Quantification of differences in bone texture from plain radiographs in knees with and without osteoarthritis

Short-term variations in trabecular bone texture parameters associated to radio-clinical biomarkers improve the prediction of radiographic knee osteoarthritis progression

The present study aims to examine whether the short-term variations in trabecular bone texture (TBT) parameters, combined with a targeted set of clinical and radiographic data, would improve the prediction of long-term radiographic knee osteoarthritis (KOA) progression. Longitudinal (baseline, 24 and 48-month) data, obtained from the Osteoarthritis Initiative cohort, were available for 1352 individuals, with preexisting OA (1 < Kellgren-Lawrence < 4) at baseline. KOA progression was defined as an increase in the medial joint space narrowing score from the 24-months to the 48-months control point. 16 regions of interest were automatically selected from each radiographic knee and analyzed using fractal dimension. Variations from baseline to 24 months in TBT descriptors as well as selected radiographic and clinical readings were calculated. Different logistic regression models were developed to evaluate the progression prediction performance when associating TBT variations with the selected clinical and radiographic readings. The most predictive model was mainly determined using the area under the receiver operating characteristic curve (AUC). The proposed prediction model including short-term variations in TBT parameters, associated with clinical covariates and radiographic scores, improved the capacity of predicting long-term radiographic KOA progression (AUC of 0.739), compared to models based solely on baseline values (AUC of 0.676, p-value < 0.008).

A fully automatic target detection and quantification strategy based on object detection convolutional neural network YOLOv3 for one-step X-ray image grading

Methods for automatic image analysis are demanded for dealing with the explosively increased imaging data in clinics. Osteoarthritis (OA) is a typical disease diagnosed based on X-ray imaging. Herein, we propose a novel modeling strategy based on YOLO version 3 (YOLOv3) for automatic simultaneous localization of knee joints and quantification of radiographic knee OA. As an advanced deep convolutional neural network (CNN) algorithm for target detection, YOLOv3 enables simultaneous small object detection and quantification due to its unique residual connection and feature map merging. Hence, a unified CNN model is built for the elegant integration of knee joint detection and corresponding OA severity grading using the YOLOv3 framework. We achieve desirable accuracy in knee OA grading using the public and clinical datasets. It provides improvements in the precision, recall, F₁ score and diagnostic accuracy of knee OA as well. Because of the fully automatic target detection and quantification, the time of handling an image is merely 40 ms from inputting the image to getting its label, supporting quick clinic decisions. It, thus, affords convenient and efficient image analysis for daily clinical diagnosis.

Trabecular bone texture analysis of conventional radiographs in the assessment of knee osteoarthritis: review and viewpoint

BACKGROUND

Trabecular bone texture analysis (TBTA) has been identified as an imaging biomarker that provides information on trabecular bone changes due to knee osteoarthritis (KOA). Consequently, it is important to conduct a comprehensive review that would permit a better understanding of this unfamiliar image analysis technique in the area of KOA research. We examined how TBTA, conducted on knee radiographs, is associated to (i) KOA incidence and progression, (ii) total knee arthroplasty, and (iii) KOA treatment responses. The primary aims of this study are twofold: to provide (i) a narrative review of the studies conducted on radiographic KOA using TBTA, and (ii) a viewpoint on future research priorities.

METHOD

Literature searches were performed in the PubMed electronic database. Studies published between June 1991 and March 2020 and related to traditional and fractal image analysis of trabecular bone texture (TBT) on knee radiographs were identified.

RESULTS

The search resulted in 219 papers. After title and abstract scanning, 39 studies were found eligible and then classified in accordance to six criteria: cross-sectional evaluation of osteoarthritis and non-osteoarthritis knees, understanding of bone microarchitecture, prediction of KOA progression, KOA incidence, and total knee arthroplasty and association with treatment response. Numerous studies have reported the relevance of TBTA as a potential bioimaging marker in the prediction of KOA incidence and progression. However, only a few studies have focused on the association of TBTA with both OA treatment responses and the prediction of knee joint replacement.

