Ultrashort echo time magnetization transfer imaging of knee cartilage and meniscus after long-distance running.

OBJECTIVE: To assess the detection of changes in knee cartilage and meniscus of amateur marathon runners before and after long-distance running using a 3D ultrashort echo time MRI sequence with magnetization transfer preparation (UTE-MT). METHODS: We recruited 23 amateur marathon runners (46 knees) in this prospective cohort study. MRI scans using UTE-MT and UTE-T2* sequences were performed pre-race, 2 days post-race, and 4 weeks post-race. UTE-MT ratio (UTE-MTR) and UTE-T2* were measured for knee cartilage (eight subregions) and meniscus (four subregions). The sequence reproducibility and inter-rater reliability were also investigated. RESULTS: Both the UTE-MTR and UTE-T2* measurements showed good reproducibility and inter-rater reliability. For most subregions of cartilage and meniscus, the UTE-MTR values decreased 2 days post-race and increased after 4 weeks of rest. Conversely, the UTE-T2* values increased 2 days post-race and decreased after 4 weeks. The UTE-MTR values in lateral tibial plateau, central medial femoral condyle, and medial tibial plateau showed a significant decrease at 2 days post-race compared to the other two time points (p < 0.05). By comparison, no significant UTE-T2* changes were found for any cartilage subregions. For meniscus, the UTE-MTR values in medial posterior horn and lateral posterior horn regions at 2 days post-race were significantly lower than those at pre-race and 4 weeks post-race (p < 0.05). By comparison, only the UTE-T2* values in medial posterior horn showed a significant difference. CONCLUSIONS: UTE-MTR is a promising method for the detection of dynamic changes in knee cartilage and meniscus after long-distance running. KEY POINTS: • Long-distance running causes changes in the knee cartilage and meniscus. • UTE-MT monitors dynamic changes of knee cartilage and meniscal non-invasively. • UTE-MT is superior to UTE-T2* in monitoring dynamic changes in knee cartilage and meniscus.

Assessment of Achilles Tendon Changes After Long-Distance Running Using Ultrashort Echo Time Magnetization Transfer MR Imaging.

BACKGROUND: Long-distance running is a common cause of Achilles tendinopathy. A reliable magnetic resonance imaging (MRI) technique to track early changes in the tendon caused by running could facilitate more effective interventions to combat progression. PURPOSE: To evaluate an ultrashort echo time sequence with magnetization transfer preparation (UTE-MT) in the detection of changes in Achilles tendons of amateur marathon runners before and after long-distance running. STUDY TYPE: Prospective. POPULATION: Thirty-two runners (19 enrolled for full marathons and 13 enrolled for half-marathons) and 5 healthy non-runners. FIELD STRENGTH/SEQUENCE: 3.0 T; UTE-MT and dual-echo UTE for T2* assessment (UTE-T2*). ASSESSMENT: MRI was performed 1-week pre-race, 2-days post-race, and 4-weeks post-race. UTE-MT ratio (UTE-MTR) and UTE-T2* of tendon were measured by two independent radiologists who were blinded to the scan time point and participant data. The Achilles tendon was divided into six regions of interest (ROIs) for data analysis, namely the insertion part (INS), middle part (MID), muscle-tendon junction (MTJ), tendon-bone insertion (TBI), tendon-muscle insertion (TMI), and whole tendon (bulk). STATISTICAL TESTS: Analysis of variance and Friedman's rank tests were used to evaluate changes in UTE-MTR and UTE-T2* between time points. Tukey test and Bonferroni method were used for further comparisons. P < 0.05 was considered significant. RESULTS: The UTE-MTR values of most tendon ROIs changed significantly between the measured time points, except for the INS region (P = 0.1977). Conversely, the UTE-T2* values only showed significant changes in the MID and TBI regions. Paired comparisons showed that the UTE-MTR decreases in the MTJ, MID, TMI, and bulk regions at 2-days post-race were significant compared to measures taken pre-race and 4-weeks post-race. For UTE-T2* measurements, significant differences were observed only for the MID region between pre-race and 2-days post-race (P = 0.0408, 95% CI: 0.0061, 0.1973), and for the TBI region between pre-race and 4-weeks post-race (P = 0.0473, 95% CI: 0.0013, 0.1766). DATA CONCLUSION: The UTE-MT sequence is able to detect biochemical changes in the Achilles tendon after long-distance running. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Resveratrol Plays a Protective Role against Premature Ovarian Failure and Prompts Female Germline Stem Cell Survival.

