ABSTRACT
PURPOSE: To evaluate the influence of skeletal maturation on sodium (23 Na) MRI relaxation parameters and the accuracy of tissue sodium concentration (TSC) quantification in human knee cartilage. METHODS: Twelve pediatric knee specimens were imaged with whole-body 10.5 T MRI using a density-adapted 3D radial projection sequence to evaluate 23 Na parameters: B1 + , T1 , biexponential T 2 * $$ {\mathrm{T}}_2^{\ast } $$ , and TSC. Water, collagen, and sulfated glycosaminoglycan (sGAG) content were calculated from osteochondral biopsies. The TSC was corrected for B1 + , relaxation, and water content. The literature-based TSC (TSCLB ) used previously published values for corrections, whereas the specimen-specific TSC (TSCSP ) used measurements from individual specimens. 23 Na parameters were evaluated in eight cartilage compartments segmented on proton images. Associations between 23 Na parameters, TSCLB - TSCSP difference, biochemical content, and age were determined. RESULTS: From birth to 12 years, cartilage water content decreased by 18%; collagen increased by 59%; and sGAG decreased by 36% (all R2 ≥ 0.557). The short T 2 * $$ {\mathrm{T}}_2^{\ast } $$ ( T 2 * S $$ {{\mathrm{T}}_2^{\ast}}_{\mathrm{S}} $$ ) decreased by 72%, and the signal fraction relaxing with T 2 * S $$ {{\mathrm{T}}_2^{\ast}}_{\mathrm{S}} $$ ( fT 2 * S $$ {{\mathrm{fT}}_2^{\ast}}_{\mathrm{S}} $$ ) increased by 55% during the first 5 years but remained relatively stable after that. TSCSP was significantly correlated with sGAG content from biopsies (R2 = 0.739). Depending on age, TSCLB showed higher or lower values than TSCSP . The TSCLB - TSCSP difference was significantly correlated with T 2 * S $$ {{\mathrm{T}}_2^{\ast}}_{\mathrm{S}} $$ (R2 = 0.850), fT 2 * S $$ {{\mathrm{fT}}_2^{\ast}}_{\mathrm{S}} $$ (R2 = 0.651), and water content (R2 = 0.738). CONCLUSION: TSC and relaxation parameters measured with 23 Na MRI provide noninvasive information about changes in sGAG content and collagen matrix during cartilage maturation. Cartilage TSC quantification assuming fixed relaxation may be feasible in children older than 5 years.
Subject(s)
Cartilage, Articular , Cartilage , Humans , Child , Child, Preschool , Magnetic Resonance Imaging/methods , Sodium , Collagen , Water , Cartilage, Articular/diagnostic imagingABSTRACT
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.
Subject(s)
Knee Joint , Magnetic Resonance Imaging , Humans , Cross-Sectional Studies , Magnetic Resonance Imaging/methods , Knee Joint/diagnostic imaging , Imaging, Three-Dimensional , Phantoms, ImagingABSTRACT
Imaging of the joint in response to loading stress may provide additional measures of joint structure and function beyond conventional, static imaging studies. Exercise such as running, stair climbing, and squatting allows evaluation of the joint response to larger loading forces than during weight bearing. Quantitative MRI (qMRI) may assess properties of cartilage and meniscus hydration and organization in vivo that have been investigated to assess the functional response of these tissues to physiological stress. [18F]sodium fluoride ([18F]NaF) interrogates areas of newly mineralizing bone and provides an opportunity to study bone physiology, including perfusion and mineralization rate, as a measure of joint loading stress. In this review article, methods utilizing quantitative MRI, PET, and hybrid PET-MRI systems for assessment of the joint response to loading from exercise in vivo are examined. Both methodology and results of various studies performed are outlined and discussed. Lastly, the technical considerations, challenges, and future opportunities for these approaches are addressed.
Subject(s)
Magnetic Resonance Imaging , Positron-Emission Tomography , Humans , Positron-Emission Tomography/methods , Magnetic Resonance Imaging/methods , Cartilage , Bone and BonesABSTRACT
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.
