SBIR Phase I: A Novel Non-Invasive Intracranial Pressure Monitoring Method

Information

  • NSF Award
  • 1448525
Owner
  • Award Id
    1448525
  • Award Effective Date
    1/1/2015 - 9 years ago
  • Award Expiration Date
    6/30/2015 - 9 years ago
  • Award Amount
    $ 149,294.00
  • Award Instrument
    Standard Grant

SBIR Phase I: A Novel Non-Invasive Intracranial Pressure Monitoring Method

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to improve the treatment and decrease the high costs associated with treating patients who suffer severe traumatic brain injuries. This project aims to develop an accurate, affordable (<$100 per use) and non-invasive device to monitor a patient?s intracranial pressure following traumatic brain injury. Increased intracranial pressure can result in serious condition or death, if left untreated. However, the only available method to monitor intracranial pressure is expensive (~$10,000 per patient) and requires neurosurgery. The lack of a method to accurately screen patients to determine who needs surgery results in misdiagnoses and incorrect treatment in about 46% of patients among an estimated 50,000 patients in the US alone, and hundreds of thousands more globally. Successful commercialization of product is expected to result in savings in the range $250 million ever year to the US healthcare system.<br/><br/>The proposed project will test the feasibility of developing a non-invasive intracranial pressure (ICP) monitoring method for use outside of the neuro ICU. To develop an accurate, affordable, and non-invasive ICP monitoring device, the team will first write and validate a software framework that analyzes Cerebral Blood Flow Velocity (CBFV) waveforms. CBFV waveforms are acquired non-invasively by using transcranial Doppler (TCD) ultrasonography. In order to use CBFVs to predict ICP, two novel signal-processing methods will be developed. First, the high noise levels typical to TCD-acquired waveforms will be reduced within a machine-learning framework. Second, we will use a method to track morphological features that predict ICP from the CBFV waveform. Both these approaches to signal processing to analyze CBFV waveforms are entirely novel. This approach is expected to allow for accurate (>92% of area under the diagnostic ROC) non-invasive real time monitoring at an affordable price point that is within current reimbursement limits for TCD procedures.

  • Program Officer
    Jesus Soriano Molla
  • Min Amd Letter Date
    12/2/2014 - 10 years ago
  • Max Amd Letter Date
    12/2/2014 - 10 years ago
  • ARRA Amount

Institutions

  • Name
    Neural Analytics
  • City
    Los Angeles
  • State
    CA
  • Country
    United States
  • Address
    2440 S. Sepulveda Blvd
  • Postal Code
    900641744
  • Phone Number
    8183174999

Investigators

  • First Name
    Robert
  • Last Name
    Hamilton
  • Email Address
    robert@neuralanalytics.com
  • Start Date
    12/2/2014 12:00:00 AM

Program Element

  • Text
    SMALL BUSINESS PHASE I
  • Code
    5371

Program Reference

  • Text
    CENTERS: BIOENG & HEALTH CARE
  • Text
    BIOMEDICAL ENGINEERING
  • Code
    5345
  • Text
    SMALL BUSINESS PHASE I
  • Code
    5371
  • Text
    Biotechnology
  • Code
    8038
  • Text
    Health and Safety
  • Code
    8042