Initial results on development and application of statistical atlas of femoral cartilage in osteoarthritis to determine sex differences in structure: data from the Osteoarthritis Initiative

Are there gender-specific differences in hip and knee cartilage composition and degeneration? A systematic literature review

The aim of the present review is to systematically analyse the current literature about gender differences in hip or knee cartilage composition and degeneration, to help explaining how and why osteoarthritis affects women more often and more severely than men. A systematic review of the literature in English was performed. Eleven studies on 1962 patients (905 females and 787 males) that reported differences on cartilage composition between males and females were included. Nine evaluated the knee, one the hip, and one both. They were heterogeneous in their methods: one conducted histological analyses, and all the others evaluated cartilage characteristics (volume, width, and composition) through magnetic resonance imaging. All authors reported gender differences in both volume and morphology of the cartilage, from infancy to menopause. In fact, a study on 92 healthy children statistically showed significant gender differences in cartilage thickness at all sites, even after adjustment for age, body, and bone size. Gender differences become more evident after menopause, when women have a lower cartilage volume and a higher cartilage loss. Men show significantly higher knee and hip cartilage volumes than women, and women carry a significantly greater risk to develop osteoarthritis. This is in part due to body and bone size, but also depends on qualitative and quantitative differences in the composition of cartilage and its degeneration rate after menopause. Structural changes in cartilage that occur between genders during ageing have significance in the development of osteoarthritis.

Anatomically Standardized Maps Reveal Distinct Patterns of Cartilage Thickness With Increasing Severity of Medial Compartment Knee Osteoarthritis

While cartilage thickness alterations are a central element of knee osteoarthritis (OA), differences among disease stages are still incompletely understood. This study aimed to quantify the spatial-variations in cartilage thickness using anatomically standardized thickness maps and test if there are characteristic patterns in patients with different stages of medial compartment knee OA. Magnetic resonance images were acquired for 75 non-OA and 100 OA knees of varying severities (Kellgren and Lawrence (KL) scores 1-4). Three-dimensional cartilage models were reconstructed and a shape matching technique was applied to convert the models into two-dimensional anatomically standardized thickness maps. Difference thickness maps and statistical parametric mapping were used to compare the four OA and the non-OA subgroups. This analysis showed distinct thickness patterns for each clinical stage that formed a coherent succession from the non-OA to the KL 4 subgroups. Interestingly, the only significant difference for early stage (KL 1) was thicker femoral cartilage. With increase in disease severity, typical patterns developed, including thinner cartilage in the anterior area of the medial condyle (significant for KL 3 and 4) and thicker cartilage in the posterior area of the medial and lateral condyles (significant for all OA subgroups). The tibial patterns mainly consisted of thinner cartilage for both medial and lateral compartments (significant for KL 2-4). Comparing anatomically standardized maps allowed identifying patterns of thickening and thinning over the entire cartilage surface, consequently improving the characterization of thickness differences associated with OA. The results also highlighted the value of anatomically standardized maps to analyze spatial variations in cartilage thickness. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2442-2451, 2017.

Investigation of random walks knee cartilage segmentation model using inter-observer reproducibility: Data from the osteoarthritis initiative

BACKGROUND

Existing knee cartilage segmentation methods have reported several technical drawbacks. In essence, graph cuts remains highly susceptible to image noise despite extended research interest; active shape model is often constraint by the selection of training data while shortest path have demonstrated shortcut problem in the presence of weak boundary, which is a common problem in medical images.

OBJECTIVES

The aims of this study is to investigate the capability of random walks as knee cartilage segmentation method.

METHODS

Experts would scribble on knee cartilage image to initialize random walks segmentation. Then, reproducibility of the method is assessed against manual segmentation by using Dice Similarity Index. The evaluation consists of normal cartilage and diseased cartilage sections which is divided into whole and single cartilage categories.

RESULTS

A total of 15 normal images and 10 osteoarthritic images were included. The results showed that random walks method has demonstrated high reproducibility in both normal cartilage (observer 1: 0.83±0.028 and observer 2: 0.82±0.026) and osteoarthritic cartilage (observer 1: 0.80±0.069 and observer 2: 0.83±0.029). Besides, results from both experts were found to be consistent with each other, suggesting the inter-observer variation is insignificant (Normal: P=0.21; Diseased: P=0.15).

CONCLUSION

The proposed segmentation model has overcame technical problems reported by existing semi-automated techniques and demonstrated highly reproducible and consistent results against manual segmentation method.

Baseline Cartilage Thickness and Meniscus Extrusion Predict Longitudinal Cartilage Loss by Quantitative Magnetic Resonance Imaging: Data From the Osteoarthritis Initiative

OBJECTIVE

This study aimed to assess how meniscus damage and baseline cartilage thickness influence the rate of cartilage loss and knee pain.

METHODS

Of 4796 participants in the Osteoarthritis Initiative, 86 had baseline and 48-month follow-up quantitative magnetic resonance imaging data for medial compartment cartilage thickness. Baseline meniscus pathology was scored by a musculoskeletal radiologist using Whole-Organ Magnetic Resonance Imaging Score. Findings were correlated with 72-month Knee injury and Osteoarthritis Outcome Score.