This study was designed to investigate the protective effect of resveratrol (RES) on premature ovarian failure (POF) and the proliferation of female germline stem cells (FGSCs) at the tissue and cell levels. POF mice were lavaged with RES, and POF ovaries were co-cultured with RES and/or GANT61 in vitro. FGSCs were pretreated with Busulfan and RES and/or GANT61 and co-cultured with M1 macrophages, which were pretreated with RES. The weights of mice and their ovaries, as well as their follicle number, were measured. Ovarian function, antioxidative stress, inflammation, and FGSCs survival were evaluated. RES significantly increased the weights of POF mice and their ovaries as well as the number of follicles, while it decreased the atresia rate of follicles. Higher levels of Mvh, Oct4, SOD2, GPx, and CAT were detected after treatment with RES in vivo and in vitro. RES treatment resulted in significantly lower TNF-α and IL-6 concentrations and an obviously higher IL-10 concentration in the ovaries. In FGSCs, higher Mvh, Oct4, and SOD2 concentrations and lower TNF-α, IL-6, and MDA concentrations were measured in the RES group. Blockage of the Hh signaling pathway reversed the protective effect of RES on FGSCs. In conclusion, RES effectively improved the ovarian function of the POF model and the productive capacity of FGSCs via relieving oxidative stress and inflammation and a mechanism involving the Hh signaling pathway, suggesting that RES is a potential agent against POF and can aid in the survival of FGSCs.

Automatic grading of knee osteoarthritis with a plain radiograph radiomics model: combining anteroposterior and lateral images.

OBJECTIVES: To establish a radiomics-based automatic grading model for knee osteoarthritis (OA) and evaluate the influence of different body positions on the model's effectiveness. MATERIALS AND METHODS: Plain radiographs of a total of 473 pairs of knee joints from 473 patients (May 2020 to July 2021) were retrospectively analyzed. Each knee joint included anteroposterior (AP) and lateral (LAT) images which were randomly assigned to the training cohort and the testing cohort at a ratio of 7:3. First, an assessment of knee OA severity was done by two independent radiologists with Kallgren-Lawrence grading scale. Then, another two radiologists independently delineated the region of interest for radiomic feature extraction and selection. The radiomic classification features were dimensionally reduced and a machine model was conducted using logistic regression (LR). Finally, the classification efficiency of the model was evaluated using receiver operating characteristic curves and the area under the curve (AUC). RESULTS: The AUC (macro/micro) of the model using a combination of AP and LAT (AP&LAT) images were 0.772/0.778, 0.818/0.799, and 0.864/0.879, respectively. The radiomic features from the combined images achieved better classification performance than the individual position image (p < 0.05). The overall accuracy of the radiomic model with AP&LAT images was 0.727 compared to 0.712 and 0.417 for radiologists with 4 years and 2 years of musculoskeletal diagnostic experience. CONCLUSIONS: A radiomic model constructed by combining the AP&LAT images of the knee joint can better grade knee OA and assist clinicians in accurate diagnosis and treatment. CRITICAL RELEVANCE STATEMENT: A radiomic model based on plain radiographs accurately grades knee OA severity. By utilizing the LR classifier and combining AP&LAT images, it improves accuracy and consistency in grading, aiding clinical decision-making, and treatment planning. KEY POINTS: Radiomic model performed more accurately in K/L grading of knee OA than junior radiologists. Radiomic features from the combined images achieved better classification performance than the individual position image. A radiomic model can improve the grading of knee OA and assist in diagnosis and treatment.

Nomogram model based on radiomics signatures and age to assist in the diagnosis of knee osteoarthritis.

