# Harnessing Coded Ptychography to Deliver AI-powered Evaluation of Unstained Lung Biopsies at the Point-Of-Care

> **NIH NIH R43** · PATHWARE INC. · 2023 · $95,567

## Abstract

The parent Phase I SBIR grant aims to analyze quantitative phase imaging of lung FNAs
using coded ptychography microscopy captured at different wavelengths of light
(Specific Aim #1), and demonstrate that Al can correctly detect cells on unstained phase
images (Specific Aim #2). Engaging the supplementee, Arianna Pryor, to directly support
specific aim #2 is expected to allow us to pursue a more diverse solution space for Al
model development to detect cells on the unstained QPI imaging, resulting in a more
robust solution and amplifying the results and impact of the parent grant. Ms. Pryer's
experience in Al model development for lung cytology, in conjunction with her education
in biomedical engineering makes her an ideal candidate for the project. Additionally, the
technical experience and mentoring, direct clinician interactions and entrepreneurial
experience gained through working in a startup directly supports her growth and future
career goals.

## Key facts

- **NIH application ID:** 10740674
- **Project number:** 3R43CA278604-01S1
- **Recipient organization:** PATHWARE INC.
- **Principal Investigator:** Torsten Lyon
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $95,567
- **Award type:** 3
- **Project period:** 2023-02-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10740674

## Citation

> US National Institutes of Health, RePORTER application 10740674, Harnessing Coded Ptychography to Deliver AI-powered Evaluation of Unstained Lung Biopsies at the Point-Of-Care (3R43CA278604-01S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10740674. Licensed CC0.

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