SBIR/STTR Research Award

SBIR Phase I:Digitizing The Pathologist In The Operating Room

Award identifier 4031d76f39744fe4ce9f8a8323202bd6ec3d9fac63f2c527e46c70814847bbf9Awarding agency National Science Foundation

Award amount

$256,000

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
SURGIVANCE INC.
Proposal award date
2022-01-15
Contract end date
2023-12-31
UEI
JH4EDZ5CQZD5
Solicitation number
NSF 21-562
Topic code
DH

Research abstract

The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the quality and reproducibility of cancer diagnosis and margin screening.Surgery currently represents the best opportunity for curing invasive cancers but is limited by modern pathology methods. Mohs surgery is the treatment of choice for skin cancer because it results in the highest cure rates, but it often takes place in stages, extending surgical procedures. The use of ex vivo confocal microscopy (XVM) is potentially faster, less costly, and inherently both 3-D and digitized, with benefits including: 1) enhanced accuracy, precision, and margin control via enriched 3D information content and simplified specimen orientation maintenance, decreasing error and improving functional outcomes; 2) decreased duration of open surgical wounds potentially reducing the rate of complications; and (3) enhanced and accelerated surgical workflows.This Small Business Innovation Research (SBIR) Phase I project aims to improve Mohs surgery and other margin screening applications. Using confocal image processing software, the proposed software will improve current pathology processing methods by enabling rapid processing and re-coloring of XVM images, visualization without the need for retraining, and automated detection of residual tumor at the patient’s bedside, all within minutes. The research described here will result in the production of a fully functional and robust software product through the following development projects: 1) Artificial intelligence (AI)-based software for image preprocessing and colorization/enhancement, and 2) AI-based software for automated identification of key morphological features and diagnosis of basal cell and squamous cell carcinoma. The proposed technology will streamline cancer specimen processing, ultimately improving patient outcomes.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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

4 SBIR/STTR records share this UEI (2019–2025). Reported award amounts total $3,754,605. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

National Science Foundation

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