Dataset Information

Reproducibility of T_1ρ and T₂ quantification in a multi-vendor multi-site study.

ABSTRACT:

Objective

To evaluate the multi-vendor multi-site reproducibility of two-dimensional (2D) multi-echo spin-echo (MESE) T₂ mapping (product sequences); and to evaluate the longitudinal reproducibility of three-dimensional (3D) magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (MAPSS) T_1ρ and T₂ mapping (research sequences), and 2D MESE T₂ mapping, separated by 6 months, in a multi-vendor multi-site setting.

Methods

Phantoms and volunteers (n = 5 from each site, n = 20 in total) were scanned on four 3 T magnetic resonance (MR) systems from four sites and three vendors (Siemens, General Electric, and Phillips). Two traveling volunteers (3 knees) scanned at all 4 sites at baseline and 6-month follow-up. Data was transferred to one site for centralized processing. Coefficients of variation (CVs) were calculated to evaluate reproducibility.

Results

For baseline 2D MESE T₂ measures, average CV were 0.37-2.45% (intra-site) and 5.96% (inter-site) for phantoms, and 3.15-8.49% (intra-site) and 14.16% (inter-site) for volunteers. For longitudinal phantom data, intra-site CVs were 1.42-3.48% for 3D MAPSS T_1ρ, 1.77-3.56% for 3D MAPSS T₂, and 1.02-2.54% for 2D MESE T₂. For the longitudinal volunteer data, the intra-site CVs were 2.60-4.86% for 3D MAPSS T_1ρ, 3.33-7.25% for 3D MAPSS T₂, and 3.11-8.77% for 2D MESE T₂.

Conclusion

This study demonstrated excellent intra-site reproducibility of 2D MESE T₂ imaging, while its inter-site variation was slightly higher than 3D MAPSS T₂ imaging (10.06% as previously reported). This study also showed excellent reproducibility of longitudinal T_1ρ and T₂ cartilage quantification, in a multi-vendor multi-site setting for both product 2D MESE T₂ and 3D MAPSS T_1p/T₂ research sequences.

SUBMITTER: Lartey R

PROVIDER: S-EPMC10016129 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reproducibility of T1ρ and T2 quantification in a multi-vendor multi-site study.

Lartey R R Nanavati A A Kim J J Li M M Xu K K Nakamura K K Shin W W Winalski C S CS Obuchowski N N Bahroos E E Link T M TM Hardy P A PA Peng Q Q Kim J J Liu K K Fung M M Wu C C Li X X

Osteoarthritis and cartilage 20221110 2

<h4>Objective</h4>To evaluate the multi-vendor multi-site reproducibility of two-dimensional (2D) multi-echo spin-echo (MESE) T2 mapping (product sequences); and to evaluate the longitudinal reproducibility of three-dimensional (3D) magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (MAPSS) T1ρ and T2 mapping (research sequences), and 2D MESE T2 mapping, separated by 6 months, in a multi-vendor multi-site setting ...[more]

PMID: 36370959

Similar Datasets

Project description:IntroductionWe present the reliability of ultra-high field T2* MRI at 7T, as part of the UK7T Network's "Travelling Heads" study. T2*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R2* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R2* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1.5-3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R2* mapping at 7T, in readiness for future multi-site clinical studies.MethodsTen healthy volunteers were scanned with harmonised single- and multi-echo T2*-weighted gradient echo pulse sequences. Participants were scanned five times at each "home" site and once at each of four other sites. The five sites had 1× Philips, 2× Siemens Magnetom, and 2× Siemens Terra scanners. QSM and R2* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https://github.com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space.Results and discussionMean susceptibility (χ) and R2* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0.001-0.005 ppm (χ) and 0.0005-0.001 ms-1 (R2*). For χ this is 2.1-4.8 fold better than 3T reports, and 1.1-3.4 fold better for R2*. The median ICC from within- and cross-site R2* data was 0.98 and 0.91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B0 inhomogeneity such as the inferior frontal cortex. Across sites, R2* values were more consistent than QSM in subcortical structures due to differences in B0-shimming. On a between-subject level, our measured χ and R2* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol.ConclusionThe harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R2* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.

