NIH-funded research R01 grant

Using AI to monitor lung fluid in sudden (acute) heart failure in the ER

Official title: An AI-Assisted Strategy for Monitoring Pulmonary Congestion in Acute Heart Failure Patients in Emergency Settings

Funded at Brigham and Women's Hospital · NIH-11267990 · Data updated 2026-11-12

This project will use an AI-assisted lung ultrasound method to track lung congestion in people who come to the emergency department with acute heart failure.

More Heart Failure research and trials

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionBrigham and Women's Hospital
NIH-funded
Lab location1 site (Boston, United States)
Project startFebruary 1, 2025
Project endJanuary 31, 2029
Funding year2026
Award (this year)$673,366
NIH project number5R01EB035679-02
Project IDNIH-11267990 on NIH RePORTER

Who could benefit from this research

Could help

Adults who present to the emergency department with symptoms of acute heart failure and suspected pulmonary congestion (shortness of breath, fluid overload) would be the intended participants.

Less likely to help

People without heart failure, those with chronic stable heart failure not seeking acute care, children, or patients unable to undergo lung ultrasound likely would not benefit from participation.

What this research studies

If you come to the ER with sudden worsening heart failure and shortness of breath, clinicians would get quick bedside lung ultrasound images while you are being treated. An AI tool would help read those images so doctors can track how much fluid is in your lungs day-to-day without waiting for slower tests. Care teams could use those real-time results to guide diuretics and other treatments to help relieve congestion before discharge. The work builds on earlier clinical studies showing lung ultrasound finds changes in congestion faster than usual measures and aims to remove the need for a specialized human reader.

Why it matters

Potential benefit: If successful, this could help clinicians find and remove lung fluid faster, lowering the chance of readmission or short-term death after an ER visit for acute heart failure.

How similar studies have gone: Prior clinical work (BLUSHED-AHF and CARVD-AHF) showed daily lung ultrasound captures congestion changes faster and can guide therapy, while the AI automation approach is a newer, building step.

Where this research is happening

  • Brigham and Women's Hospital
    Boston, United States
    Active

Researchers

  • Principal investigator: Kapur, Tina — Brigham and Women's Hospital
  • Study coordinator: Kapur, Tina

Related research

Other NIH-funded projects on the same topics.

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.