Knee Magnetic Resonance Imaging Research Articles

Evaluation of the reliability and accuracy of MRI for the diagnosis of meniscal ramp lesions.

Meniscal ramp lesions are a special type of meniscal injury that affects the periphery of the posterior horn of the medial meniscus and/or its meniscocapsular attachments, strongly associated with anterior cruciate ligament (ACL) tears. Due to their location, these lesions can be missed arthroscopically so it is essential to diagnose them on preoperative magnetic resonance imaging (MRI). To evaluate the accuracy of MRI in detecting meniscal ramp lesions in patients with ACL tears using arthroscopy as the reference standard. Two musculoskeletal radiologists, blinded to the surgical findings, retrospectively and independently evaluated 106 knee MRI scans for the presence of meniscal ramp lesions in non-consecutive patients who underwent arthroscopic ACL reconstruction between January 2019 and July 2022 by a single surgeon at one institution. Having arthroscopy as reference, the diagnostic sensitivity and specificity as well as the positive and negative predictive values (PPV/NPV) of the MRI scans were calculated. Cohen's kappa coefficient was used to test inter-observer reliability. A P value <0.05 was considered statistically significant. In the study group of 106 patients (72 men, 34 women; mean age = 33.84 ±13.12 years), 76 had an arthroscopy-confirmed meniscal ramp lesion, while 30 did not. The sensitivity and specificity of MRI for the detection of meniscal ramp lesion were 88% and 87%, respectively. The PPV and NPV were 94% and 74%, respectively. Inter-rater reliability was excellent (k = 0915). This study demonstrates that MRI can accurately detect meniscal ramp lesions.

Enhancement of Image Quality in Low-Field Knee MR Imaging Using Deep Learning

Enhancement of Image Quality in Low-Field Knee MR Imaging Using Deep Learning

Accelerating multi-coil MR image reconstruction using weak supervision.

Deep-learning-based MR image reconstruction in settings where large fully sampled dataset collection is infeasible requires methods that effectively use both under-sampled and fully sampled datasets. This paper evaluates a weakly supervised, multi-coil, physics-guided approach to MR image reconstruction, leveraging both dataset types, to improve both the quality and robustness of reconstruction. A physics-guided end-to-end variational network (VarNet) is pretrained in a self-supervised manner using a 4 under-sampled dataset following the self-supervised learning via data undersampling (SSDU) methodology. The pre-trained weights are transferred to another VarNet, which is fine-tuned using a smaller, fully sampled dataset by optimizing multi-scale structural similarity (MS-SSIM) loss in image space. The proposed methodology is compared with fully self-supervised and fully supervised training. Reconstruction quality improvements in SSIM, PSNR, and NRMSE when abundant training data is available (the high-data regime), and enhanced robustness when training data is scarce (the low-data regime) are demonstrated using weak supervision for knee and brain MR image reconstructions at 8 and 10 acceleration, respectively. Multi-coil physics-guided MR image reconstruction using both under-sampled and fully sampled datasets is achievable with transfer learning and fine-tuning. This methodology can provide improved reconstruction quality in the high-data regime and improved robustness in the low-data regime at high acceleration rates.

Text mining approach for feature extraction and cartilage disease grade classification using knee MRI radiology reports

MRI radiology reporting processes can be improved by exploiting structured and semantically labelled data that can be fed to artificial intelligence (AI) tools. AI-based tools assisting radiology reporting can help to automatically individuate cartilage grading in textual magnetic resonance imaging (MRI) reports, thus supporting clinicians' decisions regarding medical imaging utilisation, diagnosis and treatment. In this study, we extracted information (clinical findings, observations, anatomical regions, etc.) and classified knee cartilage degradation from medical reports utilising transfer-learning techniques applied to the Bidirectional Encoder Representations from Transformers (BERT) model and its variants, pre-trained on an Italian-language corpus. To realise this objective, we used a dataset of 750 MRI knee reports written by three radiologists who contributed to a manual annotation process to perform text classification (TC) and named entity recognition (NER) tasks. The dataset was obtained from an internal database of the IRCCS SYNLAB SDN. Seventy percent of the dataset was used for training, 10% was used for validation and 20% was used for testing. The best-performing configurations for NER and TC tasks were based on the pre-trained BERT model. The macro F1-scores obtained with the NER and TC models are 0.89 and 0.81, respectively. The accuracies calculated on the test set for both tasks are 0.96 and 0.99, respectively.

