Medial meniscus tears are most prevalent in type I ACL tears, while type I ACL tears only account for 8% of all ACL tears.

PURPOSE: This study aimed to assess the distribution of different anterior cruciate ligament (ACL) tear locations in different magnetic resonance imaging (MRI) planes, and to explore the relationships of ACL tear types with both meniscus injuries and bone bruising. METHODS: A retrospective study was performed in patients under 60 years old who underwent MRI scans in the sagittal and coronal oblique planes of the knee for ACL tears between 2014 and 2020. Patients with reports of chronic tears, partial tears, or prior surgeries were excluded. Tear locations were classified into five types, and the meniscus tear measurement variables included the presence of ramp, root, bucket-handle, and other types of tears. All injuries were confirmed by arthroscopy. Meanwhile, the presence and location of bone bruising were analysed and scored with the Whole-Organ Magnetic Resonance Imaging Score (WORMS) bone bruising subscale. RESULTS: A total of 291 patients were included. The prevalence rates of type I and type III injuries were 23/291 (7.9%) and 145/291 (49.8%) in the sagittal plane and 22/291 (7.6%) and 179/291 (61.5%) in the oblique coronal plane, respectively. The prevalence of medial meniscus tears with ACL tears was 126/291 (43.3%), while that of lateral meniscus tears with ACL tears was 77/291 (26.5%). The highest prevalence of medial meniscus injury with ACL tears was 15/22 (68.2%) for type I injuries. Bone bruises were located on the lateral femoral center in 125 patients (46%) and on the lateral tibia posterior in 132 patients (48%); the common areas of bone bruising were slightly correlated with type III ACL tears but not correlated with type I ACL tears. CONCLUSION: The plane in which an MRI scan is performed affects the classification of ACL tears. The tear type is associated with the prevalence of medial meniscus injuries, and medial meniscus tears are most prevalent in type I ACL tears. LEVEL OF EVIDENCE: IV.

Alteration in topological organization characteristics of gray matter covariance networks in patients with prediabetes. / ç³–å°¿ç— å‰æœŸæ‚£è€ ç°è´¨åå˜ç½‘ç»œæ‹“æ‰‘ç»„ç»‡ç‰¹æ€§çš„æ”¹å˜.

OBJECTIVES: Prediabetes is associated with an increased risk of cognitive impairment and neurodegenerative diseases. However, the exact mechanism of prediabetes-related brain diseases has not been fully elucidated. The brain structure of patients with prediabetes has been damaged to varying degrees, and these changes may affect the topological characteristics of large-scale brain networks. The structural covariance of connected gray matter has been demonstrated valuable in inferring large-scale structural brain networks. The alterations of gray matter structural covariance networks in prediabetes remain unclear. This study aims to examine the topological features and robustness of gray matter structural covariance networks in prediabetes. METHODS: A total of 48 subjects were enrolled in this study, including 23 patients with prediabetes (the PD group) and 25 age-and sex-matched healthy controls (the Ctr group). All subjects' high-resolution 3D T1 images of the brain were collected by a 3.0 Tesla MR machine. Mini-mental state examination was used to evaluate the cognitive status of each subject. We calculated the gray matter volume of 116 brain regions with automated anatomical labeling (AAL) template, and constructed gray matter structural covariance networks by thresholding interregional structural correlation matrices as well as graph theoretical analysis. The area under the curve (AUC) in conjunction with permutation testing was employed for testing the differences in network measures, which included small world parameter (Sigma), normalized clustering coefficient (Gamma), normalized path length (Lambda), global efficiency, characteristic path length, local efficiency, mean clustering coefficient, and network robustness parameters. RESULTS: The network in both groups followed small-world characteristics, showing that Sigma was greater than 1, the Lambda was much higher than 1, and Gamma was close to 1. Compared with the Ctr group, the network of the PD group showed increased Sigma, Lambda, and Gamma across a range of network sparsity. The Gamma of the PD group was significantly higher than that in the Ctr group in the network sparsity range of 0.12-0.16, but there was no difference between the 2 groups (all P>0.05). The grey matter network showed an increased characteristic path length and a decreased global efficiency in the PD group, but AUC analysis showed that there was no significant difference between groups (all P>0.05). For the network separation measures, the local efficiency and mean clustering coefficient of the gray matter network in the PD group were significantly increased and AUC analysis also confirmed it (P=0.001 and P=0.004, respectively). In addition, network robustness analysis showed that the grey matter network of the PD group was more vulnerable to random damage (P=0.001). CONCLUSIONS: The prediabetic gray matter network shows an increased average clustering coefficient and local efficiency, and is more vulnerable to random damage than the healthy control, suggesting that the topological characteristics of the prediabetes grey matter covariant network have changed (network separation enhanced and network robustness reduced), which may provide new insights into the brain damage relevant to the disease.

