Radiomics nomogram in aiding preoperatively dilatation and curettage in differentiating type II and type I endometrial cancer.

AIM: To established a radiomics nomogram for improving the dilatation and curettage (D&C) result in differentiating type II from type I endometrial cancer (EC) preoperatively. MATERIAL AND METHODS: EC patients (n=875) were enrolled retrospectively and divided randomly into a training cohort (n=437) and a test cohort (n=438), according to the ratio of 1:1. Radiomics signatures were extracted and selected from apparent diffusion coefficient (ADC) maps. A multivariate logistic regression analysis was used to identify the independent clinical risk factors. An ADC based-radiomics nomogram was built by integrating the selected radiomics signatures and the independent clinical risk factors. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the radiomics nomogram. The net reclassification index (NRI) and total integrated discrimination index (IDI) were calculated to compare the discrimination performances between the radiomics nomogram and the D&C result. RESULTS: Receiver operating characteristic (ROC) curves showed that the clinical risk factors, the D&C, and the ADC based-radiomics nomogram yielded areas under the ROC curves (AUCs) of 0.70 (95% CI: 0.64-0.76), 0.85 (95% CI: 0.80-0.89), and 0.93 (95% CI: 0.90-0.96) in the training cohort and 0.64 (95% CI: 0.57-0.71), 0.82 (95% CI: 0.77-0.87) and 0.91 (95% CI: 0.87-0.95) in the test cohort, respectively. The DCA, NRI, and IDI demonstrated the clinically usefulness of the ADC based-radiomics nomogram. CONCLUSION: The ADC-based radiomics nomogram could be used to improve the D&C result in differentiating type II from type I EC preoperatively.

MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers.

AIM: To investigate the magnetic resonance imaging (MRI) characteristics that could differentiate mucinous borderline ovarian tumours (MBOTs) from mucinous ovarian cancers (MOCs). MATERIALS AND METHODS: MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI features, including age, bilaterality, maximum diameter (MD), shape, margin, configuration, cystic-solid interface, papillae, MD of the cyst walls and septa, MD of the solid components, number of cysts, honeycomb loculi, signal of the cystic and solid components, apparent diffusion coefficient (ADC) value and enhancement ratio of the solid components, peritoneal implants and ascites, were compared using univariable analysis and multivariable logistic regression analysis. RESULTS: There were 76 MBOTs and 39 MOCs, and median patient age was 41 years (range 16-77 years) and 51 years (range 15-90 years), respectively (p=0.004). There were significant differences between MBOTs and MOCs regarding the presence of papillae (p=0.013), MD of the solid components (p=0.001), enhancement ratio of the solid components (p=0.003), ADC value (p<0.001), and ascites (p<0.001). The optimal cut-off ADC value was 1.16 × 10-3 mm2/s, with a sensitivity of 87.1%, a specificity of 83.3%, and an area under the curve (AUC) of 0.917. CONCLUSION: Compared with MOCs, MBOTs had fewer papillae or solid components, lower enhancement ratio, higher ADC values, and were less likely to have moderate or massive ascites.

Whole solid tumour volume histogram analysis of the apparent diffusion coefficient for differentiating high-grade from low-grade serous ovarian carcinoma: correlation with Ki-67 proliferation status.

AIM: To investigate whether apparent diffusion coefficient (ADC) histogram parameters based on whole solid tumour volume could differentiate high-grade (HGSOC) from low-grade serous ovarian carcinoma (LGSOC) and to correlate those parameters with the Ki-67 proliferation index. MATERIALS AND METHODS: One hundred and seven patients with HGSOCs and 19 patients with LGSOCs confirmed at surgery and histology who underwent conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) were analysed retrospectively. ADC histogram parameters (including the mean, standard deviation [SD], 10th, 25th, 50th, 75th, and 90th percentiles, kurtosis, and skewness) were obtained using the whole solid tumour volume region of interest (ROI). The Mann-Whitney U test, Pearson's chi-square test, Fisher's exact test, kappa test, Spearman's correlation, and receiver operating characteristic (ROC) curves were used for statistical analyses. RESULTS: For ADC histogram parameters, the mean (p<0.001), SD (p=0.003), and all percentiles (10th, 25th, 50th, 75th, and 90th percentile; all p<0.001) were significantly lower in HGSOC than in LGSOC, and the area under the ROC curve (AUC) was 0.717-0.807. Skewness was significantly higher in HGSOC than in LGSOC (p<0.001, AUC = 0.773); however, kurtosis was not significantly different between HGSOC and LGSOC (p=0.140). The 25th and 75th percentiles, SD and 10th percentile, and 75th percentile showed the highest sensitivity of 91.6%, specificity of 79.0%, and accuracy of 88.1%, respectively. All histogram parameters (except for kurtosis) were poorly correlated with the Ki-67 index (|r| = 0.191-0.274, p<0.05). CONCLUSION: ADC histogram parameters based on whole solid tumour volume can be helpful for differentiating between HGSOC and LGSOC.

The relationship between solitary pulmonary nodules and bronchi: multi-slice CT-pathological correlation.

AIM: To investigate the relationship between solitary pulmonary nodules (SPN) and bronchi and its value in predicting the nature of the SPN. MATERIALS AND METHODS: We performed volumetric targeted scans of 0.5 mm collimation with multi-slice computed tomography (MSCT), reconstructing multiplanar reconstructions (MPR), curved multiplanar reconstructions (CMPR) and surface-shaded display (SSD) images of bronchi in 78 consecutive patients with SPN (53 malignant and 25 benign) and correlated the findings with those of macroscopic and microscopic specimens. RESULTS: With this CT protocol, the third to seventh-order bronchi were shown continuously and very clearly in all patients. CT findings were consistent with those of specimens. CT demonstrated the relationship between the SPN and bronchi in 46 (86.8%) malignant and 18 (75.0%) benign nodules. Five types of tumour-bronchus relationships were identified with MSCT. Type I: the bronchus was obstructed abruptly by the SPN; type II: the bronchus penetrated into the SPN with tapered narrowing and interruption; type III: the bronchial lumen shown within the SPN was patent and intact; type IV: the bronchus ran around the periphery of the SPN with intact lumen; type V: the bronchus was displaced, compressed and narrowed by the SPN. Malignant nodules were most commonly of type I (58.5%), secondly of type IV (26.4%) and rarely of type V (1.9%). Benign nodules were most often of type V (36.0%), followed by type III (20.0%), type I (16.0%), and there were no type II. Types I, II and IV were more common in malignant nodules, whereas type V was seen more frequently seen in benign nodules (p<0.05). There was no statistically significant difference between the two groups regarding type III. CONCLUSION: Ultra-thin section with MSCT and MPR, CMPR and SSD reconstruction can improve the demonstration of the patterns of tumour-bronchus relationships, which can reflect the pathological changes of the nodules to some extent and help differentiate malignant from benign tumours.