Cartilage T1ρ and T2 relaxation times: longitudinal reproducibility and variations using different coils, MR systems and sites

Automated quantitative assessment of bone contusions and overlying articular cartilage following anterior cruciate ligament injury

Quantitative methods to characterize bone contusions and associated cartilage injury remain limited. We combined standardized voxelwise normalization and 3D mapping to automate bone contusion segmentation post-anterior cruciate ligament (ACL) injury and evaluate anomalies in articular cartilage overlying bone contusions. Forty-five patients (54% female, 26.4 ± 11.8 days post-injury) with an ACL tear underwent 3T magnetic resonance imaging of their involved and uninvolved knees. A novel method for voxelwise normalization and 3D anatomical mapping was used to automate segmentation, labeling, and localization of bone contusions in the involved knee. The same mapping system was used to identify the associated articular cartilage overlying bone lesions. Mean regional T1ρ was extracted from articular cartilage regions in both the involved and uninvolved knees for quantitative paired analysis against ipsilateral cartilage within the same compartment outside of the localized bone contusion. At least one bone contusion lesion was detected in the involved knee within the femur and/or tibia following ACL injury in 42 participants. Elevated T1ρ (p = 0.033) signal were documented within the articular cartilage overlying the bone contusions resulting from ACL injury. In contrast, the same cartilaginous regions deprojected onto the uninvolved knees showed no ipsilateral differences (p = 0.795). Automated bone contusion segmentation using standardized voxelwise normalization and 3D mapping deprojection identified altered cartilage overlying bone contusions in the setting of knee ACL injury.

Synthetic Knee MRI T1p Maps as an Avenue for Clinical Translation of Quantitative Osteoarthritis Biomarkers

A 2D U-Net was trained to generate synthetic T1p maps from T2 maps for knee MRI to explore the feasibility of domain adaptation for enriching existing datasets and enabling rapid, reliable image reconstruction. The network was developed using 509 healthy contralateral and injured ipsilateral knee images from patients with ACL injuries and reconstruction surgeries acquired across three institutions. Network generalizability was evaluated on 343 knees acquired in a clinical setting and 46 knees from simultaneous bilateral acquisition in a research setting. The deep neural network synthesized high-fidelity reconstructions of T1p maps, preserving textures and local T1p elevation patterns in cartilage with a normalized mean square error of 2.4% and Pearson's correlation coefficient of 0.93. Analysis of reconstructed T1p maps within cartilage compartments revealed minimal bias (-0.10 ms), tight limits of agreement, and quantification error (5.7%) below the threshold for clinically significant change (6.42%) associated with osteoarthritis. In an out-of-distribution external test set, synthetic maps preserved T1p textures, but exhibited increased bias and wider limits of agreement. This study demonstrates the capability of image synthesis to reduce acquisition time, derive meaningful information from existing datasets, and suggest a pathway for standardizing T1p as a quantitative biomarker for osteoarthritis.

Patellar Dislocation in Adolescent Patients: Influence on Cartilage Properties Based on T1ρ Relaxation Times

BACKGROUND

Adolescents who experience a patellar dislocation have an elevated risk of patellofemoral posttraumatic osteoarthritis. Magnetic resonance imaging (MRI)-based T1ρ relaxation times were measured for adolescents to evaluate patellofemoral cartilage after patellar dislocation. Long T1ρ relaxation times are an indicator of cartilage degradation.

HYPOTHESIS

The primary hypothesis is that patellofemoral cartilage T1ρ relaxation times will be elevated in the acute phase after patellar dislocation. The secondary hypothesis is that T1ρ relaxation times will be higher for knees with multiple rather than single dislocations due to repeated traumatic injury.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

In total, 23 adolescents being treated for a recent patellar dislocation, 13 for a first-time dislocation (47 ± 38 days since most recent dislocation) and 10 for multiple dislocations (55 ± 24 days since most recent dislocation), and 10 healthy controls participated in MRI-based T1ρ relaxation time mapping. For multiple regions of the patellofemoral joint, mean T1ρ values were compared between the 3 groups with multiple group comparisons and post hoc tests. T1ρ relaxation times were also correlated against measures of patellofemoral anatomy and alignment for single and multiple dislocations. Statistical significance was set at P < .05.

RESULTS

T1ρ relaxation times were significantly longer for injured knees (single and multiple dislocations) than controls at the medial and central patella and central trochlear groove. For the regions on the patella, significant differences between injured and control knees exceeded 15%. No significant differences were identified between single and multiple dislocations. For the initial dislocation group, T1ρ relaxation times within multiple regions of the patellofemoral joint were significantly correlated with lateral patellar alignment or patellar height.

CONCLUSION

Elevated patellofemoral cartilage T1ρ relaxation times are consistent with a high risk of long-term patellofemoral osteoarthritis for adolescents who experience patellar dislocations. T1ρ relaxation times were elevated for multiple regions of patellofemoral cartilage. T1ρ relaxation times were expected to increase with additional dislocation episodes, but relaxation times after single and multiple dislocations were similar. After a first dislocation, parameters related to patellar maltracking were correlated with cartilage degradation.

2D versus 3D MRI of osteoarthritis in clinical practice and research

Accurately detecting and characterizing articular cartilage defects is critical in assessing patients with osteoarthritis. While radiography is the first-line imaging modality, magnetic resonance imaging (MRI) is the most accurate for the noninvasive assessment of articular cartilage. Multiple semiquantitative grading systems for cartilage lesions in MRI were developed. The Outerbridge and modified Noyes grading systems are commonly used in clinical practice and for research. Other useful grading systems were developed for research, many of which are joint-specific. Both two-dimensional (2D) and three-dimensional (3D) pulse sequences are used to assess cartilage morphology and biochemical composition. MRI techniques for morphological assessment of articular cartilage can be categorized into 2D and 3D FSE/TSE spin-echo and gradient-recalled echo sequences. T2 mapping is most commonly used to qualitatively assess articular cartilage microstructural composition and integrity, extracellular matrix components, and water content. Quantitative techniques may be able to label articular cartilage alterations before morphological defects are visible. Accurate detection and characterization of shallow low-grade partial and small articular cartilage defects are the most challenging for any technique, but where high spatial resolution 3D MRI techniques perform best. This review article provides a practical overview of commonly used 2D and 3D MRI techniques for articular cartilage assessments in osteoarthritis.

3D T1rho sequences with FASE, UTE, and MAPSS acquisitions for knee evaluation

PURPOSE

For biochemical evaluation of soft tissues of the knee, T1rho magnetic resonance imaging (MRI) has been proposed. Purpose of this study was to compare three T1rho sequences based on fast advanced spin echo (FASE), ultrashort echo time (UTE), and magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (MAPSS) acquisitions for the knee evaluation.

MATERIALS AND METHODS

We developed two T1rho sequences using 3D FASE or 3D radial UTE acquisitions. 3D MAPSS T1rho was provided by the manufacturer. Agarose phantoms with varying concentrations were imaged. Additionally, bilateral knees of asymptomatic subjects were imaged sagittally. T1rho values of the phantoms and 4 regions of interest (ROI) of the knees (i.e., anterior and posterior meniscus, femoral and tibial cartilage) were determined.

RESULTS

In phantoms, all T1rho values monotonically decreased with increasing agarose concentration. 3D MAPSS T1rho values of 51, 34, and 38 ms were found for 2, 3, and 4% agarose, respectively, similar to published values on another platform. In the knee, the raw images were detailed with good contrast. Cartilage and meniscus T1rho values varied with the pulse sequence, being the lowest in the 3D UTE T1rho sequence. Comparing different ROIs, menisci generally had lower T1rho values compared to cartilage, as expected in healthy knees.

CONCLUSION

We have successfully developed and implemented the new T1rho sequences and validated them using agarose phantoms and volunteer knees. All sequences were optimized to be clinically feasible (~ 5 min or less) and yielded satisfactory image quality and T1rho values consistent with the literature.

MRI-based T1rho and T2 cartilage compositional imaging in osteoarthritis: what have we learned and what is needed to apply it clinically and in a trial setting?

Cartilage MRI-based T1rho and T2 compositional measurements have been developed to characterize cartilage matrix quality and diagnose cartilage damage before irreversible defects are found, allowing intervention at an early, potentially reversible disease stage. Over the last 2 decades, this technology was investigated in numerous studies and was validated using specimen studies and arthroscopy; and longitudinal studies documented its ability to predict progression of degenerative disease and radiographic osteoarthritis (OA). While T1rho and T2 measurements have shown promise in early disease stages, several hurdles have been encountered to apply this technology clinically. These include (i) challenges with cartilage segmentation, (ii) long image acquisition times, (iii) a lack of standardization of imaging, and (iv) an absence of reference databases and definitions of abnormal cut-off values. Progress has been made by developing deep-learning based automatic cartilage segmentation and faster imaging methods, enabling the feasibility of T1rho and T2 imaging for clinical and scientific trial applications. Also, the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance mechanism was used to establish standardized profiles for compositional T1rho and T2 imaging, and multi-center feasibility testing is work in progress. The last hurdles are the development of reference databases and establishing a definition of normal versus abnormal cartilage T1rho and T2 values. Finally, effective treatments for prevention and slowing progression of OA are required in order to establish T1rho and T2 as imaging biomarkers for initiating and monitoring therapies, analogous to the role of dual X-ray absorptiometry (DXA) bone mineral density measurements in the management of osteoporosis. KEY POINTS: • T1rho and T2 cartilage measurements have been validated in characterizing cartilage degenerative change using histology and arthroscopy as a reference. • They have also been shown to predict progression of cartilage degeneration and incidence of radiographic OA. • Advances have been made to facilitate clinical and trial application of T1rho and T2 by improved standardization of imaging and by establishing deep learning-based automatic cartilage segmentation. • Effective treatments with disease-modifying OA specific drugs may establish T1rho and T2 cartilage compositional measurements as biomarkers to initiate and monitor treatment.

