Knee Bone Research Articles

Investigating the Impact of Knee Prosthesis in Patients' Body on Radiation Dose Distribution: A Monte Carlo Approach.

Background:Metal prostheses in patients affect the radiotherapy dose distribution. Metal prostheses with high density and atomic number cause major changes in scattering and attenuation of radiation. The present study aims to assess the impact of metal knee prosthesis with various dimensions and materials on radiotherapy dose distribution. Material and Methods: In this research, the Varian Linac and water phantom were simulated using the MCNPX code. Dose distribution of photon beam in a water phantom, with and without the presence of knee prostheses made of cobalt-chromium-molybdenum alloy, steel, titanium, and titanium alloy used in men and women was investigated using the Monte Carlo simulation. Results:The prosthesis led to an increase in dose in comparison with cases that there was used no prosthesis. According to values of the depth dose percentage, the maximum dose increase was found to be 6.8%, 6.1%, 4%, and 4.29%, and dose reduction 41.18%, 40.66%, 37.76%, and 37.51% for prosthetics with men’s knee dimensions made of cobalt-chromium-molybdenum alloy, steel, titanium alloy, and titanium, respectively. Above all, does increasing to 6.4%, 5.9%, 3.8%, and 3.94% and doses reducing to 40.87%, 40.36%, 36.94%, and 36.69 were observed in prosthetics for women. The highest amount of dose reduction for men’s prostheses made of mentioned materials was found to be 48.75%, 47.7%, 45%, and 45.8%, respectively. In addition, it was 46.36%, 45.8%, 43.8%, and 43.95% for women’s prostheses, respectively. Conclusion: Material will have a significant impact if a part of the knee bone places behind the prosthesis. According to the obtained values, it is recommended to utilize prostheses made of titanium and titanium alloys for knee arthroplasty. The prosthesis can either increase or decrease dose in tumor or lead to increase dose at organs at risk.

Estrogen Modulates Cartilage and Subchondral Bone Remodeling in an Ovariectomized Rat Model of Postmenopausal Osteoarthritis.

BackgroundEstrogen levels regulate changes in osteoarthritis (OA) by inhibiting degradation of the extracellular matrix. Recent in vitro studies have also shown the role of microRNA-140-5p (miR-140-5p). This study aimed to investigate the role of estrogen deficiency, selective modulation of expression of the estrogen receptor (ER), and expression of miR-140-5p in cartilage and subchondral bone remodeling in an ovariectomized rat model of postmenopausal OA.Material/MethodsFemale Sprague-Dawley rats included two model groups, ovariectomized (OVX) rats and rats with destabilization of the medial meniscus (DMM) rats. Two months after surgery, estrogen levels were measured by the enzyme-linked immunosorbent assay (ELISA). Three-dimensional (3D) micro-computed tomography (micro-CT) was used to image the knee joints. Rats were treated with subcutaneous injection of estrogen (E2) or the selective estrogen receptor modulator (SERM), raloxifene (RAL), for one month. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect miR-140-5p in serum, and histology of the knee joint cartilage and bone was performed.ResultsIn the ovariectomized rat model of OA, estrogen therapy reduced the degree of cartilaginous degeneration, while treatment with raloxifene showed no significant effect. Expression levels of miR-140-5p in the OA model group were significantly lower than the control group. Micro-CT showed that in the model group, anterior cruciate ligament dislocation and subchondral bone density were significantly reduced.ConclusionsIn an ovariectomized rat model of postmenopausal OA, estrogen deficiency resulted in resorption of subchondral bone and degeneration of articular cartilage.

