Trabecular bone texture detected by plain radiography is associated with MRI-defined osteophytes in finger joints of women without radiographic osteoarthritis.

OBJECTIVE: To examine associations between trabecular bone (TB) texture and magnetic resonance imaging (MRI)-defined osteophytes in finger joints without radiographic osteoarthritis (OA) using an augmented variance orientation transform (AVOT) method. DESIGN: In a cross-sectional study, associations of the TB texture and osteophytes were examined in 21 women with mean (standard deviation) age of 69.9 (5.3) from the Oslo Hand OA cohort. The AVOT was applied to distal and proximal TB regions selected on hand radiographs of the subjects. The regions were adjacent to 57 finger joints (24 distal and 33 proximal interphalangeal) without radiographic OA (Kellgren-Lawrence [KL] grade 0), without MRI-defined joint space narrowing (JSN), bone marrow lesions (BMLs), attrition, erosion, cysts, sclerosis, malalignment (all MRI grades 0) and without or only with mild synovitis (MRI grade 0 or 1). Bone texture parameters were calculated: mean fractal dimension (FDMEAN), FDs in the horizontal (FDH) and vertical (FDV) directions, and along the roughest part (FDSta). Associations between the parameters categorized into groups using tertiles and osteophytes were evaluated using logistic regression adjusted for age. RESULTS: Lower FDSta and FDV in the distal TB regions were associated with increased odds of MRI-defined osteophytes (P < 0.037 for linear trend). No statistically significant associations were found for the proximal regions. CONCLUSIONS: Lower mean roughness and lower roughness in vertical and roughest directions of the proximal TB texture are associated with MRI-defined osteophytes in finger joints without radiographic OA. These findings suggest that TB texture may be a useful marker for detecting early hand OA.

Baseline trabecular bone and its relation to incident radiographic knee osteoarthritis and increase in joint space narrowing score: directional fractal signature analysis in the MOST study.

PURPOSE: To explore the association of baseline trabecular bone structure with incident tibiofemoral (TF) osteoarthritis (OA) and with increase in joint space narrowing (JSN) score. METHODS: The Multicenter Osteoarthritis Study (MOST) includes subjects with or at risk for knee OA. Knee radiographs were scored for Kellgren-Lawrence (KL) grade and JSN at baseline, 30, 60 and 84 months. Knees (KL ≤ 1) at baseline were assessed for incident OA (KL ≥ 2) and increases in JSN score. For each knee image at baseline, a variance orientation transform method (VOT) was applied to subchondral tibial bone regions of medial and lateral compartments. Seventeen fractal parameters were calculated per region. Associations of each parameter with OA incidence and with medial and lateral JSN increases were explored using logistic regression. Analyses were stratified by digitized film (DF) vs computer radiography (CR) and adjusted for confounders. RESULTS: Of 894 knees with CR and 1158 knees with DF, 195 (22%) and 303 (26%) developed incident OA. Higher medial bone roughness was associated with increased odds of OA incidence at 60 and 84 months and also, medial and lateral JSN increases (primarily vertical). Lower medial and lateral anisotropy was associated with increased odds of medial and lateral JSN increase. Compared to DF, CR had more associations and also, similar results at overlapping scales. CONCLUSION: Baseline trabecular bone texture was associated with incident radiographic OA and increase of JSN scores independently of risk factors for knee OA. Higher roughness and lower anisotropy were associated with increased odds for radiographic OA change.

Trabecular bone texture detected by plain radiography is associated with an increased risk of knee replacement in patients with osteoarthritis: a 6 year prospective follow up study.

OBJECTIVE: To examine the association between trabecular bone texture and knee joint replacement (KJR) measured using a variance orientation transform (VOT) method. METHODS: The association of trabecular bone texture and KJR was examined prospectively over 6 years in 123 subjects with symptomatic knee osteoarthritis (OA): data regarding KJR was available for 114 (93%). At baseline, weight-bearing anteroposterior tibio-femoral radiographs were acquired. Trabecular bone texture regions were selected from the medial and lateral subchondral tibia. The VOT method was applied to each region and five fractal bone texture parameters, i.e., mean fractal dimension (FDMEAN), fractal dimensions in the horizontal (FDH) and vertical (FDV) directions, and along the roughest part of trabecular bone (FD(Sta)), and texture aspect ratio (Str) were calculated. The association between groups with increasing baseline fractal parameters (defined using tertiles) with risk of JR was examined using logistic regression. RESULTS: 28 (25%) participants' study knees underwent KJR over 6 years. Participants with KJR had lower medial FD(MEAN) and FD(H) parameters (P = 0.02 for difference). With increasing FD(MEAN), adjusted for age, gender, body mass index (BMI), osteophyte grade, joint space narrowing (JSN) grade and WOMAC pain score, the odds of KJR was reduced (P = 0.04 for trend). CONCLUSION: This study suggests that the texture of medial tibial trabecular bone measured from plain radiographs is related to the risk of KJR: with increasing FD(MEAN) (the overall measure of bone texture roughness) the risk of KJR was reduced, independent of other clinical predictors of joint replacement. Tibial trabecular bone texture may be a useful marker of disease progression and a target of therapy in OA.