MRI Advancements in Musculoskeletal Clinical and Research Practice

Over the past decades, MRI has become increasingly important for diagnosing and longitudinally monitoring musculoskeletal disorders, with ongoing hardware and software improvements aiming to optimize image quality and speed. However, surging demand for musculoskeletal MRI and increased interest to provide more personalized care will necessitate a stronger emphasis on efficiency and specificity. Ongoing hardware developments include more powerful gradients, improvements in wide-bore magnet designs to maintain field homogeneity, and high-channel phased-array coils. There is also interest in low-field-strength magnets with inherently lower magnetic footprints and operational costs to accommodate global demand in middle- and low-income countries. Previous approaches to decrease acquisition times by means of conventional acceleration techniques (eg, parallel imaging or compressed sensing) are now largely overshadowed by deep learning reconstruction algorithms. It is expected that greater emphasis will be placed on improving synthetic MRI and MR fingerprinting approaches to shorten overall acquisition times while also addressing the demand of personalized care by simultaneously capturing microstructural information to provide greater detail of disease severity. Authors also anticipate increased research emphasis on metal artifact reduction techniques, bone imaging, and MR neurography to meet clinical needs.

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications

Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely debilitating and causes significant socioeconomic burdens to society. Magnetic resonance imaging (MRI) is the preferred imaging modality for the morphological evaluation of cartilage due to its excellent soft tissue contrast and high spatial resolution. However, its utilization typically involves subjective qualitative assessment of cartilage. Compositional MRI, which refers to the quantitative characterization of cartilage using a variety of MRI methods, can provide important information regarding underlying compositional and ultrastructural changes that occur during early OA. Cartilage compositional MRI could serve as early imaging biomarkers for the objective evaluation of cartilage and help drive diagnostics, disease characterization, and response to novel therapies. This review will summarize current and ongoing state-of-the-art cartilage compositional MRI techniques and highlight emerging methods for cartilage compositional MRI including MR fingerprinting, compressed sensing, multiexponential relaxometry, improved and robust radio-frequency pulse sequences, and deep learning-based acquisition, reconstruction, and segmentation. The review will also briefly discuss the current challenges and future directions for adopting these emerging cartilage compositional MRI techniques for use in clinical practice and translational OA research studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Magnetic resonance imaging assessments for knee segmentation and their use in combination with machine/deep learning as predictors of early osteoarthritis diagnosis and prognosis

Knee osteoarthritis (OA) is a prevalent and disabling disease that can develop over decades. This disease is heterogeneous and involves structural changes in the whole joint, encompassing multiple tissue types. Detecting OA before the onset of irreversible changes is crucial for early management, and this could be achieved by allowing knee tissue visualization and quantifying their changes over time. Although some imaging modalities are available for knee structure assessment, magnetic resonance imaging (MRI) is preferred. This narrative review looks at existing literature, first on MRI-developed approaches for evaluating knee articular tissues, and second on prediction using machine/deep-learning-based methodologies and MRI as input or outcome for early OA diagnosis and prognosis. A substantial number of MRI methodologies have been developed to assess several knee tissues in a semi-quantitative and quantitative fashion using manual, semi-automated and fully automated systems. This dynamic field has grown substantially since the advent of machine/deep learning. Another active area is predictive modelling using machine/deep-learning methodologies enabling robust early OA diagnosis/prognosis. Moreover, incorporating MRI markers as input/outcome in such predictive models is important for a more accurate OA structural diagnosis/prognosis. The main limitation of their usage is the ability to move them in rheumatology practice. In conclusion, MRI knee tissue determination and quantification provide early indicators for individuals at high risk of developing this disease or for patient prognosis. Such assessment of knee tissues, combined with the development of models/tools from machine/deep learning using, in addition to other parameters, MRI markers for early diagnosis/prognosis, will maximize opportunities for individualized risk assessment for use in clinical practice permitting precision medicine. Future efforts should be made to integrate such prediction models into open access, allowing early disease management to prevent or delay the OA outcome.

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

OBJECTIVE

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

METHODS

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

RESULTS

For baseline 2D MESE T2 measures, average CV were 0.37-2.45% (intra-site) and 5.96% (inter-site) for phantoms, and 3.15-8.49% (intra-site) and 14.16% (inter-site) for volunteers. For longitudinal phantom data, intra-site CVs were 1.42-3.48% for 3D MAPSS T1ρ, 1.77-3.56% for 3D MAPSS T2, and 1.02-2.54% for 2D MESE T2. For the longitudinal volunteer data, the intra-site CVs were 2.60-4.86% for 3D MAPSS T1ρ, 3.33-7.25% for 3D MAPSS T2, and 3.11-8.77% for 2D MESE T2.

CONCLUSION

This study demonstrated excellent intra-site reproducibility of 2D MESE T2 imaging, while its inter-site variation was slightly higher than 3D MAPSS T2 imaging (10.06% as previously reported). This study also showed excellent reproducibility of longitudinal T1ρ and T2 cartilage quantification, in a multi-vendor multi-site setting for both product 2D MESE T2 and 3D MAPSS T1p/T2 research sequences.

Multi-vendor multi-site quantitative MRI analysis of cartilage degeneration 10 Years after anterior cruciate ligament reconstruction: MOON-MRI protocol and preliminary results

OBJECTIVE

To describe the protocol of a multi-vendor, multi-site quantitative MRI study for knee post-traumatic osteoarthritis (PTOA), and to present preliminary results of cartilage degeneration using MR T1ρ and T2 imaging 10 years after anterior cruciate ligament reconstruction (ACLR).

DESIGN

This study involves three sites and two MR platforms. The patients are from a nested cohort (termed as Onsite cohort) within the Multicenter Orthopaedic Outcomes Network (MOON) cohort 10 years after ACLR. Phantoms and controls were scanned for evaluating reproducibility. Cartilage was automatically segmented, and T1ρ and T2 were compared between operated, contralateral, and control knees.

RESULTS

Sixty-eight ACL-reconstructed patients and 20 healthy controls were included. In phantoms, the intra-site coefficients of variation (CVs) of repeated scans ranged 1.8-2.1% for T1ρ and 1.3-1.7% for T2. The inter-site CVs ranged 1.6-2.1% for T1ρ and 1.1-1.4% for T2. In human subjects, the intra-site scan/rescan CVs ranged 2.2-3.5% for T1ρ and 2.6-4.9% for T2 for the six major compartments. In patients, operated knees showed significantly higher T1ρ and T2 values mainly in medial femoral condyle, medial tibia and trochlear cartilage compared with contralateral knees, and showed significantly higer T1ρ and T2 values in all six compartments compared to healthy control knees. The patient contralateral knees showed higher T1ρ and T2 values mainly in the lateral femoral condyle, lateral tibia, trochlear, and patellar cartilage compared to healthy control knees.

CONCLUSION

A platform and workflow with rigorous quality control has been established for a multi-vendor multi-site quantitative MRI study in evaluating PTOA 10 years after ACLR. Our preliminary report suggests significant cartilage matrix changes in both operated and contralateral knees compared with healthy control knees.

Computed Tomography of Cartilage: An Exploration of Novel Cationic Bismuth Contrast Agent

Accurate diagnosis of minor cartilage injuries with delayed contrast-enhanced computed tomography (CECT) is challenging as poor diffusion and toxicity issues limit the usage of common CT contrast agents. Hence, the design of safe contrast agents with physiochemical properties suitable for fast, deep cartilage imaging is imminent. Herein, a novel cationic bismuth contrast agent (Bi-DOTAPXD) based on dodecane tetraacetic acid (DOTA) was synthesized and examined for CECT of cartilage. The complex was designed to improve diagnosis by utilising a net-positive charge for enhanced permeability through cartilage, inherent low-toxicity and high X-ray attenuation of bismuth. Osteochondral plugs (n = 12), excised from visually intact porcine articular cartilage were immersed in Bi-DOTAPXD (8 mg/mL) and Gd-DOTAPXD (10 mg/mL) contrast agents and scanned with a high-resolution microcomputed tomography scanner at multiple time-points. The mean Bi-DOTAPXD and Gd-DOTAPXD partitions at 45-min time-point were 85.7 ± 35.1 and 69.8 ± 30.2%, and the partitions correlated with the histopathological analysis of cartilage proteoglycan (PG) content (r) at 0.657 and 0.632, respectively. The time diffusion constants (τ) for Bi-DOTAPXD and Gd-DOTA were 121 and 159 min, respectively. Diffusion Bi-DOTAPXD and Gd-DOTAPXD reflected inter-sample variation in cartilage PG content. Cationic Bi-DOTAPXD may have the potential as a CT agent for the diagnosis of cartilage.

