Kellgren-Lawrence Grading System Research Articles

Interobserver Agreement and Performance of Concurrent AI Assistance for Radiographic Evaluation of Knee Osteoarthritis.

Background Due to conflicting findings in the literature, there are concerns about a lack of objectivity in grading knee osteoarthritis (KOA) on radiographs. Purpose To examine how artificial intelligence (AI) assistance affects the performance and interobserver agreement of radiologists and orthopedists of various experience levels when evaluating KOA on radiographs according to the established Kellgren-Lawrence (KL) grading system. Materials and Methods In this retrospective observer performance study, consecutive standing knee radiographs from patients with suspected KOA were collected from three participating European centers between April 2019 and May 2022. Each center recruited four readers across radiology and orthopedic surgery at in-training and board-certified experience levels. KL grading (KL-0 = no KOA, KL-4 = severe KOA) on the frontal view was assessed by readers with and without assistance from a commercial AI tool. The majority vote of three musculoskeletal radiology consultants established the reference standard. The ordinal receiver operating characteristic method was used to estimate grading performance. Light kappa was used to estimate interrater agreement, and bootstrapped t statistics were used to compare groups. Results Seventy-five studies were included from each center, totaling 225 studies (mean patient age, 55 years ± 15 [SD]; 113 female patients). The KL grades were KL-0, 24.0% (n = 54); KL-1, 28.0% (n = 63); KL-2, 21.8% (n = 49); KL-3, 18.7% (n = 42); and KL-4, 7.6% (n = 17). Eleven readers completed their readings. Three of the six junior readers showed higher KL grading performance with versus without AI assistance (area under the receiver operating characteristic curve, 0.81 ± 0.017 [SEM] vs 0.88 ± 0.011 [P < .001]; 0.76 ± 0.018 vs 0.86 ± 0.013 [P < .001]; and 0.89 ± 0.011 vs 0.91 ± 0.009 [P = .008]). Interobserver agreement for KL grading among all readers was higher with versus without AI assistance (κ = 0.77 ± 0.018 [SEM] vs 0.85 ± 0.013; P < .001). Board-certified radiologists achieved almost perfect agreement for KL grading when assisted by AI (κ = 0.90 ± 0.01), which was higher than that achieved by the reference readers independently (κ = 0.84 ± 0.017; P = .01). Conclusion AI assistance increased junior readers' radiographic KOA grading performance and increased interobserver agreement for osteoarthritis grading across all readers and experience levels. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Subchondral bone expansion in advanced knee osteoarthritis: Relation with radiographic severity and role in surgical decision-making

BackgroundJoint space width (JSW) is a traditional imaging marker for knee osteoarthritis (OA) severity, but it lacks sensitivity in advanced cases. We propose tibial subchondral bone area (TSBA), a new CT imaging marker to explore its relationship with OA radiographic severity, and to test its performance for classifying surgical decisions between unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) compared to JSW. MethodsWe collected clinical, radiograph, and CT data from 182 patients who underwent primary knee arthroplasty (73 UKA, 109 TKA). The radiographic severity was scored using Kellgren-Lawrence (KL) grading system. TSBA and JSW were extracted from 3D CT-reconstruction model. We used independent t-test to investigate the relationship between TSBA and KL grade, and binary logistic regression to identify factors associated with TKA risk. The accuracy of TSBA, JSW and established classification model in differentiating between UKA and TKA was assessed using AUC. ResultsAll parameters exhibited inter- and intra-class coefficients greater than 0.966. Patients with KL grade 4 had significantly larger TSBA than those with KL grade 3. TSBA (0.708 of AUC) was superior to minimal/average JSW (0.547/0.554 of AUC) associated with the risk of receiving TKA. Medial TSBA, together with gender and Knee Society Knee Score, emerged as independent classification factors in multivariate analysis. The overall AUC of composite model for surgical decision-making was 0.822. ConclusionTibial subchondral bone area is an independent imaging marker for radiographic severity, and is superior to JSW for surgical decision-making between UKA and TKA in advanced OA patients.

The tipping point in medial opening wedge high tibial osteotomy relates to the shape of the proximal tibia more than to lower limb alignment correction.