Discovering knee osteoarthritis bone shape features using deep learning

Purpose: Osteoarthritis (OA) is a degenerative joint disease which affects 27 million U.S. adults. The onset of OA is related to several factors such as cartilage loss and changes in the meniscus. In addition to degeneration of soft tissues, it has been suggested that changes also occur in the subchondral bone. While previous studies showed associations between bone shape and OA, inferential statistics does not guarantee actual prediction abilities. This study aims to fill this gap by exploring the ability of deep learning convolutional neural networks (CNN) to use knee bone shape features in diagnosing and predicting future onset of radiographic OA based on Kellgren-Lawrence grade. Methods: The Osteoarthritis Initiative (OAI) data set used for this study contains 3D double-echo steady-state (3D-DESS, 3T Siemens, TR/TE 16.2/4.7; field of view, 14 cm; matrix, 307x348; bandwidth, 62.5 kHz; and image resolutions, [0.346 0.346 0.7] mm) MRI knee scans from a total of 4,796 unique patients for 10 different time points for both knees. Overall processing pipeline is shown in Figure 1. The femur, tibia and patella were segmented using a CNN and the segmentation masks were transformed into metric-scale isosurfaces. Each isosurface was then aligned to a reference point cloud for each bone type to account for rotational shifts during scanning. The aligned point clouds were then transformed into spherical coordinates by taking the distance from the centroid to the bone surface, in millimeters, as the intensity and the combination of angles as the pixel coordinates (Figure 2). The spherical conversions was turned into a RGB image that was used as an input for two binary classifiers. The first one was trained using the entire dataset and aimed to diagnose OA (KL 0-1 vs KL 2-3) and the second one was trained just on controls (KL=0,1) to predict future onset of radiographic OA (KL 2-3) within two years of the last healthy time point. The segmentation CNN was trained with 40 manually segmented bone masks split into 25/5/10 sets for the training, validation and holdout sets respectively. OA diagnosis dataset included a total of 23,921 MRI scans (11,517 (48.14%) KL 0-1 and 12,404 (51.85%) KL 2-4) split into 14,776/4,935/4,208 sets for the training, validation and holdout sets respectively. The training data for the OA progression model consisted of a total of 913 scans split into 590/139/182 for training, validation and holdout respectively. Both models were then connected to a gradient boosting shallow classifier to incorporate demographics data for each patient such as gender, age, and body mass index (BMI). The class balance for the OA progression model was 408 healthy controls and 504 OA progression scans. The patient male-female gender balance was 10,503 to 13,374 for the OA diagnosis and 389 to 512 for the OA progression. For model interpretation, 2D saliency maps were generated and projected onto the 3D bone surfaces (Figure 3). Results: The holdout mean DICE coefficients ranged from 88.9% to 95.2% for femur segmentation, from 87.0% to 95.8% for tibia segmentation and from 85.1% to 92.2% for the patella segmentation. The holdout sensitivity and specificity for the OA binary classifier were 79.0% and 77.1% respectively. The holdout sensitivity and specificity for the OA two-year progression binary classifier were 76.8% and 57.5% respectively. The holdout sensitivity and specificity for the shallow classifier with demographics for the OA diagnosis was 81.03% and 79.01% respectively and for the OA progression was 76.77% and 62.50% respectively. Conclusions: With this study, we have established a model for prediction of radiographic OA using bones shapes as the single factor. Additional demographic data, such as gender, age and BMI, was combined with the bone shape in order to improve the predictive accuracy of the model. While previous studies have shown associations between bone shape and OA, this study is the first to use deep learning to predict radiographic OA using bone shape features. Future directions include improving the overall accuracy of the models used in the study in order to recover the full OAI data set that was poorly segmented or processed. Augmentation techniques could be used in the binary classifiers to improve the generalizability of the models and their overall robustness.View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)

A novel, self-assembled artificial cartilage-hydroxyapatite conjugate for combined articular cartilage and subchondral bone repair: histopathological analysis of cartilage tissue engineering in rat knee joints.

PurposeWe previously created a self-assembled cartilage-like complex in vitro from only three cartilage components, hyaluronic acid (HA), aggrecan (AG) and type II collagen, without other materials such as cross-linking agents. Based on this self-organized AG/HA/collagen complex, we have created three novel types of biphasic cartilage and bone-like scaffolds combined with hydroxyapatite (HAP) for osteochondral tissue engineering. These scaffolds have been developed from self-assembled cartilage component molecules and HAP at the nanometer scale by manipulating the intermolecular relations.Patients and methodsThe surface structure of each self-organized biphasic cartilage and bone-like scaffold was evaluated by scanning electron microscopy, whereas the viscoelasticity was also analyzed in vitro. Three types of artificial cartilage–HAP conjugates were implanted into an osteochondral defect in rat knee joints, and bone and cartilage tissues of the implanted site were examined 4 and 8 weeks after implantation. The tissues were examined histopathologically to evaluate the effects of the implantation on the articular cartilage and subchondral bone tissues.ResultsOur in vitro and in vivo data reveal that the self-organized biphasic cartilage and bone-like scaffold conjugated with HAP are superior to the scaffold with no HAP in both cartilage regeneration and subchondral bone regeneration.ConclusionOur present study indicates that the self-organized biphasic cartilage and bone-like scaffold, which is conjugated with an HAP layer, may have potential not only to repair articular cartilage defects but also to ameliorate the degeneration of subchondral bone in the diseases with osteochondral defect.

