Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular

Jannike Nickander1, Magnus Lundin1, Goran Abdula1

  • 1Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.

Insights

Correcting native myocardial T1 measurements for blood R1 and R1* improves precision by ~13%. This enhancement in myocardial T1 analysis can aid disease detection and reduce sample size requirements for clinical research.

Area of Science:

  • Cardiovascular Imaging
  • Magnetic Resonance Imaging
  • Biomedical Engineering

Background:

  • Myocardial native T1 measurements are susceptible to intramyocardial blood, leading to reduced precision.
  • Blood T1 variability complicates accurate myocardial T1 assessment.
  • A correction method is needed to improve the precision of myocardial T1 measurements.

Purpose of the Study:

  • To investigate the impact of intramyocardial blood on myocardial T1 measurements.
  • To develop and validate a correction model for native myocardial T1 using blood R1 and R1*.
  • To assess the improvement in measurement precision and potential reduction in sample size.

Main Methods:

  • A cohort of 400 patients undergoing cardiac MRI (CMR) was divided into derivation and validation groups.
  • Native myocardial T1, blood T1, and T1* were measured using a Modified Look-Locker inversion recovery (MOLLI) sequence.
  • A multivariate linear regression model was used to correct myocardial T1 based on blood R1, R1*, or hematocrit.

Main Results:

  • Blood R1, R1*, and hematocrit showed significant correlations with myocardial T1, confirming blood influence.
  • Correction using blood R1 and R1* reduced myocardial T1 standard deviation by ~13% in both cohorts.
  • This reduction in variability suggests a potential 23% decrease in sample size for detecting T1 differences.

Conclusions:

  • Correcting native myocardial T1 for blood R1 and R1* enhances measurement precision.
  • Improved precision can lead to better disease detection in cardiovascular conditions.
  • The developed correction method may reduce sample size needs for future clinical research.
Abstract