The tipping point (TP) of the knee joint isthe centre of rotation of the joint in the coronal plane. This study aimed to define the TP in medial opening wedge high tibial osteotomy (MOWHTO). Data from 154 consecutive patients with varus knee malalignment, who underwent MOWHTO between 2017 and 2021, was retrospectively reviewed. The degree of preoperative osteoarthritis (OA), using the Kellgren-Lawrence (KL) grading system,was recorded. Long-leg standing radiographs were used to record the alignment parameters, including the hip-knee-ankle angle (HKA), the mechanical lateral distal femoral angle (mLDFA), the medial proximal tibial angle (MPTA), the joint line convergence angle (JLCA) and the joint line obliquity (JLO) angle. Postoperative Tegner activity scores, Western Ontario and McMaster University Scoresand patients'satisfaction were recorded. To define the TP, the relationship of all variables to Δ JLCA (absolute difference between preoperative to postoperative JLCA values) was analysed. Linear regression was employed for Δ JLCA to preoperative JLCA and postoperative and Δ MPTA (absolute difference between preoperative and postoperative values). K-means clustering was used to partition observations into clusters, in which each observation belongs to the cluster with the nearest mean serving as a prototype of the cluster, and analysed if there was any specific threshold influencing Δ JLCA. After defining the TP, further subanalysis of the TP based on the preoperative KL OA grade and analysis of variance of this TP to the KL OA grade was performed. A total of 154 patients (77.9% males and 22.1% females) were included. The mean age was 48.2 ± 11 years, and the mean body mass index was 27.1 ± 4 kg/m2. Preoperatively, 26 (16.9%) patients had KL grade IV OA. The mean preoperative and postoperative JLCA and the significance of their relation to Δ JLCA were 2.6° ± 1.8° (p < 0.0001) and 1.9° ± 1.8° (p = 0.6), respectively. The mean Δ JLCA was 1.4° ± 1.5°. The mean pre- and postoperative MPTA and the significance of their relation to Δ JLCA were 84.6 ± 2.2 (p = 0.005) and 91.8 ± 2.5 (p < 0.0007), respectively. The mean Δ MPTA was 7.2 ± 2.3 (p = 0.3). The mean preoperative and postoperative HKA and the significance of their relation to Δ JLCA were 174.6 ± 2.5 (p = 0.2) and 181.9 ± 2.4 (p = 0.7), respectively. The overall linear regression for Δ JLCA was statistically significant for preoperative JLCA (R2 = 0.3, p < 0.0001) and postoperative MPTA (R2 = 0.09, p = 0.0001) and statistically insignificant for Δ MPTA (R2 = 0.01, p = 0.2)and postoperative HKA (R2 = 0.04, p = 0.7). MPTA > 91.5° was the optimal threshold dividing this series data set between substantial and nonsignificant Δ JLCA. In this study, the main predictive factors for intra-articular correction (Δ JLCA) after MOWHTO were the preoperative value of JLCA and the postoperative value of MPTA. A value of 92° for postoperative MPTA is potentially the optimal threshold to predict intra-articular correction. Level IV, retrospective cohort study.

Association Between Pain and Radiological Changes in Patients with Knee Osteoarthritis

Background: Knee osteoarthritis (OA) is a leading cause of disability worldwide, characterized by joint degeneration, pain, and functional limitations. Despite the prevalence of knee OA, the relationship between radiographic changes and the severity of pain remains complex. Previous studies have offered conflicting views on the association between structural joint alterations and clinical symptoms. Objective: The aim of this study was to investigate the association between radiographic degenerative changes in the knee, as classified by the Kellgren and Lawrence grading system, and the severity of resting pain measured using the Numeric Pain Rating Scale (NPRS). Methods: This cross-sectional study was conducted on 70 patients diagnosed with knee OA at multiple healthcare facilities in Lahore, Pakistan, from July 2022 to January 2023. Participants aged between 40 and 80 years, both males and females, were included. The severity of knee OA was determined using the Kellgren-Lawrence grading system through X-ray evaluations. Pain severity was assessed using the NPRS. Data were analyzed using SPSS version 25.0, with chi-square tests applied to explore the association between radiographic grades of knee OA and pain severity. Results: The distribution of knee OA severity among participants was as follows: Grade I (22.9%), Grade II (25.7%), Grade III (32.9%), and Grade IV (18.6%). Pain severity reported by participants was predominantly mild (55.7%), followed by moderate (37.1%) and severe (7.1%). Statistical analysis revealed a significant association between the grade of knee OA and the severity of resting pain (Chi-square = 30.06, p &lt; 0.0001), indicating that higher grades of knee OA were correlated with increased pain severity. Conclusion: The study confirmed a significant association between radiographic degenerative changes in knee OA and the severity of resting pain. These findings suggest the need for comprehensive clinical assessments in patients with knee OA, incorporating both radiographic evaluations and pain severity measures to guide management and treatment strategies.

Positive Effect of a Financial Incentive on Radiologist Compliance With Quality Metric Placement in Knee Radiography Reports

PurposeOngoing quality improvement (QI) processes in the authors’ department include the insertion of a Kellgren-Lawrence (KL) osteoarthritis grading template in knee radiography reports to decrease unnecessary MRI. However, uniform adoption of this grading system is lacking. Department-wide financial incentives were instituted to improve compliance with QI metrics. The purpose of this study was to evaluate the effect of a financial incentive on KL grading system use and to compare compliance rates of musculoskeletal (MSK) radiologists with those of general radiologists who were not financially incentivized to use KL grading. MethodsPercentages of all knee radiography reports containing KL grading with standardized follow-up recommendations were determined by querying the departmental radiology database before and after the introduction of the new quality-based financial incentive. Preincentive compliance rates for MSK and general radiologists were compared with an adoption period and two separate 6-month postincentive periods. ResultsIn total, 52,673 reports were retrospectively analyzed for KL grading use (41,670 reports interpreted by MSK radiologists and 11,003 interpreted by general radiologists). Increase in compliance was greatest among MSK radiologists’ reports during the incentivized adoption period (from 36.1% to 53.2%). This improvement was sustained among MSK radiologists and averaged 62.7% during the most recently studied postimplementation period. A lesser degree of improvement in compliance was observed in nonincentivized general radiologists’ reports (from 19.3% to 27.5%); during the postimplementation follow-up period, their compliance decreased to 26.5%. ConclusionsThe introduction of a financial incentive resulted in significantly increased adoption of QI practices with sustained improvement among incentivized MSK radiologists compared with nonincentivized general radiologists.

