Independent evaluation of a multi-view multi-task convolutional neural network breast cancer classification model using Finnish mammography screening data.

BACKGROUND: Development of deep convolutional neural networks for breast cancer classification has taken significant steps towards clinical adoption. It is though unclear how the models perform for unseen data, and what is required to adapt them to different demographic populations. In this retrospective study, we adopt an openly available pre-trained mammography breast cancer multi-view classification model and evaluate it by utilizing an independent Finnish dataset. METHODS: Transfer learning was used, and the pre-trained model was finetuned with 8,829 examinations from the Finnish dataset (4,321 normal, 362 malignant and 4,146 benign examinations). Holdout dataset with 2,208 examinations from the Finnish dataset (1,082 normal, 70 malignant and 1,056 benign examinations) was used in the evaluation. The performance was also evaluated on a manually annotated malignant suspect subset. Receiver Operating Characteristic (ROC) and Precision-Recall curves were used to performance measures. RESULTS: The Area Under ROC [95%CI] values for malignancy classification obtained with the finetuned model for the entire holdout set were 0.82 [0.76, 0.87], 0.84 [0.77, 0.89], 0.85 [0.79, 0.90], and 0.83 [0.76, 0.89] for R-MLO, L-MLO, R-CC and L-CC views respectively. Performance on the malignant suspect subset was slightly better. On the auxiliary benign classification task performance remained low. CONCLUSIONS: The results indicate that the model performs well also in an out-of-distribution setting. Finetuning allowed the model to adapt to some of the underlying local demographics. Future research should concentrate to identify breast cancer subgroups adversely affecting performance, as it is a requirement for increasing the model's readiness level for a clinical setting.

The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images.

OBJECTIVES: The KNee OsteoArthritis Prediction (KNOAP2020) challenge was organized to objectively compare methods for the prediction of incident symptomatic radiographic knee osteoarthritis within 78 months on a test set with blinded ground truth. DESIGN: The challenge participants were free to use any available data sources to train their models. A test set of 423 knees from the Prevention of Knee Osteoarthritis in Overweight Females (PROOF) study consisting of magnetic resonance imaging (MRI) and X-ray image data along with clinical risk factors at baseline was made available to all challenge participants. The ground truth outcomes, i.e., which knees developed incident symptomatic radiographic knee osteoarthritis (according to the combined ACR criteria) within 78 months, were not provided to the participants. To assess the performance of the submitted models, we used the area under the receiver operating characteristic curve (ROCAUC) and balanced accuracy (BACC). RESULTS: Seven teams submitted 23 entries in total. A majority of the algorithms were trained on data from the Osteoarthritis Initiative. The model with the highest ROCAUC (0.64 (95% confidence interval (CI): 0.57-0.70)) used deep learning to extract information from X-ray images combined with clinical variables. The model with the highest BACC (0.59 (95% CI: 0.52-0.65)) ensembled three different models that used automatically extracted X-ray and MRI features along with clinical variables. CONCLUSION: The KNOAP2020 challenge established a benchmark for predicting incident symptomatic radiographic knee osteoarthritis. Accurate prediction of incident symptomatic radiographic knee osteoarthritis is a complex and still unsolved problem requiring additional investigation.

Quantitative evaluation of the tibiofemoral joint cartilage by T2 mapping in patients with acute anterior cruciate ligament injury vs contralateral knees: results from the subacute phase using data from the NACOX study cohort.