Technique d’alignement cinématique des prothèses unicompartimentaires médiales Oxford : une étude in vitro

BackgroundMobile bearing unicompartmental knee arthroplasty (UKA) Oxford™ components are recommended to be systematically and mechanically aligned (MA) for restoring the constitutional lower-limb alignment. Good long-term clinical outcomes have been generated with the medially implanted MA Oxford™, but some sub-optimal biomechanical-related complications still remain. Kinematic Alignment (KA) is a personalised technique for anatomically and kinematically implanting components (total knee, fixed bearing partial knee, total hip) aimed at creating more physiological prosthetic joint biomechanics. Interestingly, for decades the principles for implanting fixed bearing UKA components were consistent with those promoted by the KA technique, but differently formulated. We initiated this computational study to assess the feasibility of this technique with the Oxford™ components, as we thought this more anatomical implantation may be clinically advantageous. HypothesisWe surmised that kinematically aligning the Oxford™ medial UKA would maximise the prosthesis-bone interface through maximising the implants’ size used (question 1), and alter, within an acceptable limit, the components’ orientation (question 2) compared to conventional mechanical alignment. MethodsA cohort of 40 consecutive medial osteoarthritic knee patients scheduled for UKA had a preoperative CT scan that was segmented to create 3D knee bone models. MA and KA of medial UKA Oxford® components (Zimmer-Biomet, Warsaw, Indiana, USA) were simulated. Component sizing and positioning were compared between the two techniques. ResultsWe found no difference in component size, but significantly fewer occurrences of borderline fit with the KA simulation. KA technique oriented the femoral component 3.6° more valgus (from 1° varus to 7° valgus) and the tibial component 2.9° more varus (from 8° varus to 0°) compared to the MA technique. The tibial component slope in KA simulation was 6.4° posterior (from 0° to 12°) compared to a systematic 7° posterior for MA positioning. Discussion and conclusionKinematic alignment of the medial Oxford™ generated a different, albeit still acceptable (Oxford group recommendations), implant orientation, in addition to a likely better shape-fit between components and the supportive bone cut, compared to the MA technique. The potential to improve the implants’ interaction and to restore a more physiological bone loading makes the KA of Oxford™ an attractive, potentially clinically beneficial option. Clinical investigations are needed to assess its true value. Level of evidenceI, computational study.

Development of 3D Model of Tibia Femoral Bone in Knee Joint for FEA

Tibia femoral bone is a part of knee joint which is a very complex joint of the human body. Now a days knee pain is most frequently observed problem in elderly people. Worldwide statistics reveals about 100 million people experience knee pain hence analysis of knee is very essential for diagnosis and treatment. The change in mechanical properties of knee joint lead to knee bone fracture. Loading of the knee bone and possible fracture can be analyzed using finite element analysis(FEA). The FEA technique used for analyzing mechanical properties of complex knee bone structure which needs 3D model of knee joint bone. This work mainly focuses on segmentation and 3D rendering of tibia femoral bone from MRI/CT scan data using image processing techniques. Interactive segmentation technique is used for segmentation of tibia femoral bones. Using thesegmented images 3D volume rendering is done and 3D model of tibia femoral bone is developed. Finite element meshing technique is carried out on 3D model of tibia femoral bone to create meshed model and the developed model can be used for analysis of force during loading using finite element analysis. The developed interactive segmentation technique along with 3D model creation of bone is useful in analysis and surgery planning.

