Accuracy evaluation of automatic quantification of the articular cartilage surface curvature from MRI

Assessment of whole cartilage surface damage in an osteoarthritis rat model: the Cartilage Roughness Score (CRS) utilizing microcomputed tomography

OBJECTIVE

This study aims to establish an accurate and robust imaging biomarker for pre-clinical osteoarthritis (OA) research, focusing on early detection of cartilage surface degeneration.

METHOD

Using 50 male Wistar rats, this study aims to observe Collagenase Induced Osteoarthritis (CIOA) progression through microcomputed x-ray tomography (µCT), histopathological analysis, and gait analysis. A novel parameter, Cartilage Roughness Score (CRS), was developed for assessing cartilage structural damage from µCT data and was compared with histological OARSI Cartilage Degeneration Score (OARSI CDS). Additionally, as CRS maps the full surface, it was used to simulate the level of uncertainty in histological sampling.

RESULTS

CRS and OARSI CDS have a linear relationship. CRS for healthy cartilage is 2.75 (95% CI: 1.14-4.36) and with every 1 unit increase in OARSI, CRS is expected to increase by 0.64 (95% CI: 0.35-0.92). Cartilage degeneration due to CIOA was evident in both histopathological scoring and CRS. However, only CRS was sensitive enough to show consistent damage progression from day 10 to day 60. Furthermore, our simulation for histological sampling suggested that up to 16 coronal slices with 200µm spacing would be needed to accurately represent the full extent of cartilage surface degeneration in a slice wise manner. Gait analysis showed changes solely at eight days post-collagenase injection, normalizing by day 60.

CONCLUSION

The CRS analysis method emerges as a robust tool for cartilage surface damage assessment. This study demonstrates the potential of automatic 3D analysis over the traditional 2D histological approach when evaluating cartilage surface damage.

DATA STATEMENT

Micro-computed tomography data is available via ida.fairdata.fi46 (https://doi.org/10.23729/f33d3ba8-01b8-47af-90dd-94b7c7861247).

Evaluation of Knee Donor and Elbow Recipient Sites for Osteochondral Autologous Transplantation Surgery in Capitellar Osteochondritis Dissecans

BACKGROUND

Osteochondral autologous transplantation surgery (OATS) has been advocated for treatment of osteochondritis dissecans (OCD) of the capitellum in adolescents. However, little information is available regarding the optimal knee harvest site to match the contour and cartilage thickness of the recipient elbow lesion.

PURPOSE

To characterize the capitellar anatomic structure in adolescents with and without OCD and to compare these measurements to normal adolescent knees to identify the optimal site for osteochondral graft harvest.

STUDY DESIGN

Controlled laboratory study.

METHODS

Twenty-one patients with OCD were analyzed. Twenty-two patients with normal elbows and 25 age-, weight-, and height-matched patients with normal knees were also identified. Cartilage radii of curvatures (ROCs) in the sagittal and coronal-axial planes were measured on magnetic resonance imaging (MRI) of normal capitella and 5 sites (posterior lateral femoral condyle, medial and lateral middle trochlear ridges, and medial and lateral inferior trochlear ridges) in normal knees. Differences in ROC between the knee donor and capitellar recipient sites were calculated based on a 10-mm osteochondral plug diameter.

RESULTS

Overall, the mean apex differences between graft and recipient sites ranged from 0.4 to 0.9 mm, and mean edge differences ranged from 0.5 to 1.4 mm in the coronal-axial dimension. Of all knee sites tested, the posterior lateral femoral condyle had average ROCs (19.1 mm sagittal; 14.1 mm axial) most like the capitellum (10.6 mm sagittal, 12.6 mm coronal-axial), resulting in minimal apex and edge differences (apex difference = -0.6 mm; coronal-axial side difference = -0.5 mm; no sagittal side difference). Of the anterior nonweightbearing sites, the inferior medial trochlear ridge (28.3 mm sagittal ROC; 13.2 mm coronal-axial ROC) demonstrated the lowest apex and side differences when compared with the capitellum (apex difference = -0.8 mm; coronal-axial side difference = -0.8 mm; no sagittal side difference). The frequently used middle lateral trochlear ridge (28.8 mm sagittal; 8.7 mm coronal-axial ROCs) had the largest side difference (apex distance = -0.8 mm; coronal-axial side difference = -1.4 mm; no sagittal side difference).

