Dual-pathway multi-echo sequence for simultaneous frequency and T2 mapping

Cartilage compositional MRI-a narrative review of technical development and clinical applications over the past three decades

Articular cartilage damage and degeneration are among hallmark manifestations of joint injuries and arthritis, classically osteoarthritis. Cartilage compositional MRI (Cart-C MRI), a quantitative technique, which aims to detect early-stage cartilage matrix changes that precede macroscopic alterations, began development in the 1990s. However, despite the significant advancements over the past three decades, Cart-C MRI remains predominantly a research tool, hindered by various technical and clinical hurdles. This paper will review the technical evolution of Cart-C MRI, delve into its clinical applications, and conclude by identifying the existing gaps and challenges that need to be addressed to enable even broader clinical application of Cart-C MRI.

Quantitative MRI for Evaluation of Musculoskeletal Disease: Cartilage and Muscle Composition, Joint Inflammation, and Biomechanics in Osteoarthritis

ABSTRACT

Magnetic resonance imaging (MRI) is a valuable tool for evaluating musculoskeletal disease as it offers a range of image contrasts that are sensitive to underlying tissue biochemical composition and microstructure. Although MRI has the ability to provide high-resolution, information-rich images suitable for musculoskeletal applications, most MRI utilization remains in qualitative evaluation. Quantitative MRI (qMRI) provides additional value beyond qualitative assessment via objective metrics that can support disease characterization, disease progression monitoring, or therapy response. In this review, musculoskeletal qMRI techniques are summarized with a focus on techniques developed for osteoarthritis evaluation. Cartilage compositional MRI methods are described with a detailed discussion on relaxometric mapping (T 2 , T 2 *, T 1ρ ) without contrast agents. Methods to assess inflammation are described, including perfusion imaging, volume and signal changes, contrast-enhanced T 1 mapping, and semiquantitative scoring systems. Quantitative characterization of structure and function by bone shape modeling and joint kinematics are described. Muscle evaluation by qMRI is discussed, including size (area, volume), relaxometric mapping (T 1 , T 2 , T 1ρ ), fat fraction quantification, diffusion imaging, and metabolic assessment by 31 P-MR and creatine chemical exchange saturation transfer. Other notable technologies to support qMRI in musculoskeletal evaluation are described, including magnetic resonance fingerprinting, ultrashort echo time imaging, ultrahigh-field MRI, and hybrid MRI-positron emission tomography. Challenges for adopting and using qMRI in musculoskeletal evaluation are discussed, including the need for metal artifact suppression and qMRI standardization.

A relaxometry method that emphasizes practicality and availability

PURPOSE

Although many methods have been proposed to quantitatively map the main MRI parameters (e.g., T₁ , T₂ , C × M₀ ), these methods often involve special sequences not readily available on clinical scanners and/or may require long scan times. In contrast, the proposed method can readily run on most scanners, offer flexible tradeoffs between scan time and image quality, and map MRI parameters jointly to ensure spatial alignment.

METHODS

The approach is based on the multi-shot spin-echo (SE) EPI sequence. The corresponding signal equation was derived and strategies for solving it were developed. As usual with multi-shot EPI, scan time can readily be traded-off against image quality by adjusting the echo train length. Validation was performed against reference relaxometry methods, in gel phantoms with varying concentrations of gadobutrol and gadoterate meglumine contrast agents. In vivo examples are further presented, from 3 neuroradiology patients.

RESULTS

Bland-Altman analysis was performed: for T₂ , as compared to 2D SE, bias was 0.29 ms and the 95% limits of agreement ranged from -1.15 to +1.73 ms. For T₁ , compared to inversion-recovery SE (and MOLLI), bias was -20.2 ms (and -14.5 ms) and the limits of agreement ranged from -62.4 to +22.0 ms (and -53.8 to +24.9 ms). The mean relative T₁ error between the proposed method and each of the 2 reference methods was similar to that of the reference methods among themselves.

CONCLUSION

In the constellation of existing relaxometry methods, the proposed method is meant to stand out in terms of its practicality and availability.