Fourier Convolution Block with global receptive field for MRI reconstruction

Reconstructing images from under-sampled Magnetic Resonance Imaging (MRI) signals significantly reduces scan time and improves clinical practice. However, Convolutional Neural Network (CNN)-based methods, while demonstrating great performance in MRI reconstruction, may face limitations due to their restricted receptive field (RF), hindering the capture of global features. This is particularly crucial for reconstruction, as aliasing artifacts are distributed globally. Recent advancements in Vision Transformers have further emphasized the significance of a large RF. In this study, we proposed a novel global Fourier Convolution Block (FCB) with whole image RF and low computational complexity by transforming the regular spatial domain convolutions into frequency domain. Visualizations of the effective RF and trained kernels demonstrated that FCB improves the RF of reconstruction models in practice. The proposed FCB was evaluated on four popular CNN architectures using brain and knee MRI datasets. Models with FCB achieved superior PSNR and SSIM than baseline models and exhibited more details and texture recovery. The code is publicly available at https://github.com/Haozhoong/FCB.

Prevalence of Abnormalities and Normal Variants in the Adolescent Knee on MRI in a Population-Based Cohort of 3800 Knees.

Many adolescents experience knee pain, and only some undergo detailed imaging. In this population, the prevalence of abnormalities and normal variants on magnetic resonance imaging (MRI) scans is unknown. To investigate the prevalence of abnormalities and normal variants of the knee on MRI scans and their relationship with participant characteristics in the general young adolescent population. Cross-sectional study; Level of evidence, 3. This study was part of an open population-based cohort study that focuses on health, growth, and development from fetal life until adulthood. Between 2017 and 2020, adolescents aged 12 to 15 years underwent MRI of both knees. These MRI scans were assessed in a standardized way for abnormalities and normal variants to determine their prevalence. Logistic regression was used to analyze the presence of abnormalities and normal variants in relation to sex, height, weight, body mass index-standard deviation (BMI-SD), and ethnicity. A total of 1910 participants (median age, 13.5 years; interquartile range, 13.4-13.7 years; 52% girls) were included in this study. Of them, 370 (19.4%) participants had at least 1 abnormality or normal variant. Bone marrow edema around the knee was the most prevalent finding, affecting 140 (7.3%) participants. In 107 (5.6%) participants, nonossifying fibromas were found. A total of 43 (2.3%) participants had characteristics of Osgood-Schlatter disease, 16 (0.8%) showed characteristics of Sinding-Larsen-Johansson syndrome, and osteochondritis dissecans was found in 13 (0.7%) participants. Variants such as discoid menisci were found in 40 (2.1%) participants and a bipartite patella in 21 (1.1%) participants. There were multiple associations between abnormalities or variants and participant characteristics, including bone marrow edema being more often present in boys (odds ratio [OR], 2.44; 95% CI, 1.69-3.52) and those with a lower BMI-SD (OR, 0.85; 95% CI, 0.73-0.98). Osgood-Schlatter and osteochondritis dissecans were more often present in boys (OR, 4.21 [95% CI, 2.01-8.85] and OR, 13.18 [95% CI, 1.71-101.58], respectively). Discoid menisci were associated with a non-Western ethnicity (OR, 2.06; 95% CI, 1.07-3.96) and higher BMI-SD (OR, 2.34; 95% CI, 1.76-3.11). Abnormalities and normal variants on MRI scans of the knees are common in adolescents. Physicians who are involved in the treatment of adolescents with knee pain need to be aware of this prevalence so that these children will not be overtreated or misdiagnosed.

Evaluation of the impact of ultra-trail running on knee cartilage using magnetic resonance imaging t2 mapping.

