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E-188 The influence of artificial intelligence tools on enhancing patient follow-up compliance for unruptured intracranial aneurysms: insights from Viz Aneurysm® software
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  1. H Kaur1,
  2. I Yuki1,
  3. J Soun2,
  4. T Nguyen1,
  5. C Jin1,
  6. J Xu1,
  7. K Golshani1,
  8. F Hsu1,
  9. S Suzuki1
  1. 1Neurosurgerey, UC Irvine Medical Center, Orange, CA
  2. 2Radiology, UC Irvine Medical Center, Orange, CA

Abstract

Introduction Non-invasive imaging modalities such as CT Angiography (CTA) are increasingly being used to assess intracranial vasculature, leading to more frequent detection of incidental unruptured intracranial aneurysms (UIA). This increased detection is particularly notable in patients undergoing imaging for head injuries or suspected strokes, as recommended by treatment guidelines. Individuals with unruptured aneurysms are often referred to specialists for rupture risk assessment and treatment/observation. Recently, artificial intelligence (AI) based software for aneurysm detection has been introduced as an adjunctive tool for diagnosis. This software also can be used as a tracking system of these patients to prevent non-compliance, although the impact of AI software on patient adherence to follow-up care is unclear. Therefore, we conducted a retrospective analysis of patients with suspected aneurysms identified by an AI-based UIA software and assessed its utility in improving patient follow-up compliance.

Methods Using an AI-based UIA detection software, Viz Aneurysm®, we identified patients with UIAs between July 1, 2023, and December 31, 2023. After conducting the medical chart reviews of each patient, we selected the ones who were confirmed to have UIA based on the neuroradiologists’ reports. For those with newly diagnosed UIA, we investigated if the patient had proper follow-up scheduled with a specialist, such as a neurosurgeon, neurologist, or neuroradiologist. After the discharge, each patient was monitored using the patient tracking function of Viz Aneurysm®. Post diagnosis follow-up compliance was evaluated and was compared with the conventionally performed post-diagnosis patient referral system.

Results A total of 3,499 CTAs were conducted in our institution during the study period. 118 patients (3%) had at least one potential aneurysm detected by Viz Aneurysm®. Of these, the final radiology report validated the presence of aneurysms in 89 patients (75%). 65 patients (73%) had newly diagnosed aneurysm. 8 patients (9%) had ruptured aneurysms and 2 patients (2%) resulted in mortality during hospitalization. For the patients with UIA who opted for conservative management, 61 patients (69%) were enrolled in the standard post-diagnosis referral system and scheduled for follow-up care with a specialist. However, 24 patients (27%) who were lost to follow-up in the conventional referral system were discovered by the Viz Aneurysm®. The reasons for loss to follow-up of these patients were 1) lack of appropriate follow-up referrals for 16 patients (18%), 2) insurance or different health care network issues for 5 patients (6%), and 3) personal cancellation for 3 patients (3%).

Conclusion AI-based UIA detection software may be helpful in identifying patients who are lost to follow-up visits and improving the follow-up adherence rate.

Disclosures H. Kaur: None. I. Yuki: None. J. Soun: None. T. Nguyen: None. C. Jin: None. J. Xu: None. K. Golshani: None. F. Hsu: None. S. Suzuki: None.

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