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A Siemens Single-Shot T1 Mapping Sequence as an Alternative to MOLLI
Mariem Dali1, Narjes Benameur1, Younes Arous2
1Research Laboratory of Biophysics, and Medical Technologies, Higher Institute of Medical Technologies of Tunis, University Tunis El Manar, 1006 Tunis, Tunisia.
Background:
Native T1 mapping has become an essential tool for quantitative myocardial tissue characterization in cardiac magnetic resonance (CMR). However, widely used techniques such as Modified Look-Locker Inversion Recovery (MOLLI) remain limited by their proprietary nature and limited accessibility, particularly in resource-constrained settings.
Aim:
This study aimed to develop and validate a more accessible Single-Shot T1 mapping technique as a practical alternative to MOLLI, and to assess its agreement and diagnostic performance against a reference standard (Circle Cardiovascular Imaging, CVI⁴²).
Methods:
A retrospective study was conducted on 40 subjects (25 healthy controls and 15 patients with cardiac pathologies) who underwent 3T CMR imaging. Native T1 values were acquired using a modified Single-Shot inversion recovery scheme (3(3)3(3)5). Quantitative analysis was performed using custom MATLAB-based post-processing and compared with reference measurements obtained using CVI⁴² software. Agreement was assessed using Bland-Altman analysis, while group differences were evaluated using independent t-tests.
Results:
Pathological subjects demonstrated significantly elevated native T1 values compared to healthy controls (1566 ± 65 ms vs. 1079 ± 80 ms, p < 0.001). The proposed method showed strong agreement with the reference standard, with a mean difference of 5.7 ms and no statistically significant bias. Additionally, the Single-Shot approach exhibited significantly reduced inter-subject variability compared to CVI⁴²-based measurements.
Conclusion:
The proposed Single-Shot T1 mapping technique provides a reliable, reproducible, and accessible alternative to MOLLI, with comparable accuracy and improved numerical stability. This approach may expand access to advanced myocardial tissue characterization, particularly in low-resource settings.
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