OBJECTIVE: Immediate cartilage structural alterations in the acute phase after an anterior cruciate ligament (ACL) rupture may be a precursor to posttraumatic osteoarthritis (PTOA) development. Our aim was to describe changes in cartilage matrix in the subacute phase of the acutely ACL-injured knee compared to the contralateral uninjured knee. DESIGN: Participants (n = 118) aged 15-40 years with an acute ACL injury were consecutively included in subacute phase after acute ACL-injury and underwent MRI (mean 29 days post trauma) of both knees. Mean T2 relaxation times, T2 spatial coefficient of variation and cartilage thickness were determined for different regions of the tibiofemoral cartilage. Differences between the acutely ACL-injured and uninjured knee were evaluated using Wilcoxon signed-rank test. RESULTS: T2 relaxation time in injured knees was increased in multiple cartilage regions from both medial and lateral compartment compared to contralateral knees, mostly in medial trochlea and posterior tibia (P-value<0.001). In the same sites of injured knees, we observed significantly thinner cartilage. Moreover, injured knees presented shorter T2 relaxation time in superficial cartilage on lateral central femur and trochlea (P-value<0.001), and decreased T2 spatial coefficient of variation in lateral trochlea and load bearing regions of medial-central femoral condyle and central tibia in both compartments. CONCLUSION: Small but statistically significant differences were observed in the subacute phase between ACL-injured and uninjured knee in cartilage T2 relaxation time and cartilage thickness. Future longitudinal observations of the same cohort will allow for better understanding of early development of PTOA. TRIAL REGISTRATION NUMBER: NCT02931084.

Automated detection of patellofemoral osteoarthritis from knee lateral view radiographs using deep learning: data from the Multicenter Osteoarthritis Study (MOST).

OBJECTIVE: To assess the ability of imaging-based deep learning to detect radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs. DESIGN: Knee lateral view radiographs were extracted from The Multicenter Osteoarthritis Study (MOST) public use datasets (n = 18,436 knees). Patellar region-of-interest (ROI) was first automatically detected, and subsequently, end-to-end deep convolutional neural networks (CNNs) were trained and validated to detect the status of patellofemoral OA. Patellar ROI was detected using deep-learning-based object detection method. Atlas-guided visual assessment of PFOA status by expert readers provided in the MOST public use datasets was used as a classification outcome for the models. Performance of classification models was assessed using the area under the receiver operating characteristic curve (ROC AUC) and the average precision (AP) obtained from the Precision-Recall (PR) curve in the stratified 5-fold cross validation setting. RESULTS: Of the 18,436 knees, 3,425 (19%) had PFOA. AUC and AP for the reference model including age, sex, body mass index (BMI), the total Western Ontario and McMaster Universities Arthritis Index (WOMAC) score, and tibiofemoral Kellgren-Lawrence (KL) grade to detect PFOA were 0.806 and 0.478, respectively. The CNN model that used only image data significantly improved the classifier performance (ROC AUC = 0.958, AP = 0.862). CONCLUSION: We present the first machine learning based automatic PFOA detection method. Furthermore, our deep learning based model trained on patella region from knee lateral view radiographs performs better at detecting PFOA than models based on patient characteristics and clinical assessments.

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.

Patients', radiographers' and radiography students' experiences of 360° virtual counselling environment for the coronary computed tomography angiography: A qualitative study.

INTRODUCTION: The aim of this study was to describe patients', radiographers' and radiography students' experiences of the developed 360° virtual counselling environment (360°VCE) for the coronary computed tomography angiography (cCTA). METHODS: A descriptive qualitative approach was used. The participants were cCTA patients (n = 10), radiographers (n = 10) and radiography students (n = 10) who used the 360°VCE and visited or worked at a university hospital in Finland. The 360°VCE, resembling the authentic environments of a CT imaging unit, included digital counselling materials in text, image, animation and video formats. Data were gathered through thematic interviews individually to obtain an understanding of participants' perspectives and analyzed by inductive content analysis. RESULTS: Five main categories and 15 categories were identified. Identified benefits of the 360°VCE for patients included improvements in knowledge, spatial and environmental orientation, and senses of security and self-efficacy, with reductions in fear and nervousness. Patients found the counselling materials engaging, and that the 360° technology conveniently provided reassuring familiarity with the environment before their visit. Identified benefits for radiographers and radiography students included improvements in patients' mental preparedness, knowledge, spatial and environmental orientation, and reductions in patients' fear, which eased procedures and enhanced diagnostic success. The 360°VCE also provided useful information and familiarization with the cCTA unit for students during clinical practice and staff of referring units.  CONCLUSION: It seems that patients', radiographers' and radiography students' experiences of 360°VCE respond to patients' needs by improved knowledge and reduced fears. Thus, current counselling practices can be usefully complemented with spherical panoramic imaging technology and online information delivery. IMPLICATIONS FOR PRACTICE: The results may be used to improve patient counselling and care, thereby optimizing the cCTA examination procedure and reducing fear. However, further research is needed to characterize experiences of the 360° VCE more comprehensively.