Efficient phase-cycling strategy for high-resolution 3D gradient-echo quantitative parameter mapping

Magnetization-prepared (MP) gradient-echo (GRE) sequences suffer from signal contaminations from T₁ recovery during the readout train, which can be eliminated by paired RF phase cycling (PC) at the cost of doubling the scan time. The objective of this study was to develop and validate a novel unpaired PC strategy to eliminate the time penalty for high-resolution quantitative parameter mapping in 3D MP-GRE sequences. Based on the observation that the contaminating T₁ recovery signal along the GRE readout train is independent of magnetization preparation, its impact can be eliminated using a novel curve-fitting approach with complex-valued data without needing paired PC acquisitions. Four new unpaired PC schemes were compared with two traditional paired PC schemes in both phantom and in vivo human knee studies at 3 T using a MP angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) T_1ρ mapping sequence. In the phantom study, all methods resulted in consistent T_1ρ measurements (∆T_1ρ  < 0.5%) at the center slice when B₀ /B₁ values were uniform. Results were not consistent when off-center slices with nonideal B₀ /B₁ were included. Two unpaired PC schemes had comparable or significantly improved quantitative accuracy and scan-rescan reproducibility compared with the paired PC schemes. There was no significant T_1ρ quantitative variability increase or spatial fidelity loss using the new unpaired PC schemes. Unpaired PC schemes also had different T_1ρ spectral responses at different B₀ frequency offsets, which can potentially be exploited to reduce sensitivity to B₀ field inhomogeneities. The human knee study results were consistent with the phantom study findings. In conclusion, an unpaired PC strategy potentially allows more accurate quantitative parameter mapping with halved scan time compared with the paired PC approach to eliminate signal contaminations from T₁ recovery. It therefore offers additional flexibility in SNR optimization, spatial resolution improvement, and choice of imaging sampling points to obtain more accurate quantitative parameter mapping.

Elevated Patellofemoral and Tibiofemoral T1ρ Relaxation Times Following a First Time Patellar Dislocation

OBJECTIVE

The study was performed to evaluate cartilage within the knee following a first-time patellar dislocation, using elevated MRI-based T1ρ relaxation times as an indicator of low proteoglycan concentration. The hypothesis is that MRI-based T1ρ relaxation times for patellofemoral and tibiofemoral cartilage are significantly longer for knees being treated for patellar dislocation than for healthy control knees.

DESIGN

Twenty-one subjects being treated for a first-time, unilateral dislocation of the patella and 16 healthy controls participated in MRI-based T1ρ relaxation time mapping. Mean relaxation times were quantified for patellofemoral and tibiofemoral regions for injured knees, the contralateral knees, and healthy controls. T1ρ values for each region were compared between the 3 groups with generalized estimating equations. Linear regressions were also performed to correlate T1ρ relaxation times with time from injury.

RESULTS

The knees with a disloction had longer T1ρ relaxation times than the contralateral knees and control group at the medial patella and longer relaxation times than the control group at the lateral tibia (P < 0.05). T1ρ relaxation times at the medial patella also decreased with time from injury (r² = 0.21, P = 0.037).

CONCLUSIONS

Compositional changes to cartilage on the medial patella are related to traumatic impact during a dislocation. Potential exists for cartilage properties at the medial patella to improve with time. Cartilage degradation at the lateral tibia is not directly related to traumatic impact. The current baseline data are a starting point to characterize the pathway from a first-time dislocation to progressive cartilage degradation and osteoarthritis.

Update: Posttreatment Imaging of the Knee after Cartilage Repair

Focal cartilage lesions are common pathologies at the knee joint that are considered important risk factors for the premature development of osteoarthritis. A wide range of surgical options, including but not limited to marrow stimulation, osteochondral auto- and allografting, and autologous chondrocyte implantation, allows for targeted treatment of focal cartilage defects. Arthroscopy is the standard of reference for the assessment of cartilage integrity and quality before and after repair. However, deep cartilage layers, intrachondral composition, and the subchondral bone are only partially or not at all visualized with arthroscopy. In contrast, magnetic resonance imaging offers noninvasive evaluation of the cartilage repair site, the subchondral bone, and the soft tissues of the joint pre- and postsurgery. Radiologists need to be familiar with the different surgical procedures available and their characteristic postsurgical imaging appearances to assess treatment success and possible complications adequately. We provide an overview of the most commonly performed surgical procedures for cartilage repair at the knee and typical postsurgical imaging characteristics.

Dual-contrast computed tomography enables detection of equine posttraumatic osteoarthritis in vitro

To prevent the progression of posttraumatic osteoarthritis, assessment of cartilage composition is critical for effective treatment planning. Posttraumatic changes include proteoglycan (PG) loss and elevated water content. Quantitative dual-energy computed tomography (QDECT) provides a means to diagnose these changes. Here, we determine the potential of QDECT to evaluate tissue quality surrounding cartilage lesions in an equine model, hypothesizing that QDECT allows detection of posttraumatic degeneration by providing quantitative information on PG and water contents based on the partitions of cationic and nonionic agents in a contrast mixture. Posttraumatic osteoarthritic samples were obtained from a cartilage repair study in which full-thickness chondral defects were created surgically in both stifles of seven Shetland ponies. Control samples were collected from three nonoperated ponies. The experimental (n = 14) and control samples (n = 6) were immersed in the contrast agent mixture and the distributions of the agents were determined at various diffusion time points. As a reference, equilibrium moduli, dynamic moduli, and PG content were measured. Significant differences (p < 0.05) in partitions between the experimental and control samples were demonstrated with cationic contrast agent at 30 min, 60 min, and 20 h, and with non-ionic agent at 60 and 120 min. Significant Spearman's rank correlations were obtained at 20 and 24 h (ρ = 0.482-0.693) between the partition of cationic contrast agent, cartilage biomechanical properties, and PG content. QDECT enables evaluation of posttraumatic changes surrounding a lesion and quantification of PG content, thus advancing the diagnostics of the extent and severity of cartilage injuries.

MOntelukast as a potential CHondroprotective treatment following Anterior cruciate ligament reconstruction (MOCHA Trial): study protocol for a double-blind, randomized, placebo-controlled clinical trial

BACKGROUND

After anterior cruciate ligament (ACL) reconstruction, patient-reported outcomes are improved 10 years post-surgery; however, cytokine concentrations remain elevated years after surgery with over 80% of those with combined ACL and meniscus injuries having posttraumatic osteoarthritis (PTOA) within 10-15 years. The purpose of this multicenter, randomized, placebo-controlled trial is to assess whether a 6-month course of oral montelukast after ACL reconstruction reduces systemic markers of inflammation and biochemical and imaging biomarkers of cartilage degradation.

METHODS

We will enroll 30 individuals undergoing primary ACL reconstruction to participate in this IRB-approved multicenter clinical trial. This trial will target those at greatest risk of a more rapid PTOA onset (age range 25-50 with concomitant meniscus injury). Patients will be randomly assigned to a group instructed to take 10 mg of montelukast daily for 6 months following ACL reconstruction or placebo. Patients will be assessed prior to surgery and 1, 6, and 12 months following surgery. To determine if montelukast alters systemic inflammation following surgery, we will compare systemic concentrations of prostaglandin E2, monocyte chemoattractant protein-1, and pro-inflammatory cytokines between groups. We will also compare degradative changes on magnetic resonance imaging (MRI) collected 1 and 12 months following surgery between groups with reductions in early biomarkers of cartilage degradation assessed with urinary biomarkers of type II collagen breakdown and bony remodeling.

DISCUSSION

There is a complex interplay between the pro-inflammatory intra-articular environment, underlying bone remodeling, and progressive cartilage degradation. PTOA affects multiple tissues and appears to be more similar to rheumatoid arthritis than osteoarthritis with respect to inflammation. There is currently no treatment to delay or prevent PTOA after ACL injury. Since there is a larger and more persistent inflammatory response after ACL reconstruction than the initial insult of injury, treatment may need to be initiated after surgery, sustained over a period of time, and target multiple mechanisms in order to successfully alter the disease process. This study will assess whether a 6-month postoperative course of oral montelukast affects multiple PTOA mechanisms. Because montelukast administration can be safely sustained for long durations and offers a low-cost treatment option, should it be proven effective in the current trial, these results can be immediately incorporated into clinical practice.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04572256 . Registered on October 1, 2020.

Hip-Knee Joint Coordination Patterns are Associated With Patellofemoral Joint Cartilage Composition in Patients With Anterior Cruciate Ligament Reconstruction

Joint coordination variability during walking that is associated with patellofemoral joint cartilage degeneration after anterior cruciate ligament reconstruction are not well understood. The purpose of this study was to assess between-limb differences in joint coordination variability and to determine the relationship of coordination variability with postoperative patellofemoral joint cartilage composition. Thirty-five patients underwent bilateral gait analysis and a magnetic resonance exam of the reconstructed knee joint at 6 months post anterior cruciate ligament reconstruction. Vector coding was used to assess coordination variability during the early (1%-33%), mid (34%-66%), and late (67%-100%) stance phase. The T1ρ/T2 mapping was used to evaluate the glycosaminoglycan-collagen matrix of the patellar and femoral trochlear cartilage. Compared with the uninjured limb, the reconstructed limb exhibited higher hip sagittal/knee sagittal plane coordination variability during midstance as well as higher knee sagittal/ankle sagittal plane coordination variability during both mid and late stance. The hip sagittal/knee sagittal plane coordination variability during midstance predicted 14.6% of the variance in patellar cartilage T1ρ values within the reconstructed limb. In addition, sex of participants was able to predict 32.4% and 13.7% of the variance in femoral trochlea T1ρ and T2 values, respectively. The study results demonstrate that a multijoint mechanism may be associated with early patellofemoral joint cartilage degeneration at 6 months after anterior cruciate ligament reconstruction.