Prediction of progression of radiographic knee osteoarthritis using tibial trabecular bone texture.

OBJECTIVE: To develop a system for predicting the progression of radiographic knee osteoarthritis (OA) using tibial trabecular bone texture. METHODS: We studied 203 knees with (n = 68) or without (n = 135) radiographic tibiofemoral OA in 105 subjects (90 men and 15 women with a mean age of 54 years) in whom 2 sets of knee radiographs were obtained 4 years apart. We determined medial and lateral compartment tibial trabecular bone texture using an automated region selection method. Three texture parameters were calculated: roughness, degree of anisotropy, and direction of anisotropy based on a signature dissimilarity measure method. We evaluated tibiofemoral OA progression using a radiographic semiquantitative outcome: an increase in the medial joint space narrowing (JSN) grade. We examined the predictive ability of trabecular bone texture in knees with and those without preexisting radiographic OA, with adjustment for age, sex, and body mass index, using logistic regression (generalized estimating equations) and receiver operating characteristic curves. RESULTS: The prediction of increased medial JSN in knees with or without preexisting radiographic OA was the most accurate for medial trabecular bone texture; the area under the curve (AUC) was 0.77 and 0.75, respectively. For lateral trabecular bone texture, the AUC was 0.71 in knees with preexisting OA and 0.72 in knees without preexisting OA. CONCLUSION: We have developed a system, based on analyzing tibial trabecular bone texture, which yields good prediction of loss of tibiofemoral joint space. The predictive ability of the system needs to be further validated.

Hypothermia is associated with a low ETCO2 and low pH-stat PaCO2 in refractory cardiac arrest.

AIMS: The end-tidal carbon dioxide (ETCO2) is frequently measured in cardiac arrest (CA) patients, for management and for predicting survival. Our goal was to study the PaCO2 and ETCO2 in hypothermic cardiac arrest patients. METHODS: We included patients with refractory CA assessed for extracorporeal cardiopulmonary resuscitation. Hypothermic patients were identified from previously prospectively collected data from Poland, France and Switzerland. The non-hypothermic CA patients were identified from two French cohort studies. The primary parameters of interest were ETCO2 and PaCO2 at hospital admission. We analysed the data according to both alpha-stat and pH-stat strategies. RESULTS: We included 131 CA patients (39 hypothermic and 92 non-hypothermic). Both ETCO2 (p < 0.001) and pH-stat PaCO2 (p < 0.001) were significantly lower in hypothermic compared to non-hypothermic patients, which was not the case for alpha-stat PaCO2 (p = 0.15). The median PaCO2-ETCO2 gradient was greater for hypothermic compared to non-hypothermic patients when using the alpha-stat method (46 mmHg vs 30 mmHg, p = 0.007), but not when using the pH-stat method (p = 0.10). Temperature was positively correlated with ETCO2 (p < 0.01) and pH-stat PaCO2 (p < 0.01) but not with alpha-stat PaCO2 (p = 0.5). The ETCO2 decreased by 0.5 mmHg and the pH-stat PaCO2 by 1.1 mmHg for every decrease of 1° C of the temperature. The proportion of survivors with an ETCO2 ≤ 10 mmHg at hospital admission was 45% (9/25) for hypothermic and 12% (2/17) for non-hypothermic CA patients. CONCLUSIONS: Hypothermic CA is associated with a decrease of the ETCO2 and pH-stat PaCO2 compared with non-hypothermic CA. ETCO2 should not be used in hypothermic CA for predicting outcome.

Differences in trabecular bone texture between knees with and without radiographic osteoarthritis detected by directional fractal signature method.