Project description:BackgroundDixon-based magnetic resonance imaging (MRI) intramuscular proton density fat fraction (PDFF) is a potentially useful imaging biomarker of muscle quality. However, multi-vendor, multi-site reproducibility of intramuscular PDFF quantification, required for large clinical studies, can be strongly dependent on acquisition and processing. The purpose of this study was (I) to develop a 6-point Dixon MRI-based acquisition and processing technique for reproducible multi-vendor, multi-site quantification of thigh intramuscular PDFF; and (II) to evaluate the ability of the technique to detect differences in thigh muscle status between operated vs. non-operated limbs in a multi-site study of patients scanned at 10 years after anterior cruciate ligament reconstruction (ACLR).MethodsMRI bilateral mid-thigh data acquisition at 3T was harmonized across three sites and two vendors and included high-resolution axial T1-weighted scans and 6-point Dixon scans. Centralized, vendor-independent PDFF quantification was performed and algorithms were evaluated in phantoms to determine the most reproducible approach. A novel image post-processing method was developed to mitigate scaling errors observed on some scanner platforms to improve reproducibility. PDFF measurements in phantoms and control subjects including traveling controls were obtained for assessment of intra-scanner repeatability as well as inter-scanner, inter-vendor, and inter-site reproducibility. Patients from the Multicenter Orthopedic Outcomes Network ACLR cohort were scanned and intramuscular PDFF was compared between thigh muscles of the operated and contralateral limbs. Standard deviation (SD) of PDFF, within-subject SD (wSD), and intraclass correlation coefficient (ICC) were used to characterize repeatability and reproducibility.ResultsThe proposed scaling correction method improved overall reproducibility in phantoms and traveling controls and was incorporated as part of the Dixon processing pipeline for subsequent analyses. Intra-scanner phantom repeatability ranged between 0.2-0.9% (SD) PDFF (ICC =0.98-1.00), with overall inter-vendor/inter-site reproducibility of 0.7-1.7% (SD) PDFF (ICC =0.97). Control subject repeatability among all scanners and vendors ranged between 0.2-0.8% (wSD) PDFF (ICC =0.95-0.98) with slightly lower inter-site, inter-vendor reproducibility, 0.8-1.2% (wSD) PDFF (ICC =0.92). Intramuscular PDFF was elevated in ACLR vs contralateral thighs for the hamstrings muscle compartment (6.2%±3.5% vs. 5.7%±2.8%, P=0.006), while quadriceps (4.0%±2.0% vs. 4.0%±2.1%, P=0.961) and medial (5.7%±2.5% vs. 5.5%±2.3%, P=0.133) muscle compartments did not show significant PDFF differences.ConclusionsReproducible multi-site, multi-vendor intramuscular PDFF measurement is enabled by 6-point Dixon MRI with standardized acquisition and processing. The method is sensitive enough to detect differences in muscle groups between operated and non-operated thighs in the patient population 10 years after ACLR.

Project description:Absolute quantification of radiotracer distribution using SPECT/CT imaging is of great importance for dosimetry aimed at personalized radionuclide precision treatment. However, its accuracy depends on many factors. Using phantom measurements, this multi-vendor and multi-center study evaluates the quantitative accuracy and inter-system variability of various SPECT/CT systems as well as the effect of patient size, processing software and reconstruction algorithms on recovery coefficients (RC). METHODS:Five SPECT/CT systems were included: Discovery™ NM/CT 670 Pro (GE Healthcare), Precedence™ 6 (Philips Healthcare), Symbia Intevo™, and Symbia™ T16 (twice) (Siemens Healthineers). Three phantoms were used based on the NEMA IEC body phantom without lung insert simulating body mass indexes (BMI) of 25, 28, and 47 kg/m2. Six spheres (0.5-26.5 mL) and background were filled with 0.1 and 0.01 MBq/mL 99mTc-pertechnetate, respectively. Volumes of interest (VOI) of spheres were obtained by a region growing technique using a 50% threshold of the maximum voxel value corrected for background activity. RC, defined as imaged activity concentration divided by actual activity concentration, were determined for maximum (RCmax) and mean voxel value (RCmean) in the VOI for each sphere diameter. Inter-system variability was expressed as median absolute deviation (MAD) of RC. Acquisition settings were standardized. Images were reconstructed using vendor-specific 3D iterative reconstruction algorithms with institute-specific settings used in clinical practice and processed using a standardized, in-house developed processing tool based on the SimpleITK framework. Additionally, all data were reconstructed with a vendor-neutral reconstruction algorithm (Hybrid Recon™; Hermes Medical Solutions). RESULTS:RC decreased with decreasing sphere diameter for each system. Inter-system variability (MAD) was 16 and 17% for RCmean and RCmax, respectively. Standardized reconstruction decreased this variability to 4 and 5%. High BMI hampers quantification of small lesions (< 10 ml). CONCLUSION:Absolute SPECT quantification in a multi-center and multi-vendor setting is feasible, especially when reconstruction protocols are standardized, paving the way for a standard for absolute quantitative SPECT.