Subject(s)
Cartilage, Articular , Deep Learning , Osteoarthritis, Knee , Female , Humans , Retrospective Studies , Cartilage, Articular/pathology , Magnetic Resonance Imaging/methods , Algorithms , Osteoarthritis, Knee/pathologyABSTRACT
The dynamic contrast-enhanced (DCE)-MRI parameter Ktrans can quantify the intensity of synovial inflammation (synovitis) in knees with osteoarthritis (OA), but requires the use of gadolinium-based contrast agent (GBCA). Diffusion tensor imaging (DTI) measures the diffusion of water molecules with parameters mean diffusivity (MD) and fractional anisotropy (FA), and has been proposed as a method to detect synovial inflammation without the use of GBCA. The purpose of this study is to (1) determine the ability of DTI to quantify the intensity of synovitis in OA by comparing MD and FA with our imaging gold standard Ktrans within the synovium and (2) compare DTI and DCE-MRI measures with the semi-quantitative grading of OA severity with the Kellgren-Lawrence (KL) and MRI Osteoarthritis Knee Score (MOAKS) systems, in order to assess the relationship between synovitis intensity and OA severity. Within the synovium, MD showed a significant positive correlation with Ktrans (r = 0.79, p < 0.001), while FA showed a significant negative correlation with Ktrans (r = -0.72, p = 0.0026). These results show that DTI is able to quantify the intensity of synovitis within the whole synovium without the use of exogenous contrast agent. Additionally, MD, FA, and Ktrans values did not vary significantly when knees were separated by KL grade (p = 0.15, p = 0.32, p = 0.41, respectively), while MD (r = 0.60, p = 0.018) and Ktrans (r = 0.62, p = 0.013) had a significant positive correlation and FA (r = -0.53, p = 0.043) had a negative correlation with MOAKS. These comparisons indicate that quantitative measures of the intensity of synovitis may provide information in addition to morphological assessment to evaluate OA severity. Using DTI to quantify the intensity of synovitis without GBCA may be helpful to facilitate a broader clinical assessment of the severity of OA.
Subject(s)
Diffusion Tensor Imaging/methods , Osteoarthritis, Knee/diagnostic imaging , Synovitis/diagnostic imaging , Adult , Aged , Contrast Media , Cross-Sectional Studies , Female , Gadolinium , Humans , Image Enhancement , Male , Middle Aged , Signal-To-Noise RatioABSTRACT
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 (qDESSHigh), and qDESS with a low diffusion weighting (qDESSLow). 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 qDESSLow (AC2 = 0.74) and qDESSHigh (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 qDESSLow, AC2 = 0.64 for qDESSHigh), and good intra-rater agreement was seen for both sequences as well (qDESSLow AC2 = 0.78, qDESSHigh AC2 = 0.80). Diagnostic confidence was moderate to high for qDESSLow (mean = 2.36) and slightly less than moderate for qDESSHigh (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 (qDESSLow) 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 qDESSLow shows good inter- and intra-rater agreement for the depiction of synovitis, particularly for readers experienced with the sequence.
Subject(s)
Osteoarthritis, Knee , Synovitis , Contrast Media , Humans , Knee Joint/diagnostic imaging , Magnetic Resonance Imaging , Osteoarthritis, Knee/diagnostic imaging , Synovial Membrane , Synovitis/diagnostic imagingABSTRACT
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.
Subject(s)
Cartilage, Articular , Running , Cartilage, Articular/pathology , Female , Humans , Knee , Knee Joint/physiology , Magnetic Resonance Imaging/methods , Patella , Running/physiologyABSTRACT
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 T1ρ 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 T1ρ 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 T1ρ 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.
Subject(s)
Cartilage, Articular/chemistry , Glycosaminoglycans , Knee Joint/diagnostic imaging , Magnetic Resonance Imaging/methods , Osteoarthritis, Knee/diagnostic imaging , Proteoglycans/analysis , Adult , Aged , Female , Femur/diagnostic imaging , Healthy Volunteers , Humans , Male , Middle Aged , Osteoarthritis, Knee/metabolism , Reproducibility of ResultsABSTRACT
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 T1 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 T1 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 NTR = 400 and has O(NTR) 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.