Artificial Neural Network for Predicting the Safe Temporary Artery Occlusion Time in Intracranial Aneurysmal Surgery.

BACKGROUND: Temporary artery clipping facilitates safe cerebral aneurysm management, besides a risk for cerebral ischemia. We developed an artificial neural network (ANN) to predict the safe clipping time of temporary artery occlusion (TAO) during intracranial aneurysm surgery. METHOD: We devised a three-layer model to predict the safe clipping time for TAO. We considered age, the diameter of the right and left middle cerebral arteries (MCAs), the diameter of the right and left A1 segment of anterior cerebral arteries (ACAs), the diameter of the anterior communicating artery, mean velocity of flow at the right and left MCAs, and the mean velocity of flow at the right and left ACAs, as well as the Fisher grading scale of brain CT scans as the input values for the model. RESULTS: This study included 125 patients: 105 patients from a retrospective cohort for training the model and 20 patients from a prospective cohort for validating the model. The output of the neural network yielded up to 960 s overall safe clipping time for TAO. The input values with the greatest impact on safe TAO were mean velocity of blood at left MCA and left ACA, and Fisher grading scale of brain CT scan. CONCLUSION: This study presents an axillary framework to improve the accuracy of the estimated safe clipping time interval of temporary artery occlusion in intracranial aneurysm surgery.

A simple technique for morphological measurement of cerebral arterial circle variations using public domain software (Osiris).

This article describes a straightforward method to measure the dimensions and identify morphological variations in the cerebral arterial circle using the general-purpose software program Osiris. This user-friendly and portable program displays, manipulates, and analyzes medical digital images, and it has the capability to determine morphometric properties of selected blood vessels (or other anatomical structures) in humans and animals. To ascertain morphometric variations in the cerebral arterial circle, 132 brains of recently deceased fetuses, infants, and adults were dissected. The dissection procedure was first digitized, and then the dimensions were measured with Osiris software. Measurements of each vessel's length and external diameters were used to identify and classify morphological variations in the cerebral arterial circle. The most commonly observed anatomical variations were uni- and bilateral hypoplasia of the posterior communicating artery. This study demonstrates that public domain software can be used to measure and classify cerebral arterial circle vessels. This method could be extended to examine other anatomical regions or to study other animals. Additionally, knowledge of variations within the circle could be applied clinically to enhance diagnostic and treatment specificity.