Investigating the Association of Metabolic Biomarkers With Knee Cartilage Composition and Structural Abnormalities Using MRI: A Pilot Study

OBJECTIVE

The goal of this study was to explore the metabolic syndrome-associated phenotype of osteoarthritis by investigating the cross-sectional associations of glycemic markers and serum lipids with knee cartilage composition and structural abnormalities in middle-aged adults.

DESIGN

Twenty participants between 40 to 70 years of age with Kellgren-Lawrence score 0-1 in at least one knee were recruited at a single center. Knee cartilage composition was assessed using 3.0 T cartilage T₂ and T_1ρ mapping. Evaluation of structural knee abnormalities was performed using the modified Whole-Organ Magnetic Resonance Imaging Score (WORMS). Linear regression was used to assess the associations of standardized fasting glucose (FG), hemoglobin A1c (HbA1c), insulin, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), non-HDL cholesterol, and triglycerides with cartilage T₂ and T_1ρ as well as WORMS subscores, adjusting for body mass index.

RESULTS

Higher FG and higher HbA1c were associated with higher WORMS meniscus sum (beta coefficient 1.31 [95% confidence interval (CI): 0.57, 2.05], P = 0.002 per standard deviation [SD] increase in FG; beta coefficient 0.90 [95% CI: 0.07, 1.73], P = 0.035 per SD increase in HbA1c). Also, higher total cholesterol and higher non-HDL cholesterol were associated with higher WORMS cartilage sum (beta coefficient 0.94 [95% CI: 0.01, 1.86], P = 0.048 per SD increase in total cholesterol; beta coefficient 1.05 [95% CI: 0.14, 1.96], P = 0.03 per SD increase in non-HDL cholesterol).

CONCLUSIONS

Higher FG and HbA1c were associated with increased meniscal degeneration while higher total and non-HDL cholesterol were associated with increased cartilage degeneration.

Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning

OBJECTIVE

We evaluated a fully automated femoral cartilage segmentation model for measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo (MESE) magnetic resonance imaging (MRI). We open sourced this model and developed a web app available at https://kl.stanford.edu into which users can drag and drop images to segment them automatically.

DESIGN

We trained a neural network to segment femoral cartilage from MESE MRIs. Cartilage was divided into 12 subregions along medial-lateral, superficial-deep, and anterior-central-posterior boundaries. Subregional T2 values and four-year changes were calculated using a radiologist's segmentations (Reader 1) and the model's segmentations. These were compared using 28 held-out images. A subset of 14 images were also evaluated by a second expert (Reader 2) for comparison.

RESULTS

Model segmentations agreed with Reader 1 segmentations with a Dice score of 0.85 ± 0.03. The model's estimated T2 values for individual subregions agreed with those of Reader 1 with an average Spearman correlation of 0.89 and average mean absolute error (MAE) of 1.34 ms. The model's estimated four-year change in T2 for individual subregions agreed with Reader 1 with an average correlation of 0.80 and average MAE of 1.72 ms. The model agreed with Reader 1 at least as closely as Reader 2 agreed with Reader 1 in terms of Dice score (0.85 vs. 0.75) and subregional T2 values.

CONCLUSIONS

Assessments of cartilage health using our fully automated segmentation model agreed with those of an expert as closely as experts agreed with one another. This has the potential to accelerate osteoarthritis research.

Simultaneous T1 , T2 , and T1ρ cardiac magnetic resonance fingerprinting for contrast agent-free myocardial tissue characterization

PURPOSE

To develop a simultaneous T₁ , T₂ , and T_1ρ cardiac magnetic resonance fingerprinting (MRF) approach to enable comprehensive contrast agent-free myocardial tissue characterization in a single breath-hold scan.

METHODS

A 2D gradient-echo electrocardiogram-triggered cardiac MRF sequence with low flip angles, varying magnetization preparation, and spiral trajectory was acquired at 1.5 T to encode T₁ , T₂ , and T_1⍴ simultaneously. The MRF images were reconstructed using low-rank inversion, regularized with a multicontrast patch-based higher-order reconstruction. Parametric maps were generated and matched in the singular value domain to extended phase graph-based dictionaries. The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional methods in terms of coefficients of determination and best fits for the phantom study, and in terms of Bland-Altman agreement, average values and coefficient of variation of T₁ , T₂ , and T_1⍴ for the healthy subjects study.

RESULTS

The T₁ , T₂ , and T_1⍴ MRF values showed excellent correlation with conventional spin-echo and clinical mapping methods in phantom studies (r² > 0.97). Measured MRF values in myocardial tissue (mean ± SD) were 1133 ± 33 ms, 38.8 ± 3.5 ms, and 52.0 ± 4.0 ms for T₁ , T₂ and T1_⍴ , respectively, against 1053 ± 47 ms, 50.4 ± 3.9 ms, and 55.9 ± 3.3 ms for T₁ modified Look-Locker inversion imaging, T₂ gradient and spin echo, and T_1⍴ turbo field echo, respectively.

CONCLUSION

A cardiac MRF approach for simultaneous quantification of myocardial T₁ , T₂ , and T_1ρ in a single breath-hold MR scan of about 16 seconds has been proposed. The approach has been investigated in phantoms and healthy subjects showing good agreement with reference spin echo measurements and conventional clinical maps.

The QIBA Profile for MRI-based Compositional Imaging of Knee Cartilage

MRI-based cartilage compositional analysis shows biochemical and microstructural changes at early stages of osteoarthritis before changes become visible with structural MRI sequences and arthroscopy. This could help with early diagnosis, risk assessment, and treatment monitoring of osteoarthritis. Spin-lattice relaxation time constant in rotating frame (T1ρ) and T2 mapping are the MRI techniques best established for assessing cartilage composition. Only T2 mapping is currently commercially available, which is sensitive to water, collagen content, and orientation of collagen fibers, whereas T1ρ is more sensitive to proteoglycan content. Clinical application of cartilage compositional imaging is limited by high variability and suboptimal reproducibility of the biomarkers, which was the motivation for creating the Quantitative Imaging Biomarkers Alliance (QIBA) Profile for cartilage compositional imaging by the Musculoskeletal Biomarkers Committee of the QIBA. The profile aims at providing recommendations to improve reproducibility and to standardize cartilage compositional imaging. The QIBA Profile provides two complementary claims (summary statements of the technical performance of the quantitative imaging biomarkers that are being profiled) regarding the reproducibility of biomarkers. First, cartilage T1ρ and T2 values are measurable at 3.0-T MRI with a within-subject coefficient of variation of 4%-5%. Second, a measured increase or decrease in T1ρ and T2 of 14% or more indicates a minimum detectable change with 95% confidence. If only an increase in T1ρ and T2 values is expected (progressive cartilage degeneration), then an increase of 12% represents a minimum detectable change over time. The QIBA Profile provides recommendations for clinical researchers, clinicians, and industry scientists pertaining to image data acquisition, analysis, and interpretation and assessment procedures for T1ρ and T2 cartilage imaging and test-retest conformance. This special report aims to provide the rationale for the proposed claims, explain the content of the QIBA Profile, and highlight the future needs and developments for MRI-based cartilage compositional imaging for risk prediction, early diagnosis, and treatment monitoring of osteoarthritis.

Radiomics Feature Analysis of Cartilage and Subchondral Bone in Differentiating Knees Predisposed to Posttraumatic Osteoarthritis after Anterior Cruciate Ligament Reconstruction from Healthy Knees

Objectives

To introduce a new implementation of radiomics analysis for cartilage and subchondral bone of the knee and to compare the performance of the proposed models to classic T2 relaxation time in distinguishing knees predisposed to posttraumatic osteoarthritis (PTOA) after anterior cruciate ligament reconstruction (ACLR) and healthy controls.

Methods

114 patients following ACLR after at least 2 years and 43 healthy controls were reviewed and allocated to training (n = 110) and testing (n = 47) cohorts. Radiomics models are built for cartilage and subchondral bone regions of different compartments: lateral femur (LF), lateral tibia (LT), medial femur (MF), and medial tibia (MT) and combined models of four compartments on T2 mapping images. The model performance of discrimination between patients and controls was illustrated with the receiver operating characteristic curve and compared with a classic T2 value-based model.

Results

The T2 value model of cartilage yielded moderate predictive performance in discerning patients and controls, with an AUC of 0.731 (95% confidence interval, 0.556–0.875) in the testing cohort, while the radiomics signature of cartilage and subchondral bone of different compartments demonstrated excellent performance, with AUCs of 0.864–0.979. Furthermore, the combined model reported an even better performance, with AUCs of 0.977 (95% confidence interval, 0.919–1.000) for the cartilage and 0.934 (95% confidence interval, 0.865–0.994) for the subchondral bone in the testing cohort.