Ultra-marathon trails involve a combination of specific physiological and mechanical constraints and raise new questions regarding the osteoarticular impact on the knees and the long-term risk of osteoarthritis. Magnetic resonance imaging (MRI) T2 relaxation time measurement has shown the ability to determine cartilage response to loading. Higher T2 measurements correspond with cartilage damage. The aim of this study was to quantify the changes in MRI T2 relaxation times of knee articular cartilage after an ultra-trail run and determine knee's consequences of regular practice. Twenty participants in a 55-km race involving total elevation changes of 2600m had 1.5-T knee MRI prior to the race (V0), immediately after (V1) and one month after the race (V2) for T2 relaxation times measurement and morphological sequences (T1, T2 & T2 Fast-Spin Echo (FSE)). T2 measurements were significantly increased in V1 from V0 and remained so one month after the race (V2), despite a significant reduction from V1. Morphological sequences revealed that 65% of the participant had cartilage damage and 65% meniscal damage, 100% of which affected the posterior horn of the medial meniscus. Only one subject (5%) presented no anomaly whatsoever. Damage appeared to be stable between the assessments. Ultra-trail running leads to modifications in the knee cartilage ultrastructure, which persists for at least one month after the event. Furthermore, regular ultra-trail runners present a high number of low-grade cartilage and meniscus lesions.

Acute Knee Injury Detection with Magnetic Resonance Imaging (MRI)

The anterior cruciate ligament (ACL) is a major ligament in the knee that helps to stabilize the joint and prevent excessive forward movement of the shinbone. An ACL tear is a common injury, especially among athletes who participate in sports that involve pivoting and sudden changes in direction. This paper proposes an ensemble model, which includes three deep learning models (EfficientNet-B7, ResNet-152V2, and DenseNet-201) and a genetic algorithm, to detect and classify ACL tears using knee magnetic resonance imaging (MRI). The ensemble model was trained on the KneeMRI dataset, which comprises labeled MRI images. The deep learning models can learn to identify subtle changes in ligament structure and signal intensity that are associated with ACL tears and the genetic algorithm is used to find the optimal prediction. The proposed ensemble model was evaluated using the KneeMRI dataset. The dataset was preprocessed using data augmentation techniques. Then, the ensemble model was applied to the KneeMRI dataset, evaluated, and compared with previous models. The accuracy, recall, precision, specificity, and F1 score of our proposed ensemble model were 99.68%, 98.73%, 99.52%, 99.62%, and 98.94%, respectively. Thus, our ensemble model has an unrivaled perceptive outcome and could be used to accurately identify and classify ACL tears, improving patient outcome.

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.

Deep Learning-Enhanced Accelerated 2D TSE and 3D Superresolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment.

