AIMC Topic: Middle Cerebral Artery

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Comparative analysis of retinal and cerebral vascular responses to CO₂ using Doppler optical coherence tomography and transcranial Doppler ultrasound.

Physics in medicine and biology
Access to blood flow data in cerebral and retinal vascular beds is crucial for diagnosing cerebrovascular diseases. This study addresses two technological gaps: (1) simultaneous recording of vascular responses in the brain and eye by integrating tran...

Deep Learning-Based Automated Detection of the Middle Cerebral Artery in Transcranial Doppler Ultrasound Examinations.

Ultrasound in medicine & biology
OBJECTIVE: Transcranial Doppler (TCD) ultrasound has significant clinical value for assessing cerebral hemodynamics, but its reliance on operator expertise limits broader clinical adoption. In this work, we present a lightweight real-time deep learni...

Longitudinal twin growth discordance patterns and adverse perinatal outcomes.

American journal of obstetrics and gynecology
BACKGROUND: Growth discordance in twin pregnancies is associated with increased perinatal morbidity and mortality, yet the patterns of discordance progression and the utility of Doppler assessments remain underinvestigated.

Robotic Assisted Transcranial Doppler Monitoring in Acute Neurovascular Care: A Feasibility and Safety Study.

Neurocritical care
BACKGROUND: Transcranial color Doppler (TCD) is currently the only noninvasive bedside tool capable of providing real-time information on cerebral hemodynamics. However, being operator dependent, TCD monitoring is not feasible in many institutions. R...

MCAS-GP: Deep Learning-Empowered Middle Cerebral Artery Segmentation and Gate Proposition.

IEEE/ACM transactions on computational biology and bioinformatics
With the fast development of AI technologies, deep learning is widely applied for biomedical data analytics and digital healthcare. However, there remain gaps between AI-aided diagnosis and real-world healthcare demands. For example, hemodynamic para...

Multi-parameter MRI-Based Machine Learning Model to Evaluate the Efficacy of STA-MCA Bypass Surgery for Moyamoya Disease: A Pilot Study.

Journal of imaging informatics in medicine
Superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery represents the primary treatment for Moyamoya disease (MMD), with its efficacy contingent upon collateral vessel development. This study aimed to develop and validate a machi...

Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.

PloS one
A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeoning potential with machine learning applications in studies predicting gestational age and vascular ag...

Assistance from Automated ASPECTS Software Improves Reader Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with...

Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke
BACKGROUND AND PURPOSE: Reliable recognition of large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) may accelerate identification of endovascular treatment candidates. We aim to validate a machine learning algorithm (MethinksLVO) t...

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

Japanese journal of radiology
PURPOSE: To evaluate the usefulness of deep learning-assisted diagnosis for identifying hyperdense middle cerebral artery sign (HMCAS) on non-contrast computed tomography in comparison with the diagnostic performance of neuroradiologists.