Combination of 3.0T magnetic resonance imaging T2 mapping with texture analysis for evaluating the degeneration of lumbar facet joints. / 3.0Tç£å ±æŒ¯æˆåƒT2 mappingè”åˆçº¹ç†åˆ†æžè¯„ä¼°è °æ¤Žå°å ³èŠ‚é€€å˜ç¨‹åº¦.

OBJECTIVES: Quantitative magnetic resonance imaging has been successfully applied to assess the status of cartilage biochemical components. This study aimed to investigate the performance of 3.0T magnetic resonance imaging T2 mapping combined with texture analysis for evaluating the early degeneration of lumbar facet joints. METHODS: A total of 38 patients (20 in the asymptomatic group and 18 in the symptomatic group) were enrolled. All patients underwent 3.0T magnetic resonance imaging conventional sequences, water excitation three-dimensional spoiled gradient echo sequence (3D-WATSc), and T2 mapping scans. The bilateral L4/5 and L5/S1 lumbar facet joints were morphological graded using the Weishaupt criteria, T2 values, and texture parameters derived from T2 mapping of cartilage. The Kruskal-Wallis H test was used to compare the differences of parameters among different groups. Multivariate logistic regression analysis was used to obtain the independent predictive factors for evaluating the early degeneration of lumbar facet joints. Receiver operating characteristic (ROC) curve was performed and the area under curve (AUC) was calculated. Spearman correlation analysis was used to evaluate the correlation of the independent predictors of cartilage T2 value and texture parameters with the subjects' Japanese Orthopedic Association (JOA) score or Visual Analogue Scale (VAS) score. RESULTS: A total of 148 facet joints were selected, including 70 in Weishaupt 0 (normal) group, 58 in Weishaupt 1 group, and 20 in Weishaupt 2-3 group. T2 value, entropy, and contrast increased significantly as the exacerbation of facet joint degeneration (all P<0.05), while the inverse difference moment, energy, and correlation decreased (all P<0.05). Entropy among different groups was significantly different (all P<0.05), and the differences of T2 value, contrast, inverse difference moment, and energy between Weishaupt 0 and Weishaupt 1 groups, or Weishaupt 0 and Weishaupt 2-3 groups were statistically significant (all P<0.05). Multivariate logistic regression analysis suggested that T2 value and inverse difference moment were the independent predictors for evaluating early degeneration of facet joints. The combination of T2 value with inverse difference moment achieved the best performance in distinguishing Weishaupt 0 from Weishaupt 1 (AUC=0.85), with sensitivity and specificity at 92.7% and 76.5%, respectively. In the symptom group, the cartilage T2 value combined inverse difference moment was positively correlated with JOA score (r=0.475, P<0.05) and VAS score (r=0.452, P<0.05). CONCLUSIONS: 3.0T magnetic resonance imaging T2 mapping combined with texture analysis is helpful to quantitatively evaluate the early degeneration of lumbar facet joints, in which the T2 value and inverse difference moment show an indicative significance．.

[Combination of prostate imaging reporting and data system with the apparent diffusion coefficient map for the diagnosis of peripheral zone prostate cancer].

