# Acute Ischemic Tissue Evolution and Implications for Imaging Selection of Patients for Therapy and Clinical Trials using Sex-Disaggregated Data

> **NIH NIH R21** · UNIVERSITY OF TEXAS AT AUSTIN · 2022 · $435,875

## Abstract

Current clinical practice treats stroke without regard to potential sex differences. Is this the best approach?
Standard of care image processing thresholds are uniformly applied across all patients to identify potentially
salvageable versus irreversibly infarcted brain tissue. However, women experience ischemic stroke differently
than men with known physiological differences originating at the cellular level. As such, the long-term research
goal is to characterize acute ischemic tissue evolution for men and women in the context of personalized imaging
selection of patients for acute reperfusion therapy and trials.
It is well established that the benefit of treatment for acute ischemic stroke declines with longer onset to
treatment times. Delayed patient presentation is the major treatment limitation with only one-third of all acute
ischemic stroke patients presenting within 8 hours of symptoms. Sex disparities exist in ischemic stroke. Women
have worse functional and patient-reported outcomes. Although women's higher age, greater stroke severity,
and poorer health at the time of stroke partially explain these disparities, a substantial knowledge gap remains.
Women present more often with treatable ischemic strokes than men. Women also have better-functioning
collateral networks and slower infarct growth untreated. Why do women suffer from more disability if they are
presenting with favorable imaging profiles? Does this paradox stem from the imaging-defined thresholds used
to identify infarcted tissue and potentially salvageable tissue? Could these thresholds differ for men and women?
Recent trials have demonstrated the utility of imaging thresholds to identify patients that will respond to treatment
If the optimal thresholds for ischemic core, salvageable penumbra, and time from onset are different for men and
women, are we denying patients the benefits of treatment by not incorporating sex-specific treatment thresholds
into treatment selection algorithms?
In line with NINDS's mission to seek fundamental knowledge about the brain and nervous system and to use
that knowledge to reduce the burden of neurological disease, this project proposes to addresses these
knowledge gaps and test the hypothesis that acute ischemic tissue evolution is different between men and
women. Imaging features of cerebral hemodynamics will be directly related to infarct evolution to evaluate sex
differences in acute ischemic stroke in the context of imaging selection of patients for acute reperfusion therapy
and trials. This will address the paucity of studies on sex differences in ischemic stroke, overcoming limitations
in translational relevance of clinical trials. The proposed project will result in generalizable evidence on the
influence of sex on ischemic tissue evolution and inform on the selection of imaging-based thresholds currently
used to identify infarcted tissue and potentially salvageable tissue. Establishing evidence of sex differences in
objective imagin...

## Key facts

- **NIH application ID:** 10575791
- **Project number:** 1R21NS130494-01
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Adrienne Nicole Dula
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $435,875
- **Award type:** 1
- **Project period:** 2022-09-21 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10575791

## Citation

> US National Institutes of Health, RePORTER application 10575791, Acute Ischemic Tissue Evolution and Implications for Imaging Selection of Patients for Therapy and Clinical Trials using Sex-Disaggregated Data (1R21NS130494-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10575791. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*