OBJECTIVE: To evaluate differences in tibial trabecular bone (TB) texture between subjects with and without radiographic knee osteoarthritis (OA) using a variance orientation transform (VOT) method. DESIGN: Subjects with knee OA (Kellgren & Lawrence grade > or =2) and controls without OA (both n=26, seven women) were matched by sex, age, body mass index and compartment. The VOT method was applied to TB X-ray images and fractal signature and dimension in horizontal (FS(H), FD(H)) and vertical (FS(V), FD(V)) directions and along the roughest part of TB (FS(Sta), FD(Sta)), texture aspect ratio (Str) and signature (StrS), and mean FD (FD(MEAN)) were calculated. The VOT method was compared against an augmented Hurst orientation transform (HOT) method using paired t tests, intraclass correlation coefficients (ICCs) and coefficients of variation (CVs%). Longitudinal sensitivity to OA bone changes was not assessed. RESULTS: For the reproducibility of texture parameters, ICCs were >0.75 and CVs% were <8.2% for both methods. Compared with controls, FD(MEAN), FD(H), FD(V) and FD(Sta) for OA knees were lower (P<0.001), while Str was higher in both medial (P=0.03) and lateral (P=0.02) compartments. FS(H), FS(Sta) were lower for OA knees than for controls at sizes 0.3-0.7 mm (P<0.001) in both compartments. In lateral compartment, FS(V) for OA knees was lower than for controls at sizes 0.3-0.5 mm (P<0.001) and 0.55-0.70 mm (P<0.02), while in medial compartment at sizes 0.3-0.7 mm (P<0.001). Compared with controls, StrS for OA knees was higher at sizes 0.3, 0.55-0.70 mm in medial (P<0.03) and lateral (P<0.04) compartments. CONCLUSIONS: The VOT method is comparable to HOT method in the reproducibility of texture parameters and the ability to discriminate between non-OA and OA TB textures. However, unlike the HOT method, it quantifies texture roughness along the roughest part of the tibial bone, texture anisotropy at individual trabecular sizes and it works over a larger range of trabecular sizes. The VOT method may be a valuable tool for studying OA changes in TB.

A signature dissimilarity measure for trabecular bone texture in knee radiographs.

PURPOSE: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. METHODS: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size, anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). RESULTS: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00 - x1.35), noise associated with film graininess and quantum mottle (< 25%), blur generated by a sharp film screen, and image size (> 64 x 64 pixels). However, the measure is sensitive to changes in projection angle (> 5 degrees), image anisotropy (> 30 degrees), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND-CHARM system (64.2%). CONCLUSIONS: The SDM is well suited for the classification of TB texture images in knee OA detection and may be useful for the texture classification of medical images in general.

Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis in knee radiographs.

There is ongoing research directed towards the development of cheap and reliable decision support systems for the detection and prediction of osteoarthritis (OA) in knee joints. Fractal analysis of trabecular bone texture X-ray images is one of the most promising approaches. It is cheap and non-invasive. However, difficulties arise when the fractal signature methods are used to quantify bone roughness and anisotropy on individual scales. This is because the fractal methods are able to quantify bone texture only in the vertical and horizontal directions, and previous studies showed that OA bone changes can occur in any direction. To address these difficulties, three directional fractal signature methods were developed in this study, i.e. a fractal signature Hurst orientation transform (FSHOT) method, a variance orientation transform (VOT) method, and a blanket with rotating-grid (BRG) method. These methods were tested and the best performing method was selected. Unlike other methods, the newly developed techniques are able to calculate fractal dimensions (FDs) on individual scales (i.e. fractal signature) in all possible directions. The accuracy of the methods developed in measuring texture roughness and anisotropy on individual scales was evaluated. The effects of imaging conditions such as image noise, blur, exposure, magnification, and projection angle and the effects of translation of the bone region of interest on texture parameters were also evaluated. Computer-generated fractal surface images with known FDs and X-ray images obtained for a human tibia head were used. Results obtained show that the VOT method performs better than the FSHOT and BRG methods.

Tibio-femoral cartilage defects 3-5 years following arthroscopic partial medial meniscectomy.

