Bioinformatics tools are used to create a clinical prediction model for cervical cancer metastasis and to investigate the neurovascular-related genes that are involved in brain metastasis of cervical cancer. One hundred eighteen patients with cervical cancer were divided into two groups based on the presence or absence of metastases, and the clinical data and imaging findings of the two groups were compared retrospectively. The nomogram-based model was successfully constructed by taking into account four clinical characteristics (age, stage, N, and T) as well as one imaging characteristic (original_glszm_GrayLevelVariance Rad-score). In patients with cervical cancer, headaches and vomiting were more often reported in the brain metastasis group than in the other metastasis groups. According to the TCGA data, mRNA differential gene expression analysis of patients with cervical cancer revealed an increase in the expression of neurovascular-related gene Adrenoceptor Beta 1 (ADRB1) in the brain metastasis group. An analysis of the correlation between imaging features and ADRB1 expression revealed that ADRB1 expression was significantly higher in the low Rad-score group compared with the high Rad-score group (P = 0.025). Therefore, ADRB1 expression in cervical cancer was correlated with imaging features and was associated as a risk factor for cerebral neurovascular metastases. This study developed a nomogram prediction model for cervical cancer metastasis using age, stage, N, T and original_glszm_GrayLevelVariance. As a risk factor associated with the development of cerebral neurovascular metastases of cervical cancer, ADRB1 expression was significantly higher in brain metastases from cervical cancer.

Background: Imaging manifestations of active pulmonary tuberculosis (APTB) on CT described in previous studies did not cover a variety of imaging appearances of bronchogenic spread of pulmonary tuberculosis (PTB) and could overlap with many other diseases.Purpose: To propose a CT imaging sign-“fireworks sign” to demonstrate the bronchogenic spread of active pulmonary tuberculosis and correlate with histopathology. Methods: A total of 679 patients with confirmed PTB were enrolled in this study. The histological proof of APTB was obtained by means of sputum smear in 429 patients, bronchoalveolar lavage in 167 patients, biopsy or surgical histopathology in 83 patients. The clinical and imaging data were retrospectively reviewed. The “fireworks sign” on CT which was a focal conglomeration (clusters) of multiple nodules could be classified into three patterns: pistil pattern (consolidation or more nodules in the central region and fewer nodules in the peripheral region), dandelion pattern (fewer nodules in the central region and more nodules in the peripheral region) and peony pattern (nodules evenly distributed in the affected region). Imaging assessment included the pattern, number, site of fireworks sign and other associated imaging features. The histopathological comparison of fireworks sign was also performed in the biopsy or surgical specimens. Results: A total of 180 lesions with fireworks sign were found in 106 patients (106/679, 15.6%), including 71 pistil patterns, 21 dandelion patterns and 88 peony patterns, respectively. More than two patterns of fireworks sign presented in 68 patients. Histopathological proof was achieved in 83 patients and the fireworks sign was composed of centrilobular nodules which corresponded pathologically to caseous necrotic granulomas in bronchioles and alveolar ducts. Single lobe, multiple lobes of unilateral lung, and bilateral lungs involvement was presented in 66.0% (70/106), 6.6% (7/106), and 27.4% of patients (29/106), respectively. The fireworks sign decreased in density or turned into ground-glass opacity during or after anti-tuberculosis treatment in 34 patients in a series of follow-up CT scans. Other imaging features including tree-in-bud sign (21.7%), consolidation (18%), cavity (24%), bronchiectasis (21.7%), pleural effusion (2.8%), pneumothorax (1.9%), pleural thickening (35.9%) and mediastinal lymph node enlargement (13.2%) were also found.Conclusion: The fireworks sign is a CT feature of bronchogenic dissemination of active pulmonary tuberculosis and histopathologically corresponds to a comglomeration of caseous necrotic granulomas in the bronchiole and alveolar ducts.

Background: Patients with nonischemic dilated cardiomyopathy (NIDCM) are prone to arrhythmias, and the cause of mortality in these patients is either end-organ dysfunction due to pump failure or malignant arrhythmia-related death. However, identification of patients with NIDCM at risk of malignant ventricular arrhythmias (VAs) is challenging in clinical practice. The aim of this study was to evaluate whether Cardiovascular magnetic resonance feature tracking (CMR-FT) may help in identification of patients with NIDCM at risk of malignant VAs. Methods: 263 NIDCM patients who underwent both CMR, 24-hour Holter electrocardiography (ECG) and inpatient ECG were retrospectively evaluated. The patients with NIDCM were divided into two subgroups: NIDCM with VAs and NIDCM without VAs. From CMR-FT, the global peak radial strain (GPRS), global longitudinal strain (GPLS), and global peak circumferential strain (GPCS) were calculated respectively from left ventricle (LV) model. We investigated the possible predictors of NIDCM combined with VAs by univariate and multivariate logistic regression analyses. Results: The percent LGE (15.51±3.30 vs. 9.62±2.18, P<0.001) was higher in NIDCM patients with VAs than in NIDCM patients without VAs. Furthermore, the NIDCM patients complicated with VAs had significantly lower GPCS compared with the NIDCM patients without VAs (P< 0.05). Subgroup analysis based on LGE negative, the NIDCM patients complicated with VAs had significantly lower GPRS,GPCS,GPLS compared with the NIDCM patients without VAs (P<0.05 for all). Multivariate analysis showed that both GPCS and % LGE were independent predictors of NIDCM combined with VAs. Conclusions: CMR global strain can early differentiate of NIDCM patients complicated with VAs specifically when LGE was not present. GPCS < −13.19% and % LGE > 10.37% are independent predictors of NIDCM combined with VAs.