Project description:INTRODUCTION:We present the reliability of ultra-high field T2* MRI at 7T, as part of the UK7T Network's "Travelling Heads" study. T2*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R2* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R2* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1.5-3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R2* mapping at 7T, in readiness for future multi-site clinical studies. METHODS:Ten healthy volunteers were scanned with harmonised single- and multi-echo T2*-weighted gradient echo pulse sequences. Participants were scanned five times at each "home" site and once at each of four other sites. The five sites had 1× Philips, 2× Siemens Magnetom, and 2× Siemens Terra scanners. QSM and R2* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https://github.com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space. RESULTS AND DISCUSSION:Mean susceptibility (?) and R2* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0.001-0.005 ppm (?) and 0.0005-0.001 ms-1 (R2*). For ? this is 2.1-4.8 fold better than 3T reports, and 1.1-3.4 fold better for R2*. The median ICC from within- and cross-site R2* data was 0.98 and 0.91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B0 inhomogeneity such as the inferior frontal cortex. Across sites, R2* values were more consistent than QSM in subcortical structures due to differences in B0-shimming. On a between-subject level, our measured ? and R2* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol. CONCLUSION:The harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R2* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.

Project description:BackgroundFast and accurate T1ρ mapping in myocardium is still a major challenge, particularly in small animal models. The complex sequence design owing to electrocardiogram and respiratory gating leads to quantification errors in in vivo experiments, due to variations of the T1ρ relaxation pathway. In this study, we present an improved quantification method for T1ρ using a newly derived formalism of a T1ρ* relaxation pathway.MethodsThe new signal equation was derived by solving a recursion problem for spin-lock prepared fast gradient echo readouts. Based on Bloch simulations, we compared quantification errors using the common monoexponential model and our corrected model. The method was validated in phantom experiments and tested in vivo for myocardial T1ρ mapping in mice. Here, the impact of the breath dependent spin recovery time Trec on the quantification results was examined in detail.ResultsSimulations indicate that a correction is necessary, since systematically underestimated values are measured under in vivo conditions. In the phantom study, the mean quantification error could be reduced from - 7.4% to - 0.97%. In vivo, a correlation of uncorrected T1ρ with the respiratory cycle was observed. Using the newly derived correction method, this correlation was significantly reduced from r = 0.708 (p < 0.001) to r = 0.204 and the standard deviation of left ventricular T1ρ values in different animals was reduced by at least 39%.ConclusionThe suggested quantification formalism enables fast and precise myocardial T1ρ quantification for small animals during free breathing and can improve the comparability of study results. Our new technique offers a reasonable tool for assessing myocardial diseases, since pathologies that cause a change in heart or breathing rates do not lead to systematic misinterpretations. Besides, the derived signal equation can be used for sequence optimization or for subsequent correction of prior study results.

Project description:BackgroundTwo-dimensional speckle-tracking echocardiography (2D-STE) enables objective assessment of left atrial (LA) deformation through the analysis of myocardial strain, which can be measured by different speckle-tracking software. The aim of this study was to compare the consistency of 3 different commercially available software, which include vendor-specific software for measuring left ventricle (VSSLV), vendor-independent software packages for measuring LV strain (VISLV) and vendor-independent software packages for measuring LA strain (VISLA).MethodsSixty-four subjects (mean age: 44 ± 16 years, 50% males) underwent conventional echocardiograms using a GE Vivid 9 (GE Ultrasound, Horten, Norway) cardiac ultrasound system. Standard apical 4 and 2 chamber views of the left atrium were obtained in each subject with a frame-rate range of 40-71 frames/s. LA strain during the contraction phase (Sct), conduit phase (Scd), reservoir phase (Sr = Sct + Scd) were analyzed by 2 independent observers and 3 different software.ResultsSct, Scd, Sr were, respectively, - 11.26 ± 2.45%, - 16.77 ± 7.06%, and 28.03 ± 7.58% with VSSLV, - 14.77 ± 3.59%, - 23.17 ± 10.33%, and 38.23 ± 10.99% with VISLV, and - 14.80 ± 3.88%, - 23.94 ± 10.48%, and 38.73 ± 11.56% when VISLA was used. A comparison of strain measurements between VSSLV and VIS (VISLV and VISLA) showed VIS had significantly smaller mean differences and narrower limits of agreement. Similar results were observed in the coefficient of variation (CV) for measurements between VSSLV and VIS (VISLV and VISLA). Comparison of the intra-class correlation coefficients (ICCs) indicated that measurement reliability was weaker with VSSLV (ICC < 0.6) than with VIS (VISLV and VISLA) (ICC > 0.9). For intra-observer ICCs, VISLA > VSSLV = VISLV. For inter-observer ICCs, VSSLV > VISLA > VISLV.ConclusionsSoftware measurement results of LA strain vary considerably. We recommended not measuring LA strain across vendor platforms.

Project description:Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T2 relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T2 relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space (T2IE) in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T2 relaxometry dataset. To this end, we evaluated three different techniques for estimating the T2 spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that T2IE is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.