Rapid automated breast lump diagnosis without a radiologist or sonographer
Official title: Rapid Automatic Diagnosis of Palpable Breast Lumps Without a Radiologist or Sonographer
Funded at University of Rochester · NIH-11624472 · Data updated 2026-11-12
A new AI-powered ultrasound tool helps determine if a palpable breast lump is likely benign or malignant, using a simplified technique that can be used by people with minimal ultrasound training.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Rochester NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project start | September 1, 2026 |
| Project end | June 30, 2028 |
| Funding year | 2026 |
| Award (this year) | $56,270 |
| NIH project number | 3R21TW013363-01S1 |
| Project ID | NIH-11624472 on NIH RePORTER |
Who could benefit from this research
✓Could help
Women with palpable breast lumps in medically underserved regions who can undergo breast ultrasound and follow-up recommendations.
✕Less likely to help
Individuals without palpable breast abnormalities or those unable to participate in ultrasound-based evaluation.
What this research studies
This project aims to use a standardized, non-expert-friendly ultrasound sweeping method together with AI to quickly assess palpable breast lumps. It will compare the automated VSI-AI system to the standard ultrasound approach in diagnosing lumps and guiding next steps. The goal is to bring timely breast assessments to medically underserved areas where access to radiologists and sonographers is limited. The study will recruit women with palpable breast abnormalities in Peru, collect imaging and clinical data, and iteratively refine the AI algorithm for accurate classification and follow-up recommendations.
Why it matters
Potential benefit: If successful, the approach could speed up breast lump evaluation in underserved settings and reduce delays in diagnosis.
How similar studies have gone: Previous work shows AI and standardized imaging can aid in image interpretation, but this exact VSI+AIfusion for rapid breast assessment in low-resource settings is innovative and exploratory.
Where this research is happening
-
University of Rochester
Rochester, United States Active
Researchers
- Principal investigator: Castaneda, Benjamin — University of Rochester
- Study coordinator: Castaneda, Benjamin
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.