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

Reproducibility of Quantitative Double-Echo Steady-State T2 Mapping of Knee Cartilage

BACKGROUND

Cartilage T2 can detect joints at risk of developing osteoarthritis. The quantitative double-echo steady state (qDESS) sequence is attractive for knee cartilage T2 mapping because of its acquisition time of under 5 minutes. Understanding the reproducibility errors associated with qDESS T2 is essential to profiling the technical performance of this biomarker.

PURPOSE

To examine the combined acquisition and segmentation reproducibility of knee cartilage qDESS T2 using two different regional analysis schemes: 1) manual segmentation of subregions loaded during common activities and 2) automatic subregional segmentation.

STUDY TYPE

Prospective.

SUBJECTS

11 uninjured participants (age: 28 ± 3 years; 8 (73%) female).

FIELD STRENGTH/SEQUENCE

3-T, qDESS.

ASSESSMENT

Test-retest T2 maps were acquired twice on the same day and with a 1-week interval between scans. For each acquisition, average cartilage T2 was calculated in four manually segmented regions encompassing tibiofemoral contact areas during common activities and 12 automatically segmented regions from the deep-learning open-source framework for musculoskeletal MRI analysis (DOSMA) encompassing medial and lateral anterior, central, and posterior tibiofemoral regions. Test-retest T2 values from matching regions were used to evaluate reproducibility.

STATISTICAL TESTS

Coefficients of variation (%CV), root-mean-square-average-CV (%RMSA-CV), and intraclass correlation coefficients (ICCs) assessed test-retest T2 reproducibility. The median of test-retest standard deviations was used for T2 precision. Bland-Altman (BA) analyses examined test-retest biases. The smallest detectable difference (SDD) was defined as the BA limit of agreement of largest magnitude. Significance was accepted for P < 0.05.

RESULTS

All cartilage regions across both segmentation schemes demonstrated intraday and interday qDESS T2 CVs and RMSA-CVs of ≤5%. T2 ICC values >0.75 were observed in the majority of regions but were more variable in interday tibial comparisons. Test-retest T2 precision was <1.3 msec. The T2 SDD was 3.8 msec.

DATA CONCLUSION

Excellent CV and RMSA-CV reproducibility may suggest that qDESS T2 increases or decreases >5% (3.8 msec) could represent changes to cartilage composition.

LEVEL OF EVIDENCE: 2

TECHNICAL EFFICACY

Stage 2.

Fast T2 mapping of short-T2 tissues in knee using 3D radial dual-echo balanced steady-state free precession

BACKGROUND

T2 mapping of short-T2 tissues in the knee (meniscus, tendon, and ligament) is needed to aid the clinical MRI knee diagnosis, which is hard to realize using traditional clinical methods.

PURPOSE

To accelerate the acquisition of T2 values for short-T2 tissues in the knee by analyzing the signal equation of balanced steady-state free precession (bSSFP) sequence in MRI.

METHODS

Effect of half-radial acquisition on pixel bandwidth was analyzed mathematically. A modified 3D radial dual-echo bSSFP sequence was proposed for 0.53 mm isotropic resolution knee imaging with 2 different TEs at 3 T, which alleviated the problem of off-resonance artifacts caused by traditional half-radial acquisition scheme. A novel pixel-based optimization method was proposed for efficient T2 mapping of short-T2 tissues in the knee given off-resonance values. Simulation was conducted to evaluate the sensitivity of the proposed method to other parameters. Phantom results were compared with 2D spin-echo (SE), and in vivo results were compared with SE and previously studies.

RESULTS

Simulation showed that the proposed method is insensitive to T1 and B1 variations (estimation error < 1% for T1/B1 error of ±90%), avoiding the need for separated T1 and B1 scans. High isotropic resolution knee imaging was achieved using the modified dual-echo bSSFP. The total scan time was within 3.5 min, including a separate off-resonance scan for T2 measurement. Measured mean T2 values for phantoms correlated well with SE (R2 = 0.99), and no significant difference was observed (P = 0.45). In vivo meniscus T2 measurements and ligament T2 measurements agreed with the literature, while tendon T2 measurements were much lower (31.7% lower for patellar tendon, and 13.5% lower for quadriceps tendon), which might result in its bi-component property.

CONCLUSIONS

The proposed method provides an efficient way for fast, robust, high-resolution imaging and T2 mapping of short-T2 tissues in the knee.

Quantitative double echo steady state T2 mapping of upper extremity peripheral nerves and muscles

Introduction

T2 mapping can characterize peripheral neuropathy and muscle denervation due to axonal damage. Three-dimensional double echo steady-state (DESS) can simultaneously provide 3D qualitative information and T2 maps with equivalent spatial resolution. However, insufficient signal-to-noise ratio may bias DESS-T2 values. Deep learning reconstruction (DLR) techniques can reduce noise, and hence may improve quantitation of high-resolution DESS-T2. This study aims to (i) evaluate the effect of DLR methods on DESS-T2 values, and (ii) to evaluate the feasibility of using DESS-T2 maps to differentiate abnormal from normal nerves and muscles in the upper extremities, with abnormality as determined by electromyography.

Methods and results

Analysis of images from 25 subjects found that DLR decreased DESS-T2 values in abnormal muscles (DLR = 37.71 ± 9.11 msec, standard reconstruction = 38.56 ± 9.44 msec, p = 0.005) and normal muscles (DLR: 27.18 ± 6.34 msec, standard reconstruction: 27.58 ± 6.34 msec, p < 0.001) consistent with a noise reduction bias. Mean DESS-T2, both with and without DLR, was higher in abnormal nerves (abnormal = 75.99 ± 38.21 msec, normal = 35.10 ± 9.78 msec, p < 0.001) and muscles (abnormal = 37.71 ± 9.11 msec, normal = 27.18 ± 6.34 msec, p < 0.001). A higher DESS-T2 in muscle was associated with electromyography motor unit recruitment (p < 0.001).

Discussion

These results suggest that quantitative DESS-T2 is improved by DLR and can differentiate the nerves and muscles involved in peripheral neuropathies from those uninvolved.

Rapid whole brain 3D T2 mapping respiratory-resolved Double-Echo Steady State (DESS) sequence with improved repeatability

PURPOSE

To propose a quantitative 3D double-echo steady-state (DESS) sequence that offers rapid and repeatable T2 mapping of the human brain using different encoding schemes that account for respiratory B0 variation.

METHODS

A retrospective self-gating module was firstly implemented into the standard DESS sequence in order to suppress the respiratory artifact via data binning. A compressed-sensing trajectory (CS-DESS) was then optimized to accelerate the acquisition. Finally, a spiral Cartesian encoding (SPICCS-DESS) was incorporated to further disrupt the coherent respiratory artifact. These different versions were compared to a standard DESS sequence (fully DESS) by assessing the T2 distribution and repeatability in different brain regions of eight volunteers at 3 T.