Regenerative Semi-Supervised Bidirectional W-Network-Based Knee Bone Tumor Classification on Radiographs Guided by Three-Region Bone Segmentation

The objective of this study is to develop and evaluate a new deep learning architecture, namely regenerative semi-supervised bidirectional W-network (RSS-BW), to predict the tumor state of the knee bone from radiographic images. First, we constructed an autoencoder model, called Bidirectional W-network (BW), for segmenting three-region (i.e., femur, tibia, and fibula) of knee bone. Using these regions as input data, RSS-BW architecture consisting of the autoencoding model for regenerating the bone structures, the backbone model for extracting features with pretrained ImageNet, and the predicting model for knee bone tumor classification are established. The developed scheme rapidly obtained segmentation results of the three-region of knee bone with a mean dice score of 98.06 ± 0.08%. Moreover, two types of classification are conducted: single-step and double-step. The single-step classifies the bone images into normal, benign, and malignant states. The mean values of accuracy, precision, recall and F-beta score obtained from the segmented images were 85.23±3.91%, 82.23±3.22%, 82.15±3.31%, and 82.21±3.25%, respectively. For the double-step of bone tumor classification, the images are classified first as normal versus abnormal. The second classification is conducted for abnormal images as benign versus malignant. The double-step classification shows an improvement of the mean accuracy by 1.7% compared to the single-step classification. In conclusion, the RSS-BW model presents higher accuracy than conventional models, indicating its potential clinical decision support for bone tumor classification.

Assessment of Free Gas in the Tibial Condyle Bone of the Human Knee by Diode Laser Spectroscopy With Possible Application to Arthrosis Diagnostics

The gas in scattering media absorption spectroscopy (GASMAS) technique was used to investigate the possible presence of free gas pores in human condyle bones, extracted from the tibia in knee revision surgical procedures in response to arthrosis development. Following earlier studies showing free gas presence in femoral head bones, decaying because of inadequate blood flow, we investigated condyle bone, where the arthrosis degeneration process, affecting the cartilage cup, is of different origin. Only a minor gas presence was observed in affected condyle samples, in accordance with our finding for non-arthrosis samples. Further, studies of fresh or initially frozen samples showed very similar signals, suggesting that the handling procedure has only a minor importance in these studies. In contrast to the situation for femoral heads, the monitoring of a gas presence would add only little in assessing the arthrosis status in the view of elective surgical procedures.

Kinematic alignment technique for medial OXFORD UKA: An in-silico study

BackgroundMobile bearing unicompartmental knee arthroplasty (UKA) Oxford™ components are recommended to be systematically and mechanically aligned (MA) for restoring the constitutional lower-limb alignment. Good long-term clinical outcomes have been generated with the medially implanted MA Oxford™, but some sub-optimal biomechanical-related complications still remain. Kinematic Alignment (KA) is a personalised technique for anatomically and kinematically implanting components (total knee, fixed bearing partial knee, total hip) aimed at creating more physiological prosthetic joint biomechanics. Interestingly, for decades the principles for implanting fixed bearing UKA components were consistent with those promoted by the KA technique, but differently formulated. We initiated this computational study to assess the feasibility of this technique with the Oxford™ components, as we thought this more anatomical implantation may be clinically advantageous. HypothesisWe surmised that kinematically aligning the Oxford™ medial UKA would maximise the prosthesis-bone interface through maximising the implants’ size used (question 1), and alter, within an acceptable limit, the components’ orientation (question 2) compared to conventional mechanical alignment. MethodsA cohort of 40 consecutive medial osteoarthritic knee patients scheduled for UKA had a preoperative CT scan that was segmented to create 3D knee bone models. MA and KA of medial UKA Oxford® components (Zimmer-Biomet, Warsaw, Indiana, USA) were simulated. Component sizing and positioning were compared between the two techniques. ResultsWe found no difference in component size, but significantly fewer occurrences of borderline fit with the KA simulation. KA technique oriented the femoral component 3.6° more valgus (from 1° varus to 7° valgus) and the tibial component 2.9° more varus (from 8° varus to 0°) compared to the MA technique. The tibial component slope in KA simulation was 6.4° posterior (from 0 to 12°) compared to a systematic 7° posterior for MA positioning. Discussion and conclusionKinematic alignment of the medial Oxford™ generated a different, albeit still acceptable (Oxford group recommendations), implant orientation, in addition to a likely better shape-fit between components and the supportive bone cut, compared to the MA technique. The potential to improve the implants’ interaction and to restore a more physiological bone loading makes the KA of Oxford™ an attractive, potentially clinically beneficial option. Clinical investigations are needed to assess its true value. Level of evidenceI, computational study.

Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee

Patient-specific implant design and pre- and intra-operative planning is becoming increasingly important in the orthopaedic field. For clinical feasibility of these techniques, fast and accurate segmentation of bone structures from MRI is essential. However, manual segmentation is time intensive and subject to inter- and intra-observer variation. The challenge in developing automatic segmentation algorithms for MRI data mainly exists in the inhomogeneity problem and the low contrast among cortical bone and adjacent tissues. In this paper, we proposed a method for automatic segmentation of knee bone structures for MRI data with a 3D local intensity clustering-based level set and a novel approach to determine the cortical boundary utilizing the normal vector of the trabecular surface. Application to clinical imaging data shows that our method is robust to MRI inhomogeneity. In comparing our method to manual segmentation in 18 femurs and tibiae, we found a dice similarity coefficient (DSC) of 0.9611 ± 0.0052 for the femurs and 0.9591 ± 0.0173 for tibiae. The average surface distance error was 0.4649 ± 0.1430 mm for the femurs and 0.4712 ± 0.2113 mm for the tibiae. The results of the automatic technique thus strongly corresponded to the manual segmentation using less than 3% of the time and with virtually no workload.Graphical abstractᅟ

Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative.

We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging(MRI) that combines a priori knowledge of anatomical shape with Convolutional Neural Networks (CNNs). The proposed approach incorporates 3D Statistical Shape Models (SSMs) as well as 2D and 3D CNNs to achieve a robust and accurate segmentation of even highly pathological knee structures. The shape models and neural networks employed are trained using data from the Osteoarthritis Initiative (OAI) and the MICCAI grand challenge "Segmentation of Knee Images 2010" (SKI10), respectively. We evaluate our method on 40 validation and 50 submission datasets from the SKI10 challenge. For the first time, an accuracy equivalent to the inter-observer variability of human readers is achieved in this challenge. Moreover, the quality of the proposed method is thoroughly assessed using various measures for data from the OAI, i.e. 507 manual segmentations of bone and cartilage, and 88 additional manual segmentations of cartilage. Our method yields sub-voxel accuracy for both OAI datasets. We make the 507 manual segmentations as well as our experimental setup publicly available to further aid research in the field of medical image segmentation. In conclusion, combining localized classification via CNNs with statistical anatomical knowledge via SSMs results in a state-of-the-art segmentation method for knee bones and cartilage from MRI data.

Association of adiposity measures in childhood and adulthood with knee cartilage thickness, volume and bone area in young adults.

To describe the associations of childhood and adulthood adiposity measures with knee cartilage thickness, volume and bone area in young adults. Childhood and adulthood adiposity measures (weight, height, waist circumference and hip circumference) of 186 participants were collected in 1985 (aged 7-15 years) and during 2004-2006 (aged 26-36 years). Knee magnetic resonance imaging was conducted during 2008-2010 (aged 31-41 years) and cartilage thickness, volume and bone area were measured using a quantitative approach (Chondrometrics, Germany). Linear regressions were used to examine the above associations. The prevalence of overweight was 7.6% in childhood and 42.1% in adulthood. Childhood weight (β = - 5.57 mm2/kg) and body mass index (BMI) (β = - 11.55 mm2/kg/m2) were negatively associated with adult patellar bone area, whereas adult weight was positively associated with bone area in medial femorotibial compartment (MFTC) (β = 3.37 mm2/kg) and lateral femorotibial compartment (LFTC) (β = 2.08 mm2/kg). Adult waist-hip ratio (WHR) was negatively associated with cartilage thickness (MFTC: β = - 0.011; LFTC: β = - 0.012 mm/0.01 unit), volume (Patella: β = - 20.97; LFTC: β = - 21.71 mm3/0.01 unit) and bone area (Patella: β = - 4.39 mm2/0.01 unit). The change in WHR z-scores from childhood to adulthood was negatively associated with cartilage thickness (MFTC: β = - 0.056 mm), volume (patella: - 89.95; LFTC: - 93.98 mm3), and bone area (patella: - 20.74 mm2). All p-values < 0.05. Childhood weight and BMI were negatively but adult weight was positively associated with adult bone area. Adult WHR and the change in WHR from childhood to adulthood were negatively associated with cartilage thickness, volume, and bone area. These suggest early-life adiposity measures may affect knee structures in young adults.

