Association of quantitative measures of medial meniscal extrusion with structural and symptomatic knee osteoarthritis progression - Data from the OAI FNIH biomarker study

Evaluating Undersampling Schemes and Deep Learning Reconstructions for High-Resolution 3D Double Echo Steady State Knee Imaging at 7 T: A Comparison Between GRAPPA, CAIPIRINHA, and Compressed Sensing

OBJECTIVE

The 3-dimensional (3D) double echo steady state (DESS) magnetic resonance imaging sequence can image knee cartilage with high, isotropic resolution, particularly at high and ultra-high field strengths. Advanced undersampling techniques with high acceleration factors can provide the short acquisition times required for clinical use. However, the optimal undersampling scheme and its limits are unknown.

MATERIALS AND METHODS

High-resolution isotropic (reconstructed voxel size: 0.3 × 0.3 × 0.3 mm3) 3D DESS images of 40 knees in 20 volunteers were acquired at 7 T with varying undersampling factors (R = 4-30) and schemes (regular: GRAPPA, CAIPIRINHA; incoherent: compressed sensing [CS]), whereas the remaining imaging parameters were kept constant. All imaging data were reconstructed with deep learning (DL) algorithms. Three readers rated image quality on a 4-point Likert scale. Four-fold accelerated GRAPPA was used as reference standard. Incidental cartilage lesions were graded on a modified Whole-Organ Magnetic Resonance Imaging Score (WORMS). Friedman's analysis of variance characterized rating differences. The interreader agreement was assessed using κ statistics.

RESULTS

The quality of 16-fold accelerated CS images was not rated significantly different from that of 4-fold accelerated GRAPPA and 8-fold accelerated CAIPIRINHA images, whereas the corresponding data were acquired 4.5 and 2 times faster (01:12 min:s) than in 4-fold accelerated GRAPPA (5:22 min:s) and 8-fold accelerated CAIPIRINHA (2:22 min:s) acquisitions, respectively. Interreader agreement for incidental cartilage lesions was almost perfect for 4-fold accelerated GRAPPA (κ = 0.91), 8-fold accelerated CAIPIRINHA (κ = 0.86), and 8- to 16-fold accelerated CS (κ = 0.91).

CONCLUSIONS

Our results suggest significant advantages of incoherent versus regular undersampling patterns for high-resolution 3D DESS cartilage imaging with high acceleration factors. The combination of CS undersampling with DL reconstruction enables fast, isotropic, high-resolution acquisitions without apparent impairment of image quality. Since DESS specific absorption rate values tend to be moderate, CS DESS with DL reconstruction promises potential for high-resolution assessment of cartilage morphology and other musculoskeletal anatomies at 7 T.

Meniscal extrusion: Proposal for a novel qualitative classification

Meniscal extrusion (ME), defined as the radial displacement of the meniscal body outside the margins of the tibial plateau, has been seen as an independent and relevant predictor of intra-articular knee degeneration. Nonetheless, available classifications for ME are exclusively quantitative assessments not considering the context in which extrusion is identified. Indeed, ME can be the result of several different conditions spanning from acute tears to chronic degeneration and its definition cannot be only dependent on the numeric calculation of the radial displacement of the meniscal body. Furthermore, growing evidence supports the existence of a paraphysiological ME resulting from joint loading, limb malalignment, anatomical abnormalities of the meniscal attachments to the femur and tibia or a nonpathological finding after meniscal allograft transplantation. It is therefore clear that an exclusively quantitative assessment of ME cannot be sufficient since this condition can develop in such different clinical scenarios. For this reason, a novel qualitative classification for ME is proposed, differentiating between three distinct conditions: a paraphysiological ME, a pathological ME and ME related to degenerative conditions. Furthermore, a comprehensive review of the present literature has been conducted to report the most relevant and updated evidence on the topic highlighting the difference in the clinical management of each different category.

Level of Evidence

Not applicable.

Osteoarthritis year in review 2024: Imaging

OBJECTIVE

To review recent literature evidence describing imaging of osteoarthritis (OA) and to identify the current trends in research on OA imaging.

METHOD

This is a narrative review of publications in English, published between April, 2023, and March, 2024. A Pubmed search was conducted using the following search terms: osteoarthritis/OA, radiography, ultrasound/US, computed tomography/CT, magnetic resonance imaging/MRI, DXA/DEXA, and artificial intelligence/AI/deep learning. Most publications focus on OA imaging in the knee and hip. Imaging of OA in other joints and OA imaging with artificial intelligence (AI) are also reviewed.