Assessing the Correlation between the Radiological, Macroscopic and Histological Examination of Degenerative Changes of Articular Surfaces in Knee Osteoarthritis with Varus Deformity

Our study aims to compare the results of preoperative radiography and intraoperative visual assessment of the cartilage with histological assessment of joint surfaces of the medial and lateral compartments resected in patients during the total knee replacement. The cohort included 20 patients (9 men and 11 women) with the mean age of 66.6 (±7.0) years who met the inclusion criteria of the study. Degenerative changes of the knee joint seen on a preoperative weight-bearing anteroposterior X-ray were evaluated according to the Kellgren-Lawrence grading system separately for the medial and lateral compartment. Based on the visual appearance, the condition of articular surfaces was assessed using the International Cartilage Repair Society Score (ICRS Grade). The histological assessment of degenerative changes was conducted by a pathologist with the use of the Osteoarthritis Research Society International Osteoarthritis Cartilage Histopathology Assessment System based on six grades of articular cartilage degeneration. The mean degree of degenerative changes based on the radiological classification was assessed as 3.5 (±0.6) for the medial compartment and 2.1 (±0.4) for the lateral compartment. The visually assessed chondropathy according to the ICRS Grade was 3.7 (±0.6) for the medial femoral condyle and 1.8 (±1.0) for the lateral femoral condyle. The histological score obtained using the Osteoarthritis Research Society International Osteoarthritis Cartilage Histopathology Assessment was 4.9 (±1.1) for the medial femoral condyle and 2.4 (±0.7) for the lateral femoral condyle. In respect of the medial compartment, there was no statistically significant parametric correlation between the intraoperative visual assessment of the cartilage degeneration and the preoperative radiological grade r = 0.45. The histological assessment showed a statistically significant concordance both with the degree of chondropathy r = 0.76 and the radiological grade r = 0.64. In the lateral compartment, the parametric test showed a statistically significant concordance only between the radiological grade and the histological score r = 0.72. The correlation between the visual assessment of chondropathy and the radiological grade r = 0.27 as well as the histological score r = 0.24 was very low. In our cohort assessing the early degenerative changes of the lateral compartment as well as the more advanced degenerative changes of the medial compartment, the correlation between the intraoperative assessment of cartilage degeneration as a diagnostic method to examine the lateral compartment and the preoperative radiological grade was not confirmed. Our results failed to confirm a better reporting value of the visual cartilage degeneration assessment of the lateral compartment as against the preoperative X-ray. The space width without narrowing on an X-ray has no reporting value for this compartment in case of varus deformity. The results clearly indicate that the assessment of macroscopic appearance of the cartilage degeneration during arthroscopy does not necessarily guarantee good long-term clinical outcomes after high tibial osteotomy. The respective degrees of cartilage degeneration identified during the intraoperative visual assessment and the radiological grading of osteoarthritic changes did not correlate in either compartment. In the lateral compartment, the initial radiological and histological findings preceded the visually detectable cartilage changes. knee, cartilage, osteoarthritis, radiology, histology, arthroscopy, osteotomy.

Deep Learning-based Automated Knee Joint Localization in Radiographic Images Using Faster R-CNN.

Osteoarthritis is a condition that poses a risk to the knee joint, resulting in pain and impaired function. However, traditional knee X-ray evaluations using the Kellgren-Lawrence grading system have proven to be inefficient. These evaluations are subjective, time-consuming, and labor-intensive, particularly in busy hospital settings. The objective of this research was to present a deep learning-based approach that can detect knee joint regions in medical images. By addressing the limitations of traditional methods, the aim was to develop a more efficient and automated approach for knee joint analysis. The proposed method utilizes the Faster R-CNN model, which consists of a region proposal network (RPN) and Fast R-CNN. The RPN generates region proposals that potentially contain knee joint regions, while the Fast R-CNN network categorizes and extracts features from these proposals. To train the model, a dataset of knee joint images was employed. The performance of the model was evaluated using metrics, such as accuracy, precision, recall, F1-score, and mean IoU (Intersection Over Union). The results demonstrated the high accuracy of the proposed method in detecting knee joint regions. The model achieved a mean IoU of 94.5, indicating a strong overlap between the predicted and ground truth regions. These findings highlight the potential of deep learning-based approaches in automating medical image analysis, specifically in the diagnosis and management of knee joint disorders. This study emphasizes the significance of leveraging advanced technologies, such as deep learning, in medical imaging. By developing more efficient and accurate methods for identifying knee joint regions in medical images, it becomes feasible to enhance patient outcomes and healthcare delivery. The proposed deep learning-based approach showcases promising results, paving the way for further advancements in the field of medical image analysis and contributing to improved diagnostic capabilities for knee joint disorders.

Can bone scintigraphy reflect the progression of osteoarthritis after unicompartmental knee arthroplasty?