Image Enhancement and Segmentation Techniques for Detection of Knee Joint Diseases: A Survey

Knee bone diseases are rare but might be highly destructive. Magnetic resonance imaging (MRI) is the main approach to identify knee cancer and its treatment. Normally, the knee cancers are pointed out with the help of different MRI analysis techniques and latter image analysis strategies understand these images. Computer-based medical image analysis is getting researcher's interest due to its advantages of speed and accuracy as compared to traditional techniques. The focus of current research is MRI-based medical image analysis for knee bone disease detection. Accordingly, several approaches for features extraction and segmentation for knee bone cancer are analyzed and compared on benchmark database. Finally, the current state of the art is investigated and future directions are proposed.

Articular-surface-based automatic anatomical coordinate systems for the knee bones

Increasing use of patient-specific surgical procedures in orthopaedics means that patient-specific anatomical coordinate systems (ACSs) need to be determined. For knee bones, automatic algorithms constructing ACSs exist and are assumed to be more reliable than manual methods, although both approaches are based on non-unique numerical reconstructions of true bone geometries. Furthermore, determining the best algorithms is difficult, as algorithms are evaluated on different datasets. Thus, in this study, we developed 3 algorithms, each with 3 variants, and compared them with 5 from the literature on a dataset comprising 24 lower-limb CT-scans. To evaluate algorithms’ sensitivity to the operator-dependent reconstruction procedure, the tibia, patella and femur of each CT-scan were each reconstructed once by three different operators.Our algorithms use principal inertia axis (PIA), cross-sectional area, surface normal orientations and curvature data to identify the bone region underneath articular surfaces (ASs). Then geometric primitives are fitted to ASs, and the ACSs are constructed from the geometric primitive points and/or axes. For each bone type, the algorithm displaying the least inter-operator variability is identified. The best femur algorithm fits a cylinder to posterior condyle ASs and a sphere to the femoral head, average axis deviations: 0.12°, position differences: 0.20 mm. The best patella algorithm identifies the AS PIAs, average axis deviations: 0.91°, position differences: 0.19 mm. The best tibia algorithm finds the ankle AS center and the 1st PIA of a layer around a plane fitted to condyle ASs, average axis deviations: 0.38°, position differences: 0.27 mm.

Clinical applications of a computed tomography color "marrow mapping" algorithm to increase conspicuity of nondisplaced trabecular fractures.

To explore clinical applications of a novel conventional computed tomography (CT) color post-processing algorithm to increase conspicuity of nondisplaced trabecular fractures. The algorithm was created in Adobe Photoshop and Adobe Extendscript, utilizing DICOM images from conventional CT as source images. A total of six representative cases were selected and processed. No statistical analyses were performed. A total of six cases are demonstrated, five with MRI correlation demonstrating corresponding fractures and bone marrow edema, including a case of sacral insufficiency fracture, two cases of vertebral body fracture, two cases of nondisplaced hip fracture, and a knee bone marrow edema lesion (without MRI correlate). All cases were processed successfully without error. A conventional CT color post-processing algorithm may be clinically useful in increasing conspicuity of nondisplaced fractures and bone marrow edema. A potential pitfall is the presence of subchondral or marrow sclerosis, which may mimic edema. Future prospective studies will be necessary to evaluate diagnostic performance.

The Quality of Online Resources Available to Patients Interested in Knee Biologic Therapies Is Poor.