The aim of this study was to evaluate the use of a multicontrast deep learning (DL)-reconstructed 4-fold accelerated 2-dimensional (2D) turbo spin echo (TSE) protocol and the feasibility of 3-dimensional (3D) superresolution reconstruction (SRR) of DL-enhanced 6-fold accelerated 2D Dixon TSE magnetic resonance imaging (MRI) for comprehensive knee joint assessment, by comparing image quality and diagnostic performance with a conventional 2-fold accelerated 2D TSE knee MRI protocol. This prospective, ethics-approved study included 19 symptomatic adult subjects who underwent knee MRI on a clinical 3 T scanner. Every subject was scanned with 3 DL-enhanced acquisition protocols in a single session: a clinical standard 2-fold in-plane parallel imaging (PI) accelerated 2D TSE-based protocol (5 sequences, 11 minutes 23 seconds) that served as a reference, a DL-reconstructed 4-fold accelerated 2D TSE protocol combining 2-fold PI and 2-fold simultaneous multislice acceleration (5 sequences, 6 minutes 24 seconds), and a 3D SRR protocol based on DL-enhanced 6-fold accelerated (ie, 3-fold PI and 2-fold simultaneous multislice) 2D Dixon TSE MRI (6 anisotropic 2D Dixon TSE acquisitions rotated around the phase-encoding axis, 6 minutes 24 seconds). This resulted in a total of 228 knee MRI scans comprising 21,204 images. Three readers evaluated all pseudonymized and randomized images in terms of image quality using a 5-point Likert scale. Two of the readers (musculoskeletal radiologists) additionally evaluated anatomical visibility and diagnostic confidence to assess normal and pathological knee structures with a 5-point Likert scale. They recorded the presence and location of internal knee derangements, including cartilage defects, meniscal tears, tears of ligaments, tendons and muscles, and bone injuries. The statistical analysis included nonparametric Friedman tests, and interreader and intrareader agreement assessment using the weighted Fleiss-Cohen kappa (κ) statistic. P values of less than 0.05 were considered statistically significant. The evaluated DL-enhanced 4-fold accelerated 2D TSE protocol provided very similar image quality and anatomical visibility to the standard 2D TSE protocol, whereas the 3D SRR Dixon TSE protocol scored less in terms of overall image quality due to reduced edge sharpness and the presence of artifacts (P < 0.001). Subjective signal-to-noise ratio, contrast resolution, fluid brightness, and fat suppression were good to excellent for all protocols. For 1 reader, the Dixon method of the 3D SRR protocol provided significantly better fat suppression than the spectral fat saturation applied in the standard 2D TSE protocol (P < 0.05). The visualization of knee structures with 3D SRR Dixon TSE was very similar to the standard protocol, except for cartilage, tendons, and bone, which were affected by the presence of reconstruction and aliasing artifacts (P < 0.001). The diagnostic confidence of both readers was high for all protocols and all knee structures, except for cartilage and tendons. The standard 2D TSE protocol showed a significantly higher diagnostic confidence for assessing tendons than 3D SRR Dixon TSE MRI (P < 0.01). The interreader and intrareader agreement for the assessment of internal knee derangements using any of the 3 protocols was substantial to almost perfect (κ = 0.67-1.00). For cartilage, the interreader agreement was substantial for DL-enhanced accelerated 2D TSE (κ = 0.79) and almost perfect for standard 2D TSE (κ = 0.98) and 3D SRR Dixon TSE (κ = 0.87). For menisci, the interreader agreement was substantial for 3D SRR Dixon TSE (κ = 0.70-0.80) and substantial to almost perfect for standard 2D TSE (κ = 0.80-0.99) and DL-enhanced 2D TSE (κ = 0.87-1.00). Moreover, the total acquisition time was reduced by 44% when using the DL-enhanced accelerated 2D TSE or 3D SRR Dixon TSE protocol instead of the conventional 2D TSE protocol. The presented DL-enhanced 4-fold accelerated 2D TSE protocol provides image quality and diagnostic performance similar to the standard 2D protocol. Moreover, the 3D SRR of DL-enhanced 6-fold accelerated 2D Dixon TSE MRI is feasible for multicontrast 3D knee MRI as its diagnostic performance is comparable to standard 2-fold accelerated 2D knee MRI. However, reconstruction and aliasing artifacts need to be further addressed to guarantee a more reliable visualization and assessment of cartilage, tendons, and bone. Both the 2D and 3D SRR DL-enhanced protocols enable a 44% faster examination compared with conventional 2-fold accelerated routine 2D TSE knee MRI and thus open new paths for more efficient clinical 2D and 3D knee MRI.

Management of patellar and trochlear cartilage lesions with matrix-induced autologous chondrocyte implantation in conjunction with patellofemoral realignment procedures improves patient-reported outcomes and magnetic resonance image appearance

ObjectivesThe aim of this study is to evaluate the relationship between the achievement of clinically significant improvement in patient-reported outcome measures (PROMs) and the postoperative magnetic resonance image (MRI) appearance of matrix-associated chondrocyte implantation (MACI), in conjunction with patellofemoral realignment procedures, for the treatment of grade-IV chondral defects about the patellofemoral joint. MethodsA retrospective review of patients undergoing MACI for grade-IV chondral defects of the patella or trochlea by a single sports-medicine-fellowship-trained surgeon from 2017 to 2020 was performed. Concomitant realignment procedures, including tibial tubercle osteotomy and medial patellofemoral ligament reconstruction, were also performed as needed. Patients with preoperative and minimum 1-year postoperative PROMs and postoperative knee MRI were included. MRI scans were obtained at 6.3 (interquartile range: 5.8, 7.5) months postoperatively. A fellowship-trained musculoskeletal radiologist assigned a Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) score (range: 0–100, with 100 equating to complete graft healing) to each MRI. Achievement of the minimal clinically important difference (MCID) for International Knee Documentation Committee (IKDC), Knee Injury and Osteoarthritis Score—Quality of Life, and Kujala scores were determined for each patient. Paired t-tests or Wilcoxon rank-sum tests were used to evaluate for an association between achievement of the MCID for each PROM and MOCART score. The average follow-up time and time from surgery to PROMs were 2.7 ​± ​1.5 years and 1.7 ​± ​0.66 years, respectively. ResultsThirty patients were included. There was a significant improvement in all PROMs from preoperative to postoperative (p ​< ​0.001). More than two-thirds of patients achieved the MCID for each PROM. Patients who achieved the MCID for IKDC had significantly higher MOCART scores (66.5 ​± ​16.2) than those who did not meet the MCID for IKDC (50.6 ​± ​23.6, p ​= ​0.043). ConclusionMACI for the treatment of patellofemoral chondral injuries is associated with clinically significant improvement in PROMs at short-term follow-up. Clinically significant improvements in IKDC scores are associated with a more mature MRI appearance of the autologous chondrocyte implantation graft on postoperative MRI, as indicated by higher MOCART scores. Level of evidenceIV—Case Series.

