Pubertal hormones play an important role in brain and psychosocial development. However, the role of abnormal HPG axis states in altering brain function and structure remains unclear. The present study is aimed at determining whether there were significant differences in gray matter volume (GMV) and resting state (RS) functional connectivity (FC) patterns in girls with idiopathic central precocious puberty (CPP) and peripheral precocious puberty (PPP). We further explored the correlation between these differences and serum pubertal hormone levels. To assess this, we recruited 29 idiopathic CPP girls and 38 age-matched PPP girls. A gonadotropin-releasing hormone (GnRH) stimulation test was performed, and pubertal hormone levels (including luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol (E2), prolactin, and cortisol) were assessed. All subjects underwent multimodal magnetic resonance imaging of brain structure and function. Voxel-based morphometry (VBM) analysis was paired with seed-to-voxel whole-brain RS-FC analysis to calculate the GMV and RS-FC in idiopathic CPP and PPP girls. Correlation analyses were used to assess the effects of pubertal hormones on brain regions with structural and functional differences between the groups. We found that girls with CPP exhibited decreased GMV in the left insula and left fusiform gyrus, while connectivity between the left and right insula and the right middle frontal gyrus (MFG), as well as the left fusiform gyrus and right amygdala, was reduced in girls with CPP. Furthermore, the GMV of the left insula and peak FSH levels were negatively correlated while higher basal and peak E2 levels were associated with increased bilateral insula RS-FC. These findings suggest that premature activation of the HPG axis and pubertal hormone fluctuations alter brain structure and function involved in the cognitive and emotional process in early childhood. These findings provide vital insights into the early pathophysiology of idiopathic CPP.

A variety of tracer kinetic methods have been employed to assess tumor angiogenesis. The Standard two-Compartment model (SC) used in cervix carcinoma was less frequent, and Adiabatic Approximation to the Tissue Homogeneity (AATH) and Distributed Parameter (DP) model are lacking. This study compares two-compartment exchange models (2CXM) (AATH, SC, and DP) for determining dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in cervical cancer, with the aim of investigating the potential of various parameters derived from 2CXM for tumor diagnosis and exploring the possible relationship between these parameters in patients with cervix cancer. Parameters (tissue blood flow, F p; tissue blood volume, V p; interstitial volume, V e; and vascular permeability, PS) for regions of interest (ROI) of cervix lesions and normal cervix tissue were estimated by AATH, SC, and DP models in 36 patients with cervix cancer and 17 healthy subjects. All parameters showed significant differences between lesions and normal tissue with a P value less than 0.05, except for PS from the AATH model, F p from the SC model, and V p from the DP model. Parameter V e from the AATH model had the largest AUC (r = 0.85). Parameters F p and V p from SC and DP models and V e and PS from AATH and DP models were highly correlated, respectively, (r > 0.8) in cervix lesions. Cervix cancer was found to have a very unusual microcirculation pattern, with over-growth of cancer cells but without evident development of angiogenesis. V e has the best performance in identifying cervix cancer. Most physiological parameters derived from AATH, SC, and DP models are linearly correlated in cervix cancer.

Background To compare different fitting methods for determining IVIM (Intravoxel Incoherent Motion) parameters and to determine whether the use of different IVIM fitting methods would affect differentiation of cervix cancer from normal cervix tissue. Methods Diffusion-weighted echo-planar imaging of 30 subjects was performed on a 3.0 T scanner with b-values of 0, 30, 100, 200, 400, 1000 s/mm2. IVIM parameters were estimated using the segmented (two-step) fitting method and by simultaneous fitting of a bi-exponential function. Segmented fitting was performed using two different cut-off b-values (100 and 200 s/mm2) to study possible variations due to the choice of cut-off. Friedman’s test and Student’s t-test were respectively used to compare IVIM parameters derived from different methods, and between cancer and normal tissues. Results No significant difference was found between IVIM parameters derived from the segmented method with b-value cutoff of 200 s/mm2 and the simultaneous fitting method (P>0.05). Tissue diffusivity (D) and perfusion fraction (f) were significantly lower in cervix cancer than normal tissue (P< 0.05). Conclusions IVIM parameters derived using fitting methods with small cutoff b-values could be different, however, the segmented method with b-value cutoff of 200 s/mm2 are consistent with the simultaneous fitting method and both can be used to differentiate between cervix cancer and normal tissue.

Background Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue. Purpose To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue. Material and Methods Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann–Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis. Results All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue ( P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models ( P < 0.05). Conclusion All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

Objective. A multicenter study to evaluate risk factors for the development of moderate or severe posttraumatic osteoarthritis (PTOA) and to find potential preventions. Methods. We conducted a retrospective multicenter study including the terrible triad injury (TTI) patients with surgical treatment from January 2007 to November 2014. Demographics, injury information, and treatment history were obtained retrospectively. According to the Broberg and Morrey criterion, 198 included patients were sorted into two groups: the mild or no PTOA and moderate or severe PTOA. Uni- and multivariate logistic regression analyses were used to identify risk factors for moderate or severe PTOA. Results. Moderate or severe PTOA was present in 64 patients (32.3%). Significant risk factors were Mason III radial head fracture (OR 4.049, 95% CI 1.877-8.736, p<0.001), medial collateral ligament injury (OR 5.120, 95% CI 1.261-20.790, p=0.022), and heavy use of elbow (OR 2.333, 95% CI 1.060-5.136, p=0.035). Besides, patients suffered subluxation (p=0.007) and those with more risk factors had a higher risk to develop moderate or severe PTOA. Conclusions. Moderate or severe PTOA was common after the TTI. Patients need to be counseled about avoiding heavy use of the elbow, especially for those with Mason III radial head fractures. Surgeons should be aware of the recurrent instability of the elbow.