Moyamoya is a progressive cerebrovascular disease associated with stenosis or occlusion of the arteries of the Circle of Willis. It is uncommon in thalassemia. We present a 9-year-old girl, with HbEβ-thalassemia, who presented with headache, vomiting and episodes of transient hemiparesis with complete occlusion internal carotid arteries.

Nontraumatic Subarachnoid Hemorrhage

Subarachnoid hemorrhage (SAH) is defined as blood in the subarachnoid space. Nontraumatic SAH is most commonly caused by rupture of an aneurysm located at the circle of Willis. Patients often present with acute thunderclap headache but also may lose consciousness or have focal neurologic deficits. Detection of an aneurysm, if present, and its treatment are needed urgently to prevent recurrent bleeding. Patients with nontraumatic SAH are prone to numerous complications that require preventative measures, early recognition, and treatment.

Relationship between Circle of Willis Variations and Cerebral or Cervical Arteries Stenosis Investigated by Computer Tomography Angiography and Multitask Convolutional Neural Network

Circle of Willis (CoW) is the most critical collateral pathway that supports the redistribution of blood supply in the brain. The variation of CoW is closely correlated with cerebral hemodynamic and cerebral vessel-related diseases. But what is responsible for CoW variation remains unclear. Moreover, the visual evaluation for CoW variation is highly time-consuming. In the present study, based on the computer tomography angiography (CTA) dataset from 255 patients, the correlation between the CoW variations with age, gender, and cerebral or cervical artery stenosis was investigated. A multitask convolutional neural network (CNN) was used to segment cerebral arteries automatically. The results showed the prevalence of variation of the anterior communicating artery (Aco) was higher in the normal senior group than in the normal young group and in females than in males. The changes in the prevalence of variations of individual segments were not demonstrated in the population with stenosis of the afferent and efferent arteries, so the critical factors for variation are related to genetic or physiological factors rather than pathological lesions. Using the multitask CNN model, complete cerebral and cervical arteries could be segmented and reconstructed in 120 seconds, and an average Dice coefficient of 78.2% was achieved. The segmentation accuracy for precommunicating part of anterior cerebral artery and posterior cerebral artery, the posterior communicating arteries, and Aco in CoW was 100%, 99.2%, 94%, and 69%, respectively. Artificial intelligence (AI) can be considered as an adjunct tool for detecting the CoW, particularly related to reducing workload and improving the accuracy of the visual evaluation. The study will serve as a basis for the following research to determine an individual’s risk of stroke with the aid of AI.

Anatomic imaging study of luminal diameter of the circle of Willis in patients with ischemic stroke

Objectives: Stroke or cerebrovascular accident is associated with defects in the circle of Willis; the vascular network that supplies the brain. There is currently lack of literature on the involvement of the circle of Willis in patients with stroke or its association with impending stroke. The objective of the study was to evaluate luminal diameter of arteries that constitute the circle of Willis in patients with stroke using computed tomography angiography (CTA) and magnetic resonance imaging (MRI) scans. Material and Methods: Angiograms of 340 male and female patients aged 15–>75 (40.18 ± 1.1 and 43.68 ± 1.18) years with suspected stroke, referred for either brain CTA or MRI in selected hospitals/diagnostic centers in Nigeria were evaluated using RadiAnt and the MicroDicom viewer software applications. A retrospective descriptive research design was adopted with approval from the federal health research ethics committee. Direct measurement of luminal diameter of major arteries of the circle of Willis was done using SPSS version 25 at P < 0.05. Results: From the 340 images assessed, 256 (75.29%) patients had ischemic stroke with luminal diameter of arteries of the circle of Willis ranged from 1 mm to >3 mm while 84 (24.71%) patients were without stroke with luminal diameter ranged from 1 mm to 2.11 mm (P < 0.05). Conclusion: Patients with stroke have larger luminal diameter of arteries that form the circle of Willis when compared to patients without stroke. The study has established for the 1st time, luminal diameter of circle of Willis that may be an index in the sampled Nigerian population.