The establishment and severity assessment of ultrasound-guided prenatal bronchopulmonary dysplasia model in rat.

To study a new method for establishing animal models of prenatal bronchopulmonary dysplasia (BPD), we used lung ultrasound score (LUS) to semi-quantitatively assess the severity of lung lesions in model rats. Lipopolysaccharide (LPS) was injected into the right lung of the fetus of the rat under ultrasound-guided, and the right lung of the neonates were scanning for LUS. Specimens were collected for pathological scoring and detection of pulmonary surfactant-associated glycoprotein (SP)-C and vascular endothelial growth factor (VEGF) expression quantity. The correlation between LUS and pathological scores was analyzed. (1) The animal models were consistent with the pathological manifestations of BPD. (2) It showed a strong positive correlation between LUS and pathological scores in animal models (r = 0.84, P < 0.005), and the expression quantity of SP-C and VEGF in lung tissue were decreased (both P < 0.05). Animal models established by ultrasound-guided puncture of the lung of rats and injection of LPS were consistent with the manifestation of BPD. This method could be used to establish animal models of BPD before birth, and the severity of BPD could be assessed by using LUS.

Development and validation of a nomogram for predicting lymph node metastasis in ductal carcinoma in situ with microinvasion: A SEER population-based study.

BACKGROUND: Ductal carcinoma in situ with microinvasion (DCIS-MI) is a special type of breast cancer. It is an invasive lesion less than 1.0 mm in size related to simple ductal carcinoma in situ (DCIS). Lymph node metastasis (LNM) in DCIS-MI often indicates a poor prognosis. Therefore, the management of lymph nodes plays a vital role in the treatment strategy of DCIS-MI. Since DCIS-MI is often diagnosed by postoperative paraffin section and immunohistochemical detection, to obtain the best clinical benefits for such patients, we aim to establish and verify a nomogram to predict the possibility of lymph node metastasis in DCIS-MI patients and help preoperative or intraoperative clinical decision-making. METHODS: A retrospective analysis of patients with DCIS-MI in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2019 was performed. The study cohort was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The risk factors were determined by univariate and multivariate logistic regression analyses in the training cohort, and a nomogram was constructed. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram in the training set and validation set. An independent data cohort was obtained from the Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB) for external validation. RESULTS: This study included 3951 female patients from SEER with DCIS-MI, including 244 patients with regional lymph node metastasis, accounting for 6.18% of the total. An independent test set of 323 patients from SJTU-BCDB was used for external validation. According to the multifactorial logistic regression analysis results, age at diagnosis, ethnicity, grade, and surgical modality were included in the prediction model. The areas under the ROC curves (AUCs) were 0.739 (95% CI: 0.702~0.775), 0.732 (95% CI: 0.675~0.788), and 0.707 (95%CI: 0.607-0.807) in the training, validation and external test groups, suggesting that the column line graphs had excellent differentiation. The calibration curves slope was close to 1, and the model's predicted values were in good agreement with the actual values. The DCA curves showed good clinical utility. CONCLUSION: In this study, we constructed accurate and practical columnar maps with some clinical benefit to predict the likelihood of lymph node metastasis in patients with postoperatively diagnosed DCIS-MI and provide a reference value for specifying treatment strategies.