Abnormal Knee Research Articles

Evaluation of knee articular cartilage through calcium-suppressed technique in dual-energy computed tomography

Objectives: The evaluation of knee articular cartilage is of paramount importance in diagnosing and managing musculoskeletal disorders. Accurate and non-invasive imaging techniques are essential for assessing cartilage health, guiding treatment decisions, and monitoring disease progression. The objective of this study is to assess the potential of a calcium-suppressed technique in dual-energy computed tomography (DECT) as a viable alternative to the gold standard magnetic resonance imaging (MRI) for the evaluation of knee articular cartilage. DECT is gaining momentum in musculoskeletal imaging due to its ability to differentiate tissues with high precision. By suppressing calcium signals in DECT, the cartilage can be visualized more effectively, providing valuable insights into its integrity and structural changes. This paper seeks to compare the diagnostic accuracy and overall performance of DECT with calcium suppression to conventional MRI. The findings of this research have the potential to revolutionize the way that we approach knee cartilage evaluation, making it more accessible and efficient for both clinicians and patients. This paper contributes to the ongoing efforts in advancing medical imaging and orthopedic diagnostics, ultimately improving patient outcomes and healthcare practices. Material and Methods: In this study, we included patients who had reported knee pain and were referred for both DECT and MRI examinations. To enhance cartilage visualization, calcium-suppressed images were generated through a specialized algorithm applied to spectral-based images and were then superimposed onto conventional computed tomography (CT) images for visual assessment. The structure and thickness of knee cartilage were meticulously examined, and measurements of articular cartilage thickness were taken from sagittal proton density-weighted images and calcium-suppressed images in at lateral femoral tibial, patella femoral, and medial femoral tibial region of knee. Results: The present study was done to compare the two diagnostic modalities (DECT and MRI) for assessment of cartilage thickness of patients with knee pain. Cartilage thickness was assessed at lateral femoral tibial, patella femoral, and medial femoral tibial region of knee. Cartilage thickness of only affected knee was assessed by DECT and MRI, which showed almost perfect agreement (differences non-significant) at all the regions: (Lateral femoral region 1.61 ± 0.55 mm vs. 1.62 ± 0.55; Patella femoral: 1.62 ± 0.70 vs. 1.65 ± 0.70 mm and Medial femoral tibial: 1.82 ± 0.78 vs. 1.86 ± 0.74 mm). Conclusion: This study showed that measurements of knee cartilage thickness by DECT were as reliable as that by MRI. This study compares DECT and MRI for assessing knee articular cartilage. The rationale for combining CT and MRI provides a comprehensive evaluation of bone and soft-tissue pathology, complex injuries, and pre-surgical planning. DECT excels in bone detail, while MRI excels in soft-tissue evaluation. Our findings suggest that DECT may replace MRI for cartilage thickness assessment and qualitative evaluation of knee abnormalities, offering a cost-effective alternative with improved accessibility and reduced contraindications. DECT benefits patients of knee pain with limited MRI access or with contraindications.

Factors associated with predicting knee pain using knee X-ray and personal factors: A multivariate logistic regression and XGBoost model analysis from the Nationwide Korean Database (KNHANES).

With increasing life expectancy, knee pain has become more prevalent, highlighting the need for early prediction. Although X-rays are commonly used for diagnosis, knee pain and X-ray findings do not always match. This study aims to identify factors contributing to knee pain in individuals with both normal and abnormal knee X-ray results to bridge the gap between X-ray findings and knee pain. Data from the fifth Korea National Health and Nutrition Examination Survey (KNHANES), collected from 2010 to 2012, including data from 5,191 participants, were analyzed. The focus was on epidemiological characteristics, medical histories, knee pain, and X-ray grades. Multivariate logistic regression and extreme gradient boosting (XGBoost) models were used to predict knee pain in individuals with normal and abnormal knee X-rays, categorized by Kellgren-Lawrence grades. For normal X-rays, the logistic regression model identified aging, being female, higher BMI, lower fat percentage, osteoporosis, depression, and rural living as factors associated with knee pain. The XGBoost model highlighted BMI, age, and sex as key predictors, with a feature importance >0.1. For abnormal X-rays, logistic regression indicated that aging, being female, higher BMI, osteoporosis, depression, and rural living were associated with knee pain. The XGBoost model highlighted age, BMI, sex, and osteoporosis as key predictors, with a feature importance >0.1. Aging and being female were associated with knee pain due to hormonal changes in women, as well as cartilage and bone deterioration. Lower fat percentage was significantly associated with increased pain, which might be attributable to higher activity levels. Higher BMI and osteoporosis were significantly associated with knee pain, possibly due to increased stress and reduced resistance on knee structures, respectively. Depression was identified as a key predictor of knee pain in patients with normal X-rays, potentially attributable to psychosomatic factors. The study's limitations include its cross-sectional nature, which does not allow for the establishment of causal relationships, the lack of detailed medical history such as trauma history, and recall bias due to self-reported questionnaires. Future research should address these limitations to support our hypothesis.