RESULTS

Compared to the same period last year (April 2022 - March 2023), there has been no significant change in the number of publications utilizing CT, MRI, and AI. A notable reduction in the number of OA research papers using radiography and ultrasound is noted. There were several observational studies focusing on imaging of knee OA, such as the Multicenter Osteoarthritis Study, Rotterdam Study, Strontium ranelate efficacy in knee OA (SEKOIA) study, and the Osteoarthritis Initiative FNIH Biomarker study. Hip OA observational studies included, but not limited to, Cohort Hip and Cohort Knee study and UK Biobank study. Studies on emerging applications of AI in OA imaging were also covered. A small number of OA clinical trials were published with a focus on imaging-based outcomes.

CONCLUSION

MRI-based OA imaging research continues to play an important role compared to other modalities. Usage of various AI tools as an adjunct to human assessment is increasingly applied in OA imaging research.

Association between meniscal extrusion and disease severity in knee osteoarthritis: a retrospective case-control study

OBJECTIVE

To explore the relationship between meniscus compression and the severity of knee osteoarthritis.

MATERIALS AND METHODS

A retrospective case-control study included 95 patients with knee osteoarthritis (OA) admitted to our hospital from April 2021 to July 2023, who were grouped into slight protrusion of meniscus group (n = 48) and severe protrusion of meniscus group (n = 47) according to the degree of meniscal extrusion. Various parameters, including Kellgren/Lawrence classification, imaging findings, cartilage damage grading, physical function assessments, and correlation analyses, were used to evaluate the relationship between meniscal extrusion and disease progression.

RESULTS

The study revealed significant associations between severe meniscal extrusion and measures of disease severity, including reduced cartilage thickness(3.24 ± 0.61 versus 3.78 ± 1.45; P = 0.019), increased meniscus degeneration grade (2.86 ± 0.54 versus 2.23 ± 1.63; P = 0.013), diminished joint space width (4.56 ± 0.73 versus 4.86 ± 0.52; P = 0.025), elevated meniscal extrusion(3.68 ± 1.78 versus 2.85 ± 1.54; P = 0.018), greater bone marrow lesion volume(6.13 ± 1.85 versus 5.21 ± 1.58; P = 0.011), advanced cartilage damage(t = 0.016), and impaired physical functioning. Correlation analyses indicated a positive relationship between meniscal extrusion and disease severity(r > 0). While the predictive value of meniscal extrusion alone was modest (AUC = 0.617), a combined model integrating various parameters yielded a high predictive value for disease progression (AUC = 0.853).

CONCLUSION

Meniscal extrusion was associated with disease severity and functional decline in knee osteoarthritis patients and has potential predictive value for disease progression.

EUROVISCO Consensus Guidelines for the Use of Hyaluronic Acid Viscosupplementation in Knee Osteoarthritis Based on Patient Characteristics

OBJECTIVES

Viscosupplementation with hyaluronic acid (HA) is a commonly used intra-articular treatment for osteoarthritis (OA). We performed a Delphi consensus process to formulate guidelines for the use of intra-articular hyaluronic acid (IAHA) knee injection according to the patient's characteristics.

METHODS

The EUROVISCO group consists of 12 members who had expertise in clinical and/or research in the field of OA and IAHA treatment. This group drafted issues through an iterative process and subsequently voted according to a Delphi process on their level of agreement (LoA) on these recommendations. The scores were pooled to generate a median agreement score for each recommendation. The strength of the recommendation (SOR) was classified as strong if the median agreement score was ≥8. The level of consensus (LOC) was also obtained. The level of evidence was given for each recommendation.

RESULTS

A total of 34 statements were evaluated by the expert group. A unanimous or high LoA was obtained in 16. IAHA can be considered irrespective of the age in patients with symptomatic knee OA. It can be used in patients with diabetes and/or moderate to severe obesity. It can also be used in knee OA patients with a history of gout, meniscocalcinosis and with mild-to-moderate varus/valgus malalignment. The group recommended against the use of VS in pregnant women and in OA flare.

CONCLUSION

In summary, the working group provided strong recommendations for the use of IAHA injection that will facilitate individualized treatment decision algorithms in the management of knee OA.