Deep Learning-Assisted Automatic Diagnosis of Anterior Cruciate Ligament Tear in Knee Magnetic Resonance Images.

Anterior cruciate ligament (ACL) tears are prevalent knee injures, particularly among active individuals. Accurate and timely diagnosis is essential for determining the optimal treatment strategy and assessing patient prognosis. Various previous studies have demonstrated the successful application of deep learning techniques in the field of medical image analysis. This study aimed to develop a deep learning model for detecting ACL tears in knee magnetic resonance Imaging (MRI) to enhance diagnostic accuracy and efficiency. The proposed model consists of three main modules: a Dual-Scale Data Augmentation module (DDA) to enrich the training data on both the spatial and layer scales; a selective group attention module (SG) to capture relationships across the layer, channel, and space scales; and a fusion module to explore the inter-relationships among various perspectives to achieve the final classification. To ensure a fair comparison, the study utilized a public dataset from MRNet, comprising knee MRI scans from 1250 exams, with a focus on three distinct views: axial, coronal, and sagittal. The experimental results demonstrate the superior performance of the proposed model, termed SGNET, in ACL tear detection compared with other comparison models, achieving an accuracy of 0.9250, a sensitivity of 0.9259, a specificity of 0.9242, and an AUC of 0.9747.

Two-Year Functional Outcomes of Nonsurgical Treatment in Concomitant Anterior Cruciate Ligament and Medial Collateral Ligament Injuries: A Case-Control Study.

The anterior cruciate ligament (ACL) is a common knee injury in high-intensity sports, which can cause early career loss in young athletes. Concomitant damage to other knee stabilizers may occur, such as the medial collateral ligament (MCL). Recent studies have shown that knee stability can increase without surgical intervention in patients with ACL and MCL injuries. Regarding the importance of functional tests in return to exercise prediction, this study aims to measure nonsurgical approach's long-term outcome for concomitant ACL and MCL injuries with a focus on functional tests. This is a case-control study with a 2-year follow-up. The case group consisted of patients who had provided written consent and completed their 2-year follow-up, and the control group was made up of healthy people who did not have any knee medical conditions and were matched by age, gender, and activity level. Physical examinations, Tegner and International Knee Documentation Committee questionnaires, and knee magnetic resonance imaging were conducted, and functional performance tests were performed after a 10-minute warm-up. Lody's index (the ratio of injured-to-uninjured knee results) was calculated. The data were analyzed using independent t-test, one-way analysis of variance, chi-squared test, and Fisher's exact test. The study involved 11 patients in each concomitant ACL and MCL injury cases and healthy control groups with a mean age of 32.4 and 28 years, respectively. None of the patients reported knee instability symptoms in the 2-year follow-up. More than half of the patients continued their sports field without reinjury, with no significant difference in activity levels between case and control groups. The 6-meter hop test and single-leg hop test showed no significant difference between case and control groups (p-value: 0.326, 0.859), and no significant difference was observed in the three Carioca, cocontraction, and Shuttle tests in the 2-year follow-up. Functional tests in ACL and MCL injuries revealed normal outcomes, implying a nonsurgical approach for patients with proximal ACL tears, better knee stability, and no significant differences between the injured and control groups.

