Multiparameter MRI-based radiomics analysis for preoperative prediction of type II endometrial cancer.

Objectives: This study aimed to develop and validate a radiomics nomogram based on multiparameter MRI for preoperative differentiation of type II and type I endometrial carcinoma (EC). Methods: A total of 403 EC patients from two centers were retrospectively recruited (training cohort, 70 %; validation cohort, 30 %). Radiomics features were extracted from T2-weighted imaging, dynamic contrast-enhanced T1-weighted imaging at delayed phase(DCE4), and apparent diffusion coefficient (ADC) maps. Following dimensionality reduction, radiomics models were developed by logistic regression (LR), random forest (RF), bootstrap aggregating (Bagging), support vector machine (SVM), artificial neural network (ANN), and naive bayes (NB) algorithms. The diagnostic performance of each radiomics model was evaluated using the ROC curve. A nomogram was constructed by incorporating the optimal radiomics signatures with significant clinical-radiological features and immunohistochemistry (IHC) markers obtained from preoperative curettage specimens. The diagnostic performance and clinical value of the nomogram were evaluated using ROC curves, calibration curves, and decision curve analysis (DCA). Results: Among the radiomics models, the NB model, developed from 12 radiomics features derived from ADC and DCE4 sequences, exhibited strong performance in both training and validation sets, with the AUC values of 0.927 and 0.869, respectively. The nomogram, incorporating the radiomics model with significant clinical-radiological features and IHC markers, demonstrated superior performance in both the training (AUC = 0.951) and the validation sets (AUC = 0.915). Additionally, it exhibited excellent calibration and clinical utility. Conclusions: The radiomics nomogram has great potential to differentiate type II from type I EC, which may be an effective tool to guide clinical decision-making for EC patients.

Development and characterization of wax-bovine bone protein-grapeseed oil composite oleogels: Experimental and molecular simulation studies.

Three new types of composite oleogel formulations were designed. Specifically, oleogels were prepared using 90% grapeseed oil as the oil phase and carnauba wax (CW)/beeswax/rice bran wax-bovine bone protein (BBP) as gelators. All samples were solid and had an oil-binding capacity of >90%. BBP addition considerably improved the waxy texture of the oleogel and had an important effect on the crystalline network. X-ray diffractometry indicated that BBP increased the ß'-crystal content. All samples showed sol-gel thermodynamic behavior under temperature scanning. Fourier-transform infrared spectroscopy and molecular docking confirmed the formation of noncovalent interactions dominated by van der Waals forces during the development of the oleogel. The optimal components of the three oleogels exhibited an excellent effect of slowing down the release of free fatty acids. This study could serve as a reference for the development and application of wax-protein as a new binary gelator in the food industry.

Assessing the structural and foaming property changes in egg yolk proteins due to malondialdehyde: Experimental and molecular docking studies.

This study evaluated the effects of varying levels of malondialdehyde (MDA) on the structural and foaming properties of the egg yolk proteins (EYPs), and the interaction between them was explored by molecular docking. The results showed that oxidative modification due to MDA increased the carbonyl content of EYPs by 4.49 times. Simultaneously, the total sulfhydryl content was reduced by 21.47%, and the solubility of EYPs was significantly decreased (p < 0.05). Continuous oxidation disorders the previously ordered structure of EYPs. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis indicated that some proteins underwent crosslinking and aggregation with increased MDA oxidation, aligning with changes in particle size and zeta-potential. Moderate oxidation (<1 mmol/L) enhanced the foaming capacity and foam stability of EYPs. Additionally, molecular docking results uncovered favorable interactions between MDA and specific EYPs, primarily through hydrogen bonding. This research offers valuable insights into managing the functional and quality changes of yolk products during processing.

Development and external validation of a nomogram for predicting overall survival of patients with non-endometrioid endometrial cancer: A population-based analysis.