Conclusion

The radiomics features of the cartilage and subchondral bone may be able to provide powerful tools with more sensitive detection than T2 values in differentiating knees at risk for PTOA after ACLR from healthy knees.

Machine learning classification on texture analyzed T2 maps of osteoarthritic cartilage: oulu knee osteoarthritis study

OBJECTIVE

To introduce local binary pattern (LBP) texture analysis to cartilage osteoarthritis (OA) research and compare the performance of different classification systems in discrimination of OA subjects from healthy controls using gray-level co-occurrence matrix (GLCM) and LBP texture data. Classification algorithms were used to reduce the dimensionality of texture data into a likelihood of subject belonging to the reference class.

METHOD

T2 relaxation time mapping with multi-slice multi-echo spin echo sequence was performed for eighty symptomatic OA patients and 63 asymptomatic controls on a 3T clinical MRI scanner. Relaxation time maps were subjected to GLCM and LBP texture analysis, and classification algorithms were deployed with an in-house developed software. Implemented algorithms were K nearest neighbors, support vector machine, and neural network classifier.

RESULTS

LBP and GLCM discerned OA patients from controls with a significant difference in all studied regions. Classification models comprising GLCM and LBP showed high accuracy in classing OA patients and controls. The best performance was obtained with a multilayer perceptron type classifier with an overall accuracy of 90.2 %.

CONCLUSION

LBP texture analysis complements prior results with GLCM, and together LBP and GLCM serve as significant input data for classification algorithms trained for OA assessment. Presented algorithms are adaptable to versatile OA evaluations also for future gradational or predictive approaches.

Prediction of local fixed charge density loss in cartilage following ACL injury and reconstruction: A computational proof-of-concept study with MRI follow-up

The purpose of this proof-of-concept study was to develop three-dimensional patient-specific mechanobiological knee joint models to simulate alterations in the fixed charged density (FCD) around cartilage lesions during the stance phase of the walking gait. Two patients with anterior cruciate ligament (ACL) reconstructed knees were imaged at 1 and 3 years after surgery. The magnetic resonance imaging (MRI) data were used for segmenting the knee geometries, including the cartilage lesions. Based on these geometries, finite element (FE) models were developed. The gait of the patients was obtained using a motion capture system. Musculoskeletal modeling was utilized to calculate knee joint contact and lower extremity muscle forces for the FE models. Finally, a cartilage adaptation algorithm was implemented in both FE models. In the algorithm, it was assumed that excessive maximum shear and deviatoric strains (calculated as the combination of principal strains), and fluid velocity, are responsible for the FCD loss. Changes in the longitudinal T_1ρ and T₂ relaxation times were postulated to be related to changes in the cartilage composition and were compared with the numerical predictions. In patient 1 model, both the excessive fluid velocity and strain caused the FCD loss primarily near the cartilage lesion. T_1ρ and T₂ relaxation times increased during the follow-up in the same location. In contrast, in patient 2 model, only the excessive fluid velocity led to a slight FCD loss near the lesion, where MRI parameters did not show evidence of alterations. Significance: This novel proof-of-concept study suggests mechanisms through which a local FCD loss might occur near cartilage lesions. In order to obtain statistical evidence for these findings, the method should be investigated with a larger cohort of subjects.

T2 mapping of healthy knee cartilage: multicenter multivendor reproducibility

Background

T₂ mapping is increasingly used to quantify cartilage degeneration in knee osteoarthritis (OA), yet reproducibility studies in a multicenter setting are limited. The purpose of this study was to determine the longitudinal reproducibility and multicenter variation of cartilage T₂ mapping, using various MRI equipment and acquisition protocols.

Methods

In this prospective multicenter study, four traveling, healthy human subjects underwent T₂ mapping twice at five different centers with a 6-month-interval. Centers had various MRI scanners, field strengths, and T₂ mapping acquisition protocols. Mean T₂ values were calculated in six cartilage regions of interest (ROIs) as well as an average value per patient. A phantom was scanned once at each center. To evaluate longitudinal reproducibility, intraclass correlation coefficients (ICC), root-mean-square coefficient of variation (RMS-CV), and a Bland-Altman plot were used. To assess the variation of in vivo and phantom T₂ values across centers, ANOVA was performed.

Results

ICCs of the T₂ mapping measurements per ROI and the ROI's combined ranged from 0.73 to 0.91, indicating good to excellent longitudinal reproducibility. RMS-CVs ranged from 1.1% to 1.5% (per ROI) and 0.6% to 1.6% (ROIs combined) across the centers. A Bland-Altman plot did not reveal a systematic error. Evident, but consistent, discrepancies in T₂ values were observed across centers, both in vivo and in the phantom.

Conclusions

The results of this study suggest that T₂ mapping can be used to longitudinal assess cartilage degeneration in multicenter studies. Given the differences in absolute cartilage T₂ values across centers, absolute T₂ values derived from various centers in multicenter multivendor trials should not be pooled.

Patient-Reported Activity Levels Correlate With Early Cartilage Degeneration After Anterior Cruciate Ligament Reconstruction

BACKGROUND

The association between activity level after anterior cruciate ligament (ACL) reconstruction (ACLR) and development of posttraumatic osteoarthritis (PTOA) remains unclear. This study investigated the relationship of patient-reported outcomes and progressive cartilage degenerative changes at 3 years after ACLR.

HYPOTHESIS

Higher activity levels, as measured by Marx scores, are significantly correlated with early cartilage degeneration after ACLR.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

A total of 35 patients (16 women; mean age, 31.0 ± 7.6 years) with isolated ACLR and without pre-existing arthritis were prospectively enrolled. Patients reported Marx activity scores and Knee injury and Osteoarthritis Outcome Score (KOOS) scores and underwent T₁ρ magnetic resonance imaging (MRI) preoperatively, 6 months, 1 year, 2 years, and 3 years after ACLR with soft tissue graft (22 autograft). The change in cartilage relaxation times between preoperative and 3-year imaging was used to identify cartilage degeneration, defined as an increase in T₁ρ values by 14.3%. Correlation between Marx activity levels, KOOS scores, and T₁ρ degeneration was performed with the Spearman rank test. The Fisher exact test was used to test for association between Marx activity score cutoffs and degeneration. The Student t test was used to compare Whole-Organ Magnetic Resonance Imaging Score (WORMS) and T₁ρ relaxation times. Significance was defined as P < .05.

RESULTS

Sixteen patients (45.7%) showed evidence of cartilage degeneration at 3 years, most frequently in the medial compartment (n = 12; 34%). Higher Marx activity scores at 3 years correlated with cartilage degeneration in the medial femur (rho = 0.34; P = .045), and medial tibia (rho = 0.43; P = .01). A Marx score of 11 or greater at 3 years was significantly associated with medial compartment degeneration (P = .03), with a positive predictive value of 52.6%. No Marx score cutoff at years 1 or 2 predicted future cartilage degeneration. The KOOS Quality of Life score was inversely correlated with cartilage degeneration (rho = 0.38; P = .02). WORMS did not correlate with degeneration of the medial compartment.

CONCLUSION

Increased activity at 3 years after ACLR was significantly associated with increased risk of medial compartment PTOA. While further research is needed to fully define these relationships, patients may be counseled that return to Marx activity levels of greater than 11 may be associated with a higher risk of medial compartment cartilage degeneration.

Multi-vendor multi-site T1ρ and T2 quantification of knee cartilage

OBJECTIVE

To develop 3D T_1ρ and T₂ imaging based on the same sequence structure on MR systems from multiple vendors, and to evaluate intra-site repeatability and inter-site inter-vendor reproducibility of T_1ρ and T₂ measurements of knee cartilage.

METHODS

3D magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (3D MAPSS) were implemented on MR systems from Siemens, GE and Philips. Phantom and human subject data were collected at four sites using 3T MR systems from the three vendors with harmonized protocols. Phantom data were collected by means of different positioning of the coil. Volunteers were scanned and rescanned after repositioning. Two traveling volunteers were scanned at all sites. Data were transferred to one site for centralized processing.

RESULTS

Intra-site average coefficient of variations (CVs) ranged from 1.09% to 3.05% for T_1ρ and 1.78-3.30% for T₂ in phantoms, and 1.60-3.93% for T_1ρ and 1.44-4.08% for T₂ in volunteers. Inter-site average CVs were 5.23% and 6.45% for MAPSS T_1ρ and T₂, respectively in phantoms, and 8.14% and 10.06% for MAPSS T_1ρ and T₂, respectively, In volunteers.

CONCLUSION

This study showed promising results of multi-site, multi-vendor reproducibility of T_1ρ and T₂ values in knee cartilage. These quantitative measures may be applied in large-scale multi-site, multi-vendor trials with controlled sequence structure and scan parameters and centralized data processing.