Sonographic and Disease Activity Findings Related With Medication Change in JIA: A Historical Cohort Study.

Musculoskeletal ultrasound (MSUS) is increasingly used to evaluate pediatric inflammatory arthritis. This study aimed to explore the relationship between MSUS findings with medication modifications in patients with juvenile idiopathic arthritis (JIA) and clinical disease activity measurements (clinical Juvenile Arthritis Disease Activity Score [cJADAS-10], active joint count [AJC], patient/parent global assessment [PPGA], and physician global assessment [PGA]). Data from patients with JIA who underwent a 12-joint (bilateral second and third metacarpophalangeal, wrist, elbow, knee, and ankle) MSUS examination during a 57-month period were collected. Patients were categorized into 2 groups: a medication change group and a control group (patients without medication change). A pediatric-specific MSUS scoring system was used to assess MSUS findings. The association between clinical and MSUS findings was examined for the study groups. A total of 38 patients, 23 in the medication change group and 15 in the control group were included. The medication change group had higher AJC, PGA, and cJADAS-10. These patients also had a statistically significant presence of abnormal knee MSUS findings. For other joints, the frequency of abnormal MSUS findings was slightly higher in patients with a medication change, but the difference was not statistically significant. No strong correlation was observed between MSUS findings and clinical disease activity measurements. Abnormal MSUS findings were not observed to be higher in patients with a change in medication except for the involvement of the knee joint. Further longitudinal studies are needed to understand the role of MSUS in the medical decision-making process in JIA.

Portable Gait Analysis of Patients With Rotating Hinge Knee Megaprosthesis Compared With Total Knee Arthroplasty.

The gait analysis of patients after surgery for tumors around the knee joint relies on the use of a three-dimensional motion capture system. However, obtaining long-term, free-standing, real-world gait data with three-dimensional gait analysis is challenging. In this study, we utilized a portable gait analyzer to collect gait data from patients who underwent rotating hinge knee megaprosthesis (RHK) and total knee arthroplasty (TKA), this study aims to compare via gait analysis patients who underwent megaprosthesis with patients with TKA. A retrospective study was conducted on eight patients with knee bone tumors (RHK group) and ten patients with knee osteoarthritis who underwent standard TKA (TKA group) from January 2018 to January 2022. Gait analysis, was conducted using the Intelligent Device for Energy Expenditure and Activity (IDEEA), and the results were compared with those of a healthy control group. The lower limb alignment of the RHK and TKA groups was evaluated, and the KSS scores of the two groups were collected and compared. Energy consumption during a 20-m walk was measured and compared among the RHK, TKA, and healthy control groups using one-way ANOVA. Paired t-tests were used to compare the operated and nonoperated limbs within groups. All patients exhibited slower walking speeds and cadence than the healthy control participants (p < 0.01), While no significant differences were found between the RHK and TKA groups. The single support time (521.15 ± 94.56 ms) of the RHK-operated limb was significantly shorter than that of the nonoperated limb (576.53 ± 77.40 ms, p = 0.004). The pulling acceleration of the RHK group (0.71 ± 0.27 G) was lower than that of the TKA group (1.04 ± 0.31 G, p = 0.029). The push-off angle in the RHK group (24.91° ± 10.91°) was significantly greater than that in the TKA group (10.64° ± 5.41°, p = 0.007). The RHK group showed significant differences between the operated and nonoperated limbs in terms of swing power, ground impact, footfall, and push-off. The RHK (0.03 ± 0.01 kcal/min/kg) and TKA (0.029 ± 0.01 kcal/min/kg) groups had significantly greater energy expenditures than did the healthy control group (0.02 ± 0.00 kcal/min/kg, p < 0.05). The comparison of HKA angles and KSS scores between the TKA and RHK groups showed statistically significant differences. A portable gait analyzer appears to be suitable for evaluating the effects of RHK. RHK patients demonstrate more pronounced gait abnormalities than TKA patients, reflected in greater energy expenditure, implying reduced walking efficiency. This suggests the need for increased energy expenditure in RHK patients to compensate for abnormal knee joint conditions during walking and maintain body balance.