As the use of biologic therapies for the management of knee pathology continues to expand, it is more likely that patients will turn to the Internet to gather information on this topic. Given the lack of scientific consensus on the use of biologics, care providers must understand what information is available online. The purpose of this study was to evaluate the quality of websites that patients may use to educate themselves on knee biologics. Websites were identified using search terms relevant to multiple biologic therapies available for knee pathology. Websites were scored based on an author-derived grading rubric, with a total of 25 possible points relating to the role of knee biologics in the diagnosis, evaluation, and treatment of knee pathology. Websites were categorized based on the source (e.g., physician-operated website vs. industry-related website). Reading level was assessed with the Flesch-Kincaid readability test. The initial search yielded 375 results, with 96 websites meeting final inclusion criteria. Mean website score was poor, at 6.01 of the 25 possible points (24.0%). Physician websites were the most common, with 60% of the articles identified. Industry-related websites scored the lowest (mean, 3.2 ± 0.97) while hospital-related websites scored the highest (mean, 8.3 ± 2.93). Overall, websites published from hospitals or orthopedic professional societies had significantly higher scores than other websites. The search term "knee PRP" yielded higher-quality results than "knee platelet rich plasma." Similarly, "knee BMAC" led to better results than "knee bone marrow aspirate concentrate." The average reading level was 11.4. Many online resources are available for patients seeking information about knee biologic therapies, but the quality of websites identified was very poor. Patients should be counseled that the information available online for knee biologic therapy is unreliable. Surgeons should play an increased role in providing resources to patients and educating them on biologic options.

Concurrent Assessment of Cartilage Morphology and Bone Microarchitecture in the Human Knee Using Contrast-Enhanced HR-pQCT Imaging

Osteoarthritis (OA) is a prevalent articular disease characterized by whole joint degradation, including articular cartilage and bone. Presently, no single imaging modality is well suited to concurrently capture these changes. Recent ex vivo animal studies have demonstrated the efficacy of utilizing contrast agents in conjunction with micro-CT as a means of evaluating cartilage and bone alterations concurrently, though no work as of yet has been performed in large animal models or humans. This study sought to develop and validate a novel joint imaging technique, contrast enhanced high resolution peripheral quantitative computed tomography (CEHR-pQCT), to concurrently assess bone microarchitecture and cartilage morphology in the whole human knee. Fresh frozen cadaveric knees were harvested (n = 10) and scanned using magnetic resonance imaging (MRI), HR-pQCT without contrast, and HR- pQCT following intra-articular injection of nonionic contrast media. Cartilage morphology and bone microarchitecture were evaluated in weight bearing regions of interest in both the tibia and femur. Joints were then disarticulated, and the articular cartilage thickness measured by needle probe. Measures of cartilage morphology, thickness and volume, were found to be significantly less when measured by CEHR- pQCT compared to magnetic resonance imaging in all regions. Compared to needle probing, cartilage thickness measured by CEHR-pQCT was less in the lateral tibia and greater in the medial tibia. Bone microarchitecture was found to be significantly different when measured with CEHR-pQCT compared to HR-pQCT, where cortical bone mineral density (BMD) was depressed, and trabecular bone mineral density was greater. This study demonstrates that CEHR-pQCT can be used to concurrently measure cartilage morphology and bone microarchitecture; however, systematic errors impact both measures. This is the first study using contrast media in combination with HR-pQCT in whole joints. Additionally, all imaging parameters, as well as the contrast media, were selected to be directly transferable to in vivo studies, laying the foundation to perform in vivo scanning of knee cartilage and bone.

Selection of Reference Axis for Distal Femoral Rotation in TKA: A Literature Review

Total knee arthroplasty (TKA) is widely accepted and standard surgical procedure for osteoarthritis. Most patients are able to recover their preoperative pain completely and achieve a good range of motions to perform daily tasks after TKA. However, there is a number of patients who remained unsatisfied with the result after TKA and often complain pain in performing daily task. Exploring reason behind post-operative pain and failure of TKA; researchers had found that in 31.2% of these cases; failure is due to aseptic loosening. Aseptic loosening is closely related to improper component placement. Orienting component in the axial direction is critical for proper outcome of TKA. Measured resection and gap balancing are two methods used for rotational alignment of component. Studies have shown that the measured resection technique has an advantage over gap balancing. However, the outcome of measured resection technique depends on the proper selection of reference axis. Transepicondyle axis, Whiteside line and Posterior condyle line are mostly used for setting the component rotation in TEA. All three rotational axis has its own advantages and pitfalls, therefore selection of reference should be based upon knee bone morphology and diseased condition. Malalignment of component placement in the axial plane may cause patella maltracking, anterior knee pain, aseptic loosening and also it could be one of the reasons behind TKA revision. The Success of rotational alignment depends upon proper preoperative planning and accurately selection of landmarks involved in creating axis. In this review paper, Pros and cons of reference axis are discussed individually and their correlations with each other are explored based on existing literature.