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.

Defective WNT signaling may protect from articular cartilage deterioration - a quantitative MRI study on subjects with a heterozygous WNT1 mutation.

OBJECTIVE: WNT signaling is of key importance in chondrogenesis and defective WNT signaling may contribute to the pathogenesis of osteoarthritis and other cartilage diseases. Biochemical composition of articular cartilage in patients with aberrant WNT signaling has not been studied. Our objective was to assess the knee articular cartilage in WNT1 mutation-positive individuals using a 3.0T MRI unit to measure cartilage thickness, relaxation times, and texture features. DESIGN: Cohort comprised mutation-positive (N = 13; age 17-76 years) and mutation-negative (N = 13; 16-77 years) subjects from two Finnish families with autosomal dominant WNT1 osteoporosis due to a heterozygous missense mutation c.652T>G (p.C218G) in WNT1. All subjects were imaged with a 3.0T MRI unit and assessed for cartilage thickness, T2 and T1ρ relaxation times, and T2 texture features contrast, dissimilarity and homogeneity of T2 relaxation time maps in six regions of interest (ROIs) in the tibiofemoral cartilage. RESULTS: All three texture features showed opposing trends with age between the groups in the medial tibiofemoral cartilage (P = 0.020-0.085 for the difference of the regression coefficients), the mutation-positive individuals showing signs of cartilage preservation. No significant differences were observed in the lateral tibiofemoral cartilage. Cartilage thickness and means of T2 relaxation time did not differ between groups. Means of T1ρ relaxation time were significantly different in one ROI but the regression analysis displayed no differences. CONCLUSIONS: Our results show less age-related cartilage deterioration in the WNT1 mutation-positive than the mutation-negative subjects. This suggests, that the WNT1 mutation may alter cartilage turnover and even have a potential cartilage-preserving effect.

Osteoarthritis year in review 2018: imaging.

PURPOSE: To provide a narrative review of the most relevant original research published in 2017/2018 on osteoarthritis imaging. METHODS: The PubMed database was used to recover all relevant articles pertaining to osteoarthritis and medical imaging published between 1 April 2017 and 31 March 2018. Review articles, case studies and in vitro or animal studies were excluded. The original publications were subjectively sorted based on relevance, novelty and impact. RESULTS AND CONCLUSIONS: The publication search yielded 1,155 references. In the assessed publications, the most common imaging modalities were radiography (N = 708) and magnetic resonance imaging (MRI) (355), followed by computed tomography (CT) (220), ultrasound (85) and nuclear medicine (17). An overview of the most important publications to the osteoarthritis (OA) research community is presented in this narrative review. Imaging studies play an increasingly important role in OA research, and have helped us to understand better the pathophysiology of OA. Radiography and MRI continue to be the most applied imaging modalities, while quantitative MRI methods and texture analysis are becoming more popular. The value of ultrasound in OA research has been demonstrated. Several multi-modality predictive models have been developed. Deep learning has potential for more automatic and standardized analyses in future OA imaging research.

Assessment of meniscus with adiabatic T1ρ and T2ρ relaxation time in asymptomatic subjects and patients with mild osteoarthritis: a feasibility study.