Bone scintigraphy (BS) has been reported to be a useful predictor of osteoarthritis (OA) progression in primary knee OA. However, no previous studies have explored the relationship between BS and OA progression in the retained compartments after unicompartmental knee arthroplasty (UKA). Thus, we evaluated whether OA progresses to other compartments in patients who undergo UKA and if increased uptake on BS is associated with OA progression in other compartments after UKA. A total of 41 patients with knee BS at least five years after UKA were included. Radiographic OA progression in other compartments was assessed by grading and comparing OA severity in each patient using the Kellgren-Lawrence grading system (K-L grade) and Osteoarthritis Research Society International (OARSI) atlas score. After UKA, the correlation between BS uptake and radiographic OA progression was analyzed in each retained compartment. A correlation analysis was also performed to evaluate the association between BS uptake and OA progression grades. A significant progression of OA was observed in both contralateral tibiofemoral and patellofemoral compartments after UKA at 98.5 ± 26.0 months of follow-up (all p<0.001). No correlation was found between BS uptake and radiographic OA progression nor between BS uptake and radiographic OA progression grade in the contralateral and patellofemoral compartments. Following UKA, OA progresses in the retained contralateral tibiofemoral and patellofemoral compartments over a minimum five-year follow-up period. Thus, BS is ineffective in assessing the progression of OA in these compartments.

Assessment of a novel deep learning-based software developed for automatic feature extraction and grading of radiographic knee osteoarthritis

BackgroundThe Kellgren-Lawrence (KL) grading system is the most widely used method to classify the severity of osteoarthritis (OA) of the knee. However, due to ambiguity of terminology, the KL system showed inferior inter- and intra-observer reliability. For a more reliable evaluation, we recently developed novel deep learning (DL) software known as MediAI-OA to extract each radiographic feature of knee OA and to grade OA severity based on the KL system.MethodsThis research used data from the Osteoarthritis Initiative for training and validation of MediAI-OA. 44,193 radiographs and 810 radiographs were set as the training data and used as validation data, respectively. This AI model was developed to automatically quantify the degree of joint space narrowing (JSN) of medial and lateral tibiofemoral joint, to automatically detect osteophytes in four regions (medial distal femur, lateral distal femur, medial proximal tibia and lateral proximal tibia) of the knee joint, to classify the KL grade, and present the results of these three OA features together. The model was tested by using 400 test datasets, and the results were compared to the ground truth. The accuracy of the JSN quantification and osteophyte detection was evaluated. The KL grade classification performance was evaluated by precision, recall, F1 score, accuracy, and Cohen's kappa coefficient. In addition, we defined KL grade 2 or higher as clinically significant OA, and accuracy of OA diagnosis were obtained.ResultsThe mean squared error of JSN rate quantification was 0.067 and average osteophyte detection accuracy of the MediAI-OA was 0.84. The accuracy of KL grading was 0.83, and the kappa coefficient between the AI model and ground truth was 0.768, which demonstrated substantial consistency. The OA diagnosis accuracy of this software was 0.92.ConclusionsThe novel DL software known as MediAI-OA demonstrated satisfactory performance comparable to that of experienced orthopedic surgeons and radiologists for analyzing features of knee OA, KL grading and OA diagnosis. Therefore, reliable KL grading can be performed and the burden of the radiologist can be reduced by using MediAI-OA.

Conventional Radiography of Grade III Knee Osteoarthritis: A Case Report

Introduction: Osteoarthritis (OA) is the most common form of inflammatory joint disease. It occurs most frequently in the knees, hips, the spine (vertebrae), and ankles. Radiological prevalence of knee OA in Indonesia reaches 15.5% in men and 12.7% in women aged between 40-60 years. X-ray imaging is routinely used in clinical practice to confirm knee OA diagnosis and in clinical research to monitor the progression of knee OA. Case report: A 62-year-old female patient presented with knee pain in both knees that had been ongoing for the past 6 months. The pain was described as throbbing and stabbing, the right knee worse affected than the left. Palpation elicited tenderness, crepitus in both joints and did not reveal any deformities. Radiological AP/Lateral X-ray of the right knee revealed evidence of osteophytes, sclerosis and narrowing joint space, leading to the impression of Grade III osteoarthritis in the right knee. Discussion: Joint pain is the chief complaint that leads patients with knee osteoarthritis to seek medical attention. Pain typically worsens with movement and decreases with rest. In diagnosing OA, an AP/Lateral radiographic examination of the right knee is conducted, revealing the presence of osteophytes, subchondral bone sclerosis and accompanied by slight joint narrowing. This impression aligns with the Grade III OA criteria according to the Kellgren-Lawrence grading system. Conclusion: Diagnosis of osteoarthritis involves a comprehensive approach combining medical history, physical examination, and diagnostic tests. Radiographic examinations including conventional radiography play a significant role in diagnosing OA. In the early stages of the disease, joint radiographs may still appear normal. The severity of knee OA can be evaluated using the Kellgren-Lawrence (KL) grading scheme which ranges from grade 0 to grade 4. Keywords: Knee Osteoarthritis, Conventional Radiography, The Kellgren-Lawrence Grading

Investigation of Vitamin D Status, Age, and Body Mass Index as Determinants of Knee Osteoarthritis Severity Using the Kellgren-Lawrence Grading System in a Saudi Arabian Cohort: A Cross-Sectional Study.

