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Background: The functional connectivity (FC) has emerged as a valuable tool for comprehending the cerebral operational mechanism. Understanding the FC changes in patients with chronic ankle instability (CAI) helps reveal the underlying central nervous system mechanisms of the disease and provides clues for developing personalized treatment plans. Objectives: To explore differences between low‐ and high‐order FC in patients with CAI and healthy controls, as well as the correlation among the feature connections and clinical data. Methods: In our study, we recruited 40 patients with CAI and 42 healthy individuals who had not experienced ankle injuries. All participants underwent clinical assessments of ankle joints, collected the number of ankle sprains within the past 6 months, and performed resting‐state functional magnetic resonance imaging (rs‐fMRI) scans. Pearson correlation and matrix variate normal distribution (MVND) were used to construct low‐order and high‐order FC networks, respectively. Feature selections between groups were performed by two‐sample t‐tests, and a multi‐kernel support vector machine (MK‐SVM) was subsequently applied to combine the multiple connection patterns for the classification. Using leave‐one‐out cross‐validation (LOOCV) to assess classification performance and identify the consensus connections contributing most to classification. Results: FC was reduced in certain brain regions of CAI patients. More consensus connections were recognized in low‐order FC network than in high‐order FC network. The highest classification accuracy of 91.30% was achieved by combining three connection patterns. The most discriminating functional connections were primarily centered on the default mode network and spanned the visual network, sensorimotor network, ventral attention network, and central executive network. In addition, FC strength in the left cingulate and paracingulate gyrus (DCG.L) and right superior temporal gyrus (STG.R) was negatively correlated with the number of ankle sprains in the past 6 months in all FC networks (p < 0.05). Conclusions: Abnormalities in connectivity in patients with CAI were observed in both low‐ and high‐order FC networks. The adaptive changes in the brain related to CAI may extend beyond the sensorimotor networks, primarily involving higher‐level default mode networks associated with attention. Moreover, the FC strength between DCG.L and STG.R may predict the risk of ankle re‐sprains and help clinicians develop personalized treatment plans. [ABSTRACT FROM AUTHOR]

Background: The uterus undergoes dynamic changes throughout the menstrual cycle. Diffusion kurtosis imaging (DKI) is based on the non‐Gaussian distribution of water molecules and can perhaps represent the changes of uterine microstructure. Purpose: To investigate the temporal changes in DKI‐parameters of the normal uterine corpus and cervix during the menstrual cycle. Study Type: Prospective. Population: 21 healthy female volunteers (26.64 ± 4.72 years) with regular menstrual cycles (28 ± 7 days). Field Strength/Sequence: Readout segmentation of long variable echo‐trains (RESOLVE)‐based DKI and fast spin‐echo T2‐weighted sequences at 3.0T. Assessment: Each volunteer was scanned during the menstrual phase, ovulatory phase, and luteal phase. Regions of interest (ROI) were manually delineated in the endometrium, junctional zone, and myometrium of the uterine body, and in the mucosal layer, fibrous stroma layer, and loose stroma layer of the cervix. The mean Kapp (diffusion kurtosis coefficient), Dapp (diffusion coefficient), and ADC (apparent diffusion coefficient) values were measured in the ROI. Statistical Tests: ANOVA with Bonferroni or Tamhane correction. Intraclass correlation coefficient (ICC) for assessing agreement. P < 0.05 was considered statistically significant. Results: During the menstrual cycle, the highest Kapp (0.848 ± 0.184) and lowest Dapp (1.263 ± 0.283 *10−3 mm2/sec) values were found in the endometrium during the menstrual phase. The Dapp values for the myometrium were significantly higher than those of the endometrium and the junctional zone in every phase. Meanwhile, the Dapp values for the three zonal structures of the cervix during ovulation were significantly higher than those during the luteal phase. However, there was no significant difference in the ADC values of the loose stroma between ovulation and the luteal phase (P = 0.568). The reproducibility of DKI parameters was good (ICC, 0.857–0.944). Data Conclusion: DKI can show dynamic changes of the normal uterus during the menstrual cycle. Level of Evidence: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Objective: The purpose of our study was to describe the characteristic MRI appearance of cerebral infection with Schistosoma japonicum., Conclusion: Cerebral infection with S. japonicum can cause a characteristic MRI pattern of a large mass comprising multiple intensely enhancing nodules, sometimes with areas of linear enhancement. The typical appearance may be useful for diagnosis in endemic regions and may potentially be useful in cases imported into countries in which the disease is not endemic.