CONCLUSION

Clear evidence of biological plausibility for TBTA in KOA is already established. The review confirms the consistent association between TBT and important KOA endpoints such as KOA radiographic incidence and progression. TBTA could provide markers for enrichment of clinical trials enhancing the screening of KOA progressors. Major advances were made towards a fully automated assessment of KOA.

Machine learning classification on texture analyzed T2 maps of osteoarthritic cartilage: oulu knee osteoarthritis study

OBJECTIVE

To introduce local binary pattern (LBP) texture analysis to cartilage osteoarthritis (OA) research and compare the performance of different classification systems in discrimination of OA subjects from healthy controls using gray-level co-occurrence matrix (GLCM) and LBP texture data. Classification algorithms were used to reduce the dimensionality of texture data into a likelihood of subject belonging to the reference class.

METHOD

T2 relaxation time mapping with multi-slice multi-echo spin echo sequence was performed for eighty symptomatic OA patients and 63 asymptomatic controls on a 3T clinical MRI scanner. Relaxation time maps were subjected to GLCM and LBP texture analysis, and classification algorithms were deployed with an in-house developed software. Implemented algorithms were K nearest neighbors, support vector machine, and neural network classifier.

RESULTS

LBP and GLCM discerned OA patients from controls with a significant difference in all studied regions. Classification models comprising GLCM and LBP showed high accuracy in classing OA patients and controls. The best performance was obtained with a multilayer perceptron type classifier with an overall accuracy of 90.2 %.

CONCLUSION

LBP texture analysis complements prior results with GLCM, and together LBP and GLCM serve as significant input data for classification algorithms trained for OA assessment. Presented algorithms are adaptable to versatile OA evaluations also for future gradational or predictive approaches.

Sclerotic lesions of the femoral head-neck junction for diagnosis of femoroacetabular impingement

The morphological characteristics associated with a diagnosis of femoroacetabular impingement (FAI) observed on plain radiographs can also be seen in subjects without hip joint symptoms. Therefore, the purpose of this study was to investigate whether sclerotic lesions on femoral head-neck junction (FHNJ) could be used as a supplemental diagnostic feature. A total of 128 hips from 119 patients (43 male and 76 female) diagnosed with FAI and 24 hips from 21 patients (2 male and 19 female) with other hip pathologies as control were compared in this study. Using standing frog-leg plain radiographs, the prevalence of sclerotic lesions on the FHNJ was established. Additionally, the pixel intensity (PI) of the sclerotic lesions between the FAI and the control groups were quantitatively compared. Sclerotic lesions were present in 96.1% of FAI hips (123 of 128) and only 37.5% of control hips (9 of 24) (p < 0.05). The ratio of PI in the FAI group was significantly higher (approximately 10%) than in the control group (p < 0.05). The evaluation of sclerotic lesions may be used as a supplement to aid in the diagnosis of FAI.

Deep learning for early detection of pathological changes in X-ray bone microstructures: case of osteoarthritis

Texture features are designed to quantitatively evaluate patterns of spatial distribution of image pixels for purposes of image analysis and interpretation. Unexplained variations in the texture patterns often lead to misinterpretation and undesirable consequences in medical image analysis. In this paper we explore the ability of machine learning (ML) methods to design a radiology test of Osteoarthritis (OA) at early stage when the number of patients’ cases is small. In our experiments we use high-resolution X-ray images of knees in patients which were identified with Kellgren–Lawrence scores progressing from 1. The existing ML methods have provided a limited diagnostic accuracy, whilst the proposed Group Method of Data Handling strategy of Deep Learning has significantly extended the diagnostic test. The comparative experiments demonstrate that the proposed framework using the Zernike-based texture features has significantly improved the diagnostic accuracy on average by 11%. This allows us to conclude that the designed model for early diagnostic of OA will provide more accurate radiology tests, although new study is required when a large number of patients’ cases will be available.

