PA SECTION PAs PLAN EDUCATION, VASCULAR ‘JEOPARDY’ AT VAM

CALL IT “JEOPARDY! VISITS VAM,” complete with Daily Doubles and buzzers. But instead of “geography” or “famous artists,” all five categories will be vascular-related.

The session, “Jeopardy Cases Over Cocktails,” is for both members of the Society for Vascular Nursing and the Society for Vascular Surgery’s Physician Assistant (PA) section during this year’s VAM and the SVN Annual Conference.

Using the format of the popular Jeopardy! game show, contestants from the Society for Vascular Nursing and the Society for Vascular Surgery’s Physician Assistant (PA) Section, the contestants will compete from 3–4 p.m. Wednesday in Maryland D. “We have teams and buzzers. We have Daily Doubles and referee shirts. It should be great fun,” said Holly Grunebach, PA-C, section chair.

Then, from 12–1 p.m. Thursday, the two groups will talk about the vascular team and other topics during a lunchtime panel discussion with PAs Ricardo Morales, Erin Hanlon and Abby Keen, and nurses Katherine Hays, Gabriell Grayson and Stacy Hosenfeld. Audience members are asked to bring their questions.—Beth Bales

Aneurysmal Growth

Prediction model offers new option for forecasting AAA growth

A predictive model incorporating 3D shape features such as aneurysmal flow lumen and outer wall structure extracted from computed tomography (CT) imaging can improve the ability to predict the growth of abdominal aortic aneurysms (AAAs). By Will Date

This is according to research to be presented during this morning’s William J. von Liebig Forum (8:00–9:30 a.m., Potomac A/B) by

Anirudh Chandrashekar, DPhil, of Stony Brook Medicine, Stony Brook, New York,

who tells VS@ VAM that the research has the potential to add to existing metrics for predicting aneurysmal growth, used to inform surveillance intervals and timing for surgical intervention.

Alongside senior author Regent Lee, PhD, from University of Oxford, England, Chandrashekar and colleagues set out to develop a means of predicting aneurysm growth beyond the current gold standard—namely assessment of the diameter of the aneurysmal sac. “What we wanted to do was to develop a prediction paradigm to individualize the follow-up and risk factor management for these patients,” Chandrashekar comments. “This may better inform the timing of surgery down the line.”

The first arm of the project saw the researchers develop a deep learning process to extract and categorize geometric features of the aneurysmal sac that may be associated with AAA-growth, including curvature of the sac and surface irregularity.

The latest step of their research, which will be presented here at VAM, looks at both the lumen and outer aneurysmal wall, and how these correlate with AAA growth. “The methodology is extremely novel, and this is the first time we are incorporating the lumen in this whole decision model,” says Chandrashekar.

To test their model, the researchers have conducted a retrospective analysis of serial CT images taken during surveillance in 192 patients with infrarenal AAAs, categorising

COMMENT& ANALYSIS

TAAA