MRI deep learning models for assisted diagnosis of knee pathologies: a systematic review.

Despite showing encouraging outcomes, the precision of deep learning (DL) models using different convolutional neural networks (CNNs) for diagnosis remains under investigation. This systematic review aims to summarise the status of DL MRI models developed for assisting the diagnosis of a variety of knee abnormalities. Five databases were systematically searched, employing predefined terms such as 'Knee AND 3D AND MRI AND DL'. Selected inclusion criteria were used to screen publications by title, abstract, and full text. The synthesis of results was performed by two independent reviewers. Fifty-four articles were included. The studies focused on anterior cruciate ligament injuries (n = 19, 36%), osteoarthritis (n = 9, 17%), meniscal injuries (n = 13, 24%), abnormal knee appearance (n = 11, 20%), and other (n = 2, 4%). The DL models in this review primarily used the following CNNs: ResNet (n = 11, 21%), VGG (n = 6, 11%), DenseNet (n = 4, 8%), and DarkNet (n = 3, 6%). DL models showed high-performance metrics compared to ground truth. DL models for the detection of a specific injury outperformed those by up to 4.5% for general abnormality detection. Despite the varied study designs used among the reviewed articles, DL models showed promising outcomes in the assisted detection of selected knee pathologies by MRI. This review underscores the importance of validating these models with larger MRI datasets to close the existing gap between current DL model performance and clinical requirements. Question What is the status of DL model availability for knee pathology detection in MRI and their clinical potential? Findings Pathology-specific DL models reported higher accuracy compared to DL models for the detection of general abnormalities of the knee. DL model performance was mainly influenced by the quantity and diversity of data available for model training. Clinical relevance These findings should encourage future developments to improve patient care, support personalised diagnosis and treatment, optimise costs, and advance artificial intelligence-based medical imaging practices.

Osteoarthritis After Anterior Cruciate Ligament Reconstruction: A Systematic Review of Contributing Factors and Potential Treatments.

Anterior cruciate ligament (ACL) injuries result in abnormal knee motion and long-term joint degradation. ACL reconstruction (ACLR) is done with the aim of restoring normal knee kinematics and slowing the joint degradation process. It does appear that this inevitably happens and can be impacted by a multitude of factors. The aim of this review was to examine the factors that influence the progression of osteoarthritis (OA) after ACLR and examine possible treatments that can aid in slowing that progression. A systematic review was conducted by searching all levels of evidence for all studies in English that assessed risk factors for developing OA after ACL reconstruction, had a minimum follow-up of 10 years, and used radiographical outcomes to measure the presence of OA. Studies on trial treatments to reduce osteoarthritis after ACL reconstruction were also included. It was found that among the factors associated with an increased risk of post-ACLR OA are meniscal lesions, meniscectomy, increased age at the time of ACLR, increased time from injury to surgery, male sex, reduced range of motion, smaller thigh girth, graft complications, and failure. Additionally, in performing the ACLR, anteromedial femoral tunnel placement, higher graft tension, and following guidelines for performing anatomic ACLR have been shown to reduce the risk of OA as well. Patients should be adequately counselled on their risk pre-operatively for informed decision-making. Surgeons should also be aware of potential risk factors and how they can be mitigated.

Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities

Multi-sequence magnetic resonance imaging is crucial in accurately identifying knee abnormalities but requires substantial expertise from radiologists to interpret. Here, we introduce a deep learning model incorporating co-plane attention across image sequences to classify knee abnormalities. To assess the effectiveness of our model, we collected the largest multi-sequence knee magnetic resonance imaging dataset involving the most comprehensive range of abnormalities, comprising 1748 subjects and 12 types of abnormalities. Our model achieved an overall area under the receiver operating characteristic curve score of 0.812. It achieved an average accuracy of 0.78, outperforming junior radiologists (accuracy 0.65) and remains competitive with senior radiologists (accuracy 0.80). Notably, with the assistance of model output, the diagnosis accuracy of all radiologists was improved significantly (p < 0.001), elevating from 0.73 to 0.79 on average. The interpretability analysis demonstrated that the model decision-making process is consistent with the clinical knowledge, enhancing its credibility and reliability in clinical practice.

