World's First Artificial Intelligence-Based Evaluation of Rist Catheter Stability in Transradial Procedures: A...

Area of Science:

• Neuroendovascular Therapy
• Medical Device Technology
• Artificial Intelligence in Medicine

Background:

• Artificial intelligence (AI) shows potential for advancing neuroendovascular therapy through device evaluation.
• Clinical application of AI in real-world neuroendovascular procedures is currently limited.
• The transradial approach (TRA) is increasingly adopted for neuroendovascular interventions.

Purpose of the Study:

• To validate the feasibility of AI-based quantitative device evaluation during actual neuroendovascular procedures.
• To assess the stability of the Rist radial access guide catheter during flow diverter stent (FDS) placement.
• To explore the utility of AI in real-world device assessment.

Main Methods:

• Retrospective analysis of 4 cases of FDS placement using the Rist catheter via TRA.
• Tracking the Rist catheter in fluoroscopic videos using AI technology (Neuro-Vascular Assist).
• Calculating Rist movement distance as a quantitative indicator of catheter stability.

Main Results:

• All procedures were completed successfully without complications.
• Rist catheter stability was assessed, with average maximum movement distances of 3.03 mm and 1.42 mm/min.
• Quantitative measurements indicated sufficient stability of the Rist catheter for FDS procedures.

Conclusions:

• AI technology can be feasibly used for quantitative analysis of device stability in TRA procedures.
• This represents the first clinical evaluation of device function in a clinical setting using AI.
• Further studies are needed to validate these findings, but the method shows promise for real-world device evaluation and development.