AIMC Topic: Cerebrovascular Circulation

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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...

Cortical layer multi-parameter analysis of neurovascular impairments in AD/ADRD rodent model with in vivo optical imaging.

Translational neurodegeneration
BACKGROUND: Neurovascular biomarkers have the potential to enhance early diagnosis of Alzheimer's disease (AD) and AD-related dementias (ADRD), as cerebrovascular alterations often precede neurodegeneration. However, their clinical application remain...

More insights into disruption and decoupling of individual metabolic connectomes in Parkinson's disease.

Progress in neuro-psychopharmacology & biological psychiatry
PURPOSE: Metabolic disturbances are hallmark pathological features of Parkinson's disease (PD) and can be noninvasively captured by arterial spin labeling (ASL). However, the metabolic pattern of disconnections beyond regional alterations remains sca...

A multimodal multitask deep learning model for predicting stroke lesion and functional outcomes using 4D CTP imaging and clinical metadata.

Scientific reports
Acute ischemic stroke is a major global health challenge, leading to long-term disability or death without timely intervention. Among neuroimaging modalities, spatio-temporal (4D) computed tomography perfusion (CTP) is widely used to assess cerebral ...

Personalized MRI-based characterization of subcortical anomalies in Ataxia-Telangiectasia using deep-learning.

PloS one
BACKGROUND: Cerebellar atrophy is a known feature of ataxia-telangiectasia (A-T). However, basal ganglia dysfunction contributing to extrapyramidal movement disorders in A-T remains understudied.

Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics.

BMC medical imaging
INTRODUCTION: Accurate early prognostic prediction for acute ischemic stroke (AIS) is essential for guiding personalized treatment. This study aimed to assess the predictive value of radiomics features from whole-brain and infarct cerebral blood flow...

Reconstructing cerebral hemodynamics from sparse data using Neural Operator Transformers.

Computers in biology and medicine
Cardiovascular diseases remain a major cause of mortality and disability, underscoring the need for improved analysis of brain hemodynamics. The Circle of Willis plays a crucial role in maintaining cerebral blood flow; however, conventional measureme...

Vascular segmentation of functional ultrasound images using deep learning.

Computers in biology and medicine
Segmentation of medical images is a fundamental task with numerous applications. While MRI, CT, and PET modalities have significantly benefited from deep learning segmentation techniques, more recent modalities, like functional ultrasound (fUS), have...

perfDSA: Automatic Perfusion Imaging in Cerebral Digital Subtraction Angiography.

International journal of computer assisted radiology and surgery
PURPOSE: Cerebral digital subtraction angiography (DSA) is a standard imaging technique in image-guided interventions for visualizing cerebral blood flow and therapeutic guidance thanks to its high spatio-temporal resolution. To date, cerebral perfus...

A deep learning approach for quantifying CT perfusion parameters in stroke.

Biomedical physics & engineering express
. Computed tomography perfusion (CTP) imaging is widely used for assessing acute ischemic stroke. However, conventional methods for quantifying CTP images, such as singular value decomposition (SVD), often lead to oscillations in the estimated residu...