Learning Multiparametric Biomarkers for Assessing MR-Guided Focused Ultrasound Treatment of Malignant Tumors

Noninvasive MR-guided focused ultrasound (MRgFUS) treatments are promising alternatives to the surgical removal of malignant tumors. A significant challenge is assessing the viability of treated tissue during and immediately after MRgFUS procedures. Current clinical assessment uses the nonperfused volume (NPV) biomarker immediately after treatment from contrast-enhanced MRI. The NPV has variable accuracy, and the use of contrast agent prevents continuing MRgFUS treatment if tumor coverage is inadequate. This work presents a novel, noncontrast, learned multiparametric MR biomarker that can be used during treatment for intratreatment assessment, validated in a VX2 rabbit tumor model. A deep convolutional neural network was trained on noncontrast multiparametric MR images using the NPV biomarker from follow-up MR imaging (3-5 days after MRgFUS treatment) as the accurate label of nonviable tissue. A novel volume-conserving registration algorithm yielded a voxel-wise correlation between treatment and follow-up NPV, providing a rigorous validation of the biomarker. The learned noncontrast multiparametric MR biomarker predicted the follow-up NPV with an average DICE coefficient of 0.71, substantially outperforming the current clinical standard (DICE coefficient = 0.53). Noncontrast multiparametric MR imaging integrated with a deep convolutional neural network provides a more accurate prediction of MRgFUS treatment outcome than current contrast-based techniques.

Alternating unbalanced SSFP for 3D R 2 ' mapping of the human brain

PURPOSE

Measuring the transverse-relaxation rate R 2 ' provides valuable information in quantitative evaluation of tissue microstructure, for example, in terms of oxygenation levels. Here, we propose an alternating unbalanced SSFP pulse sequence for rapid whole-brain 3D R 2 ' mapping.

METHODS

Unlike currently practiced, spin echo-based R 2 ' measurement techniques, the proposed method alternates between SSFP-FID and SSFP-ECHO modes for rapid 3D encoding of transverse relaxation rates expressed as R₂ + R 2 ' and R₂ - R 2 ' . Z-shimming gradients embedded into multi-echo trains of each SSFP module are designed to achieve relative immunity to large-scale magnetic-field variations (ΔB₀ ). Appropriate models for the temporal evolution of the two groups of SSFP signals were constructed with ΔB₀ -induced modulations accounted for, leading to ΔB₀ -corrected estimation of R₂ , R 2 ' , and R 2 ∗ (= R₂ + R 2 ' ). Additionally, relative magnetic susceptibility (Δχ) maps were obtained by quantitative susceptibility mapping of the phase data. Numerical simulations were performed to optimize scan parameters, followed by in vivo studies at 3 T in 7 healthy subjects. Measured parameters were evaluated in six brain regions, and subjected to interparameter correlation analysis.

RESULTS

The resultant maps of R 2 ' and additionally derived R₂ , R 2 ∗ , and Δχ all demonstrated the expected contrast across brain territories (eg, deep brain structures versus cortex), with the measured values in good agreement with previous reports. Furthermore, regression analyses yielded strong linear relationships for the transverse relaxation parameters ( R 2 ' , R₂ , and R 2 ∗ ) against Δχ.

CONCLUSION

Results suggest feasibility of the proposed method as a practical and reliable means for measuring R 2 ' , R₂ , R 2 ∗ , and Δχ across the entire brain.

Synthetic MRI: Technologies and Applications in Neuroradiology

Synthetic MRI is a technique that synthesizes contrast-weighted images from multicontrast MRI data. There have been advances in synthetic MRI since the technique was introduced. Although a number of synthetic MRI methods have been developed for quantifying one or more relaxometric parameters and for generating multiple contrast-weighted images, this review focuses on several methods that quantify all three relaxometric parameters (T₁ , T₂ , and proton density) and produce multiple contrast-weighted images. Acquisition, quantification, and image synthesis techniques are discussed for each method. We discuss the image quality and diagnostic accuracy of synthetic MRI methods and their clinical applications in neuroradiology. Based on this analysis, we highlight areas that need to be addressed for synthetic MRI to be widely implemented in the clinic. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

Multi-pathway multi-echo acquisition and neural contrast translation to generate a variety of quantitative and qualitative image contrasts

PURPOSE

Clinical exams typically involve acquiring many different image contrasts to help discriminate healthy from diseased states. Ideally, 3D quantitative maps of all of the main MR parameters would be obtained for improved tissue characterization. Using data from a 7-min whole-brain multi-pathway multi-echo (MPME) scan, we aimed to synthesize several 3D quantitative maps (T₁ and T₂ ) and qualitative contrasts (MPRAGE, FLAIR, T₁ -weighted, T₂ -weighted, and proton density [PD]-weighted). The ability of MPME acquisitions to capture large amounts of information in a relatively short amount of time suggests it may help reduce the duration of neuro MR exams.

METHODS

Eight healthy volunteers were imaged at 3.0T using a 3D isotropic (1.2 mm) MPME sequence. Spin-echo, MPRAGE, and FLAIR scans were performed for training and validation. MPME signals were interpreted through neural networks for predictions of different quantitative and qualitative contrasts. Predictions were compared to reference values at voxel and region-of-interest levels.