Quantitative imaging of anterior cruciate ligament (ACL) graft demonstrates longitudinal compositional changes and relationships with clinical outcomes at 2 years after ACL reconstruction

T₁ ρ and T₂ magnetic resonance imaging (MRI) may allow for a noninvasive assessment of ligamentization after anterior cruciate ligament (ACL) reconstruction. We hypothesized that ACL graft T₁ ρ and T₂ relaxation times would decrease over time, that T₁ ρ and T₂ relaxation times would be inversely correlated with Knee Osteoarthritis Outcome Scores (KOOS), and that T₁ ρ and T₂ values would be lower for autograft relative to allograft reconstruction. Thirty-nine patients (age: 30.5 ± 8.2 years) were followed prospectively after ACL reconstruction with hamstring autograft (N = 27) or soft-tissue allograft (N = 12). Magnetic resonance (MR) imaging and KOOS surveys were completed at 6, 12, 24, and 36 months after surgery. ACL graft was segmented to define T₁ ρ and T₂ relaxation times. Relaxation times were compared between time points with ANOVA tests. Log-transformed autograft and allograft relaxation times were compared with the Student t tests. The relationship between KOOS and relaxation times at 24 months was investigated with Spearman's rank correlation. ACL graft T₁ ρ relaxation times were significantly higher at 6 months relative to 12 months (P = .042), 24 months (P < .001), and 36 months (P < .001). ACL graft T₂ relaxation times were significantly higher at 6 months relative to 12 months (P = .036), 24 months (P < .001), and 36 months (P < .001). T₁ ρ and T₂ relaxation times were significantly lower for autograft reconstruction vs allograft reconstruction at 24 months postreconstruction. Two-year KOOS Sports, Pain, and Symptoms were significantly inversely correlated with T₁ ρ and T₂ relaxation times. T₁ ρ and T₂ sequences may offer a noninvasive method for monitoring ACL graft maturation that correlates with patient-reported knee function after ACL reconstruction.

T1ρ magnetic resonance fingerprinting

T_1ρ relaxation imaging is a quantitative imaging technique that has been used to assess cartilage integrity, liver fibrosis, tumors, cardiac infarction, and Alzheimer's disease. T₁ , T₂ , and T_1ρ relaxation time constants have each demonstrated different degrees of sensitivity to several markers of fibrosis and inflammation, allowing for a potential multi-parametric approach to tissue quantification. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T₁ and T₂ relaxation time constants. In this study, T_1ρ relaxation is added to the MRF framework using spin lock preparations. An MRF sequence involving an RF-spoiled sequence with T_R , flip angle, T_1ρ , and T₂ preparation variation is described. The sequence is then calibrated against conventional T₁ , T₂ , and T_1ρ relaxation mapping techniques in agar phantoms and the abdomens of four healthy volunteers. Strong intraclass correlation coefficients (ICC > 0.9) were found between conventional and MRF sequences in phantoms and also in healthy volunteers (ICC > 0.8). The highest ICC correlation values were seen in T₁ , followed by T_1ρ and then T₂ . In this study, T_1ρ relaxation has been incorporated into the MRF framework by using spin lock preparations, while still fitting for T₁ and T₂ relaxation time constants. The acquisition of these parameters within a single breath hold in the abdomen alleviates the issues of movement between breath holds in conventional techniques.

Clinical Utility of Advanced Imaging of the Knee

Advanced imaging modalities, including computed tomography, magnetic resonance imaging (MRI), and dynamic fluoroscopic imaging, allow for a comprehensive evaluation of the knee joint. Compositional sequences for MRI can allow for an evaluation of the biochemical properties of cartilage, meniscus, and ligament that offer further insight into pathology that may not be apparent on conventional clinical imaging. Advances in image processing, shape modeling, and dynamic studies also offer a novel way to evaluate common conditions and to monitor patients after treatment. The purpose of this article is to review advanced imaging modalities of the knee and their current and anticipated future applications to clinical practice. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:473-482, 2020.

Morphological MRI of knee cartilage: repeatability and reproducibility of damage evaluation and correlation with gross pathology examination

OBJECTIVE

To assess the performance of a morphological evaluation, based on a clinically relevant magnetic resonance imaging (MRI) protocol, in scoring the severity of knee cartilage damage. Specifically, to evaluate the reproducibility, repeatability, and agreement of MRI evaluation with the gross pathology examination (GPE) of the tissue.

METHODS

MRI of the knee was performed the day before surgery in 23 patients undergoing total knee arthroplasty. Osteochondral tissue resections were collected and chondral defects were scored by GPE according to a semi-quantitative scale. MR images were independently scored by four radiologists, who assessed the severity of chondral damage according to equivalent criteria. Inter- and intra-rater agreements of MRI evaluations were assessed. Correlation, precision, and accuracy metrics between MRI and GPE scores were calculated.

RESULTS

Moderate to substantial inter-rater agreement in scoring cartilage damage by MRI was found among radiologists. Intra-rater agreement was higher than 96%. A significant positive monotonic correlation between GPE and MRI scores was observed for all radiologists, although higher correlation values were obtained by radiologists with expertise in musculoskeletal radiology and/or longer experience. The accuracy of MRI scores displayed a spatial pattern, characterized by lesion overestimation in the lateral condyle and underestimation in the medial condyle with respect to GPE.

CONCLUSIONS

Evaluation of knee cartilage morphology by MRI is a reproducible and repeatable technique, which positively correlates with GPE. Clinical expertise in musculoskeletal radiology positively impacts the evaluation reliability. These findings may help to address limitations in MRI evaluation of knee chondral lesions, thus improving MRI assessment of knee cartilage.

KEY POINTS

• MRI evaluation of knee cartilage shows moderate to strong correlation with gross pathology examination. • MRI evaluation overestimates cartilage damage in the lateral condyle and underestimates it in the medial condyle. • Education and experience of the radiologist play a role in MRI evaluation of knee chondral lesions.

Infrapatellar fat pad abnormalities are associated with a higher inflammatory synovial fluid cytokine profile in young adults following ACL tear

OBJECTIVE

To evaluate the degree of knee fat pad abnormalities after acute anterior cruciate ligament (ACL) tear via magnetic resonance fat pad scoring and to assess cross-sectionally its association with synovial fluid biomarkers and with early cartilage damage as quantified via T1ρ and T2 relaxation time measurements.

DESIGN

26 patients with acute ACL tears underwent 3T MR scanning of the injured knee prior to ACL reconstruction. The presence and degree of abnormalities of the infrapatellar (IPFP) and the suprapatellar (SPFP) fat pads were scored on MR images along with grading of effusion-synovitis and synovial proliferations. Knee cartilage composition was assessed by 3T MR T1ρ and T2 mapping in six knee compartments. We quantified concentrations of 20 biomarkers in synovial fluid aspirated at the time of ACL reconstruction. Spearman rank partial correlations with adjustments for age and gender were employed to evaluate correlations of MR, particularly cartilage composition and fat pad abnormalities, and biomarker data.

RESULTS

The degree of IPFP abnormality correlated positively with the synovial levels of the inflammatory cytokine markers IFN-γ (ρpartial = 0.64, 95% CI (0.26-0.85)), IL-10 (ρpartial = 0.47, 95% CI (0.04-0.75)), IL-6 (ρpartial = 0.56, 95% CI (0.16-0.81)), IL-8 (ρpartial = 0.49, 95% CI (0.06-0.76)), TNF-α (ρpartial = 0.55, 95% CI (0.14-0.80)) and of the chondrodestructive markers MMP-1 and -3 (MMP-1: ρpartial = 0.57, 95% CI (0.17-0.81); MMP-3: ρpartial = 0.60, 95% CI (0.21-0.83)). IPFP abnormalities were significantly associated with higher T1ρ and T2 values in the trochlear cartilage (T1ρ: ρpartial = 0.55, 95% CI (0.15-0.80); T2: ρpartial = 0.58, 95% CI (0.18-0.81)) and with higher T2 values in the medial femoral, medial tibial as well as in patellar cartilage (0.45 ≤ ρpartial ≤ 0.59). Correlations between SPFP abnormalities and synovial markers were not significant except for IL-6 (ρpartial = 0.57, 95% CI (0.17-0.81)).

CONCLUSIONS

This exploratory study suggests that acute ACL rupture can be associated with damage to knee tissues such as the inferior fat pad of the knee. Such fat pad injury could be partially responsible for the apparent post-injury pro-inflammatory response noted in ACL-injured individuals. However, future longitudinal studies are needed to link ACL-rupture associated fat pad injury with important patient outcomes such as the development of posttraumatic osteoarthritis.

Triple Contrast CT Method Enables Simultaneous Evaluation of Articular Cartilage Composition and Segmentation

Early degenerative changes of articular cartilage are detected using contrast-enhanced computed tomography (CT) with a cationic contrast agent (CA). However, cationic CA diffusion into degenerated cartilage decreases with proteoglycan depletion and increases with elevated water content, thus hampering tissue evaluation at early diffusion time points. Furthermore, the contrast at synovial fluid-cartilage interface diminishes as a function of diffusion time hindering accurate cartilage segmentation. For the first time, we employ quantitative dual-energy CT (QDECT) imaging utilizing a mixture of three CAs (cationic CA4+ and non-ionic gadoteridol which are sensitive to proteoglycan and water contents, respectively, and bismuth nanoparticles which highlight the cartilage surface) to simultaneously segment the articulating surfaces and determine of the cartilage condition. Intact healthy, proteoglycan-depleted, and mechanically injured bovine cartilage samples (n = 27) were halved and imaged with synchrotron microCT 2-h post immersion in triple CA or in dual CA (CA4+ and gadoteridol). CA4+ and gadoteridol partitions were determined using QDECT, and pairwise evaluation of these partitions was conducted for samples immersed in dual and triple CAs. In conclusion, the triple CA method is sensitive to proteoglycan depletion while maintaining sufficient contrast at the articular surface to enable detection of cartilage lesions caused by mechanical impact.