Objectives: The main objective of this study was to identify the key predictors and construct a nomogram that can be used to predict the overall survival of individuals with non-endometrioid endometrial cancer. Methods: A total of 2686 non-endometrioid endometrial cancer patients confirmed between 1988 and 2018 were selected from the Surveillance, Epidemiology, and End Results database. They were divided into a training cohort and an internal validation cohort. Independent risk factors were chosen by Cox regression analyses. A predictive nomogram model for overall survival was constructed based on above factors. A Chinese cohort of 41 patients was collected to be an external validation cohort. Results: Eight variables were estimated as independent predictors for overall survival. A nomogram was established using these factors. The C-index for predicting the overall survival of patients with non-endometrioid endometrial cancer from the nomogram was 0.734, 0.700, and 0.767 in training, internal, and external validation cohort, respectively. Calibration plots and decision curve analysis showed that the nomogram was valuable for further clinical application. Conclusion: We constructed a nomogram which can be used as an effective tool to predict the 3- and 5-year overall survival of Non-endometrioid endometrial cancer patients.

Genome-wide CRISPR screening reveals key genes and pathways associated with 20-hydroxyecdysone signal transduction in the silkworm (Bombyx mori).

Metamorphosis is a complex developmental process involving multiple pathways and a large number of genes that are regulated by juvenile hormone (JH) and 20-hydroxyecdysone (20E). Despite important progress in understanding various aspects of silkworm biology, the hormone signaling pathway in the silkworm remains poorly understood. Genome-wide screening using clustered regularly interspaced short palindromic repeats (CRISPR) / CRISPR-associated protein 9 (Cas9)-based libraries has recently emerged as a novel method for analyzing genome function, enabling further research into essential genes, drug targets, and virus-host interaction. Previously, we constructed a genome-wide CRISPR/Cas9-based library of the silkworm (Bombyx mori) and successfully revealed the genes involved in biotic or abiotic stress factor responses. In this study, we used our silkworm CRISPR library and large-scale genome-wide screening to analyze the key genes in the silkworm 20E signaling pathway and their mechanisms of action. Functional annotation showed that 20E regulates key proteins in processes that mainly occur in the cytoplasm and nucleus. Pathway enrichment analysis showed that 20E can activate phosphorylation and may affect innate immunity, interfere with intracellular nutrition and energy metabolism, and eventually cause cell apoptosis. The screening results were experimentally validated by generating cells with knockout alleles of the relevant genes, which had increased tolerance to 20E. Our findings provide a panoramic overview of signaling in response to 20E in the silkworm, underscoring the utility of genome-wide CRISPR mutant libraries in deciphering hormone signaling pathways and the mechanisms that regulate metamorphosis in insects.

A Weakly Supervised Segmentation Network Embedding Cross-Scale Attention Guidance and Noise-Sensitive Constraint for Detecting Tertiary Lymphoid Structures of Pancreatic Tumors.

The presence of tertiary lymphoid structures (TLSs) on pancreatic pathological images is an important prognostic indicator of pancreatic tumors. Therefore, TLSs detection on pancreatic pathological images plays a crucial role in diagnosis and treatment for patients with pancreatic tumors. However, fully supervised detection algorithms based on deep learning usually require a large number of manual annotations, which is time-consuming and labor-intensive. In this paper, we aim to detect the TLSs in a manner of few-shot learning by proposing a weakly supervised segmentation network. We firstly obtain the lymphocyte density maps by combining a pretrained model for nuclei segmentation and a domain adversarial network for lymphocyte nuclei recognition. Then, we establish a cross-scale attention guidance mechanism by jointly learning the coarse-scale features from the original histopathology images and fine-scale features from our designed lymphocyte density attention. A noise-sensitive constraint is introduced by an embedding signed distance function loss in the training procedure to reduce tiny prediction errors. Experimental results on two collected datasets demonstrate that our proposed method significantly outperforms the state-of-the-art segmentation-based algorithms in terms of TLSs detection accuracy. Additionally, we apply our method to study the congruent relationship between the density of TLSs and peripancreatic vascular invasion and obtain some clinically statistical results.

Application of double low-dose mode in left atrial-pulmonary venous computed tomography angiography.

