Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis for Assessing Normal-Sized Lymph Node Metastasis in Cervical Cancer: Comparison Between Readout-Segmented and Single-Shot Echo-Planar Diffusion-Weighted Imaging.

OBJECTIVE: To compare the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis derived from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) in evaluating normal-sized lymph node metastasis (LNM) in cervical cancer. METHODS: Seventy-six pathologically confirmed cervical cancer patients (stages IB and IIA) were enrolled, including 61 patients with non-LNM (group A) and 15 patients with normal-sized LNM (group B). The recorded tumor volume on T2-weighted imaging was the reference against which both DWIs were evaluated. Each ADC histogram parameter (including ADC max , ADC 90 , ADC median , ADC mean , ADC 10 , ADC min , ADC skewness , ADC kurtosis , and ADC entropy ) was compared between SS-EPI and RS-EPI and between the 2 groups. RESULTS: There was no significant difference in tumor volume between the 2 DWIs and T2-weighted imaging (both P > 0.05). Higher ADC max and ADC entropy but lower ADC 10 , ADC min and ADC skewness were found in SS-EPI than those in RS-EPI (all P < 0.05). For SS-EPI, lower ADC 90 and higher ADC kurtosis were found in group B than those in group A (both P < 0.05). For RS-EPI, lower ADC 90 and higher ADC kurtosis and ADC entropy were found in group B than those in group A (all P < 0.05). Readout-segmented echo-planar imaging ADC kurtosis showed the highest area under the curve of 0.792 in the differentiation of the 2 groups (sensitivity, 80%; specificity, 73.77%). CONCLUSIONS: Compared with SS-EPI, the ADC histogram parameters derived from RS-EPI were more accurate, and ADC kurtosis held great potential in differentiating normal-sized LNM in cervical cancer.

RESOLVE-DWI-based deep learning nomogram for prediction of normal-sized lymph node metastasis in cervical cancer: a preliminary study.

BACKGROUND: It is difficult to predict normal-sized lymph node metastasis (LNM) in cervical cancer clinically. We aimed to investigate the feasibility of using deep learning (DL) nomogram based on readout segmentation of long variable echo-trains diffusion weighted imaging (RESOLVE-DWI) and related patient information to preoperatively predict normal-sized LNM in patients with cervical cancer. METHODS: A dataset of MR images [RESOLVE-DWI and apparent diffusion coefficient (ADC)] and patient information (age, tumor size, International Federation of Gynecology and Obstetrics stage, ADC value and squamous cell carcinoma antigen level) of 169 patients with cervical cancer between November 2013 and January 2022 were retrospectively collected. The LNM status was determined by final histopathology. The collected studies were randomly divided into a development cohort (n = 126) and a test cohort (n = 43). A single-channel convolutional neural network (CNN) and a multi-channel CNN based on ResNeSt architectures were proposed for predicting normal-sized LNM from single or multi modalities of MR images, respectively. A DL nomogram was constructed by incorporating the clinical information and the multi-channel CNN. These models' performance was analyzed by the receiver operating characteristic analysis in the test cohort. RESULTS: Compared to the single-channel CNN model using RESOLVE-DWI and ADC respectively, the multi-channel CNN model that integrating both two MR modalities showed improved performance in development cohort [AUC 0.848; 95% confidence interval (CI) 0.774-0.906] and test cohort (AUC 0.767; 95% CI 0.613-0.882). The DL nomogram showed the best performance in development cohort (AUC 0.890; 95% CI 0.821-0.938) and test cohort (AUC 0.844; 95% CI 0.701-0.936). CONCLUSION: The DL nomogram incorporating RESOLVE-DWI and clinical information has the potential to preoperatively predict normal-sized LNM of cervical cancer.

A prediction model based on MRI and ultrasound to predict the risk of PAS in patient with placenta previa.

INTRODUCTION: To investigate the risk factors affecting patients with placenta previa (PP) and to construct an effective prediction model for the severity of PAS in PP. METHODS: A total of 240 pregnant women with PP were enrolled in this study. An MRI+Ultrasound-based model was developed to classify patients into placental implantation and non-placental implantation groups. Multivariate nomograms were created based on imaging features. The model was evaluated using Receiver Operating Characteristic (ROC) curve analysis. The predictive accuracy of the nomogram was assessed through calibration plots and decision curve analysis. RESULTS: The MRI+Ultrasound-based prediction model demonstrated favorable discrimination between the placental implantation and non-placental implantation groups. The calibration curve exhibited agreement between the estimated and actual probability of placental implantation. Additionally, decision curve analysis indicated a high clinical benefit across a wide range of probability thresholds. The Area under the ROC curve (AUC) was 0.911 (95 % CI: 0.76-0.947), with a sensitivity of 88.40 % and specificity of 88.10 %. CONCLUSION: The MRI+Ultrasound-based prediction model could be a valuable tool for preoperative prediction of the percentage of implantation. Our study enables obstetricians to conduct more adequate preoperative evaluations.

Neuronal activity in the anterior paraventricular nucleus of thalamus positively correlated with sweetener consumption in mice.