RESULTS

The respiratory artifact correction was determined to be optimal when the data was binned into seven respiratory phases. Compared to the fully DESS, T2 distribution was improved for the CS-DESS and SPICCS-DESS with interquartile ranges reduced significantly by a factor ranging from 2 to 12 in the caudate, putamen, and thalamus regions. In the gray and white matter areas, average absolute test-retest T2 differences across all volunteers were respectively 3.5 ± 2% and 3.1 ± 2.1% for the SPICCS-DESS, 4.6 ± 4.6% and 4.9 ± 5.1% for the CS-DESS, and 15% ± 13% and 7.3 ± 5.6% for the fully DESS. The SPICCS-DESS sequence's acquisition time could be reduced by half (<4 min) while maintaining its efficient T2 mapping.

CONCLUSION

The respiratory-resolved SPICCS-DESS sequence offers rapid, robust, and repeatable 3D T2 mapping of the human brain, which can be especially effective for longitudinal monitoring of cerebral pathologies.

Accelerated Musculoskeletal Magnetic Resonance Imaging

With a substantial growth in the use of musculoskeletal MRI, there has been a growing need to improve MRI workflow, and faster imaging has been suggested as one of the solutions for a more efficient examination process. Consequently, there have been considerable advances in accelerated MRI scanning methods. This article aims to review the basic principles and applications of accelerated musculoskeletal MRI techniques including widely used conventional acceleration methods, more advanced deep learning-based techniques, and new approaches to reduce scan time. Specifically, conventional accelerated MRI techniques, including parallel imaging, compressed sensing, and simultaneous multislice imaging, and deep learning-based accelerated MRI techniques, including undersampled MR image reconstruction, super-resolution imaging, artifact correction, and generation of unacquired contrast images, are discussed. Finally, new approaches to reduce scan time, including synthetic MRI, novel sequences, and new coil setups and designs, are also reviewed. We believe that a deep understanding of these fast MRI techniques and proper use of combined acceleration methods will synergistically improve scan time and MRI workflow in daily practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

[Formula: see text] Field inhomogeneity correction for qDESS [Formula: see text] mapping: application to rapid bilateral knee imaging

PURPOSE

[Formula: see text] mapping is a powerful tool for studying osteoarthritis (OA) changes and bilateral imaging may be useful in investigating the role of between-knee asymmetry in OA onset and progression. The quantitative double-echo in steady-state (qDESS) can provide fast simultaneous bilateral knee [Formula: see text] and high-resolution morphometry for cartilage and meniscus. The qDESS uses an analytical signal model to compute [Formula: see text] relaxometry maps, which require knowledge of the flip angle (FA). In the presence of [Formula: see text] inhomogeneities, inconsistencies between the nominal and actual FA can affect the accuracy of [Formula: see text] measurements. We propose a pixel-wise [Formula: see text] correction method for qDESS [Formula: see text] mapping exploiting an auxiliary [Formula: see text] map to compute the actual FA used in the model.

METHODS

The technique was validated in a phantom and in vivo with simultaneous bilateral knee imaging. [Formula: see text] measurements of femoral cartilage (FC) of both knees of six healthy participants were repeated longitudinally to investigate the association between [Formula: see text] variation and [Formula: see text].

RESULTS

The results showed that applying the [Formula: see text] correction mitigated [Formula: see text] variations that were driven by [Formula: see text] inhomogeneities. Specifically, [Formula: see text] left-right symmetry increased following the [Formula: see text] correction ([Formula: see text] = 0.74 > [Formula: see text] = 0.69). Without the [Formula: see text] correction, [Formula: see text] values showed a linear dependence with [Formula: see text]. The linear coefficient decreased using the [Formula: see text] correction (from 24.3 ± 1.6 ms to 4.1 ± 1.8) and the correlation was not statistically significant after the application of the Bonferroni correction (p value > 0.01).

CONCLUSION

The study showed that [Formula: see text] correction could mitigate variations driven by the sensitivity of the qDESS [Formula: see text] mapping method to [Formula: see text], therefore, increasing the sensitivity to detect real biological changes. The proposed method may improve the robustness of bilateral qDESS [Formula: see text] mapping, allowing for an accurate and more efficient evaluation of OA pathways and pathophysiology through longitudinal and cross-sectional studies.

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry

BACKGROUND

Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning is not well characterized.

PURPOSE

Evaluate the generalizability of DL-based models by deploying pretrained models on independent datasets varying by MR scanner, acquisition parameters, and subject population.

STUDY TYPE

Retrospective based on prospectively acquired data.

POPULATION

Overall test dataset: 59 subjects (26 females); Study 1: 5 healthy subjects (zero females), Study 2: 8 healthy subjects (eight females), Study 3: 10 subjects with osteoarthritis (eight females), Study 4: 36 subjects with various knee pathology (10 females).

FIELD STRENGTH/SEQUENCE

A 3-T, quantitative double-echo steady state (qDESS).

ASSESSMENT

Four annotators manually segmented knee cartilage. Each reader segmented one of four qDESS datasets in the test dataset. Two DL models, one trained on qDESS data and another on Osteoarthritis Initiative (OAI)-DESS data, were assessed. Manual and automatic segmentations were compared by quantifying variations in segmentation accuracy, volume, and T2 relaxation times for superficial and deep cartilage.

STATISTICAL TESTS

Dice similarity coefficient (DSC) for segmentation accuracy. Lin's concordance correlation coefficient (CCC), Wilcoxon rank-sum tests, root-mean-squared error-coefficient-of-variation to quantify manual vs. automatic T2 and volume variations. Bland-Altman plots for manual vs. automatic T2 agreement. A P value < 0.05 was considered statistically significant.

RESULTS

DSCs for the qDESS-trained model, 0.79-0.93, were higher than those for the OAI-DESS-trained model, 0.59-0.79. T2 and volume CCCs for the qDESS-trained model, 0.75-0.98 and 0.47-0.95, were higher than respective CCCs for the OAI-DESS-trained model, 0.35-0.90 and 0.13-0.84. Bland-Altman 95% limits of agreement for superficial and deep cartilage T2 were lower for the qDESS-trained model, ±2.4 msec and ±4.0 msec, than the OAI-DESS-trained model, ±4.4 msec and ±5.2 msec.

DATA CONCLUSION

The qDESS-trained model may generalize well to independent qDESS datasets regardless of MR scanner, acquisition parameters, and subject population.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Correction of B0 and linear eddy currents: Impact on morphological and quantitative ultrashort echo time double echo steady state (UTE-DESS) imaging

The purpose of the current study was to investigate the effects of B0 and linear eddy currents on ultrashort echo time double echo steady state (UTE-DESS) imaging and to determine whether eddy current correction (ECC) effectively resolves imaging artifacts caused by eddy currents. 3D UTE-DESS sequences based on either projection radial or spiral cones trajectories were implemented on a 3-T clinical MR scanner. An off-isocentered thin-slice excitation approach was used to measure eddy currents. The measurements were repeated four times using two sets of tested gradient waveforms with opposite polarities and two different slice locations to measure B0 and linear eddy currents simultaneously. Computer simulation was performed to investigate the eddy current effect. Finally, a phantom experiment, an ex vivo experiment with human synovium and ankle samples, and an in vivo experiment with human knee joints, were performed to demonstrate the effects of eddy currents and ECC in UTE-DESS imaging. In a computer simulation, the two echoes (S+ and S-) in UTE-DESS imaging exhibited strong distortion at different orientations in the presence of B0 and linear eddy currents, resulting in both image degradation as well as misalignment of pixel location between the two echoes. The same phenomenon was observed in the phantom, ex vivo, and in vivo experiments, where the presence of eddy currents degraded S+, S-, echo subtraction images, and T2 maps. The implementation of ECC dramatically improved both the image quality and image registration between the S+ and S- echoes. It was concluded that ECC is crucial for reliable morphological and quantitative UTE-DESS imaging.