Quantitative Ultrasound Texture Analysis to Assess the Spastic Muscles in Stroke Patients

This study aimed to investigate the feasibility of sonoelastography for determining echotexture in post-stroke patients. Moreover, the relationships of muscle echotexture features, muscle stiffness, and functional performance in spastic muscle were explored. The study population comprised 22 males with stroke. The echotexture features (entropy and energy) of the biceps brachii muscles (BBM) in both arms were extracted by local binary pattern (LBP) from ultrasound images, whereas the stiffness of BBM was assessed by shear wave velocity (SWV) in the transverse and longitudinal planes. The Fugl–Meyer assessment (FMA) was used to assess the functional performance of the upper arm. The results showed that echotexture was more inhomogeneous in the paretic BBM than in the non-paretic BBM. SWV was significantly faster in paretic BBM than in non-paretic BBM. Both echotexture features were significantly correlated with SWV in the longitudinal plane. The feature of energy was significantly negatively correlated with FMA in the longitudinal plane and was significantly positively correlated with the duration from stroke onset in the transverse plane. The echotexture extracted by LBP may be a promising approach for quantitative assessment of the spastic BBM in post-stroke patients.

Predicting ventricular tachyarrhythmia in patients with systolic heart failure based on texture features of the gray zone from contrast-enhanced magnetic resonance imaging

BACKGROUND

Previous research showed that gray zone detected by late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) imaging could help identify high-risk patients. In this study, we investigated whether LGE-CMR gray zone heterogeneity measured by image texture features could predict cardiovascular events in patients with heart failure (HF).

METHOD

This is a retrospective cohort study. Patients with systolic HF undergoing CMR imaging were enrolled. Cine and LGE images were analyzed to derive left ventricular (LV) function and scar characteristics. Entropy and uniformity of gray zones were derived by texture analysis.

RESULTS

A total of 82 systolic HF patients were enrolled. After a median 1021 (25%-75% quartiles, 205-2066) days of follow-up, the entropy (0.60 ± 0.260 vs. 0.87 ± 0.28, p = 0.013) was significantly increased while the uniformity (0.68 ± 0.14 vs. 0.53±0.15, p = 0.016) was significantly decreased in patients with ventricular tachycardia or ventricular fibrillation (VT/VF). The percentage of core scar (21.9 ± 10.6 vs. 30.6 ± 10.4, p = 0.029) was higher in cardiac mortality group than survival group while the uniformity (0.55 ± 0.17 vs. 0.67 ± 0.14, p = 0.018) was lower in cardiac mortality group than survival group. A multivariate Cox regression model showed that higher percentage of gray zone area (HR = 8.805, 1.620-47.84, p = 0.045), higher entropy (>0.85) (HR = 1.391, 1.092-1.772, p = 0.024) and lower uniformity (≦0.54) (HR = 0.535, 0.340-0.842, p = 0.022) were associated with VT/VF attacks. Also, higher percentage of gray zone area (HR = 5.716, 1.379-23.68, p = 0.017), core scar zone (HR = 1.939, 1.056-3.561, p = 0.025), entropy (>0.85) (HR = 1.434, 1.076-1.911, p = 0.008) and lower uniformity (≦0.54) (HR = 0.513, 0.296-0.888, p = 0.009) were associated with cardiac mortality during follow-up.

CONCLUSIONS

Gray zone heterogeneity by texture analysis method could provide additional prognostic value to traditional LGE-CMR substrate analysis method.

Adaptive segmentation of knee radiographs for selecting the optimal ROI in texture analysis

OBJECTIVE

The purposes of this study were to investigate: 1) the effect of placement of region-of-interest (ROI) for texture analysis of subchondral bone in knee radiographs, and 2) the ability of several texture descriptors to distinguish between the knees with and without radiographic osteoarthritis (OA).

DESIGN

Bilateral posterior-anterior knee radiographs were analyzed from the baseline of Osteoarthritis Initiative (OAI) (9012 knee radiographs) and Multicenter Osteoarthritis Study (MOST) (3,644 knee radiographs) datasets. A fully automatic method to locate the most informative region from subchondral bone using adaptive segmentation was developed. Subsequently, we built logistic regression models to identify and compare the performances of several texture descriptors and each ROI placement method using 5-fold cross validation. Importantly, we also investigated the generalizability of our approach by training the models on OAI and testing them on MOST dataset. We used area under the receiver operating characteristic curve (ROC AUC) and average precision (AP) obtained from the precision-recall (PR) curve to compare the results.

