Dataset Information

Five-minute knee MRI for simultaneous morphometry and T2 relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3T.

ABSTRACT: BACKGROUND:Biomarkers for assessing osteoarthritis activity necessitate multiple MRI sequences with long acquisition times. PURPOSE:To perform 5-minute simultaneous morphometry (thickness/volume measurements) and T2 relaxometry of both cartilage and meniscus, and semiquantitative MRI Osteoarthritis Knee Scoring (MOAKS). STUDY TYPE:Prospective. SUBJECTS:Fifteen healthy volunteers for morphometry and T2 measurements, and 15 patients (five each Kellgren-Lawrence grades 0/2/3) for MOAKS assessment. FIELD STRENGTH/SEQUENCE:A 5-minute double-echo steady-state (DESS) sequence was evaluated for generating quantitative and semiquantitative osteoarthritis biomarkers at 3T. ASSESSMENT:Flip angle simulations evaluated tissue signals and sensitivity of T2 measurements. Morphometry and T2 reproducibility was compared against morphometry-optimized and relaxometry-optimized sequences. Repeatability was assessed by scanning five volunteers twice. MOAKS reproducibility was compared to MOAKS derived from a clinical knee MRI protocol by two readers. STATISTICAL TESTS:Coefficients of variation (CVs), concordance confidence intervals (CCI), and Wilcoxon signed-rank tests compared morphometry and relaxometry measurements with their reference standards. DESS MOAKS positive percent agreement (PPA), negative percentage agreement (NPA), and interreader agreement was calculated using the clinical protocol as a reference. Biomarker variations between Kellgren-Lawrence groups were evaluated using Wilcoxon rank-sum tests. RESULTS:Cartilage thickness (P?=?0.65), cartilage T2 (P?=?0.69), and meniscus T2 (P?=?0.06) did not significantly differ from their reference standard (with a 20° DESS flip angle). DESS slightly overestimated meniscus volume (P < 0.001). Accuracy and repeatability CVs were <3.3%, except the meniscus T2 accuracy (7.6%). DESS MOAKS had substantial interreader agreement and high PPA/NPA values of 87%/90%. Bone marrow lesions and menisci had slightly lower PPAs. Cartilage and meniscus T2 , and MOAKS (cartilage surface area, osteophytes, cysts, and total score) was higher in Kellgren-Lawrence groups 2 and 3 than group 0 (P < 0.05). DATA CONCLUSION:The 5-minute DESS sequence permits MOAKS assessment for a majority of tissues, along with repeatable and reproducible simultaneous cartilage and meniscus T2 relaxometry and morphometry measurements. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1328-1341.

SUBMITTER: Chaudhari AS

PROVIDER: S-EPMC5899635 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Five-minute knee MRI for simultaneous morphometry and T<sub>2</sub> relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3T.

Chaudhari Akshay S AS Black Marianne S MS Eijgenraam Susanne S Wirth Wolfgang W Maschek Susanne S Sveinsson Bragi B Eckstein Felix F Oei Edwin H G EHG Gold Garry E GE Hargreaves Brian A BA

Journal of magnetic resonance imaging : JMRI 20171101 5

<h4>Background</h4>Biomarkers for assessing osteoarthritis activity necessitate multiple MRI sequences with long acquisition times.<h4>Purpose</h4>To perform 5-minute simultaneous morphometry (thickness/volume measurements) and T<sub>2</sub> relaxometry of both cartilage and meniscus, and semiquantitative MRI Osteoarthritis Knee Scoring (MOAKS).<h4>Study type</h4>Prospective.<h4>Subjects</h4>Fifteen healthy volunteers for morphometry and T<sub>2</sub> measurements, and 15 patients (five each Kel ...[more]

PMID: 29090500

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Project description:PurposeWe present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1+-inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone.MethodsSimulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well.ResultsIn comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs.ConclusionThe proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions.

Project description:Purpose To analyze how automatic segmentation translates in accuracy and precision to morphology and relaxometry compared with manual segmentation and increases the speed and accuracy of the work flow that uses quantitative magnetic resonance (MR) imaging to study knee degenerative diseases such as osteoarthritis (OA). Materials and Methods This retrospective study involved the analysis of 638 MR imaging volumes from two data cohorts acquired at 3.0 T: (a) spoiled gradient-recalled acquisition in the steady state T1ρ-weighted images and (b) three-dimensional (3D) double-echo steady-state (DESS) images. A deep learning model based on the U-Net convolutional network architecture was developed to perform automatic segmentation. Cartilage and meniscus compartments were manually segmented by skilled technicians and radiologists for comparison. Performance of the automatic segmentation was evaluated on Dice coefficient overlap with the manual segmentation, as well as by the automatic segmentations' ability to quantify, in a longitudinally repeatable way, relaxometry and morphology. Results The models produced strong Dice coefficients, particularly for 3D-DESS images, ranging between 0.770 and 0.878 in the cartilage compartments to 0.809 and 0.753 for the lateral meniscus and medial meniscus, respectively. The models averaged 5 seconds to generate the automatic segmentations. Average correlations between manual and automatic quantification of T1ρ and T2 values were 0.8233 and 0.8603, respectively, and 0.9349 and 0.9384 for volume and thickness, respectively. Longitudinal precision of the automatic method was comparable with that of the manual one. Conclusion U-Net demonstrates efficacy and precision in quickly generating accurate segmentations that can be used to extract relaxation times and morphologic characterization and values that can be used in the monitoring and diagnosis of OA. © RSNA, 2018 Online supplemental material is available for this article.

Dataset Information

Five-minute knee MRI for simultaneous morphometry and T2 relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3T.

Publications

Five-minute knee MRI for simultaneous morphometry and T<sub>2</sub> relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3T.

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