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Funding Acknowledgements Type of funding sources: None. Introduction Myocardial T1 mapping constitutes a reliable indicator of heart diseases related to changes of myocardial extracellular content (e.g. oedema, fibrosis) as well as fat, iron and amyloid content. T1-mapping techniques rely on fitting a model to a series of MRI measurements. Alignment between these measurements is required for accurate T1 estimation. This is limited by triggering accuracy and patient motion. Image registration is often applied to improve the alignment. In the case of MOLLI series, registration is compromised by contrast variation between the images. We present the validation of a new registration method, designed to account for the contrast properties of MOLLI data. Methods A cohort of 186 patients referred for a CMR was included in this study (115 M / 71 F; weight 75 ± 15 Kg; age 55 ± 16). Scans on a 3.0T MR included a MOLLI sequence with target parameters: 2D bSSFP, 160x148, pFOV 0.8-1.0, 1.4x1.4mm², ST 8mm, TE 1.4ms, TR 3.0ms, FA 35deg, NEX 1, BW 100kHz, 2x ASSET, 5(3)3. Cartesian 2D reconstruction followed by motion correction was applied retrospectively. A new correction algorithm was implemented, based on a similarity criterion that accounted for T1 relaxation: It consisted of an iterative approach alternating polarity estimation, T1 fitting, relaxation simulation and frame registration. The coefficient of determination (R²) was used as a quality measure. A representative subset of the results was reviewed by two experienced cardiologists. Results All reconstructions (totalling 1133 2D MOLLI series) yielded qualitatively correct T1 maps. Results with the new method were compared to conventional motion correction and no correction. The number of pixels with R²&amp;gt;0.95 was 85%±9% with standard motion correction and 90%±7% with the new dedicated method. In terms of improvement w.r.t. uncorrected data, the standard method yielded +3%±8% and the new one +9%±8%. Motion correction caused noticeable performance degradation in 12% of cases with the standard method, compared to 0.2% with the proposed method. The relative performance of the different methods can be appreciated in Figure 3. Discussion Despite T1 mapping techniques constituting a reliable diagnostic tool in cardiac imaging, they remain sensitive to patient motion and triggering inaccuracies, making them vulnerable to arrhythmia episodes. Improving the similarity criterion by accounting for T1 relaxation significantly decreased the incidence of misregistration and subsequent T1 inaccuracies. Using the R² of the voxel-wise T1 fit as a surrogate of alignment allowed to confirm the increased robustness of the new, dedicated motion correction method for MOLLI series. Conclusion We have demonstrated a new reconstruction pipeline with built-in registration, optimized for MOLLI T1-mapping. Using a large database of clinical data, the new method has been shown to improve the robustness to motion of cardiac T1 mapping. Abstract Figure.

Improving the robustness of MOLLI T1 maps with a dedicated motion correction algorithm