Background: The incidence of Large Vessel Acute Ischemic Stroke (AIS) has been estimated to be approximately 250,000 patients per year in the United States and is the leading cause of disability and fifth leading cause of death. Although interventional (stentriever) and pharmaceutical (tPA) treatments exist for large vessel occlusion (LVO), their use is limited due to the short time window from symptom onset that these treatments are indicated to be administered in. Moreover, recent estimates suggest only approximately 10% of eligible patients receive interventional treatment which has shown to lead to better outcomes in several worldwide RCTs. In order for intervention to be successful, a standardized, quantitative, field based (pre- hospital) diagnostic tool is needed to improve LVO identification and ensure rapid transfer to a capable medical facility. Currently, the gold standard for stroke diagnosis is CT angiogram (CTA) which is limited to in-hospital use or a low number of mobile stroke ambulances, all costing multi-millions of dollars, requiring expert operators and IV injection of iodine-rich contrast material. Additionally, the clinical stroke assessment scales (RACE, LAMS, CPSS) used in the field although low cost and non-invasive have proven unreliable due to training requirements and low inherent accuracies, with SEN and SPE ranging in a recent study from 0.50-0.64 and 0.83-0.92, respectively. Project Goals and Broad Specific Aims: Validate a biomarker for LVO assessment which can be measured and displayed with a fully automated, non-invasive, transcranial Doppler (TCD) robotic system with performance at or exceeding 90% ROC?AUC (targeting SEN & SPE greater than 90%) to standard of care imaging. Complete a clinical study where Arm 1 demonstrates technical feasibility of the system in acute stroke settings and Arm 2 demonstrates safety, no detrimental change to standard of care, and collect robust data to submit to the FDA an IFU expansion to drive clinical care using our robotic system and the biomarker. The ultimate and future goal of this work is to use the automated device and validated VCI biomarker in a prehospital setting to show improved clinical outcomes after stroke onset due to improved prehospital triage. This work is critical to first validate the biomarker against gold standard CTA, which must be completed in a hospital, to ultimately be used in the pre-hospital setting. Longterm Objective: CTA will not be replaced in comprehensive stroke centers and we do not aim to use our technology to do this in comprehensive centers with CTA. Instead, our technology will be available in centers without CTA or MRA and ultimately in the prehospital environment. The goal of our company is to show that our lower cost, portable, non invasive technology can be used to measure a valid biomarker of large vessel occlusion that can be performed outside of a comprehensive stroke center. The first step is to validate the biomarker, in a center with CTA as a gold standard, which is the ultimate goal of this work.

Public Health Relevance

The incidence of Large Vessel Acute Ischemic Stroke (AIS) has been estimated to be approximately 250,000 patients per year in the United States and is the leading cause of disability and fifth leading cause of death. This work will validate a biomarker for large vessel occlusion (LVO) assessment which can be measured and displayed with a fully automated, non-invasive, transcranial Doppler (TCD) robotic system with performance at or exceeding 90% ROC?AUC (targeting SEN & SPE greater than 90%) to standard of care imaging. The ultimate goal of this work is to use the automated device and validated LVO biomarker in a prehospital setting to show improved clinical outcomes after stroke onset due to improved prehospital triage.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Business Innovation Research (SBIR) Cooperative Agreements - Phase II (U44)
Project #
1U44NS109952-01A1
Application #
9980675
Study Section
National Institute of Neurological Disorders and Stroke Initial Review Group (NSD)
Program Officer
Pelleymounter, Mary A
Project Start
2020-07-01
Project End
2022-05-31
Budget Start
2020-07-01
Budget End
2021-05-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Neural Analytics, Inc.
Department
Type
DUNS #
078766464
City
Los Angeles
State
CA
Country
United States
Zip Code
90064