Biomechanical impact of progressive meniscal extrusion on the knee joint: a finite element analysis

BACKGROUND

While measuring meniscal extrusion quantitatively is an early risk factor for knee osteoarthritis (KOA), the biomechanics involved in this process are not well understood. This study aimed to investigate the effects of varying degrees of medial and lateral meniscal extrusion and their material softening on knee osteoarthritis progression.

METHODS

Finite element analysis (FEA) was utilized to simulate varying degrees of meniscal extrusion (1-5 mm) in 72 knee joint models, representing progressive meniscal degeneration and material softening due to injury. Changes in von Mises stress of the cartilage and menisci and the load distribution on the tibial plateau's meniscus and cartilage were studied under balanced standing posture in both healthy and injured knees, and statistical analysis was performed using Spearman correlation.

RESULTS

Compared to healthy knees, peak stress in medial compartment tissues increased by over 40% with 4 mm of medial meniscus extrusion, and in lateral compartment tissues with 2 mm of lateral meniscus extrusion. Meniscus extrusion reduced the contact load between the meniscus and femoral cartilage but increased it between the tibial and femoral cartilages, with a maximum increase up to fivefold. Spearman correlation analysis indicated that meniscal extrusion significantly affected peak stress and contact loads in the respective knee compartment (p < 0.001), with a lesser impact on the opposite compartment. Notably, medial meniscal extrusion also significantly increased peak stress in the lateral tibial cartilage (p < 0.05).

CONCLUSIONS

The quantitative analysis revealed that meniscal extrusion significantly affected the biomechanics of soft tissues within the same compartment, with limited impact on the opposite side. Specifically, Medial extrusion beyond 4 mm significantly affected the biomechanics of the medial compartment, while lateral extrusion over 2 mm had a similar impact on the lateral compartment. Meniscal softening, without altering joint contact characteristics, primarily affected the biomechanics of the meniscus itself, with minimal impact on other soft tissues.

The design of a sample rapid magnetic resonance imaging (MRI) acquisition protocol supporting assessment of multiple articular tissues and pathologies in knee osteoarthritis

Objective

This expert opinion paper proposes a design for a state-of-the-art magnetic resonance image (MRI) acquisition protocol for knee osteoarthritis clinical trials in early and advanced disease. Semi-quantitative and quantitative imaging endpoints are supported, partly amendable to automated analysis. Several (peri-) articular tissues and pathologies are covered, including synovitis.

Method

A PubMed literature search was conducted, with focus on the past 5 years. Further, osteoarthritis imaging experts provided input. Specific MRI sequences, orientations, spatial resolutions and parameter settings were identified to align with study goals. We strived for implementation on standard clinical scanner hardware, with a net acquisition time ≤30 ​min.

Results

Short- and long-term longitudinal MRIs should be obtained at ≥1.5T, if possible without hardware changes during the study. We suggest a series of gradient- and spin-echo-sequences, supporting MOAKS, quantitative analysis of cartilage morphology and T2, and non-contrast-enhanced depiction of synovitis. These sequences should be properly aligned and positioned using localizer images. One of the sequences may be repeated in each participant (re-test), optimally at baseline and follow-up, to estimate within-study precision. All images should be checked for quality and protocol-adherence as soon as possible after acquisition. Alternative approaches are suggested that expand on the structural endpoints presented.

Conclusions

We aim to bridge the gap between technical MRI acquisition guides and the wealth of imaging literature, proposing a balance between image acquisition efficiency (time), safety, and technical/methodological diversity. This approach may entertain scientific innovation on tissue structure and composition assessment in clinical trials on disease modification of knee osteoarthritis.

Imaging Biomarkers of Osteoarthritis

Currently no disease-modifying osteoarthritis drug has been approved for the treatment of osteoarthritis (OA) that can reverse, hold, or slow the progression of structural damage of OA-affected joints. The reasons for failure are manifold and include the heterogeneity of structural disease of the OA joint at trial inclusion, and the sensitivity of biomarkers used to measure a potential treatment effect.This article discusses the role and potential of different imaging biomarkers in OA research. We review the current role of radiography, as well as advances in quantitative three-dimensional morphological cartilage assessment and semiquantitative whole-organ assessment of OA. Although magnetic resonance imaging has evolved as the leading imaging method in OA research, recent developments in computed tomography are also discussed briefly. Finally, we address the experience from the Foundation for the National Institutes of Health Biomarker Consortium biomarker qualification study and the future role of artificial intelligence.