Improving Data-Efficiency and Robustness of Medical Imaging Segmentation Using Inpainting-Based Self-Supervised Learning

We systematically evaluate the training methodology and efficacy of two inpainting-based pretext tasks of context prediction and context restoration for medical image segmentation using self-supervised learning (SSL). Multiple versions of self-supervised U-Net models were trained to segment MRI and CT datasets, each using a different combination of design choices and pretext tasks to determine the effect of these design choices on segmentation performance. The optimal design choices were used to train SSL models that were then compared with baseline supervised models for computing clinically-relevant metrics in label-limited scenarios. We observed that SSL pretraining with context restoration using 32 × 32 patches and Poission-disc sampling, transferring only the pretrained encoder weights, and fine-tuning immediately with an initial learning rate of 1 × 10-3 provided the most benefit over supervised learning for MRI and CT tissue segmentation accuracy (p < 0.001). For both datasets and most label-limited scenarios, scaling the size of unlabeled pretraining data resulted in improved segmentation performance. SSL models pretrained with this amount of data outperformed baseline supervised models in the computation of clinically-relevant metrics, especially when the performance of supervised learning was low. Our results demonstrate that SSL pretraining using inpainting-based pretext tasks can help increase the robustness of models in label-limited scenarios and reduce worst-case errors that occur with supervised learning.

A method for measuring B0 field inhomogeneity using quantitative double-echo in steady-state

PURPOSE

To develop and validate a method forB 0 $$ {B}_0 $$ mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference (Δ θ $$ \Delta \theta $$ ) between the two echoes acquired. Contrary to a two-gradient-echo (2-GRE) method,Δ θ $$ \Delta \theta $$ depends only on the first echo time.

METHODS

Bloch simulations were applied to investigate robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and five healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi-GRE sequences.Δ B 0 $$ \Delta {B}_0 $$ maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin's concordance coefficient (ρ c $$ {\rho}_c $$ ). For in vivo subjects, the comparison was assessed in cartilage using average values in six subregions.

RESULTS

The proposed method for measuringΔ B 0 $$ \Delta {B}_0 $$ inhomogeneities from a qDESS acquisition providedΔ B 0 $$ \Delta {B}_0 $$ maps that were in good agreement with those obtained using WASSR.Δ B 0 $$ \Delta {B}_0 $$ ρ c $$ {\rho}_c $$ values were≥ $$ \ge $$ 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a 2-GRE method.

CONCLUSION

The proposed method may allow B0 correction for qDESST 2 $$ {T}_2 $$ mapping using an inherently co-registeredΔ B 0 $$ \Delta {B}_0 $$ map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliaryΔ B 0 $$ \Delta {B}_0 $$ map by exploiting a qDESS acquisition that also providesT 2 $$ {T}_2 $$ measurements and high-quality morphological imaging.

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.

Feasibility of simultaneous high-resolution anatomical and quantitative magnetic resonance imaging of sciatic nerves in patients with Charcot-Marie-Tooth type 1A (CMT1A) at 7T

INTRODUCTION/AIMS

Magnetic resonance imaging (MRI) of peripheral nerves can provide image-based anatomical information and quantitative measurement. The aim of this pilot study was to investigate the feasibility of high-resolution anatomical and quantitative MRI assessment of sciatic nerve fascicles in patients with Charcot-Marie-Tooth (CMT) 1A using 7T field strength.

METHODS

Six patients with CMT1A underwent imaging on a high-gradient 7T MRI scanner using a 28-channel knee coil. Two high-resolution axial images were simultaneously acquired using a quantitative double-echo in steady-state (DESS) sequence. By comparing the two DESS echoes, T2 and apparent diffusion coefficient (ADC) maps were calculated. The cross-sectional areas and mean T2 and ADC were measured in individual fascicles of the tibial and fibular (peroneal) portions of the sciatic nerve at its bifurcation and 10 mm distally. Disease severity was measured using Charcot-Marie-Tooth Examination Score (CMTES) version 2 and compared to imaging findings.

RESULTS

We demonstrated the feasibility of 7T MRI of the proximal sciatic nerve in patients with CMT1A. Using the higher field, it was possible to measure individual bundles in the tibial and fibular divisions of the sciatic nerve. There was no apparent correlation between diffusion measures and disease severity in this small cohort.

DISCUSSION

This pilot study indicated that high-resolution MRI that allows for combined anatomical and quantitative imaging in one scan is feasible at 7T field strengths and can be used to investigate the microstructure of individual nerve fascicles.

Advanced compositional imaging T2 mapping sequence in detection of stages of medial knee joint compartments articular cartilage degeneration

Background

The predictive value of the new imaging sequences, especially T2 mapping in assessment of articular cartilage abnormalities of the medial knee compartments in patients with medial knee pain. The purpose of this study is to evaluate the additional value of T2 mapping over using a baseline standard knee MRI to detect cartilage lesions of the medial compartments in patients representing with medial knee pain.

Results

The study included 60 patients presented with medial knee pain, where divided into two groups ; control group (20 volunteers) with age range from 19 to 41 years old 26.80 ± 8.05 (mean ± SD) and patients (40 candidates) with age range from 13 to 57 years old with a mean age 33.00 ± 14.1 (mean ± SD).

Conclusion

On adding T2 mapping sequence to the routine MRI of the knee, the sensitivity for detecting knee cartilage lesions was increased, especially in the detection of early cartilage degeneration at the medial compartment.

Compositional MR imaging including T2 mapping plays an important role in the assessment of early and potentially reversible cartilage damage especially among the young population.