Application of MRI in diagnosis of transient dislocation of patella

To explore the diagnostic value of MRI in the transient dislocation of the patella. The DR and MRI data of 35 patients with acute patellar transient dislocation from January 2015 to December 2017 were retrospectively analyzed, including 12 males and 23 females, ranging in age from 10 to 23 years old, with an average of 17 years old. The differences between DR and MRI diagnosis and surgical or discharge diagnosis were compared, and the difference between them in diagnosis of knee anatomical position, bone injury, signs and soft tissue injury were compared. The R statistical software WiLcoxon signed rank test (WiLcoxon signed rank test) was used for statistical analysis. All 35 MRI findings were completely consistent with postoperative or discharge diagnosis. According to MRI, 7 cases of high patella and 7 cases of patella subluxation were diagnosed. According to DR, 7 cases of high patella and 0 cases of patella subluxation were diagnosed. Fourteen dislocations were diagnosed by MRI and 7 dislocations were diagnosed by DR. There was statistically significant difference between the two methods in the diagnosis of abnormal position of patella(v=10, P<0.05). Total 112 cases of bone injuries were diagnosed by MRI, and 0 was diagnosed by DR. There was statistically significant difference between the two methods in the diagnosis of bone injuries(v=16, P<0.05). Total 43 cases of soft tissue injuries were diagnosed by MRI, and 0 was diagnosed by DR. There was statistically significant difference between the two methods in the diagnosis of soft tissue injuries (v=21, P<0.05). Total 35 cases of hydrops of the knee joint were diagnosed by MRI, and 30 were diagnosed by DR. There was statistically significant difference between the two methods in the diagnosis of hydrops of the knee joint(v=32, P>0.05). MRI is superior to DR in the diagnosis of acute temporal bone dislocation. MRI should be used as the first choice for imaging diagnosis of acute temporal bone dislocation. It can avoid missed diagnosis and misdiagnosis.

Association of childhood adiposity measures with adulthood knee cartilage defects and bone marrow lesions: a 25-year cohort study

To describe the associations between childhood adiposity measures and adulthood knee cartilage defects and bone marrow lesions (BMLs) measured 25 years later. 327 participants from the Australian Schools Health and Fitness Survey (ASHFS) of 1985 (aged 7-15 years) were followed up 25 years later (aged 31-41 years). Childhood measures (weight, height and skinfolds) were collected in 1985. Body mass index (BMI), overweight status and fat mass were calculated. Participants underwent 1.5T knee magnetic resonance imaging (MRI) during 2008-2010, and cartilage defects and BMLs were scored from knee MRI scans. Log binomial regressions were used to examine the associations. Among 327 participants (47.1% females), 21 (6.4%) were overweight in childhood. Childhood adiposity measures were associated with the increased risk of adulthood patellar cartilage defects (Weight relative risk (RR) 1.05/kg, 95% confidence interval (CI) 1.01-1.09; BMI 1.10/kg/m2, 1.01-1.19; Overweight 2.22/yes, 1.21-4.08; fat mass 1.11/kg, 1.01-1.22), but not tibiofemoral cartilage defects. Childhood adiposity measures were not significantly associated with adulthood knee BMLs except for the association between childhood overweight status and adulthood patellar BMLs (RR 2.87/yes, 95% CI 1.10-7.53). These significant associations persisted after adjustment for corresponding adulthood adiposity measure. Childhood adiposity measures were associated with the increased risk of adulthood patellar cartilage defects and, to a lesser extent, BMLs, independent of adulthood adiposity measures. These results suggest that adiposity in childhood has long-term effects on patellar structural abnormalities in young adults.