The Intra-articular Tendinous Graft Diameter of 10-mm Bone-Patellar Tendon-Bone Autografts in Adolescent Patients: An MRI Analysis of 100 Patients.

Bone-patellar tendon-bone (BPTB) autograft size may be one modifiable predictor of anterior cruciate ligament (ACL) reconstruction postoperative success, as smaller graft diameter has been associated with higher rates of rupture requiring revision. However, measuring the true intra-articular tendinous graft diameter of the soft tissue portion of a BPTB graft with standard intraoperative methods is difficult while keeping the graft intact. The purpose of the study was to use 3-dimensional magnetic resonance imaging (MRI) measurements to determine the cross-sectional area of the soft tissue, tendinous portion of a standard BPTB autograft with 10-mm diameter bone plugs, and, by calculation, the collagen graft size (ie, graft diameter), as would typically be reported in ACL reconstruction studies that consider soft tissue graft size. It was hypothesized that the calculated collagen graft diameter of 10-mm BPTB autografts would be significantly smaller than 10 mm. Cross-sectional study; Level of evidence, 3. A total of 100 patients (10 girls and 10 boys at each age from 13 to 17 years) who underwent a knee MRI at a single academic orthopaedic center without documented extensor mechanism pathology were identified. The central 10-mm width of the patellar tendon that would be harvested for BPTB autograft was measured. The region of interest area tool was then used to measure the cross-sectional area of a 10-mm BPTB graft with subsequent soft tissue autograft diameter calculation. The mean calculated tendinous graft diameter of a 10 mm-wide BPTB graft was 6.3 ± 0.5 mm and was significantly smaller than a 10-mm reference (P≤ .001). There was no significant association between age and cross-sectional area or graft diameter. Modern 3-dimensional imaging-based measurement techniques demonstrated that the true intra-articular tendinous soft tissue portion of 10-mm BPTB autografts shows substantial variation and is significantly smaller in diameter than the tunnels typically reamed to accommodate the bone plug portions of these grafts. Moreover, as graft size is a predictor of rupture rate, preoperative MRI-based evaluation may be an important tool when considering BPTB autograft for ACL reconstruction. Future comparative clinical research utilizing graft size as a study variable should consider quantifying and utilizing the diameter of the soft tissue component of BPTB autografts.

High-resolution oblique coronal MRI at optimal flexed-knee angle: a novel imaging method for enhanced anterior cruciate ligament tear diagnosis

BackgroundThe accuracy of traditional knee MR imaging in diagnosing anterior cruciate ligament tears, especially partial tears, is relatively low, which may lead to misdiagnosis and missed diagnosis. This study aimed to assess the diagnostic performance of a novel imaging method, high-resolution oblique coronal MRI at an optimal flexed-knee Angle, for ACL tears.Methods50 healthy volunteers were scanned with a scan-assisted device for the optimal flexion angle of ACL. For 92 knee trauma patients selected strictly according to inclusion and exclusion criteria, conventional extended-knee scans (control group) and high-resolution oblique coronal scans based on the optimal flexed-knee angle (experimental group) were conducted. Two observers rated ACL visibility blindly on a 5-point scale. Arthroscopy-defined outcomes determined diagnostic metrics for each method and sensitivity, specificity, positive predictive value, negative predictive value and accuracy were calculated.ResultsThe average optimal flexion angle for healthy volunteers was approximately 30° (30.3° ± 5.0°). Imaging demonstrated complete visualization of the ACL in 96.7% of images in the experimental group versus 12.0% in the control group. The diagnostic indicators of the experimental group surpassed those of the control group: sensitivity (94.9% vs. 76.3%), specificity (97.0% vs. 81.8%), positive predictive value (98.2% vs. 88.2%), negative predictive value(91.4% vs. 65.9%), and accuracy (95.7% vs. 78.3%). ROC analysis indicated superior diagnostic performance in the experimental group, with an AUC of 0.945 compared with 0.776 for the control group (p < 0.0001).ConclusionsHigh-resolution oblique coronal imaging at the optimal 30° flexed-knee angle improved ACL visualization and diagnostic performance compared with conventional techniques.

Dimension of normal anterior cruciate ligament on MRI in our population.