This study adopted a 256-slice iCT scanner with the double low-dose mode in left atrial-pulmonary venous computed tomography angiography (CTA) and explored its effect on image quality. 120 patients were included and randomly classified into the Observation group and Control group. Patients in the Control group underwent routine left atrial CTA, while patients in the Observation group performed a double low-dose mode. Other scanning parameters were consistent in the two groups. The Full model-based iterative reconstruction (MBIR) technique was applied to fulfill image reconstruction in observation group. Continuous variables, ordered categorical variables were analyzed by statistical test. The CT values of left atrial in the Observation group were significantly higher than those in the Control group. The exposure doses (ED) and iodine intake were lower in the Observation group, as compared to the Control group. The left atrial-pulmonary venous CTA with the 256-slice iCT scanner in a double low-dose mode can reduce the ED of radiation and iodine contrast while providing high quality images. Comparatively, the ED in the Observation group was reduced by 13% compared with the control, and the iodine intake was reduced by approximately 33%.

Di-(2-ethylhexyl) phthalate aggravates psoriasis-like skin lesions: In vitro and in vivo evaluation.

Di-(2-ethylhexyl) phthalate (DEHP), which is a widely used phthalate (PAE), has recently received public attention owing to it causing health problems. The aim of this study was to elucidate the aggravating effects of DEHP on psoriasis and skin toxicity. Human keratinocyte (HaCaT) cells were treated with gradient concentrations of DEHP, and mice with imiquimod (IMQ)-induced psoriasiform dermatitis were hypodermically injected with 40 µg/kg/day of DEHP for seven consecutive days. The skin condition was assessed based on the psoriasis area and severity index score, which indicated the deterioration of IMQ-induced psoriasis-like skin lesions after DEHP exposure. To further analyze the effect of DEHP on psoriasis, the proliferation, inflammation, and tight junction (TJ) damage were examined, which correlated with the development and severity of psoriasis. The results showed that DEHP promoted proliferation both in vivo and in vitro, which manifested as epidermal thickening; an increase in cell viability; upregulation of Ki67, CDK2, cyclinD1, and proliferating cell nuclear antigen; and downregulation of p21. An excessive inflammatory response is an important factor that exacerbates psoriasis, and our results showed that DEHP can trigger the release of inflammatory cytokines as well as the infiltration of T cells. TJ disorders were found in mice and cells after DEHP treatment. Additionally, p38 mitogen-activated protein kinase (MAPK) was strongly activated during this process, which may have contributed to skin toxicity caused by DEHP. In conclusion, DEHP treatment promotes proliferation, inflammation, TJ disruption, and p38 MAPK activation in HaCaT cells and psoriasis-like skin lesions.

Favorable effect of herbal extract on androgenic alopecia: A case report.

RATIONALE: Androgenic alopecia (AGA) is a prevalent condition with progressive miniaturization of hair follicles. Currently, reliable treatments have remained limited, and complementary medications for AGA are still being investigated. Traditional Chinese medicine formulas have conspicuous advantages in the treatment of AGA with good development prospects. Zimmer aqueous spray (ZAS) is a water spray containing Zimmer herbal extract powder (ZMWP), which consists of Ligustri lucidi Fructus, Ecliptae Herba, Fallopia multiflora (Thunb.) Harald. and Polygonatum sibiricum Delar. ex Redoute, etc. ZMWP is an active ingredient in the prevention of hair loss. Our aim is to provide evidence for the effectiveness of ZAS in the treatment of AGA. PATIENT CONCERNS: A 41-year-old man had suffered from hair loss for 8 years. INTERVENTIONS: The patient with moderate AGA received 3 to 4 mL ZAS daily or every other day for 3 months. OUTCOMES: The hair density obviously increased after 3 months of therapy. The improvement of hair diameter, vellus hair rate, and 1 hair pilosebaceous unit rate were observed with a trichoscopy and quantitatively analyzed. Besides, honeycomb pigment pattern mitigated and arborized red lines. LESSONS: The results suggested that ZMWP might have the capability of improving hair growth and attenuating AGA, which can be a promising alternative treatment of AGA.

Impact of dipeptidyl peptidase-4 inhibitors on glucose-dependent insulinotropic polypeptide in type 2 diabetes mellitus: a systematic review and meta-analysis.