OBJECTIVE: Arthroscopic partial medial meniscectomy (APMM) is a common procedure to treat a medial meniscal tear. Individuals who undergo APMM have a heightened risk of developing tibio-femoral osteoarthritis (OA). Cartilage defects scored from magnetic resonance imaging (MRI) scans predict cartilage loss over time. It is not known whether cartilage defects in the early years following APMM are more common or of greater severity than in age-matched controls. This study compared the prevalence and severity of tibio-femoral cartilage defects in patients 3-5 years post-APMM with that of age-matched controls. METHODS: Twenty-five individuals who had undergone APMM in the previous 46.9+/-5.0 months and 24 age-matched controls participated in this study. Sagittal plane knee MRI scans were acquired from the operated knees of patients and from randomly assigned knees of the controls and graded (0-4) for tibio-femoral cartilage defects. Defect prevalence (score of >or=2 for any compartment) and severity of the cartilage from both tibio-femoral compartments were compared between the groups. RESULTS: The APMM group had greater prevalence (77 vs 42%, P=0.012) and severity (4.1+/-1.9 vs 2.8+/-1.1, P=0.005) of tibio-femoral cartilage defects than controls. Age was positively associated with tibio-femoral cartilage defect severity for APMM, r=0.523, P=0.007, but not for controls, r=0.045, P=0.834. CONCLUSION: Tibio-femoral joint cartilage defects are more prevalent and of greater severity in individuals who had undergone APMM approximately 44 months earlier than in age-matched controls.

Automated selection of trabecular bone regions in knee radiographs.

Osteoarthritic (OA) changes in knee joints can be assessed by analyzing the structure of trabecular bone (TB) in the tibia. This analysis is performed on TB regions selected manually by a human operator on x-ray images. Manual selection is time-consuming, tedious, and expensive. Even if a radiologist expert or highly trained person is available to select regions, high inter- and intraobserver variabilities are still possible. A fully automated image segmentation method was, therefore, developed to select the bone regions for numerical analyses of changes in bone structures. The newly developed method consists of image preprocessing, delineation of cortical bone plates (active shape model), and location of regions of interest (ROI). The method was trained on an independent set of 40 x-ray images. Automatically selected regions were compared to the "gold standard" that contains ROIs selected manually by a radiologist expert on 132 x-ray images. All images were acquired from subjects locked in a standardized standing position using a radiography rig. The size of each ROI is 12.8 x 12.8 mm. The automated method results showed a good agreement with the gold standard [similarity index (SI) = 0.83 (medial) and 0.81 (lateral) and the offset =[-1.78, 1.27]x[-0.65,0.26] mm (medial) and [-2.15, 1.59]x[-0.58, 0.52] mm (lateral)]. Bland and Altman plots were constructed for fractal signatures, and changes of fractal dimensions (FD) to region offsets calculated between the gold standard and automatically selected regions were calculated. The plots showed a random scatter and the 95% confidence intervals were (-0.006, 0.008) and (-0.001, 0.011). The changes of FDs to region offsets were less than 0.035. Previous studies showed that differences in FDs between non-OA and OA bone regions were greater than 0.05. ROIs were also selected by a second radiologist and then evaluated. Results indicated that the newly developed method could replace a human operator and produces bone regions with an accuracy that is sufficient for fractal analyses of bone texture.

Automated classification of articular cartilage surfaces based on surface texture.

In this study the automated classification system previously developed by the authors was used to classify articular cartilage surfaces with different degrees of wear. This automated system classifies surfaces based on their texture. Plug samples of sheep cartilage (pins) were run on stainless steel discs under various conditions using a pin-on-disc tribometer. Testing conditions were specifically designed to produce different severities of cartilage damage due to wear. Environmental scanning electron microscope (SEM) (ESEM) images of cartilage surfaces, that formed a database for pattern recognition analysis, were acquired. The ESEM images of cartilage were divided into five groups (classes), each class representing different wear conditions or wear severity. Each class was first examined and assessed visually. Next, the automated classification system (pattern recognition) was applied to all classes. The results of the automated surface texture classification were compared to those based on visual assessment of surface morphology. It was shown that the texture-based automated classification system was an efficient and accurate method of distinguishing between various cartilage surfaces generated under different wear conditions. It appears that the texture-based classification method has potential to become a useful tool in medical diagnostics.

Analysis of trabecular bone texture by modified Hurst orientation transform method.