Quantitative ultrashort echo time MR imaging of knee osteochondral junction: An ex vivo feasibility study.

Compositional changes can occur in the osteochondral junction (OCJ) during the early stages and progressive disease evolution of knee osteoarthritis (OA). However, conventional magnetic resonance imaging (MRI) sequences are not able to image these regions efficiently because of the OCJ region's rapid signal decay. The development of new sequences able to image and quantify OCJ region is therefore highly desirable. We developed a comprehensive ultrashort echo time (UTE) MRI protocol for quantitative assessment of OCJ region in the knee joint, including UTE variable flip angle technique for T1 mapping, UTE magnetization transfer (UTE-MT) modeling for macromolecular proton fraction (MMF) mapping, UTE adiabatic T1ρ (UTE-AdiabT1ρ) sequence for T1ρ mapping, and multi-echo UTE sequence for T2* mapping. B1 mapping based on the UTE actual flip angle technique was utilized for B1 correction in T1, MMF, and T1ρ measurements. Ten normal and one abnormal cadaveric human knee joints were scanned on a 3T clinical MRI scanner to investigate the feasibility of OCJ imaging using the proposed protocol. Volumetric T1, MMF, T1ρ, and T2* maps of the OCJ, as well as the superficial and full-thickness cartilage regions, were successfully produced using the quantitative UTE imaging protocol. Significantly lower T1, T1ρ, and T2* relaxation times were observed in the OCJ region compared with those observed in both the superficial and full-thickness cartilage regions, whereas MMF showed significantly higher values in the OCJ region. In addition, all four UTE biomarkers showed substantial differences in the OCJ region between normal and abnormal knees. These results indicate that the newly developed 3D quantitative UTE imaging techniques are feasible for T1, MMF, T1ρ, and T2* mapping of knee OCJ, representative of a promising approach for the evaluation of compositional changes in early knee OA.

What's in a Name? Defining 'Failure' in Anterior Cruciate Ligament Reconstruction Randomized Controlled Trials: A Systematic Review.

Graft failure, one of the most common outcomes in anterior cruciate ligament reconstruction randomized controlled trials, lacks a consensus definition. The purpose of this study was to systematically summarize current practice and parameters in defining anterior cruciate ligament reconstruction graft 'failure'. Forty studies (4466 participants) satisfied the inclusion criteria. Of these, 90% either defined failure formally or referenced the etiology of failure, the remaining 10% used the term failure without referencing the anterior cruciate ligament reconstruction graft. Among the included studies, there was a high level of inconsistency between the definitions of graft failure. The extracted data was categorized into broader groups, revealing abnormal knee laxity (80%) and graft re-rupture (37.5%) as the most common parameters incorporated in the definitions of graft failure in high-level randomized controlled trials. This review shows that anterior cruciate ligament reconstruction randomized controlled trials lack a consistent definition for graft failure. A universal definition is vital for clarity in medical practice and research, ideally incorporating both objective (e.g. graft re-rupture) and subjective (e.g. validated questionnaires) parameters. A composite outcome should be established which includes some of the common parameters highlighted in this review. In the future, this review can be used to assist orthopaedic surgeons to establish a formal definition of anterior cruciate ligament reconstruction graft 'failure'.

Treatment outcome of chronic patellar tendon rupture using autogenous semitendinosus graft: a retrospective case series.

This study highlights the pattern of presentation, treatment, early functional outcome, and complications observed in the management of chronic patellar tendon ruptures using our preferred technique of autogenous semitendinosus graft reconstruction. This was a retrospective case series involving consecutive patients who underwent patellar tendon reconstruction and met the inclusion criteria. The outcome measures were determined by thepost-operative knee range of motion (R.O.M), thepost-operative International Knee Documentation Committee (IKDC) score, and pattern of post-operative complications. Nine patients were included in this case series. The mean age of the patients was 35.4 ± 6.8years (range 27-44years). Trauma to the knee accounted for majority of the cases (62.5%). Six (66.7%) of the nine patients suffered a patellar tendon rupture from contact injury during sporting activities. The mean length of time from injury to presentation was 20.5 ± 11.2weeks (range 6-69.5weeks). Normal knee function in a case (11.1%), nearly normal knee function in 7 cases (77.8%), and abnormal knee function in a case (11.1%) were recorded as a measure of outcome of surgery. The mean post-operative IKDC score was 70.0 ± 6.1 (range 55-77), which was higher than the mean pre-operative score of 26.4 ± 5.1 (range 18-32). The post-operative knee R.O.M averaged 97.2 ± 16.2° (range 70-120°) with a single case with a 10° extension lag noted. Normal to near-normal knee function was obtained with the treatment of chronic patellar tendon rupture in the majority of cases using autogenous semitendinosus graft for patellar tendon reconstruction in our series.