Characterizing the transient response of knee cartilage to running: Decreases in cartilage T2 of female recreational runners

Cartilage transmits and redistributes biomechanical loads in the knee joint during exercise. Exercise-induced loading alters cartilage hydration and is detectable using quantitative magnetic resonance imaging (MRI), where T₂ relaxation time (T₂ ) is influenced by cartilage collagen composition, fiber orientation, and changes in the extracellular matrix. This study characterized short-term transient responses of healthy knee cartilage to running-induced loading using bilateral scans and image registration. Eleven healthy female recreational runners (33.73 ± 4.22 years) and four healthy female controls (27.25 ± 1.38 years) were scanned on a 3T GE MRI scanner with quantitative 3D double-echo in steady-state before running over-ground (runner group) or resting (control group) for 40 min. Subjects were scanned immediately post-activity at 5-min intervals for 60 min. T₂ times were calculated for femoral, tibial, and patellar cartilage at each time point and analyzed using a mixed-effects model and Bonferroni post hoc. There were immediate decreases in T₂ (mean ± SEM) post-run in superficial femoral cartilage of at least 3.3% ± 0.3% (p = .002) between baseline and Time 0 that remained for 25 min, a decrease in superficial tibial cartilage T₂ of 2.9% ± 0.4% (p = .041) between baseline and Time 0, and a decrease in superficial patellar cartilage T₂ of 3.6% ± 0.3% (p = .020) 15 min post-run. There were decreases in the medial posterior region of superficial femoral cartilage T₂ of at least 5.3 ± 0.2% (p = .022) within 5 min post-run that remained at 60 min post-run. These results increase understanding of transient responses of healthy cartilage to repetitive, exercise-induced loading and establish preliminary recommendations for future definitive studies of cartilage response to running.

Synthesizing Quantitative T2 Maps in Right Lateral Knee Femoral Condyles from Multicontrast Anatomic Data with a Conditional Generative Adversarial Network

PURPOSE

To develop a proof-of-concept convolutional neural network (CNN) to synthesize T2 maps in right lateral femoral condyle articular cartilage from anatomic MR images by using a conditional generative adversarial network (cGAN).

MATERIALS AND METHODS

In this retrospective study, anatomic images (from turbo spin-echo and double-echo in steady-state scans) of the right knee of 4621 patients included in the 2004-2006 Osteoarthritis Initiative were used as input to a cGAN-based CNN, and a predicted CNN T2 was generated as output. These patients included men and women of all ethnicities, aged 45-79 years, with or at high risk for knee osteoarthritis incidence or progression who were recruited at four separate centers in the United States. These data were split into 3703 (80%) for training, 462 (10%) for validation, and 456 (10%) for testing. Linear regression analysis was performed between the multiecho spin-echo (MESE) and CNN T2 in the test dataset. A more detailed analysis was performed in 30 randomly selected patients by means of evaluation by two musculoskeletal radiologists and quantification of cartilage subregions. Radiologist assessments were compared by using two-sided t tests.

RESULTS

The readers were moderately accurate in distinguishing CNN T2 from MESE T2, with one reader having random-chance categorization. CNN T2 values were correlated to the MESE values in the subregions of 30 patients and in the bulk analysis of all patients, with best-fit line slopes between 0.55 and 0.83.

CONCLUSION

With use of a neural network-based cGAN approach, it is feasible to synthesize T2 maps in femoral cartilage from anatomic MRI sequences, giving good agreement with MESE scans.See also commentary by Yi and Fritz in this issue.Keywords: Cartilage Imaging, Knee, Experimental Investigations, Quantification, Vision, Application Domain, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021.

Multiple-echo steady-state (MESS): Extending DESS for joint T2 mapping and chemical-shift corrected water-fat separation

Purpose

To extend the double echo steady‐state (DESS) sequence to enable chemical‐shift corrected water‐fat separation.

Methods

This study proposes multiple‐echo steady‐state (MESS), a sequence that modifies the readouts of the DESS sequence to acquire two echoes each with bipolar readout gradients with higher readout bandwidth. This enables water‐fat separation and eliminates the need for water‐selective excitation that is often used in combination with DESS, without increasing scan time. An iterative fitting approach was used to perform joint chemical‐shift corrected water‐fat separation and T₂ estimation on all four MESS echoes simultaneously. MESS and water‐selective DESS images were acquired for five volunteers, and were compared qualitatively as well as quantitatively on cartilage T₂ and thickness measurements. Signal‐to‐noise ratio (SNR) and T₂ quantification were evaluated numerically using pseudo‐replications of the acquisition.

Results

The water‐fat separation provided by MESS was robust and with quality comparable to water‐selective DESS. MESS T₂ estimation was similar to DESS, albeit with slightly higher variability. Noise analysis showed that SNR in MESS was comparable to DESS on average, but did exhibit local variations caused by uncertainty in the water‐fat separation.

Conclusion

In the same acquisition time as DESS, MESS provides water‐fat separation with comparable SNR in the reconstructed water and fat images. By providing additional image contrasts in addition to the water‐selective DESS images, MESS provides a promising alternative to DESS.

Diagnostic Accuracy of Quantitative Multicontrast 5-Minute Knee MRI Using Prospective Artificial Intelligence Image Quality Enhancement

BACKGROUND. Potential approaches for abbreviated knee MRI, including prospective acceleration with deep learning, have achieved limited clinical implementation. OBJECTIVE. The objective of this study was to evaluate the interreader agreement between conventional knee MRI and a 5-minute 3D quantitative double-echo steady-state (qDESS) sequence with automatic T2 mapping and deep learning super-resolutionaugmentation and to compare the diagnostic performance of the two methods regarding findings from arthroscopic surgery. METHODS. Fifty-one patients with knee pain underwent knee MRI that included an additional 3D qDESS sequence with automatic T2 mapping. Fourier interpolation was followed by prospective deep learning super resolution to enhance qDESS slice resolution twofold. A musculoskeletal radiologist and a radiology resident performed independent retrospective evaluations of articular cartilage, menisci, ligaments, bones, extensor mechanism, and synovium using conventional MRI. Following a 2-month washout period, readers reviewed qDESS images alone followed by qDESS with the automatic T2 maps. Interreader agreement between conventional MRI and qDESS was computed using percentage agreement and Cohen kappa. The sensitivity and specificity of conventional MRI, qDESS alone, and qDESS plus T2 mapping were compared with arthroscopic findings using exact McNemar tests. RESULTS. Conventional MRI and qDESS showed 92% agreement in evaluating all tissues. Kappa was 0.79 (95% CI, 0.76-0.81) across all imaging findings. In 43 patients who underwent arthroscopy, sensitivity and specificity were not significantly different (p = .23 to > .99) between conventional MRI (sensitivity, 58-93%; specificity, 27-87%) and qDESS alone (sensitivity, 54-90%; specificity, 23-91%) for cartilage, menisci, ligaments, and synovium. For grade 1 cartilage lesions, sensitivity and specificity were 33% and 56%, respectively, for conventional MRI; 23% and 53% for qDESS (p = .81); and 46% and 39% for qDESS with T2 mapping (p = .80). For grade 2A lesions, values were 27% and 53% for conventional MRI, 26% and 52% for qDESS (p = .02), and 58% and 40% for qDESS with T2 mapping (p < .001). CONCLUSION. The qDESS method prospectively augmented with deep learning showed strong interreader agreement with conventional knee MRI and near-equivalent diagnostic performance regarding arthroscopy. The ability of qDESS to automatically generate T2 maps increases sensitivity for cartilage abnormalities. CLINICAL IMPACT. Using prospective artificial intelligence to enhance qDESS image quality may facilitate an abbreviated knee MRI protocol while generating quantitative T2 maps.