OBJECTIVE: To investigate the ability of magnetic resonance imaging (MRI) adiabatic relaxation times in the rotating frame (adiabatic T1ρ and T2ρ) to detect structural alterations in meniscus tissue of mild OA patients and asymptomatic volunteers. METHOD: MR images of 24 subjects (age range: 50-67 years, 12 male), including 12 patients with mild osteoarthritis (OA) (Kellgren-Lawrence (KL) = 1, 2) and 12 asymptomatic volunteers, were acquired using a 3 T clinical MRI system. Morphological assessment was performed using semiquantitative MRI OA Knee Score (MOAKS). Adiabatic T1ρ and T2ρ (AdT1ρ, AdT2ρ) relaxation time maps were calculated in regions of interest (ROIs) containing medial and lateral horns of menisci. The median relaxation time values of the ROIs were compared between subjects classified based on radiographic findings and MOAKS evaluations. RESULTS: MOAKS assessment of patients and volunteers indicated the presence of meniscal and cartilage lesions in both groups. For the combined cohort group, prolonged AdT1ρ was observed in the posterior horn of the medial meniscus (PHMED) in subjects with MOAKS meniscal tear (P < 0.05). AdT2ρ was statistically significantly longer in PHMED of subjects with MOAKS full-thickness cartilage loss (P < 0.05). After adjusting for multiple comparisons, differences in medians of observed AdT1ρ and AdT2ρ values between mild OA patients and asymptomatic volunteers did not reach statistical significance. CONCLUSION: AdT1ρ and AdT2ρ measurements have the potential to identify changes in structural composition of meniscus tissue associated with meniscal tear and cartilage loss in a cohort group of mild OA patients and asymptomatic volunteers.

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 (ELap) and local binary patterns (ELBP), homogeneity indices of the local angles (HIAngles,mean, HIAngles,Perp, HIAngles,Paral), and horizontal (FDHor) and vertical fractal dimensions (FDVer). Mean dGEMRIC index and T2 relaxation time of tibial cartilage were calculated to estimate cartilage composition. RESULTS: HIAngles,mean (rs = -0.22) and HIAngles,Paral (rs = -0.24) in medial subchondral bone were related (P < 0.05) to dGEMRIC index of the medial tibial cartilage. ELap (rs = -0.23), FDHor,0.34 mm (r = 0.21) and FDVer,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. FDHor 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). FDVer 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). HIAngles,Paral (r = -0.25) and FDVer,0.68 mm (rs = 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.

Magnetic resonance imaging (MRI)-defined cartilage degeneration and joint pain are associated with poor physical function in knee osteoarthritis - the Oulu Knee Osteoarthritis study.

OBJECTIVE: The main aim was to investigate the associations between Magnetic Resonance Imaging (MRI)-defined structural pathologies of the knee and physical function. DESIGN: A cohort study with frequency matching on age and sex with eighty symptomatic subjects with knee pain and suspicion or diagnosis of knee osteoarthritis (OA) and 57 asymptomatic subjects was conducted. The subjects underwent knee MRI, and the severity of structural changes was graded by MRI Osteoarthritis Knee Score (MOAKS) in separate knee locations. WOMAC function subscores were recorded and physical function tests (20-m and 5-min walk, stair ascending and descending, timed up & go and repeated sit-to-stand tests) performed. The association between MRI-defined structural pathologies and physical function tests and WOMAC function subscores were evaluated by linear regression analysis with adjustment for demographic factors, other MRI-features and pain with using effect size (ES) as a measure of the magnitude of an association. RESULTS: Cartilage degeneration showed significant association with poor physical performance in TUG-, stair ascending and descending-, 20-m- and 5-min walk-tests (ESs in the subjects with cartilage degeneration anywhere between 0.134 [95%CI 0.037-0.238] and 0.224 [0.013-0.335]) and with increased WOMAC function subscore (ES in the subjects with cartilage degeneration anywhere 0.088 [0.012-0.103]). Also, lateral meniscus maceration and extrusion were associated with poor performance in stair ascending test (ESs 0.067 [0.008-0.163] and 0.077 [0.012-0.177]). CONCLUSIONS: After adjustments cartilage degeneration was associated with both decreased self-reported physical function and poor performance in the physical function tests. Furthermore, subjects with lateral meniscus maceration and extrusions showed significantly worse performance in stair ascending tests.