BACKGROUND: Knee osteoarthritis (KOA) is a common disease in the elderly. An effective method for accurate diagnosis could affect the management and prognosis of patients. OBJECTIVES: To develop a nomogram model based on X-ray imaging data and age, and to evaluate its effectiveness in the diagnosis of KOA. METHODS: A total of 4403 knee X-rays from 1174 patients (July 2017 to November 2018) were retrospectively analyzed. Radiomics features were extracted and selected from the X-ray image data to quantify the phenotypic characteristics of the lesion region. Feature selection was performed in three steps to enable the derivation of robust and effective radiomics signatures. Then, logistic regression (LR), support vector machine (SVM) AdaBoost, gradient boosting decision tree (GBDT), and multi-layer perceptron (MLP) was adopted to verify the performance of radiomics signatures. In addition, a nomogram model combining age with radiomics signatures was constructed. At last, receiver operating characteristic (ROC) curve, calibration and decision curves were used to evaluate the discriminative performance. RESULTS: The LR model has the best classification performance among the four radiomics models in testing cohort (LR AUC vs. SVM AUC: 0.843 vs. 0.818, DeLong test P = 0.0024; LR AUC vs. GBDT AUC: 0.843 vs. 0.821, P = 0.0028; LR AUC vs. MLP AUC: 0.843 vs. 0.822, P = 0.0019). The nomogram model achieved better predictive efficacy than the radiomics model in testing cohort compared to radiomics models although the statistical difference was not significant (Nomogram AUC vs. Radiomics AUC: 0.847 vs. 0.843, P = 0.06). The decision curve analysis revealed that the constructed nomogram had clinical usefulness. CONCLUSION: The nomogram model combining radiomics signatures with age has good performance for the accurate diagnosis of KOA and may help to improve clinical decision-making.

Deep learning-assisted knee osteoarthritis automatic grading on plain radiographs: the value of multiview X-ray images and prior knowledge.

Background: Knee osteoarthritis (OA) is harmful to people's health. Effective treatment depends on accurate diagnosis and grading. This study aimed to assess the performance of a deep learning (DL) algorithm based on plain radiographs in detecting knee OA and to investigate the effect of multiview images and prior knowledge on diagnostic performance. Methods: In total, 4,200 paired knee joint X-ray images from 1,846 patients (July 2017 to July 2020) were retrospectively analyzed. Kellgren-Lawrence (K-L) grading was used as the gold standard for knee OA evaluation by expert radiologists. The DL method was used to analyze the performance of anteroposterior and lateral plain radiographs combined with prior zonal segmentation to diagnose knee OA. Four groups of DL models were established according to whether they adopted multiview images and automatic zonal segmentation as the DL prior knowledge. Receiver operating curve analysis was used to assess the diagnostic performance of 4 different DL models. Results: The DL model with multiview images and prior knowledge obtained the best classification performance among the 4 DL models in the testing cohort, with a microaverage area under the receiver operating curve (AUC) and macroaverage AUC of 0.96 and 0.95, respectively. The overall accuracy of the DL model with multiview images and prior knowledge was 0.96 compared to 0.86 for an experienced radiologist. The combined use of anteroposterior and lateral images and prior zonal segmentation affected diagnostic performance. Conclusions: The DL model accurately detected and classified the K-L grading of knee OA. Additionally, multiview X-ray images and prior knowledge improved classification efficacy.

Hedgehog pathway inhibition causes primary follicle atresia and decreases female germline stem cell proliferation capacity or stemness.

BACKGROUND: Follicle depletion is one of the causes of premature ovarian failure (POF) and primary ovarian insufficiency (POI). Hence, maintenance of a certain number of female germline stem cells (FGSCs) is optimal to produce oocytes and replenish the primordial follicle pool. The mechanism that regulates proliferation or stemness of FGSCs could contribute to restoring ovarian function, but it remains uncharacterized in postnatal mammalian ovaries. This study aims to investigate the mechanism by which inhibiting the activity of the hedgehog (Hh) signaling pathway regulates follicle development and FGSC proliferation. METHODS AND RESULTS: To understand the role of the Hh pathway in ovarian aging, we measured Hh signaling activity at different reproductive ages and the correlation between them in physiological and pathological mice. Furthermore, we evaluated the follicle number and development and the changes in FGSC proliferation or stemness after blocking the Hh pathway in vitro and in vivo. In addition, we aimed to explain one of the mechanisms for the FGSC phenotype changes induced by treatment with the Hh pathway-specific inhibitor GANT61 via oxidative stress and apoptosis. The results show that the activity of Hh signaling is decreased in the ovaries in physiological aging and POF models, which is consistent with the trend of expression levels of the germline stem cell markers Mvh and Oct4. In vitro, blocking the Hh pathway causes follicular developmental disorders and depletes ovarian germ cells and FGSCs after treating ovaries with GANT61. The proliferation or stemness of cultured primary FGSCs is reduced when Hh activity is blocked. Our results show that the antioxidative enzyme level and the ratio of Bcl-2/Bax decrease, the expression level of caspase 3 increases, the mitochondrial membrane potential is abnormal, and ROS accumulate in this system. CONCLUSIONS: We observed that the inhibition of the Hh signaling pathway with GANT61 could reduce primordial follicle number and decrease FGSC reproductive capacity or stemness through oxidative damage and apoptosis.