Comparison of Clinical and Semiquantitative Cartilage Grading Systems in Predicting Outcomes After Arthroscopic Partial Meniscectomy

The Role of Biomarkers in Predicting Outcomes of Anterior Cruciate Ligament Reconstruction: A Systematic Review

Background

Anterior cruciate ligament (ACL) injury is frequently associated with injuries to other parts of the knee, including the menisci and articular cartilage. After ACL injury and reconstruction, there may be progressive chondral degradation. Biomarkers in blood, urine, and synovial fluid can be measured after ACL injury and reconstruction and have been proposed as a means of measuring the associated cellular changes occurring in the knee.

Purpose

To systematically review the literature regarding biomarkers in urine, serum, or synovial fluid that have been associated with an outcome measure after ACL reconstruction.

Study Design

Systematic review; Level of evidence, 3.

Methods

This review was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The MEDLINE, Embase, CINAHL, and Web of Science databases were searched to identify studies published before September 2023 that reported on patients undergoing ACL reconstruction where a biomarker was measured and related to an outcome variable. Of 9360 results, 16 studies comprising 492 patients were included. Findings were reported as descriptive summaries synthesizing the available literature.

Results

A total of 45 unique biomarkers or biomarker ratios were investigated (12 serum, 3 urine, and 38 synovial fluid; 8 biomarkers were measured from >1 source). Nineteen different outcome measures were identified, including the International Knee Documentation Committee Subjective Knee Form, Knee injury and Osteoarthritis Outcome Score, numeric pain scores, radiological outcomes (magnetic resonance imaging and radiography), rates of arthrofibrosis and cyclops lesions, and gait biomechanics. Across the included studies, 17 biomarkers were found to have a statistically significant association (P < .05) with an outcome variable. Serum interleukin 6 (s-IL-6), serum and synovial fluid matrix metalloproteinase-3 (s-MMP-3 and sf-MMP-3), urinary and synovial fluid C-terminal telopeptide of type 2 collagen (u-CTX-II and sf-CTX-II), and serum collagen type 2 cleavage product (s-C2C) showed promise in predicting outcomes after ACL reconstruction, specifically regarding patient-reported outcome measures (s-IL-6 and u-CTX-II), gait biomechanical parameters (s-IL-6, sf-MMP-3, s-MMP-3, and s-C2C), pain (s-IL-6 and u-CTX-II), and radiological osteoarthritis (ratio of u-CTX-II to serum procollagen 2 C-propeptide).

Conclusion

The results highlight several biomarkers that have been associated with clinically important postoperative outcome measures and may warrant further research to understand if they can provide meaningful information in the clinical environment.

Morphological and Quantitative Parametric MRI Follow-up of Cartilage Changes Before and After Intra-articular Injection Therapy in Patients With Mild to Moderate Knee Osteoarthritis: A Randomized, Placebo-Controlled Trial

BACKGROUND

Intra-articular injections are routinely used for conservative treatment of knee osteoarthritis (OA). The detailed comparative therapeutic effects of these injections on cartilage tissue are still unclear.

OBJECTIVE

The aim of this study was to detect and compare knee cartilage changes after intra-articular injection of glucocorticoid, hyaluronic acid, or platelet-rich plasma (PRP) to placebo using quantitative (T2 and T2* mapping) and morphological magnetic resonance imaging parameters in patients with mild or moderate osteoarthritis.

MATERIALS AND METHODS

In a double-blinded, placebo-controlled, single-center trial, knees with mild or moderate osteoarthritis (Kellgren-Lawrence grade 1-3) were randomly assigned to an intra-articular injection with 1 of these substances: glucocorticoid, hyaluronic acid, PRP, or placebo. Cartilage degeneration on baseline and follow-up magnetic resonance imaging scans (after 3 and 12 months) was assessed by 2 readers using quantitative T2 and T2* times (milliseconds) and morphological parameters (modified Outerbridge grading, subchondral bone marrow edema, subchondral cysts, osteophytes).

RESULTS

One hundred twenty knees (30 knees per treatment group) were analyzed with a median patient age of 60 years (interquartile range, 54.0-68.0 years). Interreader reliability was good for T2 (ICC, 0.76; IQR, 0.68-0.83) and T2* (ICC, 0.83; IQR, 0.76-0.88) measurements. Morphological parameters showed no significant changes between all groups after 3 and 12 months. T2 mapping after 12 months showed the following significant ( P = 0.001-0.03) changes between groups in 6 of 14 compartments: values after PRP injection decreased compared with glucocorticoid in 4 compartments (complete medial femoral condyle and central part of lateral condyle) and compared with placebo in 2 compartments (anterior and central part of medial tibial plateau); values after glucocorticoid injection decreased compared with placebo in 1 compartment (central part of medial tibial plateau). No significant changes were seen for T2 and T2* times after 3 months and T2* times after 12 months. No correlation was found between T2/T2* times and Kellgren-Lawrence grade, age, body mass index, or pain (Spearman ρ, -0.23 to 0.18).