Effects of high intensity resistance aquatic training on body composition and walking speed in women with mild knee osteoarthritis: a 4-month RCT with 12-month follow-up.

OBJECTIVE: To investigate the effects of 4-months intensive aquatic resistance training on body composition and walking speed in post-menopausal women with mild knee osteoarthritis (OA), immediately after intervention and after 12-months follow-up. Additionally, influence of leisure time physical activity (LTPA) will be investigated. DESIGN: This randomised clinical trial assigned eighty-seven volunteer postmenopausal women into two study arms. The intervention group (n = 43) participated in 48 supervised intensive aquatic resistance training sessions over 4-months while the control group (n = 44) maintained normal physical activity. Eighty four participants continued into the 12-months' follow-up period. Body composition was measured with dual-energy X-ray absorptiometry (DXA). Walking speed over 2 km and the knee injury and osteoarthritis outcome score (KOOS) were measured. LTPA was recorded with self-reported diaries. RESULTS: After the 4-month intervention there was a significant decrease (P = 0.002) in fat mass (mean change: -1.17 kg; 95% CI: -2.00 to -0.43) and increase (P = 0.002) in walking speed (0.052 m/s; 95% CI: 0.018 to 0.086) in favour of the intervention group. Body composition returned to baseline after 12-months. In contrast, increased walking speed was maintained (0.046 m/s; 95% CI 0.006 to 0.086, P = 0.032). No change was seen in lean mass or KOOS. Daily LTPA over the 16-months had a significant effect (P = 0.007) on fat mass loss (f2 = 0.05) but no effect on walking speed. CONCLUSIONS: Our findings show that high intensity aquatic resistance training decreases fat mass and improves walking speed in post-menopausal women with mild knee OA. Only improvements in walking speed were maintained at 12-months follow-up. Higher levels of LTPA were associated with fat mass loss. TRIAL REGISTRATION NUMBER: ISRCTN65346593.

THE ESTABLISHMENT OF LOCAL DIAGNOSTIC REFERENCE LEVELS IN ENDOSCOPIC RETROGRADE CHOLANGIOPANCREATOGRAPHY: A PRACTICAL TOOL FOR THE OPTIMISATION AND FOR QUALITY ASSURANCE MANAGEMENT.

Fluoroscopic procedures are an area of special concern in relation to radiation protection. The aim of this study was to describe the current level of patient radiation doses in endoscopic retrograde cholangiopancreatography (ERCP) collected from a single centre, as well as to establish and review local diagnostic reference levels (DRLs) in ERCP. A total of 100 patients' radiation doses in ERCP were recorded, and the third-quartile method was adopted to establish local DRLs for ERCP. The mean dose area product (DAP) was 2.05 Gy cm2, fluoroscopy time (FT) 1.7 min and the number of images was 3. The proposed local DRLs for ERCP were 3.00 Gy cm2 and 3.0 min. Local DRLs were reviewed in a sample of 25 patients 5 y after they had been established. In reviewing data, the averages of DAP and FT were below the local DRLs. Local DRLs help in the optimisation process of fluoroscopic procedures and guides to a good clinical practice.

Effect of progressive high-impact exercise on femoral neck structural strength in postmenopausal women with mild knee osteoarthritis: a 12-month RCT.