RESULTS

We found that the adaptive ROI improves the classification performance (OA vs non-OA) over the commonly-used standard ROI (up to 9% percent increase in AUC). We also observed that, from all texture parameters, Local Binary Pattern (LBP) yielded the best performance in all settings with the best AUC of 0.840 [0.825, 0.852] and associated AP of 0.804 [0.786, 0.820].

CONCLUSION

Compared to the current state-of-the-art approaches, our results suggest that the proposed adaptive ROI approach in texture analysis of subchondral bone can increase the diagnostic performance for detecting the presence of radiographic OA.

Mkx-Deficient Mice Exhibit Hedgehog Signaling-Dependent Ectopic Ossification in the Achilles Tendons

Heterotopic ossification is the abnormal formation of mineralized bone in skin, muscle, tendon, or other soft tissues. Tendon ossification often occurs from acute tendon injury or chronic tendon degeneration, for which current treatment relies heavily on surgical removal of the ectopic bony tissues. Unfortunately, surgery creates additional trauma, which often causes recurrence of heterotopic ossification. The molecular mechanisms of heterotopic ossification are not well understood. Previous studies demonstrate that Mkx is a transcription factor crucial for postnatal tendon fibril growth. Here we report that Mkx^-/- mutant mice exhibit ectopic ossification in the Achilles tendon within 1 month after birth and the tendon ossification deteriorates with age. Genetic lineage labeling revealed that the tendon ossification in Mkx^-/- mice resulted from aberrant differentiation of tendon progenitor cells. Furthermore, tissue-specific inactivation of Mkx in tendon cells postnatally resulted in a similar ossification phenotype, indicating that Mkx plays a key role in tendon tissue homeostasis. Moreover, we show that Hedgehog signaling is ectopically activated at early stages of tendon ossification and that tissue-specific inactivation of Smoothened, which encodes the obligatory transducer of Hedgehog signaling, in the tendon cell lineage prevented or dramatically reduced tendon ossification in Mkx^-/- mice. Together, these studies establish a new genetic mouse model of tendon ossification and provide new insight into its pathogenic mechanisms. © 2018 American Society for Bone and Mineral Research.

Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis

Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and to compare the differences in bone characteristics between controls and subjects with knee osteoarthritis or medial tibial bone marrow lesions (BMLs). Tibial bone density and texture was evaluated from radiographs with both minimal and clinical post-processing in 109 subjects with and without osteoarthritis. Bone texture was evaluated using fractal signature analysis. Significant correlations (p < 0.001) were found in all regions (between 0.94 and 0.97) for calibrated bone density between radiographs with minimal and clinical post-processing. Correlations varied between 0.51 and 0.97 (p < 0.001) for FD_Ver texture parameter and between − 0.10 and 0.97 for FD_Hor. Bone density and texture were different (p < 0.05) between controls and subjects with osteoarthritis or BMLs mainly in medial tibial regions. When classifying healthy and osteoarthritic subjects using a machine learning-based elastic net model with bone characteristics, area under the receiver operating characteristics (ROCAUC) curve was 0.77. For classifying controls and subjects with BMLs, ROCAUC was 0.85. In conclusion, differences in bone density and texture can be assessed from knee radiographs when using minimal post-processing.

Comparison of bone texture between normal individuals and patients with Kashin-Beck disease from plain radiographs in knee

To compare tibial bone texture between Kashin-Beck disease (KBD) patients and normal individuals from plain radiographs using an advanced image analysis. Plain knee radiographs were obtained from KBD patients (n = 49) and age-matched healthy controls (n = 98). KBD were graded with diagnostic criteria WS/T 207-2010. The textural values related to bone structure from medial and lateral tibial subchondral and trabecular bones were evaluated using entropy of Laplacian-based image (E_Lap), entropy of local binary patterns (E_LBP), homogeneity indices (HI) of local angles (HI_Mean, HI_Perp and HI_Paral), and fractal dimensions from horizontal (FD_Hor) and vertical (FD_Ver) structures. KBD patients were shorter in height and lighter in weight, and their tibial width was wider than controls. Anatomical angle of KBD patients showed more genu valgus. Total KBD patients and subgroups had higher E_Lap, HI_Mean, HI_Perp and HI_Paral in detected tibial subchondral and trabecular bones than controls, except E_Lap in lateral subchondral bone. E_LBP, FD_Hor and FD_Ver from the detected tibial bone in KBD patients and subgroups were lower than controls, except FD_Ver in lateral trabecular bone. Our results indicate that micro-scale in bone texture in KBD-affected knees can be quantitatively examined from plain radiographs using an advanced image analysis.