CONCLUSION/CLINICAL RELEVANCE

In cases where a large single-plug OATS is considered, a 10-mm plug from the anterior nonweightbearing aspect of the distal femur is calculated to result in ≤1 mm of articular incongruity at the recipient capitellum. The inferior medial trochlear ridge should be considered as a donor site for OATS procedures for OCD given its accessibility and favorable geometry.

Automating the design of resection guides specific to patient anatomy in knee replacement surgery by enhanced 3D curvature and surface modeling of distal femur shape models

Personalized resection guides (PRG) have been recently proposed in the domain of knee replacement, demonstrating clinical outcome similar or even superior to both manual and navigated interventions. Among the mandatory pre-surgical steps for PRG prototyping, the measurement of clinical landmarks (CL) on the bony surfaces is recognized as a key issue due to lack of standardized methodologies, operator-dependent variability and time expenditure. In this paper, we focus on the reliability and repeatability of an anterior-posterior axis, also known as Whiteside line (WL), of the distal femur proposing automatic surface processing and modeling methods aimed at overcoming some of the major concerns related to the manual identification of such CL on 2D images and 3D models. We show that the measurement of WL, exploiting the principle of mean-shifting surface curvature, is highly repeatable and coherent with clinical knowledge.

Correlations between radiographic assessments and MRI features of knee osteoarthritis--a cross-sectional study

OBJECTIVES

To assess correlations between Kellgren & Lawrence (KL) gradings, minimum joint space width (mJSW) measurements and the Boston Leeds Osteoarthritis Knee Score (BLOKS) within a cohort of obese patients with knee osteoarthritis (KOA).

METHODS

192 Participants were recruited from an outpatient clinic (ClinicalTrials.gov: NCT00655941). Inclusion criteria were age ≥50 years, body mass index (BMI) ≥30 kg/m(2) plus symptomatic and verified KOA. 1.5 T magnetic resonance imaging (MRI) scans were assessed using BLOKS and bi-plane radiography by mJSW and KL. Statistics used were Spearman rank correlation coefficients.

RESULTS

The average patient was 63 years of age, female and had a BMI of 37. KL gradings correlated to cartilage damage, bone marrow lesions and meniscus pathology (r = 0.15-0.76) and similar results were found for the relationship between BLOKS and mJSW. BLOKS assessed knee joint pathology co-segregated with compartment and grade specific KL (P < 0.0001). BLOKS variables were statistically significant correlated, particularly in the medial tibiofemoral compartment (r = 0.42-0.80). Adjusting for age, gender and BMI did not alter these associations.

CONCLUSION

Extensive pathological damage is present even in mild radiographic KOA and BLOKS gradings and KL scores increase together. Analyses of compartment specific KL scores revealed differences in their relationship to the assessed MRI variables. Our study displays the segregation of MRI gradings with respect to location and level of radiographic scores, reveals a high inter-dependency of MRI-assessed structures, and describes some redundancy of specific BLOKS variables.

