# Development of a Molecular Diagnostic to Identify Dangerous Intracranial Aneurysms

> **NIH NIH R44** · NEUROVASCULAR DIAGNOSTICS, INC. · 2024 · $1,286,865

## Abstract

Project Summary
 Intracranial aneurysm (IA) rupture is the primary cause of non-traumatic subarachnoid hemorrhage, a
catastrophic event that carries high rates of mortality (>50%) and permanent disability (>50% among survivors).
When an unruptured IA is discovered, clinicians face the difficult decision of whether or not it should be treated.
Since rupture rates are low (risk of rupture ~ 0.5-1% per year), while complication risks of intervention can be
significant, it is critical to stratify rupture risk such that the dangerous IAs are treated right away while less
dangerous ones can be periodically monitored. In clinical practice, aneurysm size has been the principal criterion
for treatment, but it is not always reliable. Recently, other clinical metrics, such as the PHASES (Population,
Hypertension, Age, Size of IA, Earlier subarachnoid hemorrhage, and Site of IA) score, which use IA
characteristics and patient demographics, have been developed and validated in attempts to better stratify risk.
However, like IA size, such risk metrics can only be accurately assessed after the patient has received digital
subtraction angiography (DSA), which is invasive, expensive ($5,000-8,500 per scan), and risky for transient or
permanent complications. Furthermore, these metrics lack information about biological differences underlying
IAs that may better discriminate high- vs low-risk cases. A blood-based diagnostic of dangerous IAs would
enable more informed IA management and could offer a low-cost, non-invasive way to monitor patients
during watchful waiting or after treatment (between follow-up imaging).
 Over the past several years, Neurovascular Diagnostics has been developing a blood-based IA diagnostic
called AneuScreenTM. During development, we found that expression differences of certain genes also stratified
IA cases by IA size in a “dose-dependent” manner, leading us to hypothesize that patients with high-risk IAs
have distinguishable gene expression patterns in their blood. In a successfully completed Phase I SBIR project,
we used whole blood transcriptomes from a modestly-sized dataset of IA patients to develop and test machine
learning classifiers of high-risk aneurysm cases (delineated by PHASES score). This model had 88% testing
accuracy, 78% sensitivity, and 95% specificity. Despite these exciting results, further work is needed to translate
this biomarker into a diagnostic test, which is the focus of this Phase II SBIR project. In Aim 1, we will validate
the genes within the IA risk biomarker in a large dataset of previously-collected blood samples that will be
subjected to RNA sequencing. In Aim 2, we will standardize the assessment of the biomarker on an established
clinical platform that utilizes qPCR and capillary electrophoresis for expression readout. The models will be re-
trained to perform well using this new output data-type. Lastly, in Aim 3, we will test the developed assay, which
we call AneuScreenTM+(or AneuScreenTM Plus), in...

## Key facts

- **NIH application ID:** 10912433
- **Project number:** 5R44NS115314-03
- **Recipient organization:** NEUROVASCULAR DIAGNOSTICS, INC.
- **Principal Investigator:** Kerry Poppenberg
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,286,865
- **Award type:** 5
- **Project period:** 2019-09-30 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10912433

## Citation

> US National Institutes of Health, RePORTER application 10912433, Development of a Molecular Diagnostic to Identify Dangerous Intracranial Aneurysms (5R44NS115314-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10912433. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*