Objective: The present study will help us in establishing local statistics in our population. Study Design: Descriptive study. Setting: Department of Orthopedic Surgery at Khyber Teaching Hospital in Peshawar. Period: June 2023 to December 2023. Methods: Seventy MRI of knee were collected. Knee MR images sagittal and coronal plane (T2-Weighted Images) were reviewed by radiologist and only knees with an intact cruciate ligament were included in the study. All the measurement (length and width) were made with electronic caliper. Results: Regarding radiological length of ACL on sagittal view on MRI, the minimum length was 28mm and maximum was 46mm and mean length was 34mm and standard deviation of 4.49, Regarding width of ACL on sagittal view it was found that the minimum length was 8mm and maximum was 16mm and its mean length was 10.4mm with standard deviation of 2.02. While the width of ACL on coronal plane was such that the minimum length was 6mm maximum was 16mm its mean was 11.34 and standard deviation of 2.48. By applying one sample T-Test and compare with Kowen parameter the p value was 0.00 for both length and width showing statistically highly significant. Conclusion: In conclusion in our population ACL is shorter and thicker then westerns population. Further studies should be done arthroscopically and on cadaveric to establish our local statistics of anthropometric measurements of anterior cruciate ligament.

Synovial hemangioma presenting with chronic painful infrapatellar mass: a case report

BackgroundSynovial hemangiomas are rare benign vascular anomalies surrounded by a synovial lining and were first described by Bouchut in 1856. These neoplasms can develop in the intra-articular region, resulting in effusions and knee pain. However, their cause remains unknown. Prompt diagnosis and intervention are critical to prevent chondral damage. Histopathological examination is used to achieve the diagnosis, which is often delayed because of a lack of specific clinical signs. This report describes a unique case in which a painful infrapatellar mass was diagnosed as a synovial hemangioma. The absence of typical magnetic resonance imaging (MRI) findings highlights the importance of arthroscopic excision for diagnosis and symptom relief.Case presentationA 20-year-old woman presented with persistent anterior left knee pain that became exacerbated when she climbed stairs. Despite previous pain management and physical therapy, she developed a painful lump beneath her patella that worsened over time. She had also undergone arthrocentesis, but this did not relieve her pain. Physical examination revealed a palpable, immobile 5-cm mass along the patellar tendon with limited knee flexion and extension and normal ligament stability. T1-weighted fat-saturated MRI of the left knee with gadolinium-based contrast revealed a lobulated intra-articular mass in Hoffa’s fat pad that resembled a soft tissue chondroma. A biopsy of the mass was performed to provide histopathological evidence, confirming the benign nature of the mass. The subsequent excisional arthroscopy, combined with incision enlargement for mass removal, confirmed the histopathologic diagnosis of synovial hemangioma based on the presence of numerous dilated blood vessels and venous proliferation within sections of the synovium. Recovery was complete, and no residual tumor was detected on follow-up MRI after 1 year.ConclusionThis case study emphasizes the importance of arthroscopic excision over open surgery for patients with synovial hemangioma. The minimally invasive nature of arthroscopy combined with the well-encapsulated nature and location of the mass facilitates complete resection.

Fresh osteochondral allograft transplantation for knee full-thickness articular cartilage lesions using femoral head of living donors: short-term results.

Fresh osteochondral allograft transplantation is a good treatment option of cartilage defects. However, this treatment option is not available in all countries due to limited graft availability and tissue banks limitations. The purpose of this study is to assess the short term functional and imaging outcomes of fresh osteochondral allograft transplantation in the knee using the femoral head of living donors. Fresh osteochondral allografts from the femoral heads of living donors is a valid graft source for management of distal Femur cartilage defects. This technique can improve functional knee scores with good radiological outcomes. Prospective case series. Fifteen patients with full thickness cartilage defects of the distal femur underwent osteochondral allograft transplantation from the femoral heads of living donors. Grafts were transplanted by both shell and multiple dowels techniques. The average follow up duration was 18.3 months (range, 12-25 months). Patients were evaluated by Lysholm and International Knee Documentation Committee (IKDC) scores, radiography and MR imaging using Osteochondral Allograft MRI Scoring System (OCAMRISS). There was a statistically significant improvement (P < 0.001) in both Lysholm and IKDC average scores at 6 months and 12 months postoperative. Postoperative MRI was done at an average 6.8 months (range, 5-11 months) postoperative. The mean total OCAMRISS score was 3.4 (range, 1-7). A second look arthroscopy was done in four patients and showed intact articular cartilage in all three patients. Femoral head of living donors is a valid new source for fresh osteochondral allograft transplantation of knee osteochondral lesions. Short term results showed improvement in clinical assessment scores. Follow up imaging showed graft incorporation and good MRI scores.

