SVU 2025 Annual Conference Research Grant Recipient Session-SVU 2025 Annual Conference Research Grant Recipient Session

Video Transcription

Video Summary

The SVU research grant session showcases innovative studies advancing vascular ultrasound in patient care. Lindsey Ferrero presented a pilot study on AI-driven automation to enhance vascular ultrasound reporting. The study demonstrated AI reduced reporting time by 28%, improved report timeliness, and decreased errors by automating data extraction from imaging machines, addressing workforce shortages and manual data entry burdens.<br /><br />Sumit Senka discussed the utility of deep femoral artery (DFA) volume flow as a correlate for superficial femoral artery peripheral artery disease (SFA-PAD). They found DFA volume flow significantly higher in patients with PAD, suggesting its potential as a novel, non-invasive marker for PAD severity and management.<br /><br />Karina Newhall presented research on machine learning to identify patients with stable carotid stenosis, aiming to optimize surveillance strategies. Their model accurately predicted non-progressive disease, potentially reducing unnecessary imaging and resource utilization by identifying low-risk patients.<br /><br />Somayee Shahsabarani introduced a novel approach linking vestibular dysfunction with cerebrovascular dynamics, investigating fall risks in older adults. Using transcranial Doppler ultrasound to study blood flow patterns related to otolith organ function, this research hopes to develop biomarkers for early diagnosis and intervention to prevent falls.<br /><br />Collectively, these studies highlight the integration of AI, machine learning, and novel vascular biomarkers to improve diagnostic efficiency, patient stratification, and preventative care in vascular ultrasound.

Keywords

vascular ultrasound

AI automation

vascular ultrasound reporting

deep femoral artery volume flow

peripheral artery disease

machine learning

carotid stenosis surveillance

vestibular dysfunction

transcranial Doppler ultrasound