S-WD-EEMD: A hybrid framework for imbalanced sEMG signal analysis in diagnosis of human knee abnormality.

The diagnosis of human knee abnormalities using the surface electromyography (sEMG) signal obtained from lower limb muscles with machine learning is a major problem due to the noisy nature of the sEMG signal and the imbalance in data corresponding to healthy and knee abnormal subjects. To address this challenge, a combination of wavelet decomposition (WD) with ensemble empirical mode decomposition (EEMD) and the Synthetic Minority Oversampling Technique (S-WD-EEMD) is proposed. In this study, a hybrid WD-EEMD is considered for the minimization of noises produced in the sEMG signal during the collection, while the Synthetic Minority Oversampling Technique (SMOTE) is considered to balance the data by increasing the minority class samples during the training of machine learning techniques. The findings indicate that the hybrid WD-EEMD with SMOTE oversampling technique enhances the efficacy of the examined classifiers when employed on the imbalanced sEMG data. The F-Score of the Extra Tree Classifier, when utilizing WD-EEMD signal processing with SMOTE oversampling, is 98.4%, whereas, without the SMOTE oversampling technique, it is 95.1%.

Changes in gastrocnemius MTU stiffness and their correlation with plantar pressure in patients with knee osteoarthritis.

Abnormal, excessive, and repetitive knee load is a critical risk factor for osteoarthritis (OA). The gastrocnemius muscle-tendon unit (MTU) interacts with foot biomechanics and is vital in cushioning the knee load. Abnormal gastrocnemius activation and plantar pressure during walking in patients with knee OA may negatively affect gastrocnemius MTU stiffness, increasing knee load. Few studies investigated the relationship between gastrocnemius MTU stiffness and plantar pressure. This study aimed to evaluate the changes in gastrocnemius MTU stiffness in patients with knee OA and their correlations with plantar pressure and clinical symptoms. Thirty women patients with unilateral knee OA and 30 healthy women participants were recruited. Shear wave elastography was used to quantify gastrocnemius MTU stiffness in ankle resting and anatomical 0° positions, defined as natural and neutral positions in this study. A plantar pressure analysis system was used to collect the plantar pressure parameters on the symptomatic side in patients with knee OA. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Visual Analogue Scale (VAS) scores were used to measure the severity of clinical symptoms. Medial and lateral gastrocnemius (MG and LG) stiffness on both the asymptomatic and symptomatic sides in patients with knee OA was increased compared with that in healthy participants. The MG and LG optimal cutoff stiffness in the natural position was 15.73kPa and 14.25kPa, respectively. The optimal cutoff stiffness in the neutral position was 36.32kPa and 25.43kPa, respectively, with excellent sensitivity and specificity. The MG and LG stiffness were positively correlated with the percentages of anterior and medial plantar pressure and negatively correlated with the length of pressure center path. The LG and MG were significantly correlated with WOMAC and VAS scores. Patients with knee OA have increased gastrocnemius muscle stiffness, closely related to plantar pressure and clinical symptoms. Monitoring the gastrocnemius muscle in patients with knee OA can provide an essential basis for its prevention and treatment.

Gaussian Aquila optimizer based dual convolutional neural networks for identification and grading of osteoarthritis using knee joint images

Degenerative musculoskeletal disease known as Osteoarthritis (OA) causes serious pain and abnormalities for humans and on detecting at an early stage, timely treatment shall be initiated to the patients at the earliest to overcome this pain. In this research study, X-ray images are captured from the humans and the proposed Gaussian Aquila Optimizer based Dual Convolutional Neural Networks is employed for detecting and classifying the osteoarthritis patients. The new Gaussian Aquila Optimizer (GAO) is devised to include Gaussian mutation at the exploitation stage of Aquila optimizer, which results in attaining the best global optimal value. Novel Dual Convolutional Neural Network (DCNN) is devised to balance the convolutional layers in each convolutional model and the weight and bias parameters of the new DCNN model are optimized using the developed GAO. The novelty of the proposed work lies in evolving a new optimizer, Gaussian Aquila Optimizer for parameter optimization of the devised DCNN model and the new DCNN model is structured to minimize the computational burden incurred in spite of it possessing dual layers but with minimal number of layers. The knee dataset comprises of total 2283 knee images, out of which 1267 are normal knee images and 1016 are the osteoarthritis images with an image of 512 × 512-pixel width and height respectively. The proposed novel GAO-DCNN system attains the classification results of 98.25% of sensitivity, 98.93% of specificity and 98.77% of classification accuracy for abnormal knee case–knee joint images. Experimental simulation results carried out confirms the superiority of the developed hybrid GAO-DCNN over the existing deep learning neural models form previous literature studies.

