Dataset Information

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

ABSTRACT: Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1-9 days later, and the data were analysed centrally. The average mean diffusivities (MDs) in 0% PVP were (1.124, 1.130, 1.113) x 10^-3 mm² /s for PGSE, SE and STEAM, respectively, and accurate to within 1.5% of reference data from the literature. The coefficients of variation in MDs across sites were 2.6%, 3.1% and 2.1% for PGSE, SE and STEAM, respectively, and were similar to previous studies using only PGSE. Reproducibility in MD was excellent, with mean differences in PGSE, SE and STEAM of (0.3 ± 2.3, 0.24 ± 0.95, 0.52 ± 0.58) x 10^-5 mm² /s (mean ± 1.96 SD). We show that custom sequences for cardiac DTI provide accurate, precise, repeatable and reproducible measurements. Further work in anisotropic and/or deforming phantoms is warranted.

SUBMITTER: Teh I

PROVIDER: S-EPMC9285553 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Teh Irvin I Romero R William A WA Boyle Jordan J Coll-Font Jaume J Dall'Armellina Erica E Ennis Daniel B DB Ferreira Pedro F PF Kalra Prateek P Kolipaka Arunark A Kozerke Sebastian S Lohr David D Mongeon François-Pierre FP Moulin Kévin K Nguyen Christopher C Nielles-Vallespin Sonia S Raterman Brian B Schreiber Laura M LM Scott Andrew D AD Sosnovik David E DE Stoeck Christian T CT Tous Cyril C Tunnicliffe Elizabeth M EM Weng Andreas M AM Croisille Pierre P Viallon Magalie M Schneider Jürgen E JE

NMR in biomedicine 20220208 6

Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites ...[more]

PMID: 34967060

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Project description:The clinical translation of diffusion magnetic resonance imaging (dMRI)-derived quantitative contrasts hinges on robust reproducibility, minimizing both same-scanner and cross-scanner variability. As multi-site data sets, including multi-shell dMRI, expand in scope, enhancing reproducibility across variable MRI systems and MRI protocols becomes crucial. This study evaluates the reproducibility of diffusion kurtosis imaging (DKI) metrics (beyond conventional diffusion tensor imaging (DTI)), at the voxel and region-of-interest (ROI) levels on magnitude and complex-valued dMRI data, using denoising with and without harmonization. We compared same-scanner, cross-scanner, and cross-protocol variability for a multi-shell dMRI protocol (2-mm isotropic resolution, b = 0, 1000, 2000 s/mm2) in 20 subjects. We first evaluated the effectiveness of Marchenko-Pastur Principal Component Analysis (MPPCA) based denoising strategies for both magnitude and complex data to mitigate noise-induced bias and variance, to improve dMRI parametric maps and reproducibility. Next, we examined the impact of denoising under different population analysis approaches, specifically comparing voxel-wise versus region of interest (ROI)-based methods. We also evaluated the role of denoising when harmonizing dMRI across scanners and protocols. The results indicate that DTI and DKI maps visually improve after MPPCA denoising, with noticeably fewer outliers in kurtosis maps. Denoising, either using magnitude or complex dMRI, enhances voxel-wise reproducibility, with test-retest variability of kurtosis indices reduced from 15%-20% without denoising to 5%-10% after denoising. Complex dMRI denoising reduces the noise floor by up to 60%. Denoising not only reduced variability across scans and protocols, but also increased statistical power for low SNR voxel-wise comparisons when comparing cross sectional groups. In conclusion, MPPCA denoising, either over magnitude or complex dMRI data, enhances the reproducibility and precision of higher-order diffusion metrics across same-scanner, cross-scanner, and cross-protocol assessments. The enhancement in data quality and precision facilitates the broader application and acceptance of these advanced imaging techniques in both clinical practice and large-scale neuroimaging studies.

Project description:Background and purposeDiffusion tensor imaging fiber tractography-assisted planning of deep brain stimulation is an emerging technology. We investigated its accuracy by using electrophysiology under clinical conditions. We hypothesized that a level of concordance between electrophysiology and DTI fiber tractography can be reached, comparable with published modeling approaches for deep brain stimulation surgery.Materials and methodsEleven patients underwent subthalamic nucleus deep brain stimulation. DTI scans and high-resolution T1- and T2-weighted MR imaging was performed at 3T. Corticospinal tracts were traced. We studied electrode positions and current amplitudes that elicited corticospinal tract effects during the operation to determine relative corticospinal tract distance. Postoperatively, 3D deep brain stimulation electrode contact locations and stimulation patterns were applied for the same corticospinal tract distance estimation.ResultsIntraoperative electrophysiologic (n = 40) clinical effects in 11 patients were detected. The mean intraoperative electrophysiologic corticospinal tract distance was 3.0 ± 0.6 mm; the mean image-derived corticospinal tract distance (DTI fiber tractography) was 3.0 ± 1.3 mm. The 95% limits of agreement were ±2.4 mm. Postoperative electrophysiology (n = 44) corticospinal tract activation effects were encountered in 9 patients; 39 were further evaluated. Mean electrophysiologic corticospinal tract distance was 3.7 ± 0.7 mm; for DTI fiber tractography, it was 3.2 ± 1.9 mm. The 95% limits of agreement were ±2.5 mm.ConclusionsDTI fiber tractography depicted the medial corticospinal tract border with proved concordance. Although the overall range of measurements was relatively small and variance was high, we believe that further use of DTI fiber tractography to assist deep brain stimulation procedures is advisable if inherent limitations are respected. These results confirm our previously published electric field simulation studies.

Dataset Information

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Publications

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Similar Datasets

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