2422725
Project Grant
Overview
Grant Description
SBIR Phase I: Aneurisk - A clinical decision support tool to manage abdominal aortic aneurysm patients - The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will provide a novel software solution that enables clinicians to potentially improve the treatment of patients with an abdominal aortic aneurysm (AAA).
Abdominal aortic aneurysm is the ballooning of a major blood vessel in the body that if left untreated can rupture, leading to almost certain (85% mortality) death.
AAA is the 13th leading cause of death (1 in 100,000) in the United States.
The current clinical standard for surgical intervention relies on measuring the diameter of the aneurysm from medical images.
This undesirable method leads up to 23.4% of patients rupturing before reaching the diameter that indicates safe, surgical intervention/repair.
Therefore, there is a need to help doctors identify and treat high-risk patients who remain below the threshold of safe aneurysm diameter.
This STTR project supports the development of a unique, artificial intelligence solution that combines aneurysm diameter with stress, strain, shape analysis, and patient information to predict future patient outcomes and aneurysm growth.
The patent-pending technology can disrupt how doctors currently watch and follow aneurysms by providing them with a risk profile to avoid dangerous rupture events, allowing them to provide the patients with the right treatment at the right time.
This Small Business Innovation Research (SBIR) Phase I project aims to develop and validate machine learning models for risk classification, growth projection, and wall stress prediction for abdominal aortic aneurysms.
Abdominal aortic aneurysm (AAA) is the 13th leading cause of death in the United States, with a mortality rate exceeding 85%.
The current clinical standard for intervention is based on the diameter of the aneurysm; however, between 7 and 23.4% of patients rupture before the threshold is reached.
The Aneurisk team is developing artificial intelligence-based tools to accelerate image, biomechanical, and morphological analyses.
Additionally, the Aneurisk team will perform cross-validation of previously trained long short-term memory recurrent neural networks to forecast diameter and a classifier that predicts patient outcomes (remain stable, eventual repair, or eventual rupture).
The toolset is effectively a method to achieve virtual surveillance to provide clinicians a method to better understand when to treat patients.
If successful, the Aneurisk approach will reduce the number of surveillance visits to track diameter, reduce patient anxiety, and reduce costly and high-mortality rupture events.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
Abdominal aortic aneurysm is the ballooning of a major blood vessel in the body that if left untreated can rupture, leading to almost certain (85% mortality) death.
AAA is the 13th leading cause of death (1 in 100,000) in the United States.
The current clinical standard for surgical intervention relies on measuring the diameter of the aneurysm from medical images.
This undesirable method leads up to 23.4% of patients rupturing before reaching the diameter that indicates safe, surgical intervention/repair.
Therefore, there is a need to help doctors identify and treat high-risk patients who remain below the threshold of safe aneurysm diameter.
This STTR project supports the development of a unique, artificial intelligence solution that combines aneurysm diameter with stress, strain, shape analysis, and patient information to predict future patient outcomes and aneurysm growth.
The patent-pending technology can disrupt how doctors currently watch and follow aneurysms by providing them with a risk profile to avoid dangerous rupture events, allowing them to provide the patients with the right treatment at the right time.
This Small Business Innovation Research (SBIR) Phase I project aims to develop and validate machine learning models for risk classification, growth projection, and wall stress prediction for abdominal aortic aneurysms.
Abdominal aortic aneurysm (AAA) is the 13th leading cause of death in the United States, with a mortality rate exceeding 85%.
The current clinical standard for intervention is based on the diameter of the aneurysm; however, between 7 and 23.4% of patients rupture before the threshold is reached.
The Aneurisk team is developing artificial intelligence-based tools to accelerate image, biomechanical, and morphological analyses.
Additionally, the Aneurisk team will perform cross-validation of previously trained long short-term memory recurrent neural networks to forecast diameter and a classifier that predicts patient outcomes (remain stable, eventual repair, or eventual rupture).
The toolset is effectively a method to achieve virtual surveillance to provide clinicians a method to better understand when to treat patients.
If successful, the Aneurisk approach will reduce the number of surveillance visits to track diameter, reduce patient anxiety, and reduce costly and high-mortality rupture events.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Pittsburgh,
Pennsylvania
15217-1904
United States
Geographic Scope
Single Zip Code
Aneurisk was awarded
Project Grant 2422725
worth $275,000
from National Science Foundation in September 2024 with work to be completed primarily in Pittsburgh Pennsylvania United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I: Aneurisk - A Clinical Decision Support Tool to Manage Abdominal Aortic Aneurysm Patients
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will provide a novel software solution that enables clinicians to potentially improve the treatment of patients with an abdominal aortic aneurysm (AAA). Abdominal aortic aneurysm is the ballooning of a major blood vessel in the body that if left untreated can rupture, leading to almost certain (85% mortality) death. AAA is the 13th leading cause of death (1 in 100,000) in the United States. The current clinical standard for surgical intervention relies on measuring the diameter of the aneurysm from medical images. This undesirable method leads up to 23.4% of patients rupturing before reaching the diameter that indicates safe, surgical intervention/repair. Therefore, there is a need to help doctors identify and treat high-risk patients who remain below the threshold of safe aneurysm diameter. This STTR project supports the development of a unique, artificial intelligence, solution that combines aneurysm diameter with stress, strain, shape analysis, and patient information to predict future patient outcomes and aneurysm growth. The patent-pending technology can disrupt how doctors currently watch and follow aneurysms by providing them with a risk profile to avoid dangerous rupture events allowing them to provide the patients with the right treatment at the right time
This Small Business Innovation Research (SBIR) Phase I project aims to develop and validate machine learning models for risk classification, growth projection, and wall stress prediction for abdominal aortic aneurysms. Abdominal aortic aneurysm (AAA) is the 13th leading cause of death in the United States, with a mortality rate exceeding 85%. The current clinical standard for intervention is based on the diameter of the aneurysm, however, between 7 and 23.4% of patients rupture before the threshold is reached. The Aneurisk team is developing artificial intelligence-based tools to accelerate image, biomechanical, and morphological analyses. Additionally, the Aneurisk team will perform cross-validation of previously trained long short-term memory recurrent neural networks to forecast diameter and a classifier that predicts patient outcomes (remain stable, eventual repair, or eventual rupture). The toolset is effectively a method to achieve virtual surveillance to provide clinicians a method to better understand when to treat patients. If successful, the Aneurisk approach will reduce the number of surveillance visits to track diameter, reduce patient anxiety, and reduce costly and high-mortality rupture events.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
DH
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 9/25/24
Period of Performance
9/15/24
Start Date
8/31/25
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2422725
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
S4X2SLK696X4
Awardee CAGE
9JTB5
Performance District
PA-12
Senators
Robert Casey
John Fetterman
John Fetterman
Modified: 9/25/24