Although the brain can discriminate between various sweet substances, the underlying neural mechanisms of this complex behavior remain elusive. This study examines the role of the anterior paraventricular nucleus of the thalamus (aPVT) in governing sweet preference in mice. We fed the mice six different diets with equal sweetness for six weeks: control diet (CD), high sucrose diet (HSD), high stevioside diet (HSSD), high xylitol diet (HXD), high glycyrrhizin diet (HGD), and high mogroside diet (HMD). The mice exhibited a marked preference specifically for the HSD and HSSD. Following consumption of these diets, c-Fos expression levels in the aPVT were significantly higher in these two groups compared to the others. Utilizing fiber photometry calcium imaging, we observed rapid activation of aPVT neurons in response to sucrose and stevioside intake, but not to xylitol or water. Our findings suggest that aPVT activity aligns with sweet preference in mice, and notably, stevioside is the sole plant-based sweetener that elicits an aPVT response comparable to that of sucrose.

[Autophagy of prostate cancer PC-3 cells under the induction of oridonin].

OBJECTIVE: To investigate the mechanism of oridonin (ORI)-induced autophagy in prostate cancer PC-3 cells. METHODS: The PC-3 cells cultured in vitro were treated with ORI. The inhibitory ratio of oridonin In PC-3 cells was assayed by MTT. The ultrastructural cellular changes were observed under light microscope, scanning electron microscope (SEM) and transmission electron microscope (TEM). AO staining was used to observe the acidic vesicular organelles (AVOs). The level of MAP1-LC3 was detected by Western blot and reverse transcriptase polymerase chain reaction (RT-PCR) used to detect the level of mRNA of beclin 1. RESULTS: After oridonin treatment, the proliferation of PC-3 cells was inhibited significantly in a concentration and time-dependent manner. The SEM examination revealed cellular shrinkage and the disappearance of surface microvilli after ORI treatment. And on the TEM examination, the nuclei exhibited chromatin condensation and the appearance of a large number of autophagosome with double-membrane structure in cytoplasm. AO staining showed the existence of AVOs. Simultaneously, the expressions of autophagy-related proteins, MAP-LC3 and the mRNA level of beclin 1 were elevated by ORI. The autophagy inhibitor 3-MA reversed the elevation of beclin 1 mRNA. CONCLUSION: The growth of PC-3 cells is inhibited. And cellular is induced by oridonin with a potential anti-tumor effect.

Comparison between readout-segmented and single-shot echo-planar imaging in the evaluation of cervical cancer staging.

OBJECTIVE:: To compare the performance of diffusion-weighted imaging (DWI) based on readout-segmented echo-planar imaging (RESOLVE) and single-shot EPI (SS-EPI) sequence in evaluating cervical cancer staging. METHODS:: 61 patients with cervical cancer underwent DWI based on SS-EPI and RESOLVE. Two blinded readers independently assessed two sets of DW images for distinction of anatomical structures, delineation of lesion, susceptibility artefact and overall image quality on a 4-point scale. Geometric distortion was evaluated by measuring lesion anteroposterior (AP) length and left-right (LR) width derived from T2W images and those obtained from the corresponding DW images. Staging of cervical cancer on SS-EPI and RESOLVE were compared with T2WI and gold-standard of pathological findings. RESULTS:: RESOLVE was significantly superior to SS-EPI for all four criteria regarding qualitative comparisons (all p < 0.05). Regarding the geometric distortion, AP length on SS-EPI was significantly different from that of T2WI (p < 0.05), whereas there were no significant differences between RESOLVE and T2WI (both p > 0.05). The staging of SS-EPI was overestimated, while RESOLVE had a better consistency with pathological staging than SS-EPI in staging of cervical cancer. There was no significant difference in apparent diffusion coefficient value between SS-EPI and RESOLVE (p < 0.05). CONCLUSION:: RESOLVE is superior to SS-EPI in the accuracy of cervical cancer staging because of the improvement in image quality. ADVANCES IN KNOWLEDGE:: RESOLVE has a more accurate value comparable to SS-EPI in cervical cancer staging, with the advantage of the improvement in image quality and reduced geometric distortion.

Study on the autophagy of prostate cancer PC-3 cells induced by oridonin.

To investigate the mechanism of oridonin (ORI)-induced autophagy in prostate cancer PC-3 cells, PC-3 cells cultured in vitro were treated with ORI, and the inhibitory ratio of ORI on PC-3 cells was assayed by 3-4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide. The ultrastructural changes of the cells were observed under light microscope, scanning electron microscope (SEM), and transmission electron microscope (TEM). Acridine orange (AO) staining was used to observe the acidic vesicular organelles (AVOs). The level of autophagy-related proteins, MAP1-LC3, was detected by Western Blot, and RT-PCR was used to detect the level of mRNA of beclin 1. After ORI treatment, the proliferation of PC-3 cells was inhibited significantly in a concentration and time-dependent manner. SEM examination revealed cellular shrinkage and disappearance of surface microvilli in ORI-treated cells. Under TEM examination, the nuclei exhibited chromatin condensation and the appearance of a large number of autophagosomes with double-membrane structure in cytoplasm. AO staining showed the existence of AVOs. The expression of LC3 and the mRNA level of beclin 1 was increased by ORI. Furthermore, autophagy inhibitor 3-methyladenine reversed the increase of beclin 1 mRNA. The growth of PC-3 cells was inhibited, and autophagy was induced by ORI, indicating ORI may have a potential antitumor effect.