Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

Chronic obstructive pulmonary disease (COPD) and pulmonary hypertension (PH) are both chronic progressive respiratory diseases that cannot be completely cured. COPD is characterized by irreversible airflow limitation, chronic airway inflammation, and gradual decline in lung function, whereas PH is characterized by pulmonary vasoconstriction, remodeling, and infiltration of inflammatory cells. These diseases have similar pathological features, such as vascular hyperplasia, arteriolar contraction, and inflammatory infiltration. Despite these well-documented observations, the exact mechanisms underlying the occurrence and development of COPD and PH remain unclear. Evidence that mitochondrial dynamics imbalance is one major factor in the development of COPD and PH. Mitochondrial dynamics is precisely regulated by mitochondrial fusion proteins and fission proteins. When mitochondrial dynamics equilibrium is disrupted, it causes mitochondrial and even cell morphological dysfunction. Mitochondrial dynamics participates in various pathological processes for heart and lung disease. Mitochondrial dynamics may be different in the early and late stages of COPD and PH. In the early stages of the disease, mitochondrial fusion increases, inhibiting fission, and thereby compensatorily increasing adenosine triphosphate (ATP) production. With the development of the disease, mitochondria decompensation causes excessive fission. Mitochondrial dynamics is involved in the development of COPD and PH in a spatiotemporal manner. Based on this understanding, treatment strategies for mitochondrial dynamics abnormalities may be different at different stages of COPD and PH disease. This article will provide new ideas for the potential treatment of related diseases.
Humans ; Mitochondrial Dynamics/physiology* ; Pulmonary Disease, Chronic Obstructive/metabolism* ; Hypertension, Pulmonary/metabolism* ; Mitochondria/metabolism* ; Animals

Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

Objective The evaluation of lymph node properties before lung cancer surgery has a great impact with the choice of surgical methods.Although there are various examination methods,many methods have invasive or accuracy problems.In order to improve the accuracy of diagnosis,we mainly discuss the value of wide-body spectral CT in the differential diagnosis of mediastinal metastatic lymph nodes,non-metastatic lymph nodes in lung cancer patients and reactive hyperplastic lymph nodes.Methods The clinical and imaging data of 64 patients with lung cancer and 28 patients with pulmonary inflammatory lesions were retrospectively analyzed.All patients underwent plain scan and enhanced dual-phase spectral CT scan.The size,density,three-phase IC,NIC,and λHU of lymph nodes in metastatic,non-metastatic and inflammatory reactive hyperplasia groups