Segmentation of Articular Cartilage and Early Osteoarthritis based on the Fuzzy Soft Thresholding Approach Driven by Modified Evolutionary ABC Optimization and Local Statistical Aggregation

Articular cartilage assessment, with the aim of the cartilage loss identification, is a crucial task for the clinical practice of orthopedics. Conventional software (SW) instruments allow for just a visualization of the knee structure, without post processing, offering objective cartilage modeling. In this paper, we propose the multiregional segmentation method, having ambitions to bring a mathematical model reflecting the physiological cartilage morphological structure and spots, corresponding with the early cartilage loss, which is poorly recognizable by the naked eye from magnetic resonance imaging (MRI). The proposed segmentation model is composed from two pixel’s classification parts. Firstly, the image histogram is decomposed by using a sequence of the triangular fuzzy membership functions, when their localization is driven by the modified artificial bee colony (ABC) optimization algorithm, utilizing a random sequence of considered solutions based on the real cartilage features. In the second part of the segmentation model, the original pixel’s membership in a respective segmentation class may be modified by using the local statistical aggregation, taking into account the spatial relationships regarding adjacent pixels. By this way, the image noise and artefacts, which are commonly presented in the MR images, may be identified and eliminated. This fact makes the model robust and sensitive with regards to distorting signals. We analyzed the proposed model on the 2D spatial MR image records. We show different MR clinical cases for the articular cartilage segmentation, with identification of the cartilage loss. In the final part of the analysis, we compared our model performance against the selected conventional methods in application on the MR image records being corrupted by additive image noise.

Simultaneous Quantitation of Cationic and Non-ionic Contrast Agents in Articular Cartilage Using Synchrotron MicroCT Imaging

Early diagnosis of acute cartilage injuries enables monitoring of disease progression and improved treatment option planning to prevent post-traumatic osteoarthritis. In contrast-enhanced computed tomography (CECT), the changes in cationic agent diffusion within the tissue reflect cartilage degeneration. The diffusion in degenerated cartilage depends on proteoglycan (PG) content and water content, but each having an opposite effect on diffusion, thus compromising the diagnostic sensitivity. To overcome this limitation, we propose the simultaneous imaging of cationic (sensitive to PG and water contents) and non-ionic (sensitive to water content) agents. In this study, quantitative dual-energy CT (QDECT) imaging of two agents is reported for the first time at clinically feasible imaging time points. Furthermore, this is the first time synchrotron microCT with monochromatic X-rays is employed in cartilage CECT. Imaging was conducted at 1 and 2 h post contrast agent immersion. Intact, PG-depleted, and mechanically injured + PG-depleted cartilage samples (n = 33) were imaged in a mixture of cationic (iodine-based CA4+) and non-ionic (gadolinium-based gadoteridol) agents. Concurrent evaluation of CA4+ and gadoteridol partitions in cartilage is accomplished using QDECT. Subsequent normalization of the CA4+ partition with that of the gadoteridol affords CA4+ attenuations that significantly correlate with PG content – a key marker of OA.

Imaging of proteoglycan and water contents in human articular cartilage with full-body CT using dual contrast technique

Assessment of cartilage composition via tomographic imaging is critical after cartilage injury to prevent post-traumatic osteoarthritis. Diffusion of cationic contrast agents in cartilage is affected by proteoglycan loss and elevated water content. These changes have opposite effects on diffusion and, thereby, reduce the diagnostic accuracy of cationic agents. Here, we apply, for the first time, a clinical full-body CT for dual contrast imaging of articular cartilage. We hypothesize that full-body CT can simultaneously determine the diffusion and partitioning of cationic and non-ionic contrast agents and that normalization of the cationic agent partition with that of the non-ionic agent minimizes the effect of water content and tissue permeability, especially at early diffusion time points. Cylindrical (d = 8 mm) human osteochondral samples (n = 45; four cadavers) of a variable degenerative state were immersed in a mixture of cationic iodinated CA4+ and non-charged gadoteridol contrast agents and imaged with a full-body CT scanner at various time points. Determination of contrast agents' distributions within cartilage was possible at all phases of diffusion. At early time points, gadoteridol, and CA4+ distributed throughout cartilage with lower concentrations in the deep cartilage. At ≥24 h, the gadoteridol concentration remained nearly constant, while the CA4+ concentration increased toward deep cartilage. Normalization of the CA4+ partition with that of gadoteridol significantly (p < 0.05) enhanced correlation with proteoglycan content and Mankin score at the early time points. To conclude, the dual contrast technique was found advantageous over single contrast imaging enabling more sensitive diagnosis of cartilage degeneration. © 2019 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. J Orthop Res 9999:1-12, 2019.

MRI T2 and T1ρ relaxation in patients at risk for knee osteoarthritis: a systematic review and meta-analysis

Background

Magnetic resonance imaging (MRI) T2 and T1ρ relaxation are increasingly being proposed as imaging biomarkers potentially capable of detecting biochemical changes in articular cartilage before structural changes are evident. We aimed to: 1) summarize MRI methods of published studies investigating T2 and T1ρ relaxation time in participants at risk for but without radiographic knee OA; and 2) compare T2 and T1ρ relaxation between participants at-risk for knee OA and healthy controls.

Methods

We conducted a systematic review of studies reporting T2 and T1ρ relaxation data that included both participants at risk for knee OA and healthy controls. Participant characteristics, MRI methodology, and T1ρ and T2 relaxation data were extracted. Standardized mean differences (SMDs) were calculated within each study. Pooled effect sizes were then calculated for six commonly segmented knee compartments.

Results

55 articles met eligibility criteria. There was considerable variability between scanners, coils, software, scanning protocols, pulse sequences, and post-processing. Moderate risk of bias due to lack of blinding was common. Pooled effect sizes indicated participants at risk for knee OA had lengthened T2 relaxation time in all compartments (SMDs from 0.33 to 0.74; p < 0.01) and lengthened T1ρ relaxation time in the femoral compartments (SMD from 0.35 to 0.40; p < 0.001).

Conclusions

T2 and T1ρ relaxation distinguish participants at risk for knee OA from healthy controls. Greater standardization of MRI methods is both warranted and required for progress towards biomarker validation.

Electronic supplementary material

The online version of this article (10.1186/s12891-019-2547-7) contains supplementary material, which is available to authorized users.

Quantitative susceptibility mapping of articular cartilage in patients with osteoarthritis at 3T

BACKGROUND

Quantitative susceptibility mapping (QSM) has recently been applied in humans to quantify the magnetic susceptibility of collagen fibrils in the articular cartilage.

PURPOSE

To determine the ability of QSM to detect cartilage matrix degeneration between normal and early knee osteoarthritis (OA) patients.

STUDY TYPE

Prospective.

POPULATION

Twenty-four patients with knee OA and 24 age- and sex-matched healthy controls.

FIELD STRENGTH/SEQUENCE

3D gradient echo, T₁ turbo spin echo, and proton density-weighted (PDw) spectral attenuated inversion recovery (SPAIR) sequence at 3.0T.

ASSESSMENT

Scan-rescan reproducibility of the susceptibility values in the cartilage was assessed in control subjects. Cartilage thickness, volume, mean, and standard deviation (SD) of susceptibility values of the cartilage compartments were compared between normal and OA patients. The relationship between magnetic susceptibility values and cartilage lesion grading based on MR images was studied.

STATISTICAL TESTS

The Wilcoxon Rank-Sum test was used to compare cartilage thickness, volume, mean, and SD of susceptibility values between control subjects and OA patients. A Spearman rank correlation was performed to study the relationship between the mean and SD of susceptibility values and the cartilage thinning grades.

RESULTS

The SD of magnetic susceptibility values in the knee cartilage was significantly lower in OA patients compared with healthy controls, and it decreased with more severe MR grades of cartilage thinning degeneration. Significant correlations between the SD of susceptibility values and cartilage thinning grades were observed with R²  = 0.64 and P = 0.000, R²  = 0.47 and P = 0.002, R²  = 0.52 and P = 0.001, R²  = 0.42 and P = 0.0006, and R²  = 0.67 and P = 0.000 for medial femoral condyle (MFC), lateral femoral condyle (LFC), medial tibia (MT), lateral tibia (LT), and patella, respectively. No significant difference was found in cartilage volume (P = 0.17, P = 0.13, P = 0.20, P = 0.25, and P = 0.18 for MFC, LFC, MT, LT, and patella, respectively) and thickness (P = 0.31, P = 0.19, P = 0.16, P = 0.09, and P = 0.22 for MFC, LFC, MT, LT, and patella, respectively) between OA patients and healthy controls.

DATA CONCLUSION

The variations of susceptibility values in the knee cartilage decrease with the degree of cartilage degeneration. QSM may be a sensitive indicator for alteration of the collagen network and shows potential to detect cartilage degeneration at early stage.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018.