Aims: Glucose-dependent insulinotropic polypeptide (GIP) confers a variety of metabolic benefits in type 2 diabetes mellitus (T2DM). This meta-analysis was conducted to investigate the impact of dipeptidyl peptidase 4 (DPP4) inhibitors on GIP levels in T2DM patients. Methods: Medline (PubMed), CENTER (Cochrane Library), and Embase (Ovid) were searched and randomized controlled trials (RCTs) evaluating the impact of DPP4 inhibitors on fasting and postprandial GIP levels were obtained. For postprandial GIP, only studies with the data of GIP changes reported as the total area under the curve (AUCGIP) using a meal or oral glucose tolerance test were included. A random-effects model was used for data pooling after incorporating heterogeneity. Results: Overall, 14 RCTs with 541 T2DM patients were included. Compared to placebo/no treatment, the use of DPP4 inhibitors significantly increased the fasting GIP level (standard mean difference [SMD]: 0.77, 95% confidence interval [CI]: 0.48-1.05, P<0.001; I2 = 52%) and postprandial AUCGIP (SMD: 1.33, 95% CI: 1.02-1.64, P<0.001; I2 = 65%). Influence analysis by excluding one dataset at a time showed consistent results. Sensitivity analyses only including studies with radioimmunoassay showed also consistent results (fasting GIP: SMD: 0.75, 95% CI: 0.51-1.00, P<0.001; I2 = 0%; and postprandial AUCGIP: SMD: 1.48, 95% CI: 1.18-1.78, P<0.001; I2 = 54%). Further subgroup analyses demonstrated that the influence of DPP4 inhibitors on fasting and postprandial GIP levels in T2DM patients was not significantly changed by study characteristics such as study design, patient mean age, baseline glycated hemoglobin (HbA1c) concentration, body mass index (BMI), background treatment, treatment duration, or method for postprandial GIP measurement (all P for subgroup effects <0.05). Conclusion: The use of DPP4 inhibitors effectively increases the fasting and postprandial GIP concentrations in T2DM patients. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022356716.

Development and external validation of a clinical-radiomics nomogram for preoperative prediction of LVSI status in patients with endometrial carcinoma.

PURPOSE: To develop and validate a model that incorporates radiomics based on MRI scans and clinical characteristics to predict lymphovascular invasion (LVSI) in endometrial cancer (EC) patients. METHODS: There were 332 patients with EC enrolled retrospectively in this multicenter study. Radiomics score (Radscore) were computed using the valuable radiomics features. The independent predictors of LVSI were identified by univariate logistic analysis. Multivariate logistic regression was used to develop a clinical-radiomics predictive model. Based on the model, a nomogram was developed and validated internally and externally. The nomogram was evaluated with discrimination, calibration, decision curve analysis (DCA), and clinical impact curves (CIC). RESULTS: Three predictive models were constructed based on clinicopathological features, radiomic factors and a combination of them, and that the clinic-radiomic model performed best among the three models. Four independent factors comprised the clinical-radiomics model: dynamic contrast enhancement rate of late arterial phase (DCE2), deep myometrium invasion (DMI), lymph node metastasis (LNM), and Radscore. Clinical-radiomics model performance was 0.901 (95% CI 0.84-0.96) in the training cohort, 0.80 (95% CI 0.68-0.92) in the internal validation cohort, and 0.81 (95% CI 0.73-0.9) in the external validation cohort for identifying patients with LVSI, respectively. The model is used to develop a nomogram for clinical use. CONCLUSIONS: The MRI-based radiomics nomogram could serve as a noninvasive tool to predict LVSI in EC patients.

A review of transgenerational and multigenerational toxicology in the in vivo model animal Caenorhabditis elegans.

A large number of pollutants existing in the environment can last for a long time, and their potential toxic effects can transfer from parents to their offspring. Thus, it is necessary to investigate the toxicity of environmental pollutants across multigenerations and the underlying mechanisms in organisms. Due to its short life cycle and sensitivity to environmental exposures, Caenorhabditis elegans is an important animal model for toxicity assessment of environmental pollutants across multigenerations. In this review, we introduced the transgenerational and multigenerational toxicity caused by various environmental pollutants in C. elegans. Moreover, we discussed the underlying mechanisms for the observed transgenerational and multigenerational toxicity of environmental contaminants in C. elegans.