OBJECTIVE: To explore the value of prostate imaging reporting and data system version 2 (PI-RADS V2) combined with quantitative parameters derived from apparent diffusion coefficient (ADC) map in the diagnosis of peripheral zone prostate cancer.
 Methods: A total of 50 patients who underwent prostate multiparametric MRI (mpMRI) with suspicious peripheral nodules were retrospectively enrolled, and all patients were biopsy-proven histologically. Two radiologists analyzed the position and category of peripheral zone lesions based on PI-RADS V2. Then 12 ADC quantitative parameters were calculated regarding each lesion on the ADC map by post-processing software. The lesions were divided into malignant group and benign group according to histopathological findings. The ADC quantitative parameters between groups were compared, and stepwise logistic regression analysis was used to build a discriminative model. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were performed to evaluate the diagnostic power and clinical benefit.
 Results: Twenty-eight peripheral zone prostate malignant lesions and 25 benign lesions were obtained finally. The area under the ROC curve, sensitivity and specificity to differentiate peripheral zone prostate malignant from benign lesions were as follows: 0.803, 60.71%, 92.00% (PI-RADS V2 score), 0.857, 89.29%, 76.00% (ADC model), and 0.891, 71.43%, 92.00% (combined model), respectively. The discriminative power of the combined model was significantly improved compared with PI-RADS V2 score (P=0.012). The combined model had relatively optimal overall net benefit, which outperformed the PI-RADS V2 score when threshold probability varied in the range of 0.05-0.27 and 0.46-0.81.
 Conclusion: PI-RADS V2 combined with quantitative analysis of ADC map improve the power in discriminating peripheral zone prostate cancer from benign lesions, and the clinical benefit as well.

Proton Magnetic Resonance Spectroscopy-Detected Changes of Marrow Fat Content in a Rabbit Model of Osteoporosis Treated With Epigallocatechin-3-Gallate.

OBJECTIVE: The aim of this study was to longitudinally evaluate the changes in marrow fat content of ovariectomized (OVX) rabbits treated with epigallocatechin-3-gallate (EGCG) using proton magnetic resonance spectroscopy (H-MRS). METHODS: Thirty-six female New Zealand rabbits were equally divided into sham operation, OVX controls, and OVX treated with EGCG (intraperitoneally, 1.8 mg/kg) for 5 months. Marrow fat fraction by H-MRS and bone density by peripheral quantitative computed tomography were determined at 0, 3, and 5 months. Serum biomarkers and marrow adipocytes were determined at the end of experiment. RESULTS: Estrogen deficiency increased marrow fat content in a time-dependent manner, with a variation of marrow fat fraction (FF) (+25.3%) at month 3 from baseline, and it was maintained until month 5 (+66.6%, all P < 0.001). In comparison with the sham-operated controls, adipocytes density, size, and percentage of adipocytes area in the OVX controls increased by 62.9%, 44.4%, and 178%, respectively (all P < 0.05). These OVX-induced pathological changes were partly reversed by EGCG treatment. In addition, EGCG treatment reduced bone turnover and increased bone density of OVX rabbits. CONCLUSIONS: Epigallocatechin-3-gallate exhibits an anabolic effect on osteoporotic bone by concomitantly rescuing bone mass and mitigating marrow adiposity. H-MRS appears to be a useful tool for monitoring osteoporosis-related treatments.

[A cross-sectional study on the correlation between MRI signal for IPFP and knee osteoarthritis].