Association between radiography-based subchondral bone structure and MRI-based cartilage composition in postmenopausal women with mild osteoarthritis

OBJECTIVE

Our aim was to investigate the relation between radiograph-based subchondral bone structure and cartilage composition assessed with delayed gadolinium enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T₂ relaxation time.

DESIGN

Ninety-three postmenopausal women (Kellgren-Lawrence grade 0: n = 13, 1: n = 26, 2: n = 54) were included. Radiograph-based bone structure was assessed using entropy of the Laplacian-based image (E_Lap) and local binary patterns (E_LBP), homogeneity indices of the local angles (HI_Angles,mean, HI_Angles,Perp, HI_Angles,Paral), and horizontal (FD_Hor) and vertical fractal dimensions (FD_Ver). Mean dGEMRIC index and T₂ relaxation time of tibial cartilage were calculated to estimate cartilage composition.

RESULTS

HI_Angles,mean (r_s = -0.22) and HI_Angles,Paral (r_s = -0.24) in medial subchondral bone were related (P < 0.05) to dGEMRIC index of the medial tibial cartilage. E_Lap (r_s = -0.23), FD_Hor,0.34 mm (r = 0.21) and FD_Ver,0.68 mm (r = 0.24) in medial subchondral bone were related (P < 0.05) to T₂ relaxation time values of the medial tibial cartilage. FD_Hor at different scales in lateral subchondral bone were related (P < 0.01) to dGEMRIC index (r = 0.29-0.41) and T₂ values of lateral tibial cartilage (r = -0.28 to -0.36). FD_Ver at larger scales were related (P < 0.05) to dGEMRIC index (r = 0.24-0.25) and T₂ values of lateral tibial cartilage (r = -0.21). HI_Angles,Paral (r = -0.25) and FD_Ver,0.68 mm (r_s = 0.22) in the lateral tibial trabecular bone were related (P < 0.05) to dGEMRIC index of the lateral tibial cartilage.

CONCLUSION

Our results support the presumption that several tissues are affected in the early osteoarthritis (OA). Furthermore, they indicate that the detailed analysis of radiographs may serve as a complementary imaging tool for OA studies.

Subchondral bone in osteoarthritis: association between MRI texture analysis and histomorphometry

OBJECTIVE

Magnetic resonance imaging (MRI) texture analysis is a method of analyzing subchondral bone alterations in osteoarthritis (OA). The objective of this study was to evaluate the association between MR texture analysis and ground-truth subchondral bone histomorphometry at the tibial plateau.

DESIGN

The local research ethics committee approved the study. All subjects provided written, informed consent. This was a cross-sectional study carried out at our institution between February and August 2014. Ten participants aged 57-84 with knee OA scheduled for total knee arthroplasty (TKA) underwent pre-operative MRI of the symptomatic knee at 3T using a high spatial-resolution coronal T1 weighted sequence. Tibial plateau explants obtained at the time of TKA underwent histological preparation to allow calculation of bone volume fraction (BV.TV), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp) and trabecular number (Tb.N). Texture analysis was performed on the tibial subchondral bone of MRI images matched to the histological sections. Regression models were created to assess the association of texture analysis features with BV.TV, Tb.Th, Tb.Sp and Tb.N.

RESULTS

MRI texture features were significantly associated with BV.TV (R² = 0.76), Tb.Th (R² = 0.47), Tb.Sp (R² = 0.75) and Tb.N (R² = 0.60, all P < 0.001). Simple gray-value histogram based texture features demonstrated the highest standardized regression coefficients for each model.

CONCLUSION

MRI texture analysis features were significantly associated with ground-truth subchondral bone histomorphometry at the tibial plateau.

Differences in tibial subchondral bone structure evaluated using plain radiographs between knees with and without cartilage damage or bone marrow lesions - the Oulu Knee Osteoarthritis study

Objectives

To investigate whether subchondral bone structure from plain radiographs is different between subjects with and without articular cartilage damage or bone marrow lesions (BMLs).