Complementary protective effects of autophagy and oxidative response against graphene oxide toxicity in Caenorhabditis elegans.

Graphene oxide (GO) exposure may cause damage to C. elegans. However, the role of autophagy and its interactive effect with oxidative response in GO toxicity still remain largely unclear. In the present study, we investigated the protective role of autophagy against GO and its association with oxidative response using C. elegans as an in vivo system. Results indicated that GO exposure induced autophagy in a dose dependent manner in C. elegans. Autophagy inhibitor 3-methyladenine (3-MA) and silencing autophagy genes lgg-1, bec-1 and unc-51 exacerbated the toxicity of GO whereas autophagy activator rapamycin alleviated it. In addition, the antioxidant N-Acetyl-L-cysteine (NAC) effectively suppressed the toxicity of GO with increased resistance to oxidative stress. Worms with RNAi-induced antioxidative genes sod-1, sod-2, sod-3 and sod-4 knockdown were more sensitive to GO. 3-MA increased the expression of superoxide dismutase SOD-3 under GO exposure conditions and exacerbated the toxicity of GO under the anti-oxidation inaction condition by sod-3 RNAi. In contrast, NAC reduced autophagy levels in GO exposed nematodes and increased tolerance to GO in autophagy-defective worms. These results suggested that autophagy and antioxidative response provide complementary protection against GO in C. elegans.

The NPC Families Mediate BmNPV Entry.

Baculovirus is a powerful tool for biological control in agriculture and foreign gene expression and delivery in insect and mammalian cells. Baculovirus enters host cells by multiple endocytic pathways; however, the current understanding of the Bombyx mori nucleopolyhedrovirus (BmNPV) entry mechanism remains limited. Previous studies have identified NPC1 and NPC2 as important host factors for viral infection in insect cells, although their exact role in viral infection has not yet been determined. In this study, we demonstrate that the BmNPC1 protein is an important intracellular factor for BmNPV escape from the endosomal compartment, and the expression of BmNPC1 in Sf9 cells confers the virus the ability to enter into the nucleus of Sf9 cells. Additionally, the second luminal domain of BmNPC1 (BmNPC1-C) binds to the viral glycoprotein gp64, and preincubation of BmNPV with purified BmNPC1-C inhibits virus infection. Furthermore, knockout of the BmNPC2 protein results in reduced efficiency of viral fusion with the endosomal membrane, and BmNPC2 protein interacts directly with both viral envelope glycoprotein gp64 and the host BmNPC1 protein. BmNPC2 was found to be incorporated into progeny viral particles. Taken together, our results suggest that NPC2 protein incorporated into viral particles may facilitate viral infection through promoting the interaction of BmNPV and NPC1 in the endosome, thus enhancing viral fusion and escape from endosomes. These results, combined with those from previous studies, support that BmNPV hijacks two important cholesterol receptor members (NPC1 and NCP2) in the cholesterol intracellular transport pathway for viral entry into host cells. IMPORTANCE Baculovirus is an important biological factor for controlling insect populations and represents a powerful biological tool for gene delivery and expression. However, the host receptor of baculovirus is still unknown. In this study, we demonstrate that BmNPC1 protein is an important intracellular factor for BmNPV escape from the endosomal compartment, and the expression of BmNPC1 confers the ability of virus to enter into the host cell nucleus in nonpermissive Sf9 cells. BmNPC2 can bind to the virus and promote progeny virion infection through the NPC1-NPC2 endosome cholesterol transport pathway. We believe that our study on the BmNPV entry mechanism will further facilitate the application of baculovirus systems in eukaryotic gene delivery. Not only can the cholesterol transport pathway NPC1 protein be used by a variety of enveloped viruses, but the NPC2 protein can also be used by viruses to infect host cells. This will provide new insights into the study of enveloped virus infection mechanisms.

MRI-based nomogram for differentiation of ovarian fibrothecoma and broad ligament myoma.