OBJECTIVE: To investigate the correlation between MRI signal for infrapatellar fat pad (IPFP) and pathological changes in knee osteoarthritis (KOA), and to analyze the role of IPFP in the development of knee osteoarthritis.
 Methods: A total of 114 subjects (without special knee disease) were enrolled for this study. The intensity of MRI signal for IPFP was determined by fat-suppressed proton-density-weighted turbospin-echo magnetic resonance imaging. Based on the cartilage defects and osteophytes of knee joint, the subjects were divided into a KOA group and a control group. The difference of MRI signal for IPFP between two groups was analyzed.
 Results: After excluding the potential confounders of age, gender and BMI, the intensity of MRI signal for IPFP was positively correlated with defections in patellar, medial femur, lateral tibial or knee joint (OR 1.333 to 2.168, P 0.006 to 0.023); the intensity of MRI signal for IPFP was also positively correlated with osteophytes in patellar, medial femur, lateral tibial or knee joint (OR 1.309 to1.781, P 0.004 to 0.046); the intensity of MRI signal for IPFP in the KOA group was significantly higher than that in the control group (P=0.028).
 Conclusion: The increase in the density of MRI signal for IPFP is an imaging manifestation for knee degeneration. IPFP inflammation and endocrine abnormalities may play an important role in KOA.

An injectable, chitosan-based hydrogel prepared by Schiff base reaction for anti-bacterial and sustained release applications.

Injectable hydrogels, providing sustained release as implanted materials, have received tremendous attention. In this study, chitosan-based hydrogels were prepared via Schiff base reaction of the aldehyde groups on Poly(NIPAM-co-FBEMA) and the amine groups on chitosan. Owing to the dynamic covalent linkage, the SC/PNF hydrogels exhibit pH-responsive, reversible sol-gel transition, injectable, and self-healing capacity. The mechanical strength of SC/PNF hydrogels can be operated simply by switching the composition or solid content of Poly(NIPAM-co-FBEMA) copolymers. Rheological analyses, including frequency sweeps, strain sweep scanning, and dynamic time sweeps, were employed to demonstrate the relationship between storage modulus (G'), loss modulus (G″), and composition of the SC/PNF hydrogels. In vitro release behaviors reveal that vancomycin-loaded SC/PNF hydrogel could contribute to both the initial burst release (over 1000 ppm within 4 h) and the sustained release (3000 ppm for at least 30 days). Pristine SC/PNF hydrogel holds good biocompatibility toward L929 cells and S. aureus that it degrades as incubated with S. aureus. However, vancomycin-wrapped SC/PNF hydrogel possesses a rapid bacterial-killing effect with a clear inhibition zone. In short, the SC/PNF hydrogels deliver not only sustainable release ability but also tunable physical properties, which are expected to be an outstanding candidate for non-invasive, anti-infection applications.

An innovative method based on Gaussian cloud distribution and sample information richness for eutrophication assessment of Yangtze's lakes and reservoirs under uncertainty.

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33-50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment.

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

BACKGROUND: The 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. METHODS: 50 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. RESULTS: The 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). CONCLUSIONS: High-resolution oblique coronal imaging at the optimal 30° flexed-knee angle improved ACL visualization and diagnostic performance compared with conventional techniques.

Topological abnormality of structural covariance network in MRI-negative frontal lobe epilepsy.

Background: Frontal lobe epilepsy (FLE) is the second most common type of focal epilepsy, however, imaging studies of FLE have been far less than Temporal lobe epilepsy (TLE) and the structural findings were not consistent in previous literature. Object: Investigate the changes in cortical thickness in patients with FLE and the alteration of the structural covariance networks (SCNs) of cortical thickness with graph-theory. Method: Thirty patients with FLE (18 males/12 females; 28.33 ± 11.81 years) and 27 demographically matched controls (15 males/12 females; 29.22 ± 9.73 years) were included in this study with high-resolution structural brain MRI scans. The cortical thickness was calculated, and structural covariance network (SCN) of cortical thickness were reconstructed using 68 × 68 matrix and analyzed with graph-theory approach. Result: Cortical thickness was not significantly different between two groups, but path length and node betweenness were significantly increased in patients with FLE, and the regional network alterations were significantly changed in right precentral gyrus and right temporal pole (FDR corrected, p < 0.05). Comparing to HC group, network hubs were decreased and shifted away from frontal lobe. Conclusion: The topological properties of cortical thickness covariance network were significantly altered in patients with FLE, even without obvious surface-based morphological damage. Graph-theory based SCN analysis may provide sensitive neuroanatomical biomarkers for FLE.