Non-contrast MRI of synovitis in the knee using quantitative DESS

OBJECTIVES

To determine whether synovitis graded by radiologists using hybrid quantitative double-echo in steady-state (qDESS) images can be utilized as a non-contrast approach to assess synovitis in the knee, compared against the reference standard of contrast-enhanced MRI (CE-MRI).

METHODS

Twenty-two knees (11 subjects) with moderate to severe osteoarthritis (OA) were scanned using CE-MRI, qDESS with a high diffusion weighting (qDESS_High), and qDESS with a low diffusion weighting (qDESS_Low). Four radiologists graded the overall impression of synovitis, their diagnostic confidence, and regional grading of synovitis severity at four sites (suprapatellar pouch, intercondylar notch, and medial and lateral peripatellar recesses) in the knee using a 4-point scale. Agreement between CE-MRI and qDESS, inter-rater agreement, and intra-rater agreement were assessed using a linearly weighted Gwet's AC2.

RESULTS

Good agreement was seen between CE-MRI and both qDESS_Low (AC2 = 0.74) and qDESS_High (AC2 = 0.66) for the overall impression of synovitis, but both qDESS sequences tended to underestimate the severity of synovitis compared to CE-MRI. Good inter-rater agreement was seen for both qDESS sequences (AC2 = 0.74 for qDESS_Low, AC2 = 0.64 for qDESS_High), and good intra-rater agreement was seen for both sequences as well (qDESS_Low AC2 = 0.78, qDESS_High AC2 = 0.80). Diagnostic confidence was moderate to high for qDESS_Low (mean = 2.36) and slightly less than moderate for qDESS_High (mean = 1.86), compared to mostly high confidence for CE-MRI (mean = 2.73).

CONCLUSIONS

qDESS shows potential as an alternative MRI technique for assessing the severity of synovitis without the use of a gadolinium-based contrast agent.

KEY POINTS

The use of the quantitative double-echo in steady-state (qDESS) sequence for synovitis assessment does not require the use of a gadolinium-based contrast agent. Preliminary results found that low diffusion-weighted qDESS (qDESS_Low) shows good agreement to contrast-enhanced MRI for characterization of the severity of synovitis, with a relative bias towards underestimation of severity. Preliminary results also found that qDESS_Low shows good inter- and intra-rater agreement for the depiction of synovitis, particularly for readers experienced with the sequence.

Ultrashort echo time Cones double echo steady state (UTE-Cones-DESS) for rapid morphological imaging of short T2 tissues

PURPOSE

In this study, we aimed to develop a new technique, ultrashort echo time Cones double echo steady state (UTE-Cones-DESS), for highly efficient morphological imaging of musculoskeletal tissues with short T₂ s. We also proposed a novel, single-point Dixon (spDixon)-based approach for fat suppression.

METHODS

The UTE-Cones-DESS sequence was implemented on a 3T MR system. It uses a short radiofrequency (RF) pulse followed by a pair of balanced spiral-out and spiral-in readout gradients separated by an unbalanced spoiling gradient in-between. The readout gradients are applied immediately before or after the RF pulses to achieve a UTE image (S₊ ) and a spin/stimulated echo image (S_- ). Weighted echo subtraction between S₊ and S_- was performed to achieve high contrast specific to short T₂ tissues, and spDixon was applied to suppress fat by using the intrinsic complex signal of S₊ and S_- . Six healthy volunteers and five patients with osteoarthritis were recruited for whole-knee imaging. Additionally, two healthy volunteers were recruited for lower leg imaging.

RESULTS

The UTE-Cones-DESS sequence allows fast volumetric imaging of musculoskeletal tissues with excellent image contrast for the osteochondral junction, tendons, menisci, and ligaments in the knee joint as well as cortical bone and aponeurosis in the lower leg within 5 min. spDixon yields efficient fat suppression in both S₊ and S_- images without requiring any additional acquisitions or preparation pulses.

CONCLUSION

The rapid UTE-Cones-DESS sequence can be used for high contrast morphological imaging of short T₂ tissues, providing a new tool to assess their association with musculoskeletal disorders.

Utilizing shared information between gradient-spoiled and RF-spoiled steady-state MRI signals

This work presents an analytical relationship between gradient-spoiled and RF-spoiled steady-state signals. The two echoes acquired in double-echo in steady-state scans are shown to lie on a line in the signal plane, where the two axes represent the amplitudes of each echo. The location along the line depends on the amount of spoiling and the diffusivity. The line terminates in a point corresponding to an RF-spoiled signal. In addition to the main contribution of demonstrating this signal relationship, we also include the secondary contribution of preliminary results from an example application of the relationship, in the form of a heuristic denoising method when both types of scans are performed. This is investigated in simulations, phantom scans, and in vivo scans. For the signal model, the main topic of this study, simulations confirmed its accuracy and explored its dependency on signal parameters and image noise. For the secondary topic of its preliminary application to reduce noise, simulations demonstrated the denoising method giving a reduction in noise-induced standard deviation of about 30%. The relative effect of the method on the signals is shown to depend on the slope of the described line, which is demonstrated to be zero at the Ernst angle. The phantom scans show a similar effect as the simulations. In vivo scans showed a slightly lower average improvement of about 28%.

Preoperative MRI of Articular Cartilage in the Knee: A Practical Approach

Articular cartilage of the knee can be evaluated with high accuracy by magnetic resonance imaging (MRI) in preoperative patients with knee pain, but image quality and reporting are variable. This article discusses the normal MRI appearance of articular cartilage as well as the common MRI abnormalities of knee cartilage that may be considered for operative treatment. This article focuses on a practical approach to preoperative MRI of knee articular cartilage using routine MRI techniques. Current and future directions of knee MRI related to articular cartilage are also discussed.

Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis

Osteoarthritis (OA) of the knee is a major source of disability that has no known treatment or cure. Morphological and compositional MRI is commonly used for assessing the bone and soft tissues in the knee to enhance the understanding of OA pathophysiology. However, it is challenging to extend these imaging methods and their subsequent analysis techniques to study large population cohorts due to slow and inefficient imaging acquisition and postprocessing tools. This can create a bottleneck in assessing early OA changes and evaluating the responses of novel therapeutics. The purpose of this review article is to highlight recent developments in tools for enhancing the efficiency of knee MRI methods useful to study OA. Advances in efficient MRI data acquisition and reconstruction tools for morphological and compositional imaging, efficient automated image analysis tools, and hardware improvements to further drive efficient imaging are discussed in this review. For each topic, we discuss the current challenges as well as potential future opportunities to alleviate these challenges. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Depth-dependent changes in cartilage T2 under compressive strain: a 7T MRI study on human knee cartilage

OBJECTIVE

To assess the potential of using ΔT2 as an indirect index of cartilage strain by quantifying the relationship between local in situ compressive strain and ΔT2 through the full depth of human tibial and femoral articular cartilage.

