Pituitary adenomas (PAs) are a common subtype of intracranial tumors. The aim of the present study was to analyse the clinical and pathological features of different types of pituitary adenomas (PAs) according to the 2017 World Health Organisation Endocrine Organ Tumor Classification guidelines. The clinical data of 250 patients with PAs were collected and analysed. Differences in the incidence of invasion, recurrence and apoplexy in patients between high-and low-risk PAs were compared, as were differences in the Ki-67 index between invasive and non-invasive PAs and between recurrent PAs and non-recurrent PAs. Of the 250 cases, 45 cases were diagnosed as somatotroph adenomas, 26 cases as lactotroph adenomas, 1 case as thyrotroph adenoma, 61 cases as corticotroph adenomas, 93 cases as gonadotropin adenomas, 15 cases as null cell adenomas and 9 cases as plurihormonal adenomas. There were 5 types of high-risk pituitary adenoma identified: 17 cases of sparsely granulated somatotroph adenoma, 11 cases of lactotroph adenoma in men, 3 cases of plurihormonal PIT-1 positive adenoma and 42 cases of silent corticotroph adenoma. Crooke's cell adenoma was not identified. High-risk PAs had significantly higher rates of invasion, recurrence and apoplexy compared with that in low-risk types (P<0.001). Invasive PAs had a significantly higher Ki-67 index compared with that in non-invasive PAs (3.5±1.8 vs. 2.8±1.3; P<0.01). Recurrent PAs had a significantly higher Ki-67 index compared with that in non-recurrent PAs (3.9±1.9 vs. 2.8±1.3; P<0.001). According to the 2017 classification criteria, patients most frequently had gonadotrophin cell adenomas, followed by corticotroph adenomas and the proportion of null cell adenomas was reduced. Differences were noted in the proliferation, recurrence and apoplexy characteristics of high-risk PAs and low-risk PAs. The invasion and recurrence of PAs were found to be related to the Ki-67 index.

Background: To explore whether a multiparametric radiomics nomogram on computed tomography (CT) images based on radiomics and relevant parameters of esophageal varices (EV) can be used for predicting the EV severity in patients with cirrhotic livers. Methods:From January 2016 to August 2018, 136 consecutive patients with clinicopathologically confirmed liver cirrhosis were included for the development of a predictive model. The patients were then divided into two groups, including non-conspicuous EV group (mild-to-moderate EV, n=30) and conspicuous EV group (severe EV, n=106) by using the endoscopic validation as the reference standard.The radiomic scores (Rad scores) were constructed using the binary logistic regression model from the radiomics features of regions of interest (ROIs) in the left liver (LL) and right liver (RL), respectively. The multiparametric nomogram combined the best performance Rad-score and EV-relevant factors, and the calibration, discrimination, and clinical usefulness of developed nomogram were evaluated using calibration curves, decision curve analysis (DCA) and net reclassification index (NRI) analysis respectively. Results:The LL Rad-score calculated from radiomics features was selected with a relatively higher area under the curve (AUC) (AUC; 0.88, training cohort; 0.87, the validation cohort) compared with RL Radscore (AUC; 0.86, training cohort; 0.83, the validation cohort). In addition, cross-sectional surface area (CSA) was identified as the important predictor (P<0.05), the multiparametric nomogram containing LL Rad-score and CSA was shown to have a better predictive performance and good calibration in the training model (C-index, 0.953, 95% CI, 0.892 to 0.973) and the validation cohort (C-index, 0.938, 95% CI, 0.841 to 0.961), resulting in an improved NRI (categorical NRI of 25.9%, P=0.0128; continuous NRI of 120%, P<0.001) and integrated discriminatory improvement (IDI) (IDI =13.9%, P<0.001). DCA demonstrated that the multiparametric radiomics nomogram was clinically useful.Conclusions: A multiparametric radiomics nomogram, which incorporates the liver radiomics signature and EV-relevant indices, is a useful tool for noninvasively predicting EV severity and may complement the standard endoscopy for evaluating EV severity in patients with cirrhosis.

Intracranial epidermoid cysts are benign lesions and are rarely seen in clinical practice. Owing to similarities in imaging findings to those of common cystic lesions, the preoperative diagnosis is rendered challenging. Here, we present a case report of an epidermoid cyst at the right oculomotor nerve, which was initially misdiagnosed as a common cyst. A 14-year-old female child was admitted to our department due to a previous magnetic resonance imaging scan of a cystic lesion on the right side of the saddle that was suspected to be an oculomotor nerve cyst. In our department, this patient underwent a complete surgical resection of the tumor, and the pathology results revealed an epidermoid cyst. This is the first study that reported an epidermoid cyst at the right oculomotor nerve entering the orbit, mimicking a common cyst in imaging. We hope that this study would allow clinicians to consider this type of lesion as a differential diagnosis. Moreover, we suggest that specific diffusion-weighted imaging scan should be performed to aid in the diagnosis.

Background We aimed to assess whether the quantitative parameters of esophageal varices (EV) based on computed tomography (CT) can noninvasively predict severe EV and the risk of esophageal variceal bleeding (EVB). Methods A total of 136 endoscopically confirmed EV patients were included in this retrospective study and were divided into a non-conspicuous (mild-to-moderate EV, n = 30) and a conspicuous EV group (severe EV, n = 106), a bleeding (n = 89) and a non-bleeding group (n = 47). EV grade (EVG), EV diameter (EVD), cross-sectional surface area (CSA), EV volume (EVV), spleen volume (SV), splenic vein (SNV), portal vein (PV), diameter of left gastric vein (DLGV), and the opening type of LGV were measured independently using 3D-slicer. Univariate and multivariate logistic analysis were used to determine the independent factors and the receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance. Results The difference of EVG, EVD, CSA, EVV, DLGV, SNV between the conspicuous and non-conspicuous EV group were statistically significant (p < 0.05), area under the curves (AUCs) of them for predicting severe EV were 0.72, 0.772, 0.704, 0.768, 0.707, 0.65, with corresponding sensitivities of 70.3%, 63.5%, 50%, 74.3%, 52.7%, 48.6%, specificities of 71.4%, 85.7%, 100%, 71.4%, 81%, 81%, respectively. EVG, CSA (odds ratio 3.258, 95% CI 1.597–6.647; 1.029, 95% CI 1.008–1.050) were found to be independent predictive factors. However, there was no significant difference of the included indices between the bleeding and non-bleeding group (p > 0.05). Conclusions CT can be used as a noninvasive method to predict the severity of EV, which may reduce the invasive screening of endoscopy.

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