# Cardiac Magnetic Resonance for Tissue Characterization Based Risk Stratification of Cardiopulmonary Symptoms, Effort Tolerance, and Prognosis Among COVID-19 Survivors

> **NIH NIH R01** · WEILL MEDICAL COLL OF CORNELL UNIV · 2024 · $625,046

## Abstract

PROJECT SUMMARY / ABSTRACT
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic. Despite substantial short term mortality
risk, the overwhelming majority of infected patients survive acute illness, resulting in a growing population at risk
for long term events. Cardiopulmonary symptoms are common after COVID-19, as shown by survey data
reporting fatigue (53%), dyspnea (43%), and worsened quality of life (44%) 60 days after acute infection, but
mechanism and time course of symptoms are unknown. Recent studies and our own preliminary data have
shown myocardial tissue abnormalities on cardiac magnetic resonance (CMR) to be common in COVID-19
survivors – raising the possibility that symptoms stem from viral effects on the heart. However, CMR findings to
date are limited by small size and clinical data susceptible to referral bias, raising uncertainty as to
generalizability. It is also unknown whether altered myocardial tissue properties (fibrosis, edema) impact clinical
outcomes.
The central hypothesis of our research is that CMR tissue characterization will be incremental to clinical
assessment and cardiac contractile function for prediction of long-term cardiopulmonary symptoms, effort
tolerance, and prognosis among COVID-19 survivors. To test this, we will study patients from an active multi-
ethnic NYC registry of COVID-19 survivors: We have already leveraged echocardiographic imaging data from
this registry to show that (1) adverse cardiac remodeling (dilation, dysfunction) markedly augments short term
mortality, (2) COVID-19 acutely alters left and right ventricular remodeling, and (3) many patients who survive
initial hospitalization for COVID-19 have adverse cardiac remodeling – including 40% with left ventricular (LV)
dysfunction and 32% with adverse RV remodeling (dilation, dysfunction): Our current proposal will extend
logically on our preliminary data to test whether CMR tissue characterization provides incremental predictive
utility with respect to reverse remodeling and prognosis. At least 510 COVID-19 survivors will be studied. Echo
will be analyzed at time of and following COVID-19 for longitudinal remodeling, as will CMR at pre-specified (6-
12, 36 month) follow-up timepoints. Established and novel CMR technologies will be employed, including
assessment of cardiac and lung injury, high resolution (3D) myocardial tissue characterization, and
cardiopulmonary blood oxygenation. In parallel, QOL, effort tolerance (6-minute walk test), biomarkers, and
rigorous follow-up will be obtained to discern clinical implications and relative utility of imaging findings. Aim 1
will identify determinants of impaired quality of life and effort intolerance among COVID-19 survivors. Aim 2 will
test whether myocardial tissue injury on CMR is associated with impaired contractility, and whether fibrosis
predicts contractile recovery. Aim 3 will determine whether myocardial tissue injury is independently associated
with adverse prognosis (new o...

## Key facts

- **NIH application ID:** 10904011
- **Project number:** 5R01HL159055-04
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Jiwon Kim
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $625,046
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10904011

## Citation

> US National Institutes of Health, RePORTER application 10904011, Cardiac Magnetic Resonance for Tissue Characterization Based Risk Stratification of Cardiopulmonary Symptoms, Effort Tolerance, and Prognosis Among COVID-19 Survivors (5R01HL159055-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10904011. Licensed CC0.

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