Currently, there are no effective approaches for differentiating ovarian fibrothecoma (OF) from broad ligament myoma (BLM). This retrospective study aimed to construct a nomogram prediction model based on MRI to differentiate OF from BLM. The quantitative and qualitative MRI features of 41 OFs and 51 BLMs were compared. Three models were established based on the combination of these features. The ability of the models to differentiate between the two cancers was assessed by ROC analysis. A nomogram based on the best model was constructed for clinical application. The three models showed good performance in differentiating between OF and BLM. The areas under the curve (AUC) of the models based on quantitative and qualitative variables were 0.88 (95% CI: 0.79-0.96) and 0.85 (95% CI: 0.76-0.93), respectively. The combined model designed from the significant variables exhibited the best diagnostic performance with the highest AUC of 0.92 (95% CI: 0.86-0.98). Calibration of the nomogram showed that the predicted probability matched the actual probability well. Analysis of the decision curve demonstrated that the nomogram was clinically useful. Relative T1 value, stone paving sign, enhancement patterns, and ascites were identified as valuable predictors for identifying OF or BLM. The MRI-based nomogram can serve as a preoperative tool to differentiate OF from BLM.

Sensory Properties and Main Differential Metabolites Influencing the Taste Quality of Dry-Cured Beef during Processing.

This study adopted widely targeted high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) metabolomics and multivariate data analysis methods to evaluate the correlation between changes in metabolites and their taste formation in dry-cured beef during processing. The physicochemical profile changed significantly in the maturity period (RG), especially due to the continuous hydrolysis and oxidation of proteins. The sensory characteristic of dry-cured beef was highest in saltiness, umami, overall taste, and after-taste in RG. Overall, 400 metabolites were mainly identified, including amino acids, peptides, organic acids, and their derivatives, nucleotides, and their metabolites, as well as carbohydrates. Cysteine and succinic acid were significantly up-regulated during the process of dry-curing beef compared to the control group (CG). Moreover, glutamine and glutathione were significantly down-regulated in the fermentation period (FG) and in RG. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that glyoxylate and dicarboxylate metabolism, glutathione metabolism, alanine, aspartate, and glutamate metabolism, arginine biosynthesis, taurine, and hypotaurine metabolism were the main metabolic pathways influencing the taste of dry-cured beef during processing. Results of correlation analysis revealed that umami is positively correlated with salty, L-cysteine, L-arginine, inosine, creatinine, and succinic acid. Our study results provide a better understanding of the changes in taste substances and will contribute to quality evaluation of dry-cured beef.

Sublethal toxicity of graphene oxide in Caenorhabditis elegans under multi-generational exposure.

Nanomaterials have received increasing attentions owing to their potential hazards to the environment and human health; however, the multi-generational toxicity of graphene oxide under consecutive multi-generational exposure scenario still remains unclear. In the present study, Caenorhabditis elegans as an in vivo model organism was employed to explore the multi-generational toxicity effects of graphene oxide and the underlying mechanisms. Endpoints including development and lifespan, locomotion behaviors, defecation cycle, brood sizes, and oxidative response were evaluated in the parental generation and subsequent five filial generations. After continuous exposure for several generations, worms grew smaller and lived shorter. The locomotion behaviors were reduced across the filial generations and these reduced trends were following the impairments of locomotion-related neurons. In addition, the extended defecation cycles from the third filial generation were in consistency with the relative size reduction of the defecation related neuron. Simultaneously, the fertility function of the nematode was impaired under consecutive exposure as reduced brood sizes and oocytes numbers, increased apoptosis of germline, and aberrant expression of reproductive related genes ced-3, ced-4, ced-9, egl-1 and ced-13 were detected in exposed worms. Furthermore, the antioxidant enzyme, SOD-3 was significantly increased in the parent and filial generations. Thus, continuous multi-generational exposure to graphene oxide caused damage to the neuron development and the reproductive system in nematodes. These toxic effects could be reflected by indicators such as growth inhibition, shortened lifespan, and locomotion behavior impairment and induced oxidative response.

Preoperative MRI and immunohistochemical examination for the prediction of high-risk endometrial cancer.

