Cerebral hemodynamic response to generalized anxiety disorder

Area of Science:

• Neuroscience
• Medical Imaging
• Cardiovascular Physiology

Background:

• Generalized anxiety disorder (GAD) remains understudied compared to other anxiety disorders.
• Extracranial cervical artery hemodynamics in GAD are not well understood.

Purpose of the Study:

• To compare cervical blood flow velocities in untreated chronic GAD patients versus healthy individuals.
• To investigate the potential of machine learning models for GAD diagnosis using cervical artery data.

Main Methods:

• Doppler ultrasonography was used to assess blood flow velocities in the common carotid artery (CCA), internal carotid artery (ICA), and vertebral artery (VA).
• Thirty-eight GAD patients and thirty-eight healthy controls were included.
• Machine learning models were trained using cervical artery characteristics.

Main Results:

• GAD patients exhibited significantly increased peak systolic velocity (PSV) in bilateral CCA and ICA.
• GAD patients showed significantly decreased end-diastolic velocity (EDV) in bilateral CCA, VA, and left ICA.
• The Resistive Index (RI) was significantly elevated in GAD patients. A Support Vector Machine (SVM) model demonstrated high accuracy in GAD identification.

Conclusions:

• Generalized anxiety disorder is associated with hemodynamic changes in extracranial cervical arteries.
• Machine learning models show promise for GAD diagnosis, warranting further research with larger datasets.