DESIGN

Osteochondral samples (n = 4) of human tibial and femoral cartilage were harvested from cadavers and imaged in a Bruker 7T research MRI scanner under increasing displacement-controlled compressive strains. T2 was calculated for 3D double echo steady state (DESS) image volumes at each strain level. A decaying exponential model estimated local, depth-dependent strains. Strained image volumes were non-linearly warped back to their unloaded configurations and ΔT2 was calculated by image subtraction. Linear modeling assessed local relationships between strain and ΔT2.

RESULTS

Bulk average tibial T2 was 13.2 ms for unstrained cartilage and ranged from 13.0 to 13.1 ms under strain; femoral T2 was 14.0 ms for unstrained cartilage and ranged from 13.5 to 14.8 ms under strain. Local ΔT2 in strained cartilage varied with depth. Linear modeling revealed significant correlations between in situ strain and ΔT2 for both tibial and femoral cartilage; correlation coefficients were higher for tibial cartilage.

CONCLUSIONS

Changes in bulk average T2 are unsuitable as a quantitative surrogate measure of cartilage strain because bulk averaging masks important local variations. High-resolution measures of local ΔT2 have potential value as a surrogate for strain; however, their value is limited until we fully understand the influence of factors like age, joint surface and degeneration on the strain vs T2 relationship.

Rapid volumetric gagCEST imaging of knee articular cartilage at 3 T: evaluation of improved dynamic range and an osteoarthritic population

Chemical exchange saturation transfer of glycosaminoglycans, gagCEST, is a quantitative MR technique that has potential for assessing cartilage proteoglycan content at field strengths of 7 T and higher. However, its utility at 3 T remains unclear. The objective of this work was to implement a rapid volumetric gagCEST sequence with higher gagCEST asymmetry at 3 T to evaluate its sensitivity to osteoarthritic changes in knee articular cartilage and in comparison with T₂ and T_1ρ measures. We hypothesize that gagCEST asymmetry at 3 T decreases with increasing severity of osteoarthritis (OA). Forty-two human volunteers, including 10 healthy subjects and 32 subjects with medial OA, were included in the study. Knee Injury and Osteoarthritis Outcome Scores (KOOS) were assessed for all subjects, and Kellgren-Lawrence grading was performed for OA volunteers. Healthy subjects were scanned consecutively at 3 T to assess the repeatability of the volumetric gagCEST sequence at 3 T. For healthy and OA subjects, gagCEST asymmetry and T₂ and T_1ρ relaxation times were calculated for the femoral articular cartilage to assess sensitivity to OA severity. Volumetric gagCEST imaging had higher gagCEST asymmetry than single-slice acquisitions (p = 0.015). The average scan-rescan coefficient of variation was 6.8%. There were no significant differences in average gagCEST asymmetry between younger and older healthy controls (p = 0.655) or between healthy controls and OA subjects (p = 0.310). T₂ and T_1ρ relaxation times were elevated in OA subjects (p < 0.001 for both) compared with healthy controls and both were moderately correlated with total KOOS scores (rho = -0.181 and rho = -0.332 respectively). The gagCEST technique developed here, with volumetric scan times under 10 min and high gagCEST asymmetry at 3 T, did not vary significantly between healthy subjects and those with mild-moderate OA. This further supports a limited utility for gagCEST imaging at 3 T for assessment of early changes in cartilage composition in OA.

pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage

Transparent research in musculoskeletal imaging is fundamental to reliably investigate diseases such as knee osteoarthritis (OA), a chronic disease impairing femoral knee cartilage. To study cartilage degeneration, researchers have developed algorithms to segment femoral knee cartilage from magnetic resonance (MR) images and to measure cartilage morphology and relaxometry. The majority of these algorithms are not publicly available or require advanced programming skills to be compiled and run. However, to accelerate discoveries and findings, it is crucial to have open and reproducible workflows. We present pyKNEEr, a framework for open and reproducible research on femoral knee cartilage from MR images. pyKNEEr is written in python, uses Jupyter notebook as a user interface, and is available on GitHub with a GNU GPLv3 license. It is composed of three modules: 1) image preprocessing to standardize spatial and intensity characteristics; 2) femoral knee cartilage segmentation for intersubject, multimodal, and longitudinal acquisitions; and 3) analysis of cartilage morphology and relaxometry. Each module contains one or more Jupyter notebooks with narrative, code, visualizations, and dependencies to reproduce computational environments. pyKNEEr facilitates transparent image-based research of femoral knee cartilage because of its ease of installation and use, and its versatility for publication and sharing among researchers. Finally, due to its modular structure, pyKNEEr favors code extension and algorithm comparison. We tested our reproducible workflows with experiments that also constitute an example of transparent research with pyKNEEr, and we compared pyKNEEr performances to existing algorithms in literature review visualizations. We provide links to executed notebooks and executable environments for immediate reproducibility of our findings.

Time-saving opportunities in knee osteoarthritis: T2 mapping and structural imaging of the knee using a single 5-min MRI scan

Objectives

To assess the discriminative power of a 5-min quantitative double-echo steady-state (qDESS) sequence for simultaneous T₂ measurements of cartilage and meniscus, and structural knee osteoarthritis (OA) assessment, in a clinical OA population, using radiographic knee OA as reference standard.

Methods

Fifty-three subjects were included and divided over three groups based on radiographic and clinical knee OA: 20 subjects with no OA (Kellgren-Lawrence grade (KLG) 0), 18 with mild OA (KLG2), and 15 with moderate OA (KLG3). All patients underwent a 5-min qDESS scan. We measured T₂ relaxation times in four cartilage and four meniscus regions of interest (ROIs) and performed structural OA evaluation with the MRI Osteoarthritis Knee Score (MOAKS) using qDESS with multiplanar reformatting. Between-group differences in T₂ values and MOAKS were calculated using ANOVA. Correlations of the reference standard (i.e., radiographic knee OA) with T₂ and MOAKS were assessed with correlation analyses for ordinal variables.

Results

In cartilage, mean T₂ values were 36.1 ± SD 4.3, 40.6 ± 5.9, and 47.1 ± 4.3 ms for no, mild, and moderate OA, respectively (p < 0.001). In menisci, mean T₂ values were 15 ± 3.6, 17.5 ± 3.8, and 20.6 ± 4.7 ms for no, mild, and moderate OA, respectively (p < 0.001). Statistically significant correlations were found between radiographic OA and T₂ and between radiographic OA and MOAKS in all ROIs (p < 0.05).

Conclusion

Quantitative T₂ and structural assessment of cartilage and meniscus, using a single 5-min qDESS scan, can distinguish between different grades of radiographic OA, demonstrating the potential of qDESS as an efficient tool for OA imaging.

Key Points

• Quantitative T₂values of cartilage and meniscus as well as structural assessment of the knee with a single 5-min quantitative double-echo steady-state (qDESS) scan can distinguish between different grades of knee osteoarthritis (OA).

• Quantitative and structural qDESS-based measurements correlate significantly with the reference standard, radiographic degree of OA, for all cartilage and meniscus regions.