It is uncertain whether subjects with mild knee osteoarthritis, and who may be at risk of osteoporosis, can exercise safely with the aim of improving hip bone strength. This RCT showed that participating in a high-impact exercise program improved femoral neck strength without any detrimental effects on knee cartilage composition. INTRODUCTION: No previous studies have examined whether high-impact exercise can improve bone strength and articular cartilage quality in subjects with mild knee osteoarthritis. In this 12-month RCT, we assessed the effects of progressive high-impact exercise on femoral neck structural strength and biochemical composition of knee cartilage in postmenopausal women. METHODS: Eighty postmenopausal women with mild knee radiographic osteoarthritis were randomly assigned into the exercise (n = 40) or control (n = 40) group. Femoral neck structural strength was assessed with dual-energy X-ray absorptiometry. The knee cartilage region exposed to exercise loading was measured by the quantitative MRI techniques of T2 mapping and delayed gadolinium-enhanced MRI of cartilage (dGEMRIC). Also, an accelerometer-based body movement monitor was used to evaluate the total physical activity loading on the changes of femoral neck strength in all participants. Training effects on the outcome variables were estimated by the bootstrap analysis of covariance. RESULTS: A significant between-group difference in femoral neck bending strength in favor of the trainees was observed after the 12-month intervention (4.4%, p < 0.01). The change in femoral neck bending strength remained significant after adjusting for baseline value, age, height, and body mass (4.0%, p = 0.020). In all participants, the change in bending strength was associated with the total physical activity loading (r = 0.29, p = 0.012). The exercise participation had no effect on knee cartilage composition. CONCLUSION: The high-impact training increased femoral neck strength without having any harmful effect on knee cartilage in women with mild knee osteoarthritis. These findings imply that progressive high-impact exercise is a feasible method in seeking to prevent hip fractures in postmenopausal women whose articular cartilage may also be frail.

Effect of collagen cross-linking on quantitative MRI parameters of articular cartilage.

OBJECTIVE: To investigate the sensitivity of quantitative magnetic resonance imaging (MRI) parameters to increase of collagen cross-linking in articular cartilage, a factor possibly contributing to the aging-related development of osteoarthritis (OA). The issue has not been widely studied although collagen cross-links may significantly affect the evaluation of cartilage imaging outcome. DESIGN: Osteochondral samples (n = 14) were prepared from seven bovine patellae. To induce cross-linking, seven samples were incubated in threose while the other seven served as non-treated controls. The specimens were scanned at 9.4 T for T1, T1Gd (dGEMRIC), T2, adiabatic and continuous wave (CW) T1ρ, adiabatic T2ρ and T1sat relaxation times. Specimens from adjacent tissue were identically treated and used for reference to determine biomechanical properties, collagen, proteoglycan and cross-link contents, fixed charge density (FCD), collagen fibril anisotropy and water concentration of cartilage. RESULTS: In the threose-treated sample group, cross-links (pentosidine, lysyl pyridinoline (LP)), FCD and equilibrium modulus were significantly (P < 0.05) higher as compared to the non-treated group. Threose treatment resulted in significantly greater T1Gd relaxation time constant (+26%, P < 0.05), although proteoglycan content was not altered. Adiabatic and CW-T1ρ were also significantly increased (+16%, +28%, P < 0.05) while pre-contrast T1 was significantly decreased (-10%, P < 0.05) in the threose group. T2, T2ρ and T1sat did not change significantly. CONCLUSION: Threose treatment induced collagen cross-linking and changes in the properties of articular cartilage, which were detected by T1, T1Gd and T1ρ relaxation time constants. Cross-linking should be considered especially when interpreting the outcome of contrast-enhanced MRI in aging populations.

Associations between MRI-defined structural pathology and generalized and localized knee pain - the Oulu Knee Osteoarthritis study.

OBJECTIVE: To determine the associations between multi-feature structural pathology assessed using magnetic resonance imaging (MRI) and the presence of knee pain, and to determine the associations between the locations of structural changes and different knee pain patterns. METHOD: Eighty symptomatic subjects with knee pain and suspicion or diagnosis of knee OA and 63 asymptomatic subjects underwent knee MRI. Severity of structural changes was graded by MRI Osteoarthritis Knee Score (MOAKS) in separate knee locations. The associations between cartilage damage, bone marrow lesions (BMLs), osteophytes, Hoffa's synovitis, effusion-synovitis, meniscal damage and structural pathologies in ligaments, tendons and bursas and both the presence of pain and the knee pain patterns were assessed. RESULTS: The presence of Hoffa's synovitis (adjusted RR 1.6, 95% CI 1.2-1.3) and osteophytes in any region (2.07, 1.19-3.60) was significantly associated with the presence of pain. Any Hoffa's synovitis was associated with patellar pain (adjusted RR 4.70, 95% CI 1.19-3.60) and moderate-to-severe Hoffa's synovitis with diffuse pain (2.25, 1.13-4.50). Medial knee pain was associated with cartilage loss in the medial tibia (adjusted RR 2.66, 95% CI 1.22-5.80), osteophytes in the medial tibia (2.66, 1.17-6.07) and medial femur (2.55, 1.07-6.09), medial meniscal maceration (2.20, 1.01-4.79) and anterior meniscal extrusions (2.78, 1.14-6.75). CONCLUSIONS: Hoffa's synovitis and osteophytes were strongly associated with the presence of knee pain. Medial pain was associated most often with medially located structural pathologies.