Methods

Radiography-based bone structure was assessed from 80 subjects with different stages of knee osteoarthritis using entropy of Laplacian-based image (E_Lap) and local binary patterns (E_LBP), homogeneity index of local angles (HI_Angles,mean), and horizontal (FD_Hor) and vertical fractal dimensions (FD_Ver). Medial tibial articular cartilage damage and BMLs were scored using the magnetic resonance imaging osteoarthritis knee score. Level of statistical significance was set to p < 0.05.

Results

Subjects with medial tibial cartilage damage had significantly higher FD_Ver and E_LBP as well as lower E_Lap and HI_Angles,mean in the medial tibial subchondral bone region than subjects without damage. FD_Hor, FD_Ver, and E_LBP were significantly higher, whereas E_Lap and HI_Angles,mean were lower in the medial trabecular bone region. Subjects with medial tibial BMLs had significantly higher FD_Ver and E_LBP as well as lower E_Lap and HI_Angles,mean in medial tibial subchondral bone. FD_Hor, FD_Ver, and E_LBP were higher, whereas E_Lap and HI_Angles,mean were lower in medial trabecular bone.

Conclusions

Our results support the use of bone structural analysis from radiographs when examining subjects with osteoarthritis or at risk of having it.

Key points

• Knee osteoarthritis causes changes in articular cartilage and subchondral bone

• Magnetic resonance imaging is a comprehensive imaging modality for knee osteoarthritis

• Radiography-based bone structure analysis can provide additional information of osteoarthritic subjects

Association between subchondral bone structure and osteoarthritis histopathological grade

Despite increasing evidence that subchondral bone contributes to osteoarthritis (OA) pathogenesis, little is known about local changes in bone structure compared to cartilage degeneration. This study linked structural adaptation of subchondral bone with histological OA grade. Twenty-five osteochondral samples of macroscopically different degeneration were prepared from tibiae of 14 patients. Samples were scanned with micro-computed tomography (μCT) and both conventional structural parameters and novel 3D parameters based on local patterns were analyzed from the subchondral plate and trabecular bone. Subsequently, samples were processed for histology and evaluated for OARSI grade. Each bone parameter and OARSI grade was compared to assess structural adaptation of bone with OA severity. In addition, thicknesses of cartilage, calcified cartilage, and subchondral plate were analyzed from histological sections and compared with subchondral bone plate thickness from μCT. With increasing OARSI grade, the subchondral plate became thicker along with decreased specific bone surface, while there was no change in tissue mineral density. Histological analysis showed that subchondral plate thickness from μCT also includes calcified cartilage. Entropy of local patterns increased with OA severity, reflecting higher tissue heterogeneity. In the trabecular compartment, bone volume fraction and both trabecular thickness and number increased with OARSI grade while trabecular separation and structure model index decreased. Also, elevation of local patterns became longitudinal in the subchondral plate and axial transverse in trabecular bone with increasing OARSI grade. This study demonstrates the possibility of radiological assessment of OA severity by structural analysis of bone. © 2016 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. J Orthop Res 35:785-792, 2017.

Subchondral bone histology and grading in osteoarthritis

Objective

Osteoarthritis (OA) has often regarded as a disease of articular cartilage only. New evidence has shifted the paradigm towards a system biology approach, where also the surrounding tissue, especially bone is studied more vigorously. However, the histological features of subchondral bone are only poorly characterized in current histological grading scales of OA. The aim of this study is to specifically characterize histological changes occurring in subchondral bone at different stages of OA and propose a simple grading system for them.

Design

20 patients undergoing total knee replacement surgery were randomly selected for the study and series of osteochondral samples were harvested from the tibial plateaus for histological analysis. Cartilage degeneration was assessed using the standardized OARSI grading system, while a novel four-stage grading system was developed to illustrate the changes in subchondral bone. Subchondral bone histology was further quantitatively analyzed by measuring the thickness of uncalcified and calcified cartilage as well as subchondral bone plate. Furthermore, internal structure of calcified cartilage-bone interface was characterized utilizing local binary patterns (LBP) based method.

