SBIR/STTR Research Award

Development and evaluation of a combined X-ray transmission and diffraction imaging system for pathology

Award identifier 5bc1fbfbd40ac27e78c47b4b2516ca5478e5a32be3b5b265ce355501c72315e1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,811,280

Program and phase

SBIR · Phase II

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
QUADRIDOX INC.
Proposal award date
2023-09-08
Contract end date
2025-08-31
UEI
J8EKVLUY96J9
Solicitation number
PA22-176
Topic code
NIBIB

Research abstract

ABSTRACT Pathology, which plays a vital role in clinical diagnosis, faces numerous challenges that impact its efficacy. For example, resected specimens often require preparing and analysis of as many as 30-40 slide blocks under a microscope until the disease is confirmed; selection of slices for slide preparation uses subjective methods such as palpation, which depend greatly on the skill of the individual performing the assessment and introduces inconsistency in the clinical process; and for each slide block examined, analysis and annotation requires manual observation of every microscopic region of the tissue. As a result, most pathology evaluations often take 1-3 weeks to analyze samples and reach a conclusion regarding potential cancers. An added challenge is that insurance reimbursements are capped per case regardless of the number of slide blocks processed, with any additional costs being absorbed by the hospital. Consequently, hospitals must balance the trade-off between minimizing the number of slices (for economic viability) and not compromising diagnostic care. These challenges affect not only clinical pathology but also research involving pathology specimens and tissue selection for biobanking. There is a critical need to eliminate subjectivity, reduce pathologists’ workload, and increase throughput in histological analysis. We propose to meet this need by developing a new technology called X-ray diffraction imaging (XRDI), which can scan any number of surgically resected, sliced pathology specimens and automatically indicate the likelihood and location of disease in each slice within minutes. In collaboration with Duke University, we previously built a research prototype XRDI system and demonstrated its utility by scanning and evaluating 300 breast cancer slices with high accuracy and resolution. In this direct-to-phase-II SBIR application, we will now construct a new clinical version of the XRDI scanner that is affordable, reliable, and accurate, and can be directly integrated into the clinical pathology workflow. We will build the scanner, test and evaluate its performance, and demonstrate its utility through field-testing in collaboration with clinical pathology laboratories in the US. This project will provide a first-of-its-kind, commercially feasible XRDI scanner for rapid, non-destructive imaging of pathology specimens with the ability to inform pathologists about the presence and location of cancer within the different tissue slices. The proposed clinical scanner will enable: 1) analysis of the whole slice volume of the specimen rather than a few microns at the surface of a subset of the slices, which is the current standard of care process using microscopy, 2) quantitative identification of disease based on XRD information obtained directly from the tissue, and 3) slice selection based on quantitative, reproducible measurements, thereby eliminating user-related subjectivity. Importantly, it would significantly speed up pathology workflow, providing decisions within hours instead of days, and improve the productivity and profitability of pathology labs by reducing the number of slide blocks analyzed per case.

Technology keywords

Not reported

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.