Background Knee osteoarthritis (OA) is a common and disabling condition affecting millions worldwide. This cross-sectional study endeavors to investigate the relationship between vitamin D status, age, body mass index (BMI), and knee OA in a cohort of individuals in Saudi Arabia. Methods In this cross-sectional study, we assessed vitamin D serum levels, conducted knee radiographs, and evaluated the severity of knee OA using the Kellgren-Lawrence grading system (KLGS). The analysis incorporated both descriptive and inferential statistics, including chi-square tests and a regression model to investigate the relationship between KLGS grades as indicators of knee OA severity and vitamin D levels, considering demographics as covariants. Results The study included 93 participants with suspected knee OA, of which a substantial portion of the sample population presented with knee OA (58 [62.4%]). Knee OA exhibited a higher prevalence among females, comprising 47 (50.54%) of the total, while 11 (11.83%) were male. The largest age group with knee OA was those older than 58 years, 27 (29.03%), followed by the age group of 48-58 years, 19 (20.43%). Obesity was a prevalent factor among knee OA patients (36 [38.7%]), with grade 2 (17 [18.3%]) and grade 3 (24 [25.8%]) being the most frequent. Vitamin D deficiency was prevalent in 54 (58%) of patients. Among knee OA cases, bilateral involvement was predominant in 46 (79%), with a substantial portion, 36 (62%), presenting deficient vitamin D levels. The regression model revealed that age (95% CI: 0.54-1.03, p < 0.001) and BMI (95% CI: 0.01-0.60, p = 0.04) significantly predict higher KLGS grades, indicating that increasing age and higher BMI are associated with higher KLGS grades. However, Vitamin D levels did not show a significant impact on the severity of knee OA. Conclusions The findings from this study highlight the importance of monitoring and maintaining adequate vitamin D levels to potentially reduce the risk of knee OA and the need for early detection and intervention to manage knee OA, particularly in females, older poplulation, and obese adults. They may guide healthcare providers in developing comprehensive approaches to reduce the risk of this condition.

The relation of psychological status and type D personality with central sensitization in knee osteoarthritis: everything is in your mind!

To evaluate the relation of psychosocial parameters and type D personality with central sensitization in knee osteoarthritis (OA). The study included 126 patients with knee OA according to the American College of Rheumatology criteria. Sociodemographic variables (age, gender, education, marital status, annual income), alcohol consumption/smoking, body mass index, comorbidities, and duration of symptoms were noted. Radiographic evaluation was performed according to the Kellgren-Lawrence grading system. The Western Ontario and McMaster Universities Osteoarthritis Index was used for clinical evaluation. Type D personality, negative affectivity, and social inhibition were evaluated using the type D Scale-14 (DS14). Central sensitization was assessed by the central sensitization inventory (CSI), while psychological status, quality of life, and sleep were assessed by the Hospital Anxiety and Depression Scale (HADS), an abbreviated version of the World Health Organization Quality of Life Instrument (WHOQOL-BREF), and the Jenkins Sleep Evaluation Scale (JSS), respectively. The effect of type D personality on study parameters including central sensitization, as well as the risk factors for the development of central sensitization were assessed by regression analyses. Patients with type D personality had higher CSI, HADS scores and lower WHOQOL-BREF scores for psychological health, social relationship, environment and general quality of life. Linear regression analysis showed that the DS14 total score has a significant positive relation with CSI (β = 0.4, p < 0.05), HADS-depression (β = 0.4, p < 0.05), HADS-anxiety (β = 0.5, p < 0.05), and HADS-total scores (β = 0.5, p < 0.05). It also had a significant negative effect on all domains of WHOQOL-BREF (p < 0.05 for all). Logistic regression analysis revealed that JSS [Odds ratio (OR) 0.83, 95% CI 0.73-0.94; p = 0.003] and negative affectivity (OR 0.78, 95% CI 0.65-0.94; p = 0.008) were independent risk factors for the development of central sensitization in knee OA. Type D personality has an impact on quality of life, central sensitization, and psychological health, with negative affectivity and sleep impairment serving as independent risk factors for central sensitization. While managing patients with knee OA, these intimate relationships should be taken into consideration.

Evaluating the efficacy of deep learning models for knee osteoarthritis prediction based on Kellgren-Lawrence grading system

Osteoarthritis of the knee, also known as OA has been determined that osteoarthritis of the knee is the leading cause of activity limitations and the development of disability, particularly in people who are older. The utilisation of artificial intelligence (AI) methodologies grounded in deep learning (DL) has yielded promising outcomes in the realm of radiographic interpretation. The utilisation of deep learning in the healthcare industry has yielded remarkable outcomes and elevated the benchmark for the quality of medical treatment. This study used knee OA as a clinical scenario to compare twelve transfer learning DL models for detecting the grade of KOA from a radiograph, compared their accuracy, and determined the best model for detecting KOA. The models exhibited a range of 30% to 98% in detecting the KOA. It was determined that MobileNet was responsible for the highest level of accuracy, which came in at 98.36%. It has high training and validation accuracy. The maximum loss was observed for EfficientNetB7. DL approaches created by skilled radiologists and orthopaedic specialists could help smaller hospitals learn and make more emergency room. This would be especially helpful in situations when medical personnel may not be available.