RESULTS

Mean absolute errors (MAEs) for T₁ and T₂ maps were 216 ms and 11 ms, respectively. In ROIs containing white matter (WM) and thalamus tissues, the mean T₁ /T₂ predicted values were 899/62 ms and 1139/58 ms, consistent with reference values of 850/66 ms and 1126/58 ms, respectively. For qualitative contrasts, signals were normalized to those of WM, and MAEs for MPRAGE, FLAIR, T₁ -weighted, T₂ -weighted, and PD-weighted contrasts were 0.14, 0.15, 0.13, 0.16, and 0.05, respectively.

CONCLUSIONS

Using an MPME sequence and neural-network contrast translation, whole-brain results were obtained with a variety of quantitative and qualitative contrast in ~6.8 min.

Multipathway multi-echo (MPME) imaging: all main MR parameters mapped based on a single 3D scan

PURPOSE

Quantitative parameter maps, as opposed to qualitative grayscale images, may represent the future of diagnostic MRI. A new quantitative MRI method is introduced here that requires a single 3D acquisition, allowing good spatial coverage to be achieved in relatively short scan times.

METHODS

A multipathway multi-echo sequence was developed, and at least 3 pathways with 2 TEs were needed to generate T₁ , T₂ , T₂ ^* , B₁ ⁺ , and B₀ maps. The method required the central k-space region to be sampled twice, with the same sequence but with 2 very different nominal flip angle settings. Consequently, scan time was only slightly longer than that of a single scan. The multipathway multi-echo data were reconstructed into parameter maps, for phantom as well as brain acquisitions, in 5 healthy volunteers at 3 T. Spatial resolution, matrix size, and FOV were 1.2 × 1.0 × 1.2 mm³ , 160 × 192 × 160, and 19.2 × 19.2 × 19.2 cm³ (whole brain), acquired in 11.5 minutes with minimal acceleration. Validation was performed against T₁ , T₂ , and T₂ ^* maps calculated from gradient-echo and spin-echo data.

RESULTS

In Bland-Altman plots, bias and limits of agreement for T₁ and T₂ results in vivo and in phantom were -2.9/±125.5 ms (T₁ in vivo), -4.8/±20.8 ms (T₂ in vivo), -1.5/±18.1 ms (T₁ in phantom), and -5.3/±7.4 ms (T₂ in phantom), for regions of interest including given brain structures or phantom compartments. Due to relatively high noise levels, the current implementation of the approach may prove more useful for region of interest-based as opposed to pixel-based interpretation.

CONCLUSIONS

We proposed a novel approach to quantitatively map MR parameters based on a multipathway multi-echo acquisition.

Rotation relaxation splitting for optimizing parallel RF excitation pulses with T1- and T2-relaxations in MRI

Exact solutions of the Bloch equations with T₁- and T₂-relaxation terms for piecewise constant magnetic fields are numerically challenging. We therefore investigate an approximation for the achieved magnetization in which rotations and relaxations are split into separate operations. We develop an estimate for its accuracy and explicit first and second order derivatives with respect to the complex excitation radio frequency voltages. In practice, the deviation between an exact solution of the Bloch equations and this rotation relaxation splitting approximation seems negligible. Its computation times are similar to exact solutions without relaxation terms. We apply the developed theory to numerically optimize radio frequency excitation waveforms with T₁- and T₂-relaxations in several examples.

Imaging of osteoarthritis-recent research developments and future perspective

In osteoarthritis research, imaging plays an important role in clinical trials and epidemiological observational studies. In this narrative review article, we will describe recent developments in imaging of osteoarthritis in the research arena, mainly focusing on literature evidence published within the past 3 years (2014-2017). We will primarily focus on MRI including advanced imaging techniques that are not currently commonly used in routine clinical practice, although radiography, ultrasound and nuclear medicine (radiotracer) imaging will also be discussed. Research efforts to uncover the disease process of OA as well as to discover a disease modifying OA drug continue. MRI continues to play a large role in these endeavors, while compositional MRI techniques will increasingly become important due to their ability to assess "premorphologic" biochemical changes of articular cartilage and other tissues in and around joints. Radiography remain the primary imaging modality for defining inclusion/exclusion criteria as well as an outcome measure in OA clinical trials, despite known limitations for visualization of OA features. Compositional MRI techniques show promise for predicting structural and clinical outcomes in OA research. Ultrasound can be a useful adjunct to radiography and MRI particularly for evaluation of hand OA. Newer imaging techniques such as hybrid PET/MRI may have a potential but require further research and validation.