Automatic quantification of tibio-femoral contact area and congruity

We present methods to quantify the medial tibio- femoral (MTF) joint contact area (CA) and congruity index (CI) from low-field magnetic resonance imaging (MRI). Firstly, based on the segmented MTF cartilage compartments, we computed the contact area using the Euclidian distance transformation. The CA was defined as the area of the tibial superior surface and the femoral inferior surface that are less than a voxel width apart. Furthermore, the CI is computed point-by-point by assessing the first- and second-order general surface features over the contact area. Mathematically, it is the inverse distance between the local normal vectors (first-order features) scaled by the local normal curvatures (second-order features) along the local direction of principal knee motion in a local reference coordinate system formed by the directions of principal curvature and the surface normal vector. The abilities of the CA and the CI for diagnosing osteoarthritis (OA) at different levels (disease severity was assessed using the Kellgren and Lawrence Index, KL) were cross-validated on 288 knees at baseline. Longitudinal analysis was performed on 245 knees. The precision quantified on 31 scan-rescan pairs (RMS CV) for CA was 13.7% and for CI 7.5%. The CA increased with onset of the disease and then decreased with OA progression. The CI was highest in healthy and decreased with the onset of OA and further with disease progression. The CI showed an AUC of 0.69 (p < 0.0001) for separating KL = 0 and KL > 0. For separating KL < 1 or KL = 1 and KL > 1 knees, the AUC for CI was 0.73 (p < 0.0001). The CA demonstrated longitudinal responsiveness (SRM) at all stages of OA, whereas the CI did for advanced OA only. Eventually, the quantified CA and the CI might be suitable to help explaining OA onset, diagnosis of (early) OA, and measuring the efficacy of DMOADs in clinical trials.

Advances in imaging of osteoarthritis and cartilage

Osteoarthritis (OA) is the most frequent form of arthritis, with major implications for individual and public health care without effective treatment available. The field of joint imaging, and particularly magnetic resonance (MR) imaging, has evolved rapidly owing to technical advances and the application of these to the field of clinical research. Cartilage imaging certainly is at the forefront of these developments. In this review, the different aspects of OA imaging and cartilage assessment, with an emphasis on recent advances, will be presented. The current role of radiography, including advances in the technology for joint space width assessment, will be discussed. The development of various MR imaging techniques capable of facilitating assessment of cartilage morphology and the methods for evaluating the biochemical composition of cartilage will be presented. Advances in quantitative morphologic cartilage assessment and semiquantitative whole-organ assessment will be reviewed. Although MR imaging is the most important modality in imaging of OA and cartilage, others such as ultrasonography play a complementary role that will be discussed briefly.

Systematic review of the concurrent and predictive validity of MRI biomarkers in OA

OBJECTIVE

To summarize literature on the concurrent and predictive validity of MRI-based measures of osteoarthritis (OA) structural change.

METHODS

An online literature search was conducted of the OVID, EMBASE, CINAHL, PsychInfo and Cochrane databases of articles published up to the time of the search, April 2009. 1338 abstracts obtained with this search were preliminarily screened for relevance by two reviewers. Of these, 243 were selected for data extraction for this analysis on validity as well as separate reviews on discriminate validity and diagnostic performance. Of these 142 manuscripts included data pertinent to concurrent validity and 61 manuscripts for the predictive validity review. For this analysis we extracted data on criterion (concurrent and predictive) validity from both longitudinal and cross-sectional studies for all synovial joint tissues as it relates to MRI measurement in OA.

RESULTS

Concurrent validity of MRI in OA has been examined compared to symptoms, radiography, histology/pathology, arthroscopy, CT, and alignment. The relation of bone marrow lesions, synovitis and effusion to pain was moderate to strong. There was a weak or no relation of cartilage morphology or meniscal tears to pain. The relation of cartilage morphology to radiographic OA and radiographic joint space was inconsistent. There was a higher frequency of meniscal tears, synovitis and other features in persons with radiographic OA. The relation of cartilage to other constructs including histology and arthroscopy was stronger. Predictive validity of MRI in OA has been examined for ability to predict total knee replacement (TKR), change in symptoms, radiographic progression as well as MRI progression. Quantitative cartilage volume change and presence of cartilage defects or bone marrow lesions are potential predictors of TKR.

CONCLUSION

MRI has inherent strengths and unique advantages in its ability to visualize multiple individual tissue pathologies relating to pain and also predict clinical outcome. The complex disease of OA which involves an array of tissue abnormalities is best imaged using this imaging tool.

Responsiveness and reliability of MRI in knee osteoarthritis: a meta-analysis of published evidence

OBJECTIVE

To summarize literature on the responsiveness and reliability of MRI-based measures of knee osteoarthritis (OA) structural change.