BACKGROUND: Magnetic resonance imaging (MRI) and immunohistochemical (IHC) examination provides useful information for the risk stratification of endometrial cancer (EC). However, the use of the combination of MRI and IHC for the prediction of high-risk EC is controversial. The aim of this study was to evaluate the value of preoperative MRI and IHC examination in prediction of patients with high-risk EC. METHODS: This retrospective case-control study was conducted from January 1, 2018 to May 1, 2021 at two hospitals. A primary cohort (n=102) comprised patients with histologically confirmed EC in one hospital between January 1, 2018 and May 31, 2020. An additional external cohort (n=35) comprising patients with histologically confirmed EC in a different hospital from January 1, 2020 to May 1, 2021 was included for validation. Imaging features including tumor size, tumor margin, relative T2 value, tumor signal intensity on diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) were determined from preoperative MRI images. IHC markers including ER, PR, p53 and Ki67 were determined through IHC staining of preoperative curettage specimen. Patients were divided into high-risk and low-intermediate- risk group based on the final histological results. Differences between categorical and numerical variables were assessed using chi-square test and independent-sample t-test, respectively. Multivariate binary logistic regression analyses were used for construction of the prediction model A fusion prediction model was constructed by combining MRI features and IHC markers. The predictive performance of the model was then validated using the external cohort. RESULTS: Imaging and IHC markers were significantly associated with risk ranks. Model 1 based on MRI features showed an area under the curve (AUC) of 0.822 [95% confidence interval (CI), 0.741-0.903] whereas Model 2 based on IHC markers showed an AUC of 0.894 (95% CI, 0.829-0.960). Notably, model 3 integrating independent MRI and IHC risk factors demonstrated good calibration and high differentiation ability with an AUC of 0.958 (95% CI, 0.923-0.993), and showed good discrimination with an AUC of 0.84 (95% CI, 0.677-0.942) using the external validation set. CONCLUSIONS: This study proposes a comprehensive predictive model comprising MRI and IHC features as a powerful tool for preoperative risk stratification to assist in clinical decision-making for EC patients.

Imaging, clinical, and pathologic findings of Sertoli-leydig cell tumors.

To explore the clinical features, imaging findings, and pathological manifestations of ovarian Sertoli-Leydig cell tumors (SLCTs). The clinical and pathological manifestations, tumor location, size, morphology, vascularity, computed tomography (CT) density, magnetic resonance imaging (MRI) signal intensity, and contrast enhancement patterns in five cases with SLCTs were retrospectively reviewed. SLCTs most commonly occurred in young women. Virilization was observed in three cases (60%). All five tumors were unilateral and oval or round, with a clear boundary. The solid part of the tumor was isoattenuated on the conventional CT scan, and showed isoattenuation or slight hypoattenuation relative to adjacent myometrium on T1 weighted imaging (T1WI) and T2 weighted imaging (T2WI). On contrast-enhanced images, three tumors showed marked enhancement. DICER1 hotspot mutations were commonly seen in SLCTs. A highly vascularized mass with low signal intensity (SI) of the solid part on T2WI and androgen overproduction symptoms may suggest an SLCT.

MRI-Based Radiomic Model for Preoperative Risk stratification in Stage I Endometrial Cancer.

Introduction: Preoperative risk stratification is crucial for clinical treatment of endometrial cancer (EC). This study aimed to establish a model based on magnetic resonance imaging (MRI) and clinical factors for risk classification of EC. Materials and Methods: A total of 102 patients with pathologically proven Stage I EC were included. Preoperative MRI examinations were performed in all the patients. 720 radiomic features were extracted from T2-weighted images. Least absolute shrinkage and selection operator (LASSO) regression model was performed to reduce irrelevant features. Logistic regression was used to build clinical, radiomic and combined predictive models. A nomogram was developed for clinical application. Results: The radiomic model has a better performance than the model based on clinical and conventional MRI characteristics [AUC of 0.946 (95% CI: 0.882-0.973) vs AUC of 0.756 (95% CI: 0.65, 0.86)]. The combined model consisting of radiomic features and tumor size showed the best predictive performance in the training cohort with AUC of 0.955 in the training and 0.889 in the validation cohorts. Conclusions: MRI-based radiomic model has great potential in prediction of low-risk ECs.