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

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.

Exploiting multicompartment effects in triple-echo steady-state T2 mapping for fat fraction quantification

PURPOSE

To investigate and exploit the effect of intravoxel off-resonance compartments in the triple-echo steady-state (TESS) sequence without fat suppression for T₂ mapping and to leverage the results for fat fraction quantification.

METHODS

In multicompartment tissue, where at least one compartment is excited off-resonance, the total signal exhibits periodic modulations as a function of echo time (TE). Simulated multicompartment TESS signals were synthesized at various TEs. Fat emulsion phantoms were prepared and scanned at the same TE combinations using TESS. In vivo knee data were obtained with TESS to validate the simulations. The multicompartment effect was exploited for fat fraction quantification in the stomach by acquiring TESS signals at two TE combinations.

RESULTS

Simulated and measured multicompartment signal intensities were in good agreement. Multicompartment effects caused erroneous T₂ offsets, even at low water-fat ratios. The choice of TE caused T₂ variations of as much as 28% in cartilage. The feasibility of fat fraction quantification to monitor the decrease of fat content in the stomach during digestion is demonstrated.

CONCLUSIONS

Intravoxel off-resonance compartments are a confounding factor for T₂ quantification using TESS, causing errors that are dependent on the TE. At the same time, off-resonance effects may allow for efficient fat fraction mapping using steady-state imaging. Magn Reson Med 79:423-429, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

A simple analytic method for estimating T2 in the knee from DESS

PURPOSE

To introduce a simple analytical formula for estimating T₂ from a single Double-Echo in Steady-State (DESS) scan.

METHODS

Extended Phase Graph (EPG) modeling was used to develop a straightforward linear approximation of the relationship between the two DESS signals, enabling accurate T₂ estimation from one DESS scan. Simulations were performed to demonstrate cancellation of different echo pathways to validate this simple model. The resulting analytic formula was compared to previous methods for T₂ estimation using DESS and fast spin-echo scans in agar phantoms and knee cartilage in three volunteers and three patients. The DESS approach allows 3D (256×256×44) T₂-mapping with fat suppression in scan times of 3-4min.

RESULTS

The simulations demonstrated that the model approximates the true signal very well. If the T₁ is within 20% of the assumed T₁, the T₂ estimation error was shown to be less than 5% for typical scans. The inherent residual error in the model was demonstrated to be small both due to signal decay and opposing signal contributions. The estimated T₂ from the linear relationship agrees well with reference scans, both for the phantoms and in vivo. The method resulted in less underestimation of T₂ than previous single-scan approaches, with processing times 60 times faster than using a numerical fit.

CONCLUSION

A simplified relationship between the two DESS signals allows for rapid 3D T₂ quantification with DESS that is accurate, yet also simple. The simplicity of the method allows for immediate T₂ estimation in cartilage during the MRI examination.

Integration of accelerated MRI and post-processing software: a promising method for studies of knee osteoarthritis

OBJECTIVE

Magnetic resonance imaging (MRI) is a widely used imaging modality for studies of knee osteoarthritis (OA). Compared to radiography, MRI offers exceptional soft tissue imaging and true three-dimensional (3D) visualization. However, MRI is expensive both due to the cost of acquisition and evaluation of the images. The goal of our study is to develop a new method to address the cost of MRI by combining innovative acquisition methods and automated post-processing software.

METHODS

Ten healthy volunteers were scanned with three different MRI protocols: A standard 3D dual-echo steady state (DESS) pulse sequence, an accelerated DESS (DESS_Acc), acquired at approximately half the time compared to DESS, and a multi-echo time DESS (DESS_MTE), which is capable of producing measurements of T2 relaxation time. A software tool was used to measure cartilage volume. Accuracy was quantified by comparing DESS to DESS_Acc and DESS_MTE and precision was measured using repeat readings and acquisitions. T2 precision was determined using duplicate DESS_MTE acquisitions. Intra-class correlation coefficients (ICCs), root-mean square standard deviation (RMSSD), and the coefficient of variation (CoV) were used to quantify accuracy and precision.

RESULTS

The accuracies of DESS_Acc and DESS_MTE were CoV = 3.7% and CoV = 6.6% respectively, while precision was 3.8%, 3.0%, and 3.1% for DESS, DESS_Acc and DESS_MTE. T2 repositioning precision was 5.8%.

CONCLUSION

The results demonstrate that accurate and precise quantification of cartilage volume is possible using a combination of substantially faster MRI acquisition and post-processing software. Precise measurements of cartilage T2 and volume can be made using the same acquisition.