Current Status of Fear of Disease Progression in Patients with Advanced Cancer and Usefulness of Dignity Therapy Intervention.

With changes in lifestyle and an increase in bad health habits, cancer has become a noncommunicable and frequently occurring disease that poses a serious threat to human life. Cancer is associated with high rates of morbidity and mortality worldwide. As a major negative life event, advanced malignancies lead to strong mood swings in most patients. Furthermore, various internal and external factors can have a huge impact on patients' physical and mental health and put them in a stressful situation, causing a series of psychological stress responses. To explore the degree of fear of disease progression in patients with advanced cancer and the usefulness of dignity therapy. Overall, 120 patients with advanced malignant tumors admitted to Shijiazhuang No. 1 hospital between January 2019 and January 2020 were enrolled. The selected patients were divided into the test and control groups (60 people per group) using a random number table. All patients received basic treatment. Patients in the trial group also received dignity therapy. The intervention period was 4 weeks. Simplified scales were used for assessing disease progression (FoP-Q-SF) and quality of life (QLQ-C30) before and after the intervention, and the scores were compared between the groups. After the intervention, the degree of fear in the experimental group was lower than that of the control group. Cognitive function, emotional function, and the scores of the overall health status of the experimental group were higher than those of the control group. Additionally, the scores of fatigue, insomnia, loss of appetite, and diarrhea in the experimental group were lower than those of the control group (P < 0.05). The social support level scale scores, depression scores, hospital anxiety and depression scale scores, and patient dignity inventory scores of the experimental group were lower than those of the control group (P < 0.05). Patients with advanced malignant tumors have fear, anxiety, and depression related to disease progression. Dignity therapy is useful for improving the patients' quality of life, increasing dignity, and enhancing social support.

Simultaneous Segmentation of Four Cardiac Chambers in Fetal Echocardiography.

Accurate segmentation of cardiac chambers is helpful for the diagnosis of Congenital Heart Disease (CHD) in fetal echocardiography. Previous studies mainly focused on single cardiac chamber segmentation, which cannot provide sufficient information for the cardiologists. In this paper, we present an instance segmentation approach capable of segmenting four cardiac chambers accurately and simultaneously. A novel object proposal recovery strategy is further deployed to retrieve possible missing objects. To alleviate the shortage of medical data and further improve the segmentation performance, we utilize a rotation and distortion method for data augmentation. Experiments on a fetal echocardiography dataset of 319 fetuses demonstrate that the proposed approach can achieve superior performance according to common-used evaluation metrics.Clinical relevance-This can be used to help the cardiologists to better analyze the structure and function of the fetal heart.

A category attention instance segmentation network for four cardiac chambers segmentation in fetal echocardiography.

Fetal echocardiography is an essential and comprehensive examination technique for the detection of fetal heart anomalies. Accurate cardiac chambers segmentation can assist cardiologists to analyze cardiac morphology and facilitate heart disease diagnosis. Previous research mainly focused on the segmentation of single cardiac chambers, such as left ventricle (LV) segmentation or left atrium (LA) segmentation. We propose a generic framework based on instance segmentation to segment the four cardiac chambers accurately and simultaneously. The proposed Category Attention Instance Segmentation Network (CA-ISNet) has three branches: a category branch for predicting the semantic category, a mask branch for segmenting the cardiac chambers, and a category attention branch for learning category information of instances. The category attention branch is used to correct instance misclassification of the category branch. In our collected dataset, which contains echocardiography images with four-chamber views of 319 fetuses, experimental results show our method can achieve superior segmentation performance against state-of-the-art methods. Specifically, using fivefold cross-validation, our model achieves Dice coefficients of 0.7956, 0.7619, 0.8199, 0.7470 for the four cardiac chambers, and with an average precision of 45.64%.