CONCLUSIONS

Platelet-rich plasma injection has a positive long-term effect on cartilage quality in the medial femoral compartment compared to glucocorticoid, resulting in significantly improved T2 values after 12 months. For morphological cartilage parameters, injections with glucocorticoid, PRP, or hyaluronic acid showed no better effect in the short or long term compared with placebo.

Quantitative and Compositional MRI of the Articular Cartilage: A Narrative Review

This review examines the latest advancements in compositional and quantitative cartilage MRI techniques, addressing both their potential and challenges. The integration of these advancements promises to improve disease detection, treatment monitoring, and overall patient care. We want to highlight the pivotal task of translating these techniques into widespread clinical use, the transition of cartilage MRI from technical validation to clinical application, emphasizing its critical role in identifying early signs of degenerative and inflammatory joint diseases. Recognizing these changes early may enable informed treatment decisions, thereby facilitating personalized medicine approaches. The evolving landscape of cartilage MRI underscores its increasing importance in clinical practice, offering valuable insights for patient management and therapeutic interventions. This review aims to discuss the old evidence and new insights about the evaluation of articular cartilage through MRI, with an update on the most recent literature published on novel quantitative sequences.

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.

Screening for or diagnosing medial meniscal root injury using peripheral medial joint space width ratio in plain radiographs

To evaluate the sensitivity and specificity for screening and diagnosis of medial meniscal root injury using the distance ratio of medial joint space width between affected and unaffected knees in patients with potential medial meniscal root injury (MMRI) using plain radiographs, the study enrolled 49 patients with suspected MMRI who were then evaluated for MMRI using plain radiographs of both knees in the anteroposterior view and magnetic resonance imaging (MRI) findings. The ratios of peripheral medial joint space width between the affected and unaffected sides were calculated. The cut point value, sensitivity and specificity were calculated according to a receiver operating characteristic (ROC) curve. In the study, 18 and 31 patients were diagnosed with and without MMRI, respectively. The mean peripheral medial joint space width ratios comparing the affected side to the unaffected side in the standing position of the anteroposterior view of both knees in the MMRI and non-MMRI groups were 0.83 ± 0.11 and 1.04 ± 0.16, respectively, which was a significant difference (p-value < 0.001). The cut point value of the peripheral medial joint space width ratio between the affected and unaffected sides for suspected MMRI was 0.985, with sensitivity and specificity of 0.83 and 0.81, respectively, and for diagnosis was 0.78, with sensitivity and specificity of 0.39 and 1.00, respectively. The area under the ROC curve was 0.881. Patients with a possible MMRI had peripheral medial joint space width ratios less than patients with non-MMRI. This test can be used for reliably screening for or diagnosing medial meniscal root injury in primary or secondary care settings.

Imaging of Cartilage and Chondral Defects: An Overview

A healthy articular cartilage is paramount to joint function. Cartilage defects, whether acute or chronic, are a significant source of morbidity. This review summarizes various imaging modalities used for cartilage assessment. While radiographs are insensitive, they are still widely used to indirectly assess cartilage. Ultrasound has shown promise in the detection of cartilage defects, but its efficacy is limited in many joints due to inadequate visualization. CT arthrography has the potential to assess internal derangements of joints along with cartilage, especially in patients with contraindications to MRI. MRI remains the favored imaging modality to assess cartilage. The conventional imaging techniques are able to assess cartilage abnormalities when cartilage is already damaged. The newer imaging techniques are thus targeted at detecting biochemical and structural changes in cartilage before an actual visible irreversible loss. These include, but are not limited to, T2 and T2* mapping, dGEMRI, T1ρ imaging, gagCEST imaging, sodium MRI and integrated PET with MRI. A brief discussion of the advances in the surgical management of cartilage defects and post-operative imaging assessment is also included.

Establishment of a New Qualitative Evaluation Method for Articular Cartilage by Dynamic T2w MRI Using a Novel Contrast Medium as a Water Tracer

OBJECTIVE

In the early stages of cartilage damage, diagnostic methods focusing on the mechanism of maintaining the hydrostatic pressure of cartilage are thought to be useful. ¹⁷O-labeled water, which is a stable isotope of oxygen, has the advantage of no radiation exposure or allergic reactions and can be detected by magnetic resonance imaging (MRI). This study aimed to evaluate MRI images using ¹⁷O-labeled water in a rabbit model.

DESIGN

Contrast MRI with ¹⁷O-labeled water and macroscopic and histological evaluations were performed 4 and 8 weeks after anterior cruciate ligament transection surgery in rabbits. A total of 18 T2-weighted images were acquired, and ¹⁷O-labeled water was manually administered on the third scan. The ¹⁷O concentration in each phase was calculated from the signal intensity at the articular cartilage. Macroscopic and histological grades were evaluated and compared with the ¹⁷O concentration.

RESULTS

An increase in ¹⁷O concentration in the macroscopic and histologically injured areas was observed by MRI. Macroscopic evaluation showed that the ¹⁷O concentration significantly increased in the damaged site group. Histological evaluations also showed that ¹⁷O concentrations significantly increased at 36 minutes 30 seconds after initiating MRI scanning in the Osteoarthritis Research Society International (OARSI) grade 3 (0.493 in grade 0, 0.659 in grade 1, 0.4651 in grade 2, and 0.9964 in grade 3, P < 0.05).