There is a growing need for noninvasive and inexpensive methods that can effectively be used on a large scale, to detect an onset of early osteoarthritis in human knee joints. Of many possible options, fractal analysis of two-dimensional projection x-ray images of trabecular bone (TB) texture, appears as one of the best approaches. However, there are some problems associated with the characterization of the roughness and anisotropy of the bone texture. To resolve these problems, a modified Hurst orientation transform (HOT) method, previously developed by the authors, has been used in this study. The advantages of the HOT method over other techniques used to analyze bone texture, are that it calculates a two-dimensional fractal dimension in all possible directions and also provides a measure of anisotropy for both surfaces exhibiting strong anisotropy and surfaces exhibiting weak anisotropy. In this study, the accuracy of the HOT method in measuring the bone texture roughness and anisotropy; together with the effects of image noise, blur, exposure, magnification, and projection angle on its performance were investigated. Computer-generated images of fractal surfaces and x-ray images obtained for a human tibia head were used. Results obtained show that the HOT method can effectively be used to characterize the roughness and anisotropy (isotropy) of TB texture.

Analysis of wear particle boundaries found in sheep knee joints during in vitro wear tests without muscle compensation.

Pair of sheep knee joints were used in the experiments. One of the joints was worn in a simulator over different periods of time under carefully simulated physiological forces and kinematic cycles while the other, 'control joint', was kept intact for comparison. Wear particles were extracted from a synovial fluid from both the worn and unworn sheep joints by a ferrography technique and then examined in a scanning electron microscope (SEM). The shape of the particles was characterized by boundary fractal dimension, shape factor and convexity. The shape parameters obtained for particle populations were statistically compared using a Wilcoxon rank test. It has been found that subtle changes in the shape of the particle boundary occur during the wear process. Studying the changes in wear particle boundaries provides important information about the cause and progression of wear in synovial joints.

Directional fractal signature methods for trabecular bone texture in hand radiographs: data from the Osteoarthritis Initiative.

PURPOSE: To develop directional fractal signature methods for the analysis of trabecular bone (TB) texture in hand radiographs. Problems associated with the small size of hand bones and the orientation of fingers were addressed. METHODS: An augmented variance orientation transform (AVOT) and a quadrant rotating grid (QRG) methods were developed. The methods calculate fractal signatures (FSs) in different directions. Unlike other methods they have the search region adjusted according to the size of bone region of interest (ROI) to be analyzed and they produce FSs defined with respect to any chosen reference direction, i.e., they work for arbitrary orientation of fingers. Five parameters at scales ranging from 2 to 14 pixels (depending on image size and method) were derived from rose plots of Hurst coefficients, i.e., FS in dominating roughness (FSSta), vertical (FSV) and horizontal (FSH) directions, aspect ratio (StrS), and direction signatures (StdS), respectively. The accuracy in measuring surface roughness and isotropy/anisotropy was evaluated using 3600 isotropic and 800 anisotropic fractal surface images of sizes between 20 × 20 and 64 × 64 pixels. The isotropic surfaces had FDs ranging from 2.1 to 2.9 in steps of 0.1, and the anisotropic surfaces had two dominating directions of 30° and 120°. The methods were used to find differences in hand TB textures between 20 matched pairs of subjects with (cases: approximate Kellgren-Lawrence (KL) grade ≥ 2) and without (controls: approximate KL grade <2) radiographic hand osteoarthritis (OA). The OA Initiative public database was used and 20 × 20 pixel bone ROIs were selected on 5th distal and middle phalanges. The performance of the AVOT and QRG methods was compared against a variance orientation transform (VOT) method developed earlier [M. Wolski, P. Podsiadlo, and G. W. Stachowiak, "Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis in knee radiographs," Proc. Inst. Mech. Eng., Part H 223, 211-236 (2009)]. RESULTS: The AVOT method correctly quantified the isotropic and anisotropic surfaces for all image sizes and scales. Values of FSSta were significantly different (P < 0.05) between the isotropic surfaces. Using the VOT and QRG methods no differences were found at large scales for the isotropic surfaces that are smaller than 64 × 64 and 48 × 48 pixels, respectively, and at some scales for the anisotropic surfaces with size 48 × 48 pixels. Compared to controls, using the AVOT and QRG methods the authors found that OA TB textures were less rough (P < 0.05) in the dominating and horizontal directions (i.e., lower FSSta and FSH), rougher in the vertical direction (i.e., higher FSV) and less anisotropic (i.e., higher StrS) than controls. No differences were found using the VOT method. CONCLUSIONS: The AVOT method is well suited for the analysis of bone texture in hand radiographs and it could be potentially useful for early detection and prediction of hand OA.