Anterior knee pain patients without structural knee abnormalities and normal lower limb skeletal alignment have a higher prevalence of cam-femoroacetabular impingement syndrome than the general population

ObjectivesThis study aimed to ascertain the prevalence of cam femoroacetabular impingement syndrome (cam-FAIS) in anterior knee pain (AKP) patients devoid of both structural patellofemoral joint abnormalities and lower limb skeletal malalignment. A secondary objective was to examine pain and disability differences between AKP patients with and without cam-FAIS. MethodsA total of 209 AKP patients were screened for eligibility. Inclusion criteria were normal imaging studies and normal lower limb alignment, and exclusion criteria were previous knee surgery and knee and/or hip osteoarthritis. Of those, 49 (23.4%) were eligible and this number matched a previous power analysis to detect statistically significant differences in prevalence of cam-FAIS in a population of AKP patients. The first step in the study sequence was to ask the patient whether they had groin pain. If so, the impingement test was done. Then, the femoral cam morphology defined by an alpha angle greater than or equal to 55° in a 45° Dunn axial view of the hip was ruled out. Additionally, patients completed Kujala and International Knee Documentation Committee (IKDC) functional knee scores for disability assessment. General population control group was obtained from literature. ResultsThe study included 9 males and 40 females, with an average age of 36 (20–50, ±SD 8.03) years. Groin pain and positive impingement test were found in 26/49 patients (53%). An alpha angle ≥55° was observed in 35/49 patients (71%). A combination of groin pain, positive impingement test and an alpha angle ≥55° was seen in 18/49 patients (37%). The AKP patients with groin pain, a positive impingement test and an alpha angle ≥55° exhibited statistically similar pain and disability levels as AKP patients without cam-FAIS. ConclusionThe results of this study suggest that AKP patients without structural abnormalities in the patellofemoral joint and without lower limbs malalignment have a statistically significantly higher prevalence of cam-FAIS than the general population. Moreover, AKP patients with cam-FAIS have a statistically similar degree of pain and disability than AKP patients without it. Study designCross-sectional study. Level of EvidenceIV.

An Insight into the Characteristics of 3D Printed Polymer Materials for Orthoses Applications: Experimental Study.

Knee orthoses assist patients with impaired gait through the amendment of knee abnormalities, restoration of mobility, alleviation of pain, shielding, and immobilization. The inevitable issues with laborious traditional plaster molding procedures for orthoses can be resolved with 3D printing. However, a number of challenges have limited the adoption of 3D printing, the most significant of which is the proper material selection for orthoses. This is so because the material used to make an orthosis affects its strength, adaptability, longevity, weight, moisture response, etc. This study intends to examine the mechanical, physical, and dimensional characteristics of three-dimensional (3D) printing materials (PLA, ABS, PETG, TPU, and PP). The aim of this investigation is to gain knowledge about these materials' potential for usage as knee orthosis materials. Tensile testing, Olympus microscope imaging, water absorption studies, and coordinate measuring machine-based dimension analysis are used to characterize the various 3D printing materials. Based on the investigation, PLA outperforms all other materials in terms of yield strength (25.98 MPa), tensile strength (30.89 MPa), and shrinkage (0.46%). PP is the least water absorbent (0.15%) and most flexible (407.99%); however, it is the most difficult to fabricate using 3D printing. When producing knee orthoses with 3D printing, PLA can be used for the orthosis frame and other structural elements, PLA or ABS for moving parts like hinges, PP for padding, and TPU or PP for the straps. This study provides useful information for scientists and medical professionals who are intrigued about various polymer materials for 3D printing and their effective utilization to fabricate knee orthoses.

Multiparametric MRI of Knees in Collegiate Basketball Players: Associations With Morphological Abnormalities and Functional Deficits.