METHODS

A literature search was conducted using articles published up to the time of the search, April 2009. 1338 abstracts obtained with this search were preliminarily screened for relevance and of these, 243 were selected for data extraction. For this analysis we extracted data on reliability and responsiveness for every reported synovial joint tissue as it relates to MRI measurement in knee OA. Reliability was defined by inter- and intra-reader intra-class correlation (ICC), or coefficient of variation, or kappa statistics. Responsiveness was defined as standardized response mean (SRM) - ratio of mean of change over time divided by standard deviation of change. Random-effects models were used to pool data from multiple studies.

RESULTS

The reliability analysis included data from 84 manuscripts. The inter-reader and intra-reader ICC were excellent (range 0.8-0.94) and the inter-reader and intra-reader kappa values for quantitative and semi-quantitative measures were all moderate to excellent (range 0.52-0.88). The lowest value (kappa=0.52) corresponded to semi-quantitative synovial scoring intra-reader reliability and the highest value (ICC=0.94) for semi-quantitative cartilage morphology. The responsiveness analysis included data from 42 manuscripts. The pooled SRM for quantitative measures of cartilage morphometry for the medial tibiofemoral joint was -0.86 (95% confidence intervals (CI) -1.26 to -0.46). The pooled SRM for the semi-quantitative measurement of cartilage morphology for the medial tibiofemoral joint was 0.55 (95% CI 0.47-0.64). For the quantitative analysis, SRMs are negative because the quantitative value, indicating a loss of cartilage, goes down. For the semi-quantitative analysis, SRMs indicating a loss in cartilage are positive (increase in score).

CONCLUSION

MRI has evolved substantially over the last decade and its strengths include the ability to visualize individual tissue pathologies, which can be measured reliably and with good responsiveness using both quantitative and semi-quantitative techniques.

Diagnosis of Osteoarthritis by Cartilage Surface Smoothness Quantified Automatically from Knee MRI

OBJECTIVE

We investigated whether surface smoothness of articular cartilage in the medial tibiofemoral compartment quantified from magnetic resonance imaging (MRI) could be appropriate as a diagnostic marker of osteoarthritis (OA).

METHOD

At baseline, 159 community-based subjects aged 21 to 81 with normal or OA-affected knees were recruited to provide a broad range of OA states. Smoothness was quantified using an automatic framework from low-field MRI in the tibial, femoral, and femoral subcompartments. Diagnostic ability of smoothness was evaluated by comparison with conventional OA markers, specifically cartilage volume from MRI, joint space width (JSW) from radiographs, and pain scores.

RESULTS

A total of 140 subjects concluded the 21-month study. Cartilage smoothness provided diagnostic ability in all compartments (P < 0.0001). The diagnostic smoothness markers performed at least similar to JSW and were superior to volume markers (e.g., the AUC for femoral smoothness of 0.80 was higher than the 0.57 for volume, P < 0.0001, and marginally higher than 0.73 for JSW, P = 0.25). The smoothness markers allowed diagnostic detection of pain presence (P < 0.05) and showed some correlation with pain severity (e.g., r = -0.32). The longitudinal change in smoothness was correlated with cartilage loss (r up to 0.60, P < 0.0001 in all compartments).

CONCLUSIONS

This study demonstrated the potential of cartilage smoothness markers for diagnosis of moderate radiographic OA. Furthermore, correlations between smoothness and pain values and smoothness loss and cartilage loss supported a link to progression of OA. Thereby, smoothness markers may allow detection and monitoring of OA-supplemented currently accepted markers.