Differences in trabecular bone texture between knees with and without radiographic osteoarthritis detected by fractal methods.

OBJECTIVE: To develop an accurate method for quantifying differences in the trabecular structure in the tibial bone between subjects with and without knee osteoarthritis (OA). METHODS: Standard knee radiographs were taken from 26 subjects (seven women) with meniscectomy and radiographic OA Kellgren & Lawrence grade 2 or worse in the medial compartment. Each case knee was individually matched by sex, age, body mass index and medial or lateral compartment with a control knee. A newly developed augmented Hurst orientation transform (HOT) method was used to calculate texture parameters for regions selected in X-ray images of non-OA and OA tibial bones. This method produces a mean value of fractal dimensions (FD MEAN), FDs in the vertical (FDV) and horizontal (FDH) directions and along a direction of the roughest part of the tibial bone (FDSta), fractal signatures and a texture aspect ratio (Str). The ratio determines a degree of the bone texture anisotropy. Reproducibility was calculated using an intraclass correlation coefficient (ICC). Comparisons between cases and controls were made with paired t tests. The performance of the HOT method was evaluated against a benchmark fractal signature analysis (FSA) method. RESULTS: Compared with controls, trabecular bone in OA knees showed significantly lower FD MEAN, FDV, FDH and FDSta and higher Str at trabecular image sizes 0.2-1.1mm (P<0.05, HOT). The reproducibility of all parameters was very good (ICC>0.8). In the medial compartment, fractal signatures calculated for OA horizontal and vertical trabeculae were significantly lower at sizes 0.3-0.55 mm (P<0.05, HOT) and 0.3-0.65 mm (P<0.001, FSA). In the lateral compartment, FDs calculated for OA trabeculae were lower than controls (horizontal: 0.3-0.55 mm (P<0.05, HOT) and 0.3-0.65 mm (P<0.001, FSA); vertical: 0.3-0.4mm (P<0.05, HOT) and 0.3-0.35 mm (P<0.001, FSA). CONCLUSION: The augmented HOT method produces fractal signatures that are comparable to those obtained from the benchmark FSA method. The HOT method provides a more detailed description of OA changes in bone anisotropy than the FSA method. This includes a degree of bone anisotropy measured using data from all possible directions and a texture roughness calculated for the roughest part of the bone. It appears that the augmented HOT method is well suited to quantify OA changes in the tibial bone structure.

A rig for acquisition of standardized trabecular bone radiographs.

To assess osteoarthritic changes in knee joints a radiography rig for acquisition of standardized radiographs of trabecular bone has been developed. The rig contains a steel frame on castors, a turntable, a cassette holder frame, calibration Plexiglas sheets, body supports and points. It is used to lock the patient in a standardized position. A film cassette holder frame was also developed to reduce scattering of X-rays, and consequently the amount of noise in the radiographs. Calibration Plexiglas sheets were mounted on ball bearing slides to obtain radiographs without a calibration pattern (suitable for the analysis of trabecular bone texture) and radiographs containing a calibration pattern (suitable for the measurement of leg alignment).

Shape of wear particles found in human knee joints and their relationship to osteoarthritis.

OBJECTIVE: To analyse and compare the shape of wear particles found in healthy and osteoarthritic human knee joints for monitoring the progress of osteoarthritis, the long-term prognosis and to evaluate therapeutic regimens. METHOD: Joint particles from seven patients with normal cartilage in all compartments of the knee joint, 12 patients with fibrillation of less than half the cartilage thickness (grade 1), seven patients with fibrillation of more than half the cartilage thickness (grade 2) and four patients with erosions down to bone (grade 3) were analysed. A total of 565 particles were extracted from synovial fluid samples by ferrography and analysed in a scanning electron microscope. A number of numerical descriptors, i.e. boundary fractal dimension, shape factor, convexity and elongation, were calculated for each particle image and correlated to the degree of osteoarthritis using non-parametric tests. RESULTS: Experiments demonstrated that there were significant differences between the numerical descriptors calculated for wear particles from healthy and osteoarthritic knee joints (P < 0.01), suggesting that the particle shape can be used as an indicator of the joint condition. In particular, the fractal dimension of the particle boundary was shown to correlate directly with the degree of osteoarthritis. CONCLUSION: Numerical analysis of the shape of wear particles found in human knee joints may provide a reliable means for the assessment of cartilage repair after surgical or conservative treatment of osteoarthritis.