Rates of cartilage degeneration in asymptomatic elite basketball players are significantly higher compared with the general population due to excessive loads on the knee. Compositional quantitative magnetic resonance imaging (qMRI) techniques can identify local biochemical changes of macromolecules observed in cartilage degeneration. The purpose of this study was to utilize multiparametric qMRI to (1) quantify how T1ρ and T2 relaxation times differ based on the presence of anatomic abnormalities and (2) correlate T1ρ and T2 with self-reported functional deficits. It was hypothesized that prolonged relaxation times will be associated with knees with MRI-graded abnormalities and knees belonging to basketball players with greater self-reported functional deficits. Cross-sectional study; Level of evidence, 3. A total of 75 knees from National Collegiate Athletic Association Division I basketball players (40 female, 35 male) were included in this multicenter study. All players completed the Knee injury and Osteoarthritis Outcome Score (KOOS) and had bilateral knee MRI scans taken. T1ρ and T2 were calculated on a voxel-by-voxel basis. The cartilage surfaces were segmented into 6 compartments: lateral femoral condyle, lateral tibia, medial femoral condyle, medial tibia (MT), patella (PAT), and trochlea (TRO). Lesions from the MRI scans were graded for imaging abnormalities, and statistical parametric mapping was performed to study cross-sectional differences based on MRI scan grading of anatomic knee abnormalities. Pearson partial correlations between relaxation times and KOOS subscore values were computed, obtaining r value statistical parametric mappings and P value clusters. Knees without patellar tendinosis displayed significantly higher T1ρ in the PAT compared with those with patellar tendinosis (average percentage difference, 10.4%; P = .02). Significant prolongation of T1ρ was observed in the MT, TRO, and PAT of knees without compared with those with quadriceps tendinosis (average percentage difference, 12.7%, 13.3%, and 13.4%, respectively; P ≤ .05). A weak correlation was found between the KOOS-Symptoms subscale values and T1ρ/T2. Certain tissues that bear the brunt of impact developed tendinosis but spared cartilage degeneration. Whereas participants reported minimal functional deficits, their high-impact activities resulted in structural damage that may lead to osteoarthritis after their collegiate careers.

Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach.

Large numbers of radiographic images are available in musculoskeletal radiology practices which could be used for training of deep learning models for diagnosis of knee abnormalities. However, those images do not typically contain readily available labels due to limitations of human annotations. The purpose of our study was to develop an automated labeling approach that improves the image classification model to distinguish normal knee images from those with abnormalities or prior arthroplasty. The automated labeler was trained on a small set of labeled data to automatically label a much larger set of unlabeled data, further improving the image classification performance for knee radiographic diagnosis. We used BioBERT and EfficientNet as the feature extraction backbone of the labeler and imaging model, respectively. We developed our approach using 7382 patients and validated it on a separate set of 637 patients. The final image classification model, trained using both manually labeled and pseudo-labeled data, had the higher weighted average AUC (WA-AUC 0.903) value and higher AUC values among all classes (normal AUC 0.894; abnormal AUC 0.896, arthroplasty AUC 0.990) compared to the baseline model (WA-AUC = 0.857; normal AUC 0.842; abnormal AUC 0.848, arthroplasty AUC 0.987), trained using only manually labeled data. Statistical tests show that the improvement is significant on normal (p value < 0.002), abnormal (p value < 0.001), and WA-AUC (p value = 0.001). Our findings demonstrated that the proposed automated labeling approach significantly improves the performance of image classification for radiographic knee diagnosis, allowing for facilitating patient care and curation of large knee datasets.

Poster 327: Objectively measuring knee extension is critical when analyzing long term outcomes after an anterior cruciate ligament reconstruction