RESULTS

Univariate analysis showed cartilage change was not influenced by demographic variables. Multivariable regression revealed that initial cartilage thickness (-1.07 mm at 48 months for every 1 mm decrease at baseline, P < 0.001) and meniscus extrusion (-0.33 mm if present at baseline, P < 0.001) were the strongest predictors of medial compartment cartilage thickness at 48 months. Knee injury and Osteoarthritis Outcome Score pain scores did not correlate with cartilage loss.

CONCLUSIONS

Baseline cartilage thickness and meniscus extrusion are important and independent predictors for accelerated cartilage loss. However, the degree of cartilage loss did not correlate with midterm change in clinical outcome scores.

Imaging research results from the osteoarthritis initiative (OAI): a review and lessons learned 10 years after start of enrolment

The Osteoarthritis Initiative (OAI) is a multicentre, prospective, observational, cohort study of knee osteoarthritis (OA) that began recruitment in 2004. The OAI provides public access to clinical and image data, enabling researchers to examine risk factors/predictors and the natural history of knee OA incidence and progression, and the qualification of imaging and other biomarkers. In this narrative review, we report imaging findings and lessons learned 10 years after enrolment has started. A literature search for full text articles published from the OAI was performed up to 31 December 2013 using Pubmed and the OAI web page. We summarise the rationale, design and imaging protocol of the OAI, and the history of OAI publications. We review studies from early partial, and later full OAI public data releases. The latter are structured by imaging method and tissue, reviewing radiography and then MRI findings on cartilage morphology, cartilage lesions and composition (T2), bone, meniscus, muscle and adipose tissue. Finally, analyses directly comparing findings from MRI and radiography are summarised. Ten years after the first participants were enrolled and first papers published, the OAI has become an invaluable resource to the OA research community. It has fuelled novel methodological approaches of analysing images, and has provided a wealth of information on OA pathophysiology. Continued collection and public release of long-term observations will help imaging measures to gain scientific and regulatory acceptance as 'prognostic' or 'efficacy of intervention' biomarkers, potentially enabling shorter and more efficient clinical trials that can test structure-modifying therapeutic interventions (NCT00080171).

Automatic model-based semantic registration of multimodal MRI knee data

PURPOSE

To propose a robust and automated model-based semantic registration for the multimodal alignment of the knee bone and cartilage from three-dimensional (3D) MR image data.

MATERIALS AND METHODS

The movement of the knee joint can be semantically interpreted as a combination of movements of each bone. A semantic registration of the knee joint was implemented by separately reconstructing the rigid movements of the three bones. The proposed method was validated by registering 3D morphological MR datasets of 25 subjects into the corresponding T2 map datasets, and was compared with rigid and elastic methods using two criteria: the spatial overlap of the manually segmented cartilage and the distance between the same landmarks in the reference and target datasets.

RESULTS

The mean Dice Similarity Coefficient (DSC) of the overlapped cartilage segmentation was increased to 0.68 ± 0.1 (mean ± SD) and the landmark distance was reduced to 1.3 ± 0.3 mm after the proposed registration method. Both metrics were statistically superior to using rigid (DSC: 0.59 ± 0.12; landmark distance: 2.1 ± 0.4 mm) and elastic (DSC: 0.64 ± 0.11; landmark distance: 1.5 ± 0.5 mm) registrations.

CONCLUSION

The proposed method is an efficient and robust approach for the automated registration between morphological knee datasets and T2 MRI relaxation maps.

On Subregional Analysis of Cartilage Loss from Knee MRI

OBJECTIVE

Understanding how knee cartilage is affected by osteoarthritis (OA) is critical in the development of sensitive biomarkers that may be used as surrogate endpoints in clinical trials. The objective of this study was to analyze longitudinal changes in cartilage thickness using detailed change maps and to examine if current methods for subregional analysis are able to capture the underlying cartilage changes.

MATERIALS AND METHODS

MRI images of 267 knees from 135 participants were acquired at baseline and 21-month follow-up and processed using a fully automatic framework for cartilage segmentation and quantification. The framework provides an anatomical coordinate system that allows for direct comparison across cartilage thickness maps. The reproducibility of this method was evaluated on 37 scan-rescan image pairs.

RESULTS

In OA knees, an annualized thickness loss of 3.7% was observed in the medial femoral cartilage plate (MF) whereas subregional measurements varied between -9.0% (loss) and 1.6%. The largest changes were observed in the posterior part of the MF. In the medial tibial cartilage plate (MT), a thickness increase of 0.4% was observed whereas subregional measurements varied between -0.8% (loss) and 1.6%. In addition, notable differences in the patterns of cartilage change were observed between genders.

CONCLUSIONS

This study indicated that the spatial changes, although highly heterogeneous, showed distinct patterns of cartilage thinning and cartilage thickening in both the MF and the MT. These patterns were not accurately reflected when thickness changes were averaged over large, predefined subregions as defined in current methods for subregional analysis.