Quantitative cartilage imaging in knee osteoarthritis

Quantitative measures of cartilage morphology (i.e., thickness) represent potentially powerful surrogate endpoints in osteoarthritis (OA). These can be used to identify risk factors of structural disease progression and can facilitate the clinical efficacy testing of structure modifying drugs in OA. This paper focuses on quantitative imaging of articular cartilage morphology in the knee, and will specifically deal with different cartilage morphology outcome variables and regions of interest, the relative performance and relationship between cartilage morphology measures, reference values for MRI-based knee cartilage morphometry, imaging protocols for measurement of cartilage morphology (including those used in the Osteoarthritis Initiative), sensitivity to change observed in knee OA, spatial patterns of cartilage loss as derived by subregional analysis, comparison of MRI changes with radiographic changes, risk factors of MRI-based cartilage loss in knee OA, the correlation of MRI-based cartilage loss with clinical outcomes, treatment response in knee OA, and future directions of the field.

Magnetic resonance imaging-based semiquantitative and quantitative assessment in osteoarthritis

Whole organ magnetic resonance imaging (MRI)-based semiquantitative (SQ) assessment of knee osteoarthritis (OA), based on reliable scoring methods and expert reading, has become a powerful research tool in OA. SQ morphologic scoring has been applied to large observational cross-sectional and longitudinal epidemiologic studies as well as interventional clinical trials. SQ whole organ scoring analyzes all joint structures that are potentially relevant as surrogate outcome measures of OA and potential disease modification, including cartilage, subchondral bone, osteophytes, intra- and periarticular ligaments, menisci, synovial lining, cysts, and bursae. Resources needed for SQ scoring rely on the MRI protocol, image quality, experience of the expert readers, method of documentation, and the individual scoring system that will be applied. The first part of this article discusses the different available OA whole organ scoring systems, focusing on MRI of the knee, and also reviews alternative approaches. Rheumatologists are made aware of artifacts and differential diagnoses when applying any of the SQ scoring systems. The second part focuses on quantitative approaches in OA, particularly measurement of (subregional) cartilage loss. This approach allows one to determine minute changes that occur relatively homogeneously across cartilage structures and that are not apparent to the naked eye. To this end, the cartilage surfaces need to be segmented by trained users using specialized software. Measurements of knee cartilage loss based on water-excitation spoiled gradient recalled echo acquisition in the steady state, fast low-angle shot, or double-echo steady-state imaging sequences reported a 1% to 2% decrease in cartilage thickness annually, and a high degree of spatial heterogeneity of cartilage thickness changes in femorotibial subregions between subjects. Risk factors identified by quantitative measurement technology included a high body mass index, meniscal extrusion and meniscal tears, knee malalignment, advanced radiographic OA grade, bone marrow alterations, and focal cartilage lesions.

Identification of progressors in osteoarthritis by combining biochemical and MRI-based markers

Introduction

At present, no disease-modifying osteoarthritis drugs (DMOADS) are approved by the FDA (US Food and Drug Administration); possibly partly due to inadequate trial design since efficacy demonstration requires disease progression in the placebo group. We investigated whether combinations of biochemical and magnetic resonance imaging (MRI)-based markers provided effective diagnostic and prognostic tools for identifying subjects with high risk of progression. Specifically, we investigated aggregate cartilage longevity markers combining markers of breakdown, quantity, and quality.

Methods

The study included healthy individuals and subjects with radiographic osteoarthritis. In total, 159 subjects (48% female, age 56.0 ± 15.9 years, body mass index 26.1 ± 4.2 kg/m²) were recruited. At baseline and after 21 months, biochemical (urinary collagen type II C-telopeptide fragment, CTX-II) and MRI-based markers were quantified. MRI markers included cartilage volume, thickness, area, roughness, homogeneity, and curvature in the medial tibio-femoral compartment. Joint space width was measured from radiographs and at 21 months to assess progression of joint damage.

Results

Cartilage roughness had the highest diagnostic accuracy quantified as the area under the receiver-operator characteristics curve (AUC) of 0.80 (95% confidence interval: 0.69 to 0.91) among the individual markers (higher than all others, P < 0.05) to distinguish subjects with radiographic osteoarthritis from healthy controls. Diagnostically, cartilage longevity scored AUC 0.84 (0.77 to 0.92, higher than roughness: P = 0.03). For prediction of longitudinal radiographic progression based on baseline marker values, the individual prognostic marker with highest AUC was homogeneity at 0.71 (0.56 to 0.81). Prognostically, cartilage longevity scored AUC 0.77 (0.62 to 0.90, borderline higher than homogeneity: P = 0.12). When comparing patients in the highest quartile for the longevity score to lowest quartile, the odds ratio of progression was 20.0 (95% confidence interval: 6.4 to 62.1).