CONCLUSION

¹⁷O-labeled water could visualize earlier articular cartilage damage, which is difficult to detect by conventional methods.

Concentration of synovial fluid biomarkers on the day of anterior cruciate ligament (ACL)-reconstruction predict size and depth of cartilage lesions on 5-year follow-up

PURPOSE

The current investigation evaluated the relationship between the synovial fluid cytokine microenvironment at the time of isolated anterior cruciate ligament (ACL) reconstruction and the presence of subsequent chondral wear and radiologic evidence of osteoarthritis (OA) on cartilage-specific MRI sequences at a minimum of 5-year follow-up.

METHODS

Patients who underwent primary ACL reconstruction with no baseline concomitant cartilage or meniscal defects and had synovial fluid samples obtained at the time of surgery were retrospectively identified. Patients with a minimum of 5 years of postoperative follow-up were contacted and asked to complete patient-reported outcome (PRO) measures including Visual Analog Scale (VAS) for pain, Lysholm Scale, Knee Injury and Osteoarthritis Outcome Score (KOOS), and Tegner Activity Scale, along with postoperative magnetic resonance imaging (MRI). The concentration of ten biomarkers that have previously been suggested to play a role in cartilage degradation and inflammation in the joint space was measured. Linear regression controlling for age, sex, and body mass index (BMI) was performed to create a model using the synovial fluid concentrations at the time of surgery to predict postoperative semiquantitative cartilage lesion size and depth on MRI at a minimum of 5 years follow up.

RESULTS

The patients were comprised of eight males (44.4%) and ten females (55.6%) with a mean age at the time of surgery of 30.8 ± 8.7 years (range 18.2-44.5 years). The mean follow-up time was 7.8 ± 1.5 years post-operatively (range 5.7-9.7 years). MCP-1, VEGF, and IL-1Ra were found to have significant associations with the presence of postoperative cartilage wear (p < 0.05). No correlations were demonstrated among the biomarker concentrations at the time of injury with PRO scores at final follow-up (NS).

CONCLUSION

Synovial fluid inflammatory biomarker concentrations at the time of injury can predict progression of early-stage post-traumatic osteoarthritis at a mean of almost 8 years post-operatively. Findings from this study may help identify treatment targets to alter the natural history of cartilage loss following anterior cruciate ligament injury.

LEVEL OF EVIDENCE

Level III, retrospective cohort study.

Automated knee cartilage segmentation for heterogeneous clinical MRI using generative adversarial networks with transfer learning

BACKGROUND

This study aimed to build a deep learning model to automatically segment heterogeneous clinical MRI scans by optimizing a pre-trained model built from a homogeneous research dataset with transfer learning.

METHODS

Conditional generative adversarial networks pretrained on the Osteoarthritis Initiative MR images was transferred to 30 sets of heterogenous MR images collected from clinical routines. Two trained radiologists manually segmented the 30 sets of clinical MR images for model training, validation and test. The model performance was compared to models trained from scratch with different datasets, as well as two radiologists. A 5-fold cross validation was performed.

RESULTS

The transfer learning model obtained an overall averaged Dice coefficient of 0.819, an averaged 95 percentile Hausdorff distance of 1.463 mm, and an averaged average symmetric surface distance of 0.350 mm on the 5 random holdout test sets. A 5-fold cross validation had a mean Dice coefficient of 0.801, mean 95 percentile Hausdorff distance of 1.746 mm, and mean average symmetric surface distance of 0.364 mm. It outperformed other models and performed similarly as the radiologists.

CONCLUSIONS

A transfer learning model was able to automatically segment knee cartilage, with performance comparable to human, using heterogeneous clinical MR images with a small training data size. In addition, the model proved robust when tested through cross validation and on images from a different vendor. We found it feasible to perform fully automated cartilage segmentation of clinical knee MR images, which would facilitate the clinical application of quantitative MRI techniques and other prediction models for improved patient treatment planning.

Specimen specific imaging and joint mechanical testing data for next generation virtual knees

Virtual knees, with specimen-specific anatomy and mechanics, require heterogeneous data collected on the same knee. Specimen-specific data such as the specimen geometry, physiological joint kinematics-kinetics and contact mechanics are necessary in the development of virtual knee specimens for clinical and scientific simulations. These data are also required to capture or evaluate the predictive capacity of the model to represent joint and tissue mechanical response. This document details the collection of magnetic resonance imaging data and, tibiofemoral joint and patellofemoral joint mechanical testing data. These data were acquired for a cohort of eight knee specimens representing different populations with varying gender, age and perceived health of the joint. These data were collected as part of the Open Knee(s) initiative. Imaging data when combined with joint mechanics data, may enable development and assessment of authentic specimen-specific finite element models of the knee. The data may also guide prospective studies for association of anatomical and biomechanical markers in a specimen-specific manner.