Results

The histological appearance of subchondral bone changed drastically in correlation with the OARSI grading of cartilage degeneration. As the cartilage layer thickness decreases the subchondral plate thickness and disorientation, as measured with LBP, increases. Calcified cartilage thickness was highest in samples with moderate OA.

Conclusion

The proposed grading system for subchondral bone has significant relationship with the corresponding OARSI grading for cartilage. Our results suggest that subchondral bone remodeling is a fundamental factor already in early stages of cartilage degeneration.

Quantitative imaging methods in osteoporosis

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

Serum Collagen Type II Cleavage Epitope and Serum Hyaluronic Acid as Biomarkers for Treatment Monitoring of Dogs with Hip Osteoarthritis

The aim of this study was to evaluate the use of serum type II collagen cleavage epitope and serum hyaluronic acid as biomarkers for treatment monitoring in osteoarthritic dogs. For this purpose, a treatment model based on mesenchymal stem cells derived from adipose tissue combined with plasma rich in growth factors was used. This clinical study included 10 dogs with hip osteoarthritis. Both analytes were measured in serum at baseline, just before applying the treatment, and 1, 3, and 6 months after treatment. These results were compared with those obtained from force plate analysis using the same animals during the same study period. Levels of type II collagen cleavage epitope decreased and those of hyaluronic acid increased with clinical improvement objectively verified via force plate analysis, suggesting these two biomarkers could be effective as indicators of clinical development of joint disease in dogs.

Osteoarthritis year in review 2015: imaging

PURPOSE

This narrative review covers original publications related to imaging in osteoarthritis (OA) published in English between 1 April 2014 and 30 April 2015. Novel lessons relating to imaging are described.

METHODS

An extensive PubMed database search was performed based on, but not limited to the terms "OA" in combination with "Magnetic resonance imaging (MRI)", "Imaging", "Radiography", "Ultrasound", "Computed tomography (CT)" and "Nuclear medicine" to extract relevant studies. In vitro data and animal studies were excluded. This review focuses on the new developments and observations based on the aforementioned imaging modalities, as well as a 'whole-organ' approach by presenting findings from different tissues (bone, meniscus, synovium, muscle and fat) and joints (hip, lumbar spine and hand).

RESULTS AND CONCLUSIONS

Over the past year, studies using imagine have made a major contribution to the understanding of the pathogenesis of OA. Significant work has continued at the knee, with MRI now being increasingly used to assess structural endpoints in clinical trials. This offers the exciting opportunity to explore potential disease modifying OA therapies. There has been a clear interest in the role of bone in the pathogenesis of OA. There is now a growing body of literature examining the pathogenesis of OA at the hip, lumbar spine and hand. The future of imaging in OA offers the exciting potential to better understand the disease process across all joints and develop more effective preventive and therapeutic interventions.

Correlation of Subchondral Bone Density and Structure from Plain Radiographs with Micro Computed Tomography Ex Vivo

Osteoarthritis causes changes in the subchondral bone structure and composition. Plain radiography is a cheap, fast, and widely available imaging method. Bone tissue can be well seen from plain radiograph, which however is only a 2D projection of the actual 3D structure. Therefore, the aim was to investigate the relationship between bone density- and structure-related parameters from 2D plain radiograph and 3D bone parameters assessed from micro computed tomography (µCT) ex vivo. Right tibiae from eleven cadavers without any diagnosed joint disease were imaged using radiography and with µCT. Bone density- and structure-related parameters were calculated from four different locations from the radiographs of proximal tibia and compared with the volumetric bone microarchitecture from the corresponding regions. Bone density from the plain radiograph was significantly related with the bone volume fraction (r = 0.86; n = 44; p < 0.01). Mean homogeneity index for orientation of local binary patterns (HI_angle,mean) and fractal dimension of vertical structures (FD_Ver) were related (p < 0.01) with connectivity density (HI_angle,mean: r = −0.73, FD_Ver: r = 0.69) and trabecular separation (HI_angle,mean: r = 0.73, FD_Ver: r = −0.70) when all ROIs were pooled together (n = 44). Bone density and structure in tibia from standard clinically available 2D radiographs are significantly correlated with true 3D microstructure of bone.