Objectives: Structural abnormalities, such as meniscus tears and chondral injuries, seen at the time of an anterior cruciate ligament (ACL) reconstruction, as well as abnormal objective measures, like knee extension stiffness, can lead to unfavorable short term outcomes following surgery. Furthermore, a lack of full knee extension in the short term has been shown to lead to a lack of full knee extension in the long term. However, long term outcomes based on knee extension are unknown as they are typically judged with subjective data only or are based on whether or not the patient had meniscus tears or chondral injuries seen at the time of surgery. The purpose of this study was to determine long term functional outcome differences after an ACL reconstruction, for those with varying structural abnormalities, based on normal and abnormal knee extension. Methods: Between 1982 and 2012, 3432 patients having an ACL reconstruction using a patellar tendon graft were enrolled into the study. Exclusion criteria included revisions, bilateral involvement, and osteoarthritis (OA) at the time of surgery. Patients were split into four groups based on structural abnormalities, normal (group 1), meniscus tear (group 2), chondral injury (group 3), and a combination of meniscus tear and chondral injury (group 4). Patients followed up for data collection and radiographs at a minimum 10 years postoperative. Abnormal knee extension was defined as more than 2° off compared to the noninvolved knee, per the International Knee Documentation Committee (IKDC) objective criteria. The IKDC subjective was collected and radiographs were graded based on the medial and lateral compartment. Additionally, short term knee extension at 2 months postoperative was compared to long term knee extension. Results: Of the 3432 patients, 899 (26%) had subjective, objective, and radiographic data at a mean 17.7 ± 6.2 years (range, 10-39) while another 898 (26%) had subjective data only at a mean 20.2 ± 7.4 years (range, 10-39). Patients with abnormal knee extension at 2 months postoperative were 6.4 times more likely to have abnormal knee extension at long term follow up ( p&lt;.001). At long term follow up, 84% of patients had normal knee extension. The rate of moderate to severe knee OA for groups 1-4 was 6%, 12%, 18%, and 25%, respectively ( p&lt;.05). The rate of moderate to severe OA and IKDC scores, when spilt based on knee extension, can be seen in table 1. Overall, patients with abnormal knee extension were 4.8 times more likely to have OA compared to those with normal knee extension. Patients with a meniscus tear were 2.1 times more likely to have OA and those with chondral injuries were 2.7 times more likely to have OA, when compared to those without a structural abnormality, p&lt;.05. Conclusions: Abnormal knee extension early after surgery can negatively affect knee extension long term as those that are lacking motion early rarely have normal knee extension long term. Abnormal knee extension long term can lead to lower subjective scores and higher rates of OA when compared to those with normal knee extension. A loss of knee extension long term results in more negative outcomes than meniscus tears or chondral injuries. Objectively measuring knee extension long term after surgery can help explain positive and negative outcomes for patients, regardless of their meniscus or chondral status at the time of surgery. [Table: see text]

Conformity design can change the effect of tibial component malrotation on knee biomechanics after total knee arthroplasty

BackgroundComponent alignment is essential to improve knee function and survival in total knee arthroplasty. However, it is still unclear whether the conformity design of tibiofemoral component can mitigate abnormal knee biomechanics caused by component malrotation. The purpose of this study was to investigate whether the sagittal/coronal conformity design of the tibial component could change the effect of the tibial component malrotation on knee biomechanics in total knee arthroplasty. MethodsA developed patient-specific musculoskeletal multi-body dynamics model of total knee arthroplasty was used to investigate the effects of the sagittal/coronal conformity of the tibial component on knee contact forces and kinematics caused by tibial component malrotation during the walking gait. FindingsMedial and lateral contact forces, internal-external rotation, and anterior-posterior translation were significantly affected by tibial component malrotation after total knee arthroplasty during the walking gait. The lower sagittal conformity of the tibial component can mitigate the abnormal internal-external rotation caused by tibial component malrotation in total knee arthroplasty, the higher coronal conformity of the tibial component can mitigate the abnormal medial-lateral translation caused by tibial component malrotation in total knee arthroplasty. InterpretationThis study highlights the importance of the tibiofemoral conformity designs on knee biomechanics caused by component malrotation in total knee arthroplasty. The optimization of the tibiofemoral conformity designs should be thoroughly considered in the design of new implants and in the planning of surgical procedures.

Anterior cruciate ligament failure and management.

Anterior cruciate ligament (ACL) reconstruction failure can be defined as abnormal knee function due to graft insufficiency with abnormal laxity or failure to recreate a functional knee according to the expected outcome. Traumatic ruptures have been reported as the most common reason for failure. They are followed by technical errors, missed concomitant knee injuries, and biological failures. An in-depth preoperative examination that includes a medical history, clinical examinations, advanced imaging, and other appropriate methods is of utmost importance. There is still no consensus as to the ideal graft, but autografts are the favorite choice even in ACL revision. Concomitant meniscal treatment, ligamentous reconstruction, and osteotomies can be performed in the same surgical session to remove anatomical or biomechanical risk factors for the failure. Patient expectations should be managed since outcomes after ACL revision are not as good as those following primary ACL reconstruction.