Accelerated High-Resolution Deep Learning Reconstruction Turbo Spin Echo MRI of the Knee at 7 T.

The aim of this study was to compare the image quality of 7 T turbo spin echo (TSE) knee images acquired with varying factors of parallel-imaging acceleration reconstructed with deep learning (DL)-based and conventional algorithms. This was a prospective single-center study. Twenty-three healthy volunteers underwent 7 T knee magnetic resonance imaging. Two-, 3-, and 4-fold accelerated high-resolution fat-signal-suppressing proton density (PD-fs) and T1-weighted coronal 2D TSE acquisitions with an encoded voxel volume of 0.31 × 0.31 × 1.5 mm3 were acquired. Each set of raw data was reconstructed with a DL-based and a conventional Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) algorithm. Three readers rated image contrast, sharpness, artifacts, noise, and overall quality. Friedman analysis of variance and the Wilcoxon signed rank test were used for comparison of image quality criteria. The mean age of the participants was 32.0 ± 8.1 years (15 male, 8 female). Acquisition times at 4-fold acceleration were 4 minutes 15 seconds (PD-fs, Supplemental Video is available at http://links.lww.com/RLI/A938) and 3 minutes 9 seconds (T1, Supplemental Video available at http://links.lww.com/RLI/A939). At 4-fold acceleration, image contrast, sharpness, noise, and overall quality of images reconstructed with the DL-based algorithm were significantly better rated than the corresponding GRAPPA reconstructions (P < 0.001). Four-fold accelerated DL-reconstructed images scored significantly better than 2- to 3-fold GRAPPA-reconstructed images with regards to image contrast, sharpness, noise, and overall quality (P ≤ 0.031). Image contrast of PD-fs images at 2-fold acceleration (P = 0.087), image noise of T1-weighted images at 2-fold acceleration (P = 0.180), and image artifacts for both sequences at 2- and 3-fold acceleration (P ≥ 0.102) of GRAPPA reconstructions were not rated differently than those of 4-fold accelerated DL-reconstructed images. Furthermore, no significant difference was observed for all image quality measures among 2-fold, 3-fold, and 4-fold accelerated DL reconstructions (P ≥ 0.082). This study explored the technical potential of DL-based image reconstruction in accelerated 2D TSE acquisitions of the knee at 7 T. DL reconstruction significantly improved a variety of image quality measures of high-resolution TSE images acquired with a 4-fold parallel-imaging acceleration compared with a conventional reconstruction algorithm.

Anterior cruciate ligament tear detection using gated recurrent unit and flexible fitness dependent optimizer

Anterior Cruciate Ligament (ACL) tear is a common knee injury that can be diagnosed using Magnetic Resonance Imaging (MRI). In this study, a novel approach has been proposed for improving the accuracy of ACL tear detection using an optimized Gated Recurrent Unit (GRU) model. The GRU model is a type of Recurrent Neural Network (RNN) that can capture the temporal features of MRI images. The optimization of the GRU model is based on a modified metaheuristic technique, called the Flexible Fitness Dependent Optimizer (FFDO). The FFDO is a flexible and problem-dependent algorithm that can find the best solutions to optimize problems by generating and evaluating a set of candidate solutions based on a fitness function. The proposed approach is applied to the MRNet dataset, and the results are compared with 17 state-of-the-art methods. The results show that the proposed approach can achieve a high accuracy of97.95%for ACL tear detection, which is higher than the existing deep learning and machine learning methods. The proposed approach can also achieve high values for other performance metrics, such as specificity, sensitivity, precision, MCC, F1-score, and AUC. The proposed approach can effectively extract the essential features of knee MRI images that are indicative of ACL tears with high diagnostic accuracy.