Conclusions

Combination of biochemical and MRI-based biomarkers improved diagnosis and prognosis of knee osteoarthritis and may be useful to select high-risk patients for inclusion in DMOAD clinical trials.

Quantitative assessment of articular cartilage morphology via EPIC-microCT

OBJECTIVE

The objective of the present study was to validate the ability of Equilibrium Partitioning of an Ionic Contrast agent via microcomputed tomography (EPIC-microCT) to nondestructively assess cartilage morphology in the rat model.

DESIGN

An appropriate contrast agent (Hexabrix) concentration and incubation time for equilibration were determined for reproducible segmentation of femoral articular cartilage from contrast-enhanced microCT scans. Reproducibility was evaluated by triplicate scans of six femora, and the measured articular cartilage thickness was independently compared to thickness determined from needle probe testing and histology. The validated technique was then applied to quantify age-related differences in articular cartilage morphology between 4, 8, and 16-week-old (n=5 each) male Wistar rats.

RESULTS

A 40% Hexabrix/60% phosphate buffered saline (PBS) solution with 30 min incubation was optimal for segmenting cartilage from the underlying bone tissue and other soft tissues in the rat model. High reproducibility was indicated by the low coefficient of variation (1.7-2.5%) in cartilage volume, thickness and surface area. EPIC-microCT evaluation of thickness showed a strong linear relationship and good agreement with both needle probing (r(2)=0.95, slope=0.81, P<0.01, mean difference 11+/-22 microm, n=43) and histology (r(2)=0.99, slope=0.97, P<0.01, mean difference 12+/-10 microm, n=30). Cartilage volume and thickness significantly decreased with age while surface area significantly increased.

CONCLUSION

EPIC-microCT imaging has the ability to nondestructively evaluate three-dimensional articular cartilage morphology with high precision and accuracy in a small animal model.

Quantitative MR imaging using "LiveWire" to measure tibiofemoral articular cartilage thickness

OBJECTIVE

To assess the reliability and accuracy of manual and semi-automated segmentation methods for quantifying knee cartilage thickness. This study employed both manual and LiveWire-based semi-automated segmentation methods, ex vivo and in vivo, to measure tibiofemoral (TF) cartilage thickness.

METHODS

The articular cartilage of a cadaver knee and a healthy volunteer's knee were segmented manually and with LiveWire from multiple 3T MR images. The cadaver specimen's cartilage thickness was also evaluated with a 3D laser scanner, which was assumed to be the gold standard. Thickness measurements were made within specific cartilage regions. The reliability of each segmentation method was assessed both ex vivo and in vivo, and accuracy was assessed ex vivo by comparing segmentation results to those obtained with laser scanning.

RESULTS

The cadaver specimen thickness measurements showed mean coefficients of variation (CVs) of 4.16%, 3.02%, and 1.59%, when evaluated with manual segmentation, LiveWire segmentation, and laser scanning, respectively. The cadaver specimen showed mean absolute errors versus laser scanning of 4.07% and 7.46% for manual and LiveWire segmentation, respectively. In vivo thickness measurements showed mean CVs of 2.71% and 3.65% when segmented manually and with LiveWire, respectively.

CONCLUSIONS

Manual segmentation, LiveWire segmentation, and laser scanning are repeatable methods for quantifying knee cartilage thickness; however, the measurements are technique-dependent. Ex vivo, the manual segmentation error was distributed around the laser scanning mean, while LiveWire consistently underestimated laser scanning by 8.9%. Although LiveWire offers repeatability and decreased segmentation time, manual segmentation more closely approximates true cartilage thickness, particularly in cartilage contact regions.