Longitudinal analysis of tibiofemoral cartilage contact area and position in ACL reconstructed patients

Patients who have suffered ACL injury are more likely to develop early onset post-traumatic osteoarthritis despite reconstruction. The purpose of our study was to evaluate the longitudinal changes in the tibiofemoral cartilage contact area size and location after ACL injury and reconstruction. Thirty-one patients with isolated unilateral ACL injury were followed with T₂ weighted Fast Spin Echo, T_1ρ and T₂ MRI at baseline prior to reconstruction, and 6 months, 1 year, and 2 years after surgery. Areas were delineated in FSE images with an in-house Matlab program using a spline-based semi-automated segmentation algorithm. Tibiofemoral contact area and centroid position along the anterior-posterior axis were calculated along with T_1ρ and T₂ relaxation times on both the injured and non-injured knees. At baseline, the injured knees had significantly smaller and more posteriorly positioned contact areas on the medial tibial surface compared to corresponding healthy knees. These differences persisted 6 months after reconstruction. Moreover, subjects with more anterior medial centroid positions at 6 months had elevated T_1ρ and T₂ measures in the posterior medial tibial plateau at 1 year. Changes in contact area and centroid position after ACL injury and reconstruction may characterize some of the mechanical factors contributing to post-traumatic osteoarthritis. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:2718-2727, 2018.

Systematic review and meta-analysis of the reliability and discriminative validity of cartilage compositional MRI in knee osteoarthritis

OBJECTIVE

To assess reliability and discriminative validity of cartilage compositional magnetic resonance imaging (MRI) in knee osteoarthritis (OA).

DESIGN

The study was carried out per PRISMA recommendations. We searched MEDLINE and EMBASE (1974 - present) for eligible studies. We performed qualitative synthesis of reliability data. Where data from at least two discrimination studies were available, we estimated pooled standardized mean difference (SMD) between subjects with and without OA. Discrimination analyses compared controls and subjects with mild OA (Kellgren-Lawrence (KL) grade 1-2), severe OA (KL grade 3-4) and OA not otherwise specified (NOS) where not possible to stratify. We assessed quality of the evidence using Quality Appraisal of Diagnostic Reliability (QAREL) and Quality Assessment of Diagnostic Accuracy (QUADAS-2) tools.

RESULTS

Fifty-eight studies were included in the reliability analysis and 26 studies were included in the discrimination analysis, with data from a total of 2,007 knees. Intra-observer, inter-observer and test-retest reliability of compositional techniques were excellent with most intraclass correlation coefficients >0.8 and coefficients of variation <10%. T1rho and T2 relaxometry were significant discriminators between subjects with mild OA and controls, and between subjects with OA (NOS) and controls (P < 0.001). T1rho showed best discrimination for mild OA (SMD [95% CI] = 0.73 [0.40 to 1.06], P < 0.001) and OA (NOS) (0.60 [0.41 to 0.80], P < 0.001). Quality of evidence was moderate for both parts of the review.

CONCLUSIONS

Cartilage compositional MRI techniques are reliable and, in the case of T1rho and T2 relaxometry, can discriminate between subjects with OA and controls.

Diagnostic utility of fluorogenic peptide-conjugated Au nanoparticle probe corroborated by rabbit model of mild cartilage injury and panel of osteoarthritic patients

Using a rabbit model of early-stage osteoarthritis (OA) and a sampling patients with OA, we evaluated the diagnostic utility of a fluorogenic peptide-conjugated gold nanoparticle (AuNP) probe in detecting mild cartilage injury, based on the a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4) enzyme. Synthesis of this fluorescent turn-on probe (or AU-probe) required conjugation of AuNPs with a fluorescein isothiocyanate (FITC)-modified ADAMTS-4-specific peptide (DVQEFRGVTAVIR). Synovial fluid samples were then collected from 48 adult rabbits and 100 patients for comparative testing (ADAMTS-4 ELISA and AU-probe). Rabbit and patient MRI images were also evaluated and scored. Receiver operating characteristic (ROC) curve analysis was applied to various diagnostic methods (MRI, ELISA, AU-probe, and arthroscopy), performing comparisons via logistic regression. In rabbits, the AU-probe proved nonsuperior to MRI T2 mapping and ELISA (fluorescence cutpoint > 864.965 au). In patient groups, logistic regression analysis indicated that combined AU-probe/MRI testing outperformed MRI alone, thus offsetting low MRI sensitivity and low AU-probe specificity for improved detection of mild cartilage injury (sensitivity, 82.5%; specificity, 80.0%). We have consequently confirmed the efficacy of this AU-probe, using ADAMTS-4 activity in synovial fluid to diagnose mild cartilage injury. Combining the AU-probe with conventional MRI assessment proved optimal in this setting.

Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry

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

Synovial Fluid Profile at the Time of Anterior Cruciate Ligament Reconstruction and Its Association With Cartilage Matrix Composition 3 Years After Surgery

BACKGROUND

Anterior cruciate ligament tears can lead to posttraumatic osteoarthritis. In addition to biomechanical factors, changes in biochemical profiles within the knee joint after injury and anterior cruciate ligament reconstruction (ACLR) may play a role in accelerating joint degeneration. Hypothesis/Purpose: It was hypothesized that cartilage matrix composition after ACLR is associated with the degree of inflammatory response after initial injury. This study evaluated the association between the inflammatory response after injury-as indicated by cytokine, metalloproteinase, and cartilage degradation marker concentrations in synovial fluid-and articular cartilage degeneration, measured by T1ρ and T2 quantitative magnetic resonance imaging up to 3 years after ACLR.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

Twenty-six subjects from a longitudinal cohort study who underwent ACLR at a mean 8.5 weeks after injury (range, 4-19 weeks) had synovial fluid aspirated at the time of surgery. Immunoassays quantified biomarkers in synovial fluid. T1ρ and T2 values of articular cartilage were calculated with magnetic resonance scans acquired prior to surgery and at 6 months and 1, 2, and 3 years after surgery. Pearson correlation coefficients were calculated among the various biomarkers. K-means clustering was used to group subjects with similar biomarker profiles. Generalized estimating equations were used to find the overall differences in T1ρ and T2 values throughout these first 3 years after surgery between the clusters while controlling for other factors.

RESULTS

Significant and strong correlations were observed between several cytokines (interleukin 6 [IL-6], IL-8, IL-10, and tumor necrosis factor α) and 2 matrix metalloproteinases (MMP-1 and MMP-3) ( P < .05). Moderate correlations were found among combinations of C-terminal crosslinked telopeptide type II collagen, N-terminal telopeptide, cartilage oligomeric matrix protein, and sulfated glycosaminoglycan ( P < .05). Two clusters were generated, 1 of which was characterized by lower concentrations of cytokines (IL-6, IL-8, IL-10, tumor necrosis factor α) and MMP-1 and MMP-3 and higher sulfated glycosaminoglycan. This cluster was associated with significantly higher T1ρ and T2 values in the medial tibial and patellar cartilage over the first 3 years after ACLR.

CONCLUSION

At the time of ACLR surgery, profiles of synovial fluid inflammatory cytokines, degradative enzymes, and cartilage breakdown products show promise as predictors of abnormal cartilage tissue integrity (increased T1ρ and T2 values) throughout the first 3 years after surgery.

CLINICAL RELEVANCE

The results suggest an intricate relationship between inflammation and cartilage turnover, which can in turn be influenced by timing after injury and patient factors.

Frontal Plane Knee Mechanics and Early Cartilage Degeneration in People With Anterior Cruciate Ligament Reconstruction: A Longitudinal Study

BACKGROUND

Abnormal frontal plane gait mechanics are known risk factors for knee osteoarthritis, but their role in early cartilage degeneration after anterior cruciate ligament reconstruction (ACLR) is not well understood. Hypothesis/Purpose: The objective was to evaluate the association of frontal plane gait mechanics with medial knee cartilage magnetic resonance (MR) relaxation times over 1 year in patients with ACLR and controls. It was hypothesized that (1) there will be an increase in frontal plane medial knee loading and medial knee MR relaxation times over time in the patients with ACLR, and (2) increases in frontal plane medial knee loading will be associated with an increase in medial knee MR relaxation times.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

Patients with ACLR (n = 37) underwent walking gait analyses and bilateral quantitative MR imaging (MRI) before surgery and at 6 and 12 months after ACLR. Healthy control participants (n = 13) were evaluated at baseline and 12 months. Gait variables included peak knee adduction moment (KAM), KAM impulse, and peak knee adduction angle. MRI variables included medial femur and medial tibia whole compartment and subregional T_1ρ and T₂ relaxation times. Statistical analyses included a comparison of changes over time for gait and MRI variables, correlations between changes in gait and MRI variables over time, and differences in change in MRI variables in patients who showed an increase versus decrease in KAM impulse.

RESULTS

There were significant increases in medial T_1ρ (Δ 4%-11%) and T₂ (Δ 2%-10%) relaxation times from baseline to 6 months for both knees in the ACLR group and in KAM (Δ 13%) for the injured knee. From baseline to 6 months, patients who had an increase in KAM impulse in the injured knee had a greater increase in medial T_1ρ and T₂ relaxation times as compared with those who did not have an increase in KAM impulse. Longitudinal changes for the control group were not significant.

CONCLUSION

There is an increase in medial knee relaxation times over the first 6 months after ACLR. People with an increase in medial knee loading show an increase in medial knee relaxation times when compared with those who do not have an increase in medial knee loading over the first 6 months.