The MRI-based 3D morphologic changes of knee meniscus under knee weight-bearing and early flexion conditions

There are few studies investigate morphologic changes of knee meniscus in vivo mechanical loading and three-dimensions (3D) deformation and displacement of the whole meniscus between in vivo mechanical loading and unloading conditions are still unclear. To investigate the displacements and 3D morphological changes of the menisci under knee weight-bearing and early flexion conditions in healthy adults using a Magnetic Resonance Imaging (MRI)-compatible loading device (a 3.0 T MR imaging system) combined with a newly developed 3D comparison technique. Fifteen healthy volunteers were recruited in this cross-sectional observational study. Each subject underwent MRIs of their dominant right knee in eight different scanning conditions using a 3.0-T MRI scanner with a custom-made MRI-compatible loading device. The knee meniscus images were 3D reconstructed, and dimensional comparisons were made for each meniscal model with baseline (0°-unloaded model). The morphologic changes of the meniscal-anterior horn (AH), body (BD), and posterior horn (PH) regions were expressed as mean positive and negative deviations. The displacements were further investigated, and the meniscal extrusions of different subregions were measured. The morphologic changing patterns of human meniscus under loading and flexions were presented using 3D chromatic maps. The bilateral menisci were generally shifting laterally and posteriorly in most flexion angles and were changing medially and anteriorly under fully extended knee loading conditions. The mean deviations were more significant with loading at 0° of knee flexion, while the PH region in the lateral side changed further posteriorly with loading in 30° flexion. Most of the differences were not significant in other flexion angles between loading conditions. The extrusion of meniscus’s medial body was greater in full extension compared to any other flexing angles. Mechanical loading can significantly deform the menisci in knee extension; however, this effect is limited during knee flexion. Current study can be used as a reference for the evaluations of the integrity in meniscal functions.

Deep Learning-Based Image Feature with Arthroscopy-Aided Early Diagnosis and Treatment of Meniscus Injury of Knee Joint

The aim of this study is to explore the clinical effect of deep learning-based MRI-assisted arthroscopy in the early treatment of knee meniscus sports injury. Based on convolutional neural network algorithm, Adam algorithm was introduced to optimize it, and the magnetic resonance imaging (MRI) image super-resolution reconstruction model (SRCNN) was established. Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) were compared between SRCNN and other algorithms. Sixty patients with meniscus injury of knee joint were studied. Arthroscopic surgery was performed according to the patients’ actual type of injury, and knee scores were evaluated for all patients. Then, postoperative scores and MRI results were analyzed. The results showed that the PSNR and SSIM values of the SRCNN algorithm were (42.19 ± 4.37) dB and 0.9951, respectively, which were significantly higher than those of other algorithms ( P < 0.05). Among patients with meniscus injury, 17 cases (28.33%) were treated with meniscus suture, 39 cases (65.00%) underwent secondary resection, 3 cases (5.00%) underwent partial resection, and 1 case (1.67%) underwent full resection. After meniscus suture, secondary resection, partial resection, and total resection, the knee function scores of patients after treatment were (83.17 ± 8.63), (80.06 ± 7.96), (84.34 ± 7.74), and (85.52 ± 5.97), respectively. There was no great difference in knee function scores after different methods of treatment ( P > 0.05), and there were considerable differences compared with those before treatment ( P < 0.01). Compared with the results of arthroscopy, there was no significant difference in the grading of meniscus injury by MRI ( P > 0.05). To sum up, the SRCNN algorithm based on the deep convolutional network algorithm improved the MRI image quality and the diagnosis of knee meniscus injuries. Arthroscopic knee surgery had good results and had great clinical application and promotion value.

Magnetic Resonance Image Characterization of Knee Meniscus Signal Intensity using Crue’s Approach: Results from a Multi-centre Evidence

This study aimed to characterize knee meniscus signal-intensity using magnetic resonance imaging. Our research included knee MR images of 138 subjects from multi-centres in Nigeria, between September 2016 and December 2017. Knee images were retrieved from patients' folder of MRI scanners and transfered to a DICOM workstation (Onis 2.6) for image analysis. Knee meniscus was characterized into 0, 1, 2 & 3 grades using Crue’s grading approach. Our research revealed 58% incidence of meniscal lesion. Study yielded a significant relationship between meniscal lesion and gender (p <.005) with a greater proportion of these lesions in women than in men. Meniscal lesions showed significant association with osteoarthritis (OA) (p < 0.05). Grade 3 lesions (actual tears) were largely of horizontal configuration.

