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Henningsson, M.

Publications and source records attributed to Henningsson, M..

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Clinical evaluation of the Multimapping technique for simultaneous myocardial T1 and T2 mapping

The Multimapping technique was recently proposed for simultaneous myocardial T1 and T2 mapping. In this study we evaluate its correlation with clinical reference mapping techniques in patients with a range of cardiovascular diseases (CVD), compare image quality and inter- and intra-observer repeatability. Multimapping consists of a ECG-triggered, 2D single-shot bSSFP readout with inversion recovery and T2 preparation modules, acquired across 10 cardiac cycles. The sequence was implemented at 1.5T and compared to clinical reference mapping techniques, Modified Look-Locker inversion recovery (MOLLI) and T2 prepared bSSFP with four echo times (T2bSSFP), and compared in 47 patients with CVD (of which 44 were analyzed). In diseased myocardial segments (defined as presence of late gadolinium enhancement) there was a high correlation between Multimapping and MOLLI for native myocardium T1 (r2=0.73), ECV (r2=0.91) and blood T1 (r2=0.88), and Multimapping and T2bSSFP for native myocardial T2 (r2=0.80). In healthy myocardial segments a bias for native T1 (Multimapping=1116{+/-}21 ms, MOLLI=1002{+/-}21, P<0.001), post-contrast T1 (Multimapping=479{+/-}31 ms, MOLLI=426{+/-}27 ms, 0.001), ECV (Multimapping=21.5{+/-}1.9%, MOLLI=23.7{+/-}2.3%, P=0.001) and native T2 (Multimapping=48.0{+/-}3.0 ms, T2bSSFP=53.9{+/-}3.5 ms, P<0.001) was observed. The image quality for Multimapping was scored as higher for all mapping techniques (native T1, post- contrast T1, ECV and T2bSSFP) compared to the clinical reference techniques. The inter- and intra- observer agreement was excellent (intraclass correlation coefficient, ICC>0.9) for most measurements, except for inter-observer repeatability of Multimapping native T1 (ICC=0.87), post-contrast T1 (ICC=0.73) and T2bSSFP native T2 (ICC=0.88). Multimapping show high correlations with clinical reference mapping techniques for T1, T2 and ECV in a diverse cohort of patients with different cardiovascular diseases. Multimapping enables simultaneous T1 and T2 mapping and can be performed in a short breath-hold, with image quality superior to that of the clinical reference techniques.

bioengineering↗

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising

PurposeTo accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a novel post-processing 3D denoising technique to maintain high accuracy and precision.\n\nMethods3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and precision is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising.\n\nResultsIn the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P=0.99 and P=0.99 for accuracy, P=0.64 and P=0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1-weighted images after denoising.\n\nConclusionWe demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.

bioengineering↗