Anterior and posterior hip osteoarthritis: prevalence and potential value of CT compared to radiographs.

To determine the added value of computed tomography (CT) to identify severe hip osteoarthritis (OA). A retrospective query of all cases of hip or knee arthroplasty planning CTs between January 2018 and March 2022 was performed. Age, sex, and symptoms were collected from the medical record. CTs were evaluated for the degree of osteoarthritis and classified using an adapted Kellgren-Lawrence (KL) grading system in the anterior, posterior, superior, and superomedial hip. Frontal hip or pelvis radiographs within 1 year of the CT were also graded. There were 265 eligible hips in 178 subjects, age 66 ± 11 (range 31-93) years, with 85/178 (48%) males and 93/178 (52%) females, and 127/265 (48%) right and 138/265 (52%) left hips. The posterior hip joint was the most common location for grade 2/3 OA (20%), followed by superior hip joint (14%). Anterior or posterior grade 2/3 OA occurred concurrently with superior or superomedial grade 2/3 OA in 32/68 (47%) of hips. Grade 2/3 OA was detected on CT more commonly than on XR both in the superior (14 vs 8.6%, P = 0.0016) and superomedial (8.7 vs 4.8%, P = 0.016) hip joint. Of the 71 symptomatic hips, 22 (31%) hips demonstrated either anterior and/or posterior grade 2/3 OA on CT, and 9 (9/22, 41%) of these hips had superior or superomedial grade 0/1 OA. CT may be warranted when the patient has pain suggestive of osteoarthritis not detected on radiographs.

Effect of open-wedge high tibial osteotomy and lateral patellofemoral retinacular release on patellar position: an X-ray imaging-based comparative study.

Open-wedge high tibial osteotomy (OWHTO) may cause adverse changes in the mechanical environment of the patellofemoral joint. For patients with lateral patellar compression syndrome or patellofemoral arthritis, intraoperative management is still challenging. The effect of lateral retinacular release (LRR) on patellofemoral joint mechanics after OWHTO remains unclear. Our study aimed to evaluate the effect of OWHTO and LRR on the patellar position based on lateral and axial radiographs of the knee joint. The study comprised 101 knees (OWHTO group) undergoing OWHTO alone and 30 knees (LRR group) undergoing OWHTO and concomitant LRR. The following radiological parameters were statistically analyzed preoperatively and postoperatively: femoral tibial angle (FTA), medial proximal tibial angle (MPTA), weight-bearing line percentage (WBLP), Caton-Deschamps index (CDI), Insall-Salvati index (ISI), lateral patellar tilt angle (LPTA), and lateral patellar shift (LPS). The follow-up duration ranged from 6 to 38 months, with a mean of 13.51±6.84 months in the OWHTO group and 12.47±7.81 months in the LRR group. The Kellgren-Lawrence (KL) grading system was used to evaluate changes in patellofemoral osteoarthritis (OA). Regarding the patellar height, preliminary analysis demonstrated a statistically significant decrease in the CDI and ISI in both groups (P<0.05). However, there was no significant difference in changes in CDI or ISI between the groups (P>0.05). In the OWHTO group, although there was a significant increase in the LPTA (P=0.033), the postoperative decrease in the LPS was not significant (P=0.981). In the LRR group, both the LPTA and LPS significantly decreased postoperatively (P=0.000). The mean changes in LPS were 0.03 mm in the OWHTO group and 1.44 mm in the LRR group, indicating a significant change in LPS (P=0.000). However, there was no significant difference in changes in LPTA between the groups, which was contrary to our expectations. Imaging showed no change in patellofemoral OA in the LRR group and progressive changes (from KL grade I to II) in patellofemoral OA in 2 (1.98%) patients in the OWHTO group. OWHTO can cause a significant decrease in patellar height and an increase in lateral tilt. LRR can significantly improve the lateral tilt and shift of the patella. The concomitant arthroscopic LRR should be considered for the treatment of patients with lateral patellar compression syndrome or patellofemoral arthritis.

Effect of platelet-rich plasma scaffolding combined with osteochondral autograft transfer for full-thickness articular cartilage defects of the femoral condyle

We aimed to investigate the local application methods of platelet-rich plasma (PRP) and the effect and safety of PRP scaffolding combined with osteochondral autograft transfer (OAT) in the treatment of full-thickness articular cartilage defects of the femoral condyle. Patients with cartilage defects of the femoral condyle were treated with OAT combined with PRP scaffolding between July 2017 and December 2020. Preoperative magnetic resonance imaging (MRI) and computed tomography were utilized to assess the size, location, and severity of the osteochondral defects. X-ray and MRI images of the knee were obtained at the final follow-up to assess the osseointegration and integrity of the implanted articular cartilage. Osteoarthritic changes in the knee joint were evaluated using the Kellgren–Lawrence grading system. Clinical status was assessed using the visual analog scale (VAS), International Knee Documentation Committee (IKDC), and Lysholm scores before the treatment and at the final follow-up. Complications and patient satisfaction were recorded to assess the safety of this combination therapy. Twenty-one patients were recruited, with a mean follow-up duration of 18.23 ± 6.84 months. The mean lesion size was 2.3 ± 0.59 cm2. The mean platelet concentration in PRP at baseline was 6.27 ± 0.63 times greater than that in the peripheral blood. The VAS, IKDC, and Lysholm scores had improved significantly at the final follow-up (P < 0.001). No serious complications such as joint infection, deep venous thrombosis, or hematoma were observed. Eighteen patients (85.72%) were satisfied with their knee function and quality of life at the final follow-up. Three patients (14.28%) complained of mild anterior knee pain, which was relieved by oral administration of nonsteroidal anti-inflammatory drugs. MRI examinations of all patients showed bony consolidation and the defect surface was covered with cartilage-like tissue. X-ray evaluations indicated that osteoarthritis in two knees (9.5%) had progressed from grade 1 to grade 2 at the final follow-up. The preliminary results showed that OAT combined with PRP may be a safe and effective technique for the treatment of full-thickness articular cartilage defects in the knee.