• By providing quantitative measurements and diagnostic image quality in one rapid MRI scan, qDESS has great potential for application in large-scale clinical trials in knee OA.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06542-9) contains supplementary material, which is available to authorized users.

Emerging quantitative MR imaging biomarkers in inflammatory arthritides

PURPOSE

To review quantitative magnetic resonance imaging (qMRI) methods for imaging inflammation in connective tissues and the skeleton in inflammatory arthritis. This review is designed for a broad audience including radiologists, imaging technologists, rheumatologists and other healthcare professionals.

METHODS

We discuss the use of qMRI for imaging skeletal inflammation from both technical and clinical perspectives. We consider how qMRI can be targeted to specific aspects of the pathological process in synovium, cartilage, bone, tendons and entheses. Evidence for the various techniques from studies of both adults and children with inflammatory arthritis is reviewed and critically appraised.

RESULTS

qMRI has the potential to objectively identify, characterize and quantify inflammation of the connective tissues and skeleton in both adult and pediatric patients. Measurements of tissue properties derived using qMRI methods can serve as imaging biomarkers, which are potentially more reproducible and informative than conventional MRI methods. Several qMRI methods are nearing transition into clinical practice and may inform diagnosis and treatment decisions, with the potential to improve patient outcomes.

CONCLUSIONS

qMRI enables specific assessment of inflammation in synovium, cartilage, bone, tendons and entheses, and can facilitate a more consistent, personalized approach to diagnosis, characterisation and monitoring of disease.

Flexible and efficient optimization of quantitative sequences using automatic differentiation of Bloch simulations

PURPOSE

To investigate a computationally efficient method for optimizing the Cramér-Rao Lower Bound (CRLB) of quantitative sequences without using approximations or an analytical expression of the signal.

METHODS

Automatic differentiation was applied to Bloch simulations and used to optimize several quantitative sequences without the need for approximations or an analytical expression. The results were validated with in vivo measurements and comparisons to prior art. Multi-echo spin echo and DESPO T 1 were used as benchmarks to verify the CRLB implementation. The CRLB of the Magnetic Resonance Fingerprinting (MRF) sequence, which has a complicated analytical formulation, was also optimized using automatic differentiation.

RESULTS

The sequence parameters obtained for multi-echo spin echo and DESPO T 1 matched results obtained using conventional methods. In vivo, MRF scans demonstrate that the CRLB optimization obtained with automatic differentiation can improve performance in presence of white noise. For MRF, the CRLB optimization converges in 1.1 CPU hours for N TR = 400 and has O ( N TR ) asymptotic runtime scaling for the calculation of the CRLB objective and gradient.

CONCLUSIONS

Automatic differentiation can be used to optimize the CRLB of quantitative sequences without using approximations or analytical expressions. For MRF, the runtime is computationally efficient and can be used to investigate confounding factors as well as MRF sequences with a greater number of repetitions.

Combined 5-minute double-echo in steady-state with separated echoes and 2-minute proton-density-weighted 2D FSE sequence for comprehensive whole-joint knee MRI assessment

BACKGROUND

Clinical knee MRI protocols require upwards of 15 minutes of scan time.

PURPOSE/HYPOTHESIS

To compare the imaging appearance of knee abnormalities depicted with a 5-minute 3D double-echo in steady-state (DESS) sequence with separate echo images, with that of a routine clinical knee MRI protocol. A secondary goal was to compare the imaging appearance of knee abnormalities depicted with 5-minute DESS paired with a 2-minute coronal proton-density fat-saturated (PDFS) sequence.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-six consecutive patients (19 male) referred for a routine knee MRI.

FIELD STRENGTH/SEQUENCES

DESS and PDFS at 3T.

ASSESSMENT

Five musculoskeletal radiologists evaluated all images for the presence of internal knee derangement using DESS, DESS+PDFS, and the conventional imaging protocol, and their associated diagnostic confidence of the reading.

STATISTICAL TESTS

Differences in positive and negative percent agreement (PPA and NPA, respectively) and 95% confidence intervals (CIs) for DESS and DESS+PDFS compared with the conventional protocol were calculated and tested using exact McNemar tests. The percentage of observations where DESS or DESS+PDFS had equivalent confidence ratings to DESS+Conv were tested with exact symmetry tests. Interreader agreement was calculated using Krippendorff's alpha.

RESULTS

DESS had a PPA of 90% (88-92% CI) and NPA of 99% (99-99% CI). DESS+PDFS had increased PPA of 99% (95-99% CI) and NPA of 100% (99-100% CI) compared with DESS (both P < 0.001). DESS had equivalent diagnostic confidence to DESS+Conv in 94% of findings, whereas DESS+PDFS had equivalent diagnostic confidence in 99% of findings (both P < 0.001). All readers had moderate concordance for all three protocols (Krippendorff's alpha 47-48%).

DATA CONCLUSION

Both 1) 5-minute 3D-DESS with separated echoes and 2) 5-minute 3D-DESS paired with a 2-minute coronal PDFS sequence depicted knee abnormalities similarly to a routine clinical knee MRI protocol, which may be a promising technique for abbreviated knee MRI.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Super-resolution musculoskeletal MRI using deep learning

PURPOSE

To develop a super-resolution technique using convolutional neural networks for generating thin-slice knee MR images from thicker input slices, and compare this method with alternative through-plane interpolation methods.

METHODS

We implemented a 3D convolutional neural network entitled DeepResolve to learn residual-based transformations between high-resolution thin-slice images and lower-resolution thick-slice images at the same center locations. DeepResolve was trained using 124 double echo in steady-state (DESS) data sets with 0.7-mm slice thickness and tested on 17 patients. Ground-truth images were compared with DeepResolve, clinically used tricubic interpolation, and Fourier interpolation methods, along with state-of-the-art single-image sparse-coding super-resolution. Comparisons were performed using structural similarity, peak SNR, and RMS error image quality metrics for a multitude of thin-slice downsampling factors. Two musculoskeletal radiologists ranked the 3 data sets and reviewed the diagnostic quality of the DeepResolve, tricubic interpolation, and ground-truth images for sharpness, contrast, artifacts, SNR, and overall diagnostic quality. Mann-Whitney U tests evaluated differences among the quantitative image metrics, reader scores, and rankings. Cohen's Kappa (κ) evaluated interreader reliability.

RESULTS

DeepResolve had significantly better structural similarity, peak SNR, and RMS error than tricubic interpolation, Fourier interpolation, and sparse-coding super-resolution for all downsampling factors (p < .05, except 4 × and 8 × sparse-coding super-resolution downsampling factors). In the reader study, DeepResolve significantly outperformed (p < .01) tricubic interpolation in all image quality categories and overall image ranking. Both readers had substantial scoring agreement (κ = 0.73).

CONCLUSION

DeepResolve was capable of resolving high-resolution thin-slice knee MRI from lower-resolution thicker slices, achieving superior quantitative and qualitative diagnostic performance to both conventionally used and state-of-the-art methods.