Efficacy of progressive aquatic resistance training for tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis: a randomised controlled trial.

OBJECTIVE: To study the efficacy of aquatic resistance training on biochemical composition of tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis (OA). DESIGN: Eighty seven volunteer postmenopausal women, aged 60-68 years, with mild knee OA (Kellgren-Lawrence grades I/II and knee pain) were recruited and randomly assigned to an intervention (n = 43) and control (n = 44) group. The intervention group participated in 48 supervised aquatic resistance training sessions over 16 weeks while the control group maintained usual level of physical activity. The biochemical composition of the medial and lateral tibiofemoral cartilage was estimated using single-slice transverse relaxation time (T2) mapping and delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC index). Secondary outcomes were cardiorespiratory fitness, isometric knee extension and flexion force and knee injury and OA outcome (KOOS) questionnaire. RESULTS: After 4-months aquatic training, there was a significant decrease in both T2 -1.2 ms (95% confidence interval (CI): -2.3 to -0.1, P = 0.021) and dGEMRIC index -23 ms (-43 to -3, P = 0.016) in the training group compared to controls in the full thickness posterior region of interest (ROI) of the medial femoral cartilage. Cardiorespiratory fitness significantly improved in the intervention group by 9.8% (P = 0.010). CONCLUSIONS: Our results suggest that, in postmenopausal women with mild knee OA, the integrity of the collagen-interstitial water environment (T2) of the tibiofemoral cartilage may be responsive to low shear and compressive forces during aquatic resistance training. More research is required to understand the exact nature of acute responses in dGEMRIC index to this type of loading. Further, aquatic resistance training improves cardiorespiratory fitness. TRIAL REGISTRATION NUMBER: ISRCTN65346593.

Bone and cartilage characteristics in postmenopausal women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis.

OBJECTIVES: To evaluate the association between radiographically-assessed knee osteoarthritis and femoral neck bone characteristics in women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis. METHODS: Ninety postmenopausal women (mean age [SD], 58 [4] years; height, 163 [6] cm; weight, 71 [11] kg) participated in this cross-sectional study. The severity of radiographic knee osteoarthritis was defined using Kellgren-Lawrence grades 0=normal (n=12), 1=doubtful (n=25) or 2=minimal (n=53). Femoral neck bone mineral content (BMC), section modulus (Z), and cross-sectional area (CSA) were measured with DXA. The biochemical composition of ipsilateral knee cartilage was estimated using quantitative MRI measures, T2 mapping and dGEMRIC. The associations between radiographic knee osteoarthritis grades and bone and cartilage characteristics were analyzed using generalized linear models. RESULTS: Age-, height-, and weight-adjusted femoral neck BMC (p for linearity=0.019), Z (p for linearity=0.033), and CSA (p for linearity=0.019) increased significantly with higher knee osteoarthritis grades. There was no linear relationship between osteoarthritis grades and knee cartilage indices. CONCLUSIONS: Increased DXA assessed hip bone strength is related to knee osteoarthritis severity. These results are hypothesis driven that there is an inverse relationship between osteoarthritis and osteoporosis. However, MRI assessed measures of cartilage do not discriminate mild radiographic osteoarthritis severity.