Correlation between osteopontin and cartilage oligomeric matrix protein levels in joint synovial fluid of patients with knee osteoarthritis and disease severity

To investigate the correlation between osteopontin(OPN) and cartilage oligomeric matrix protein (COMP) levels in synovial fluid of patients with knee osteoarthritis(KOA) and the severity of the disease. A total of 59 patients with KOA admitted to our hospital from February 2018 to May 2020 were selected as the KOA group, including 25 males and 34 females, age ranged 60 to 75 years old with an average of(65.57±1.56) years old, the body mass index(BMI) ranged 21.4 to 30.7(26.12±1.54) kg/m2. After admission, X-ray examination was performed, and Kellgren-Lawrence(K-L) grading system was used to evaluate the X-ray examination results. There were 14 cases in gradeⅡ(K-L2 group), 27 cases in grade Ⅲ(K-L3 group), and 18 cases in grade Ⅳ(K-L4 group). Eighteen patients who underwent arthroscopy for ligament or meniscus disease without cartilage damage were selected as control group, including 7 males and 11 females, age ranged 61 to 78 years old with an average of (64.88±1.60) years old, BMI ranged 22.8 to 29.9(25.89±1.49) kg/m2. Before treatment, synovial fluid samples of subjects were collected, and the OPN and COMP levels of synovial fluid were detected by Elisa. The OPN and COMP levels of synovial fluid in KOA group and control group were compared. The clinical data of KOA patients with different K-L grades were collected, including gender, age and BMI. The biochemical indices of interleukin-1 β(IL-1β), OPN, COMP and matrix metalloproteinase 3(MMP-3) in synovitic fluid were detected by enzyme-linked immunoassay, and the clinical data and biochemical indices of KOA patients with different K-L grades were compared. Logistic regression was used to analyze the factors affecting the K-L classification of KOA patients, and the area under the ROC curve(AUC) was used to predict the severity of KOA. All the 59 patients were followed up for 8 to 27(15.75±3.27) months. The levels of OPN and COMP in synovial fluid in KOA group were significantly higher than those in control group (t=16.991, 17.387, P<0.001). The levels of IL-1β, OPN, COMP and MMP-3 in synovitic fluid were significantly different among those in different K-L grade KOA patients(P<0.001). Compared with the K-L2 group, the levels of IL-1β, OPN, COMP, and MMP-3 in the synovial fluid of K-L3 and K-L4 were increased (P<0.05). Compared with the K-L3 group, the levels of IL-1β, OPN, COMP, and MMP-3 in the K-L4 joint were increased (P<0.05). Multivariate Logistic regression analysis showed that the levels of OPN, COMP and MMP-3 were independent risk factors for K-L grading of KOA patients(OR=6.653, 4.229, 1.579, P<0.001). AUC of OPN in synovial fluid predicting K-L4 KOA was 0.720[95%CI(0.588-0.851)], and the sensitivity was 94.4%. the specificity was 65.9%. The AUC of COMP in synoviac fluid predicting K-L4 KOA was 0.731[95%CI(0.592-0.870)], the sensitivity was 88.9%, the specificity was 63.4%. The AUC of OPN combined with COMP in synoviac fluid predicting K-L4 KOA was 0.839 [95%CI(0.724-0.953)], the sensitivity was 94.4%, and the specificity was 51.2%. The AUC of OPN combined with COMP in synoviac fluid predicting K-L4 grade KOA was greater than that of OPN and COMP alone(Z=4.037, 3.540, P<0.05). The levels of OPN and COMP in synovial fluid increase in patients with KOA, and they increase with the increase of K-L grade. Synovitic fluid OPN and COMP are independent risk factors affecting K-L grade of KOA patients, and they have high AUC, sensitivity and specificity in predicting of K-L4 KOA, and can be used to evaluate the progression of KOA disease.

A Strong Correlation Between the Severity of Flatfoot and Symptoms of Knee Osteoarthritis in 95 Patients.