SNR-weighted regularization of ADC estimates from double-echo in steady-state (DESS)

PURPOSE

To improve the homogeneity and consistency of apparent diffusion coefficient (ADC) estimates in cartilage from the double-echo in steady-state (DESS) sequence by applying SNR-weighted regularization during post-processing.

METHODS

An estimation method that linearizes ADC estimates from DESS is used in conjunction with a smoothness constraint to suppress noise-induced variation in ADC estimates. Simulations, phantom scans, and in vivo scans are used to demonstrate how the method reduces ADC variability. Conventional diffusion-weighted echo-planar imaging (DW EPI) maps are acquired for comparison of mean and standard deviation (SD) of the ADC estimate.

RESULTS

Simulations and phantom scans demonstrated that the SNR-weighted regularization can produce homogenous ADC maps at varying levels of SNR, whereas non-regularized maps only estimate ADC accurately at high SNR levels. The in vivo maps showed that the SNR-weighted regularization produced ADC maps with similar heterogeneity to maps produced with standard DW EPI, but without the distortion of such reference scans.

CONCLUSION

A linear approximation of a simplified model of the relationship between DESS signals allows for fast SNR-weighted regularization of ADC maps that reduces estimation error in relatively short T₂ tissue such as cartilage.

Quantitative imaging of bone-cartilage interactions in ACL-injured patients with PET-MRI

OBJECTIVE

To investigate changes in bone metabolism by positron emission tomography (PET), as well as spatial relationships between bone metabolism and magnetic resonance imaging (MRI) quantitative markers of early cartilage degradation, in anterior cruciate ligament (ACL)-reconstructed knees.

DESIGN

Both knees of 15 participants with unilateral reconstructed ACL tears and unaffected contralateral knees were scanned using a simultaneous 3.0T PET-MRI system following injection of 18F-sodium fluoride (18F-NaF). The maximum pixel standardized uptake value (SUVmax) in the subchondral bone and the average T2 relaxation time in cartilage were measured in each knee in eight knee compartments. We tested differences in SUVmax and cartilage T2 relaxation times between the ACL-injured knee and the contralateral control knee as well as spatial relationships between these bone and cartilage changes.

RESULTS

Significantly increased subchondral bone 18F-NaF SUVmax and cartilage T2 times were observed in the ACL-reconstructed knees (median [inter-quartile-range (IQR)]: 5.0 [5.8], 36.8 [3.6] ms) compared to the contralateral knees (median [IQR]: 1.9 [1.4], 34.4 [3.8] ms). A spatial relationship between the two markers was also seen. Using the contralateral knee as a control, we observed a significant correlation of r = 0.59 between the difference in subchondral bone SUVmax (between injured and contralateral knees) and the adjacent cartilage T2 (between the two knees) [P < 0.001], with a slope of 0.49 ms/a.u. This correlation and slope were higher in deep layers (r = 0.73, slope = 0.60 ms/a.u.) of cartilage compared to superficial layers (r = 0.40, slope = 0.43 ms/a.u.).

CONCLUSIONS

18F-NaF PET-MR imaging enables detection of increased subchondral bone metabolism in ACL-reconstructed knees and may serve as an important marker of early osteoarthritis (OA) progression. Spatial relationships observed between early OA changes across bone and cartilage support the need to study whole-joint disease mechanisms in OA.

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.

Simultaneous bilateral-knee MR imaging

PURPOSE

To demonstrate and evaluate the scan time and quantitative accuracy of simultaneous bilateral-knee imaging compared with single-knee acquisitions.

METHODS

Hardware modifications and safety testing was performed to enable MR imaging with two 16-channel flexible coil arrays. Noise covariance and sensitivity-encoding g-factor maps for the dual-coil-array configuration were computed to evaluate coil cross-talk and noise amplification. Ten healthy volunteers were imaged on a 3T MRI scanner with both dual-coil-array bilateral-knee and single-coil-array single-knee configurations. Two experienced musculoskeletal radiologists compared the relative image quality between blinded image pairs acquired with each configuration. Differences in T₂ relaxation time measurements between dual-coil-array and single-coil-array acquisitions were compared with the standard repeatability of single-coil-array measurements using a Bland-Altman analysis.

RESULTS

The mean g-factors for the dual-coil-array configuration were low for accelerations up to 6 in the right-left direction, and minimal cross-talk was observed between the two coil arrays. Image quality ratings of various joint tissues showed no difference in 89% (95% confidence interval: 85-93%) of rated image pairs, with only small differences ("slightly better" or "slightly worse") in image quality observed. The T₂ relaxation time measurements between the dual-coil-array configuration and the single-coil configuration showed similar limits of agreement and concordance correlation coefficients (limits of agreement: -0.93 to 1.99 ms; CCC: 0.97 (95% confidence interval: 0.96-0.98)), to the repeatability of single-coil-array measurements (limits of agreement: -2.07 to 1.96 ms; CCC: 0.97 (95% confidence interval: 0.95-0.98)).

CONCLUSION

A bilateral coil-array setup can image both knees simultaneously in similar scan times as conventional unilateral knee scans, with comparable image quality and quantitative accuracy. This has the potential to improve the value of MRI knee evaluations. Magn Reson Med 80:529-537, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

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.

Imaging and T2 relaxometry of short-T2 connective tissues in the knee using ultrashort echo-time double-echo steady-state (UTEDESS)

PURPOSE

To develop a radial, double-echo steady-state (DESS) sequence with ultra-short echo-time (UTE) capabilities for T₂ measurement of short-T₂ tissues along with simultaneous rapid, signal-to-noise ratio (SNR)-efficient, and high-isotropic-resolution morphological knee imaging.

METHODS

THe 3D radial UTE readouts were incorporated into DESS, termed UTEDESS. Multiple-echo-time UTEDESS was used for performing T₂ relaxometry for short-T₂ tendons, ligaments, and menisci; and for Dixon water-fat imaging. In vivo T₂ estimate repeatability and SNR efficiency for UTEDESS and Cartesian DESS were compared. The impact of coil combination methods on short-T₂ measurements was evaluated by means of simulations. UTEDESS T₂ measurements were compared with T₂ measurements from Cartesian DESS, multi-echo spin-echo (MESE), and fast spin-echo (FSE).

RESULTS

UTEDESS produced isotropic resolution images with high SNR efficiency in all short-T₂ tissues. Simulations and experiments demonstrated that sum-of-squares coil combinations overestimated short-T₂ measurements. UTEDESS measurements of meniscal T₂ were comparable to DESS, MESE, and FSE measurements while the tendon and ligament measurements were less biased than those from Cartesian DESS. Average UTEDESS T₂ repeatability variation was under 10% in all tissues.

CONCLUSION

The T₂ measurements of short-T₂ tissues and high-resolution morphological imaging provided by UTEDESS makes it promising for studying the whole knee, both in routine clinical examinations and longitudinal studies. Magn Reson Med 78:2136-2148, 2017. © 2017 International Society for Magnetic Resonance in Medicine.