The Functionally Grading Elastic and Viscoelastic Properties of the Body Region of the Knee Meniscus

The knee meniscus is a highly porous structure which exhibits a grading architecture through the depth of the tissue. The superficial layers on both femoral and tibial sides are constituted by a fine mesh of randomly distributed collagen fibers while the internal layer is constituted by a network of collagen channels of a mean size of 22.14 $$\mu $$ μ m aligned at a $$30^{\circ }$$ 30 ∘ inclination with respect to the vertical. Horizontal dog-bone samples extracted from different depths of the tissue were mechanically tested in uniaxial tension to examine the variation of elastic and viscoelastic properties across the meniscus. The tests show that a random alignment of the collagen fibers in the superficial layers leads to stiffer mechanical responses (E = 105 and 189 MPa) in comparison to the internal regions (E = 34 MPa). All regions exhibit two modes of relaxation at a constant strain ($$\tau _1 = 6.4$$ τ 1 = 6.4 to 7.7 s, $$\tau _2$$ τ 2 = 49.9 to 59.7 s).

Clinical Diagnostic Value of Magnetic Resonance Imaging in Knee Joint Sports Injury

This article mainly analyzes the clinical effects of magnetic resonance diagnosis in knee meniscus injury. Patients with knee meniscus injury were taken as the research object. All patients used magnetic resonance examination and surgery and arthroscopy examination, and surgery and arthroscopy examination as the control parameters. The analysis used magnetic resonance diagnosis results and the classification of meniscus injury diagnosed by magnetic resonance and surgery and arthroscopy. The results showed that the sensitivity, specificity, and accuracy of conventional MR1 sequence diagnosis of medial meniscus injury were 86.3%, 95.6%, and 92.4%, respectively. The sensitivity, specificity and accuracy of conventional MRI in diagnosing lateral meniscus injury of the knee joint were 91.3%, 94.5%, and 92.5% respectively. The sensitivity of MRI to medial and lateral meniscus injury was (χ2 = 0.07, P > 0.77), There were no significant differences in specificity χ2 = 0.01, P > 0.77) and accuracy χ2 = 0.01, P > 0.77). The knee meniscus injury has a greater impact on patients. The diagnostic effect of magnetic resonance imaging is better and the diagnostic accuracy is higher. It can help clinical judgment and treatment. The effect is obvious and worthy of clinical promotion.

Comparative effects on pain arising from injury to the knee meniscus in adults: A systematic review and network meta-analysis

Objective: To identify the most effective pain management method for meniscus injuries by comparing pain relief observed with several common interventions including combined different combinations of surgery and exercise, surgery alone, supervised exercise alone and home exercise alone. Methods: PubMed, Embase, CINAHL, Cochrane Library, Web of Science, SportDiscus, and PEDro were searched from database inception through October 15, 2020. Randomized controlled trials investigating the effect of surgery and exercise for meniscus injuries by using the visual analogue scale (VAS) assessment were eligible for inclusion. Primary outcome was mean change in VAS score from baseline. Comparisons between interventions were made through use of random-effects network meta-analysis over the short-term (three months) and mid-term (12 months). Relative ranking of therapies was assessed by the surface-under-the-cumulative ranking possibilities. All reference lists of included studies were hand-searched. Results: We investigated six RCTs (total n = 796 patients). No significant difference was found between different treatments of pain control in three months and 12 months. The surface under the cumulative ranking curves suggested that supervised exercise combined with surgery was considered most likely to overshadow other treatments in reducing short-term pain (surface under cumulative ranking curve (SUCRA) values: 98.1; mean ranks: 1.1) and mid-term pain (SUCRA values: 97.2; mean rank: 1.1). Conclusion: There is not sufficient evidence to identify any preferred or more effective surgical and/or exercise-based treatment program.