ObjectiveThe purpose of this study is to assess the association between the presence and severity of flatfoot and symptoms of knee OA.Methods95 participants with knee OA were recruited from a patient cohort at a regional hospital. Symptoms of knee OA, including knee degeneration, femorotibial alignment, pain, stiffness and dysfunction were assessed using the Kellgren-Lawrence (K-L) grading system, femoral-tibial angle (FTA), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Participants were divided into groups with flatfoot (mild, moderate and severe) and without flatfoot based on the Clarke's angle. Linear regression and ordinal logistic regression were used for statistical analysis, as appropriate.ResultsHaving flatfoot was associated with a significantly increased risk of having a higher K-L grade (OR: 20.03; 95% CI, 5.88, 68.27; p < 0.001), smaller FTA (Beta: −2.96; 95% CI, −4.41, −1.50; p < 0.001), higher pain score (Beta: 0.47; 95% CI, 0.24, 0.69; p < 0.001) and greater loss of function (Beta: 0.25; 95% CI, 0.02, 0.48; p = 0.03). Severe grades of flat feet were associated with a higher K-L grade (OR: 0.19; 95% CI, 0.08, 0.44; p < 0.001), smaller FTA (Beta: 1.51; 95% CI, 0.66, 2.35; p = 0.001), higher pain score (Beta: −0.25; 95% CI, −0.39, −0.11; p = 0.001), greater stiffness (Beta: −0.24; 95% CI, −0.38, −0.09; p = 0.002) and greater loss of function (Beta: −0.27; 95% CI, −0.41, −0.14; p < 0.001).ConclusionThe results indicated that the severity of flattening is significantly associated with symptoms of knee OA. For the conservative management of knee OA, both flatfoot and its severity should be carefully considered.

Strategy to Estimate Sample Sizes to Justify the Association between MMP1 SNP and Osteoarthritis.

Background: the impact of knee osteoarthritis (OA) poses a formidable challenge to older adults. Studies have reported that genetic factors, such as MMP1, are one of important risk factors for knee OA. Although the relationship between the genetic polymorphism of MMP1 rs1799750 and the risk of knee OA has been explored, conclusions have been nonunanimous and pending due to research sample sizes, one of determinants in studying genetic polymorphisms associated with disease. Objective: to establish a model to assess whether the genetic polymorphism of MMP1 rs1799750 is associated with knee OA based on an estimation of sample sizes. Methods: samples were collected from a case–control and meta-analysis study. In the case–control study, patients who underwent knee X-ray examinations based on the Kellgren–Lawrence Grading System (KL) as diagnostic criteria were recruited at the Health Examination Center of the Tri-Service General Hospital from 2015 to 2019. Gene sequencing was conducted using iPLEX Gold. Those with unsuccessful gene sequencing were excluded. Finally, there were 569 patients in the knee OA group (KL ≥ 2) and 534 participants in the control group (KL < 2). In the meta-analysis, we used the databases PubMed, EMBASE, and Cochrane to search for studies on the relationship between MMP1 rs1799750 and knee OA. Next, we adopted the trial sequential analysis (TSA) method to assess whether sample sizes were sufficient or not to determine the risk of the genetic polymorphism of MMP1 rs1799750 on knee OA in Caucasians and Asians. Results: in Caucasians, the MMP1 rs1799750 was not significantly associated with knee OA with an odds ratios (OR) of 1.10 (95% confidence interval, CI: 0.45–2.68). Some extra 8559 samples were needed to conclude this relationship in Caucasians by the TSA model. In Asians, neither our case–control study results (n = 1103) nor a combination of samples from the case–control and meta-analysis results showed an association between MMP1 rs1799750 and knee OA. The OR (95% CI) was 1.10 (0.81–1.49) in a combination of Asian samples. Some extra 5517 samples were needed to justify this relationship in Asians by the TSA model. Conclusions: this research shows that an extra 8559 and 5517 samples are needed in Caucasians and Asians, respectively, in order to justify the association between MMP1 rs1799750 and knee OA.

Automatic detection and classification of knee osteoarthritis using deep learning approach.

We developed a tool for locating and grading knee osteoarthritis (OA) from digital X-ray images and illustrate the possibility of deep learning techniques to predict knee OA as per the Kellgren-Lawrence (KL) grading system. The purpose of the project is to see how effectively an artificial intelligence (AI)-based deep learning approach can locate and diagnose the severity of knee OA in digital X-ray images. Selection criteria: Patients above 50years old withOAsymptoms (knee joint pain, stiffness, crepitus, and functional limitations) were included in the study. Medical experts excluded patients with post-surgical evaluation, trauma, and infection from the study. We used 3172Anterior-posterior view knee joint digital X-ray images. We have trained the FasterRCNNarchitecture to locate the knee joint space width (JSW) region in digital X-ray images and we incorporate ResNet-50 with transfer learning to extract the features. We have used another pre-trained network (AlexNet with transfer learning) for the classification of knee OA severity. We trained the region proposal network (RPN) using manual extract knee area as the ground truth image and the medical experts graded the knee joint digital X-ray images based on the Kellgren-Lawrence score. An X-ray image is an input for the final model, and the output is a Kellgren-Lawrence grading value. The proposed model identified the minimal kneeJSWarea with a maximum accuracy of 98.516%, and the overall kneeOAseverity classification accuracy was 98.90%. Today numerous diagnostic methods are available, but tools are not transparent and automated analysis ofOAremains a problem. The performance of the proposed model increases while fine-tuning the network and it is higher than the existing works. We will extend this work to grade OA in MRI data in the future.