Myocardial extracellular volume fraction quantification based on T1 mapping at 3 T: quality optimization by contour-based registration and segmental analysis

Acta Radiologica, vol. 64, pp. 80–89

Abstract

Background Myocardial extracellular volume fraction (ECV) assessment can be affected by various technical and subject-related factors. Purpose To evaluate the role of contour-based registration in quantification of ECV and investigate normal segment-based myocardial ECV values at 3T. Material and Methods Pre- and post-contrast T1 mapping images of the left ventricular basal, mid-cavity, and apical slices were obtained in 26 healthy volunteers. ECV maps were generated using motion correction with and without contour-based registration. The image quality of all ECV maps was evaluated by a 4-point scale. Slices were dichotomized according to the occurrence of misregistration in the source data. Contour-registered ECVs and standard ECVs were compared within each subgroup using analysis of variance for repeated measurements and generalized linear mixed models. Results In all three slices, higher quality of ECV maps were found using contour-registered method than using standard method. Standard ECVs were statistically different from contour-registered ECVs in global (26.8% ± 2.8% vs. 25.8% ± 2.4%; P = 0.001), mid-cavity (25.4% ± 3.1% vs. 24.3% ± 2.5%; P = 0.016), and apical slices (28.7% ± 4.1% vs. 27.2% ± 3.4%; P = 0.010). In the misregistration subgroups, contour-registered ECVs were lower with smaller SDs (basal: 25.2% ± 1.8% vs. 26.7% ± 2.6%; P = 0.038; mid-cavity: 24.4% ± 2.3% vs. 26.8% ± 3.1%; P = 0.012; apical: 27.5% ± 3.6% vs. 29.7% ± 4.5%; P = 0.016). Apical (27.2% ± 3.4%) and basal-septal ECVs (25.6% ± 2.6%) were statistically higher than mid-cavity ECV (24.3% ± 2.5%; both P < 0.001). Conclusion Contour-based registration can optimize image quality and improve the precision of ECV quantification in cases demonstrating ventricular misregistration among source images.

Authors 5

1. Ling Lin Aachen Department of Radiology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands

2. Chao Zhou corresponding

   Eighth Affiliated Hospital of Sun Yat-sen University

   Affiliation as printed

   Department of Radiology, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, PR China

3. Qiuxia Xie

   Eighth Affiliated Hospital of Sun Yat-sen University

   Affiliation as printed

   Department of Radiology, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, PR China

4. Qian Tao Aachen Department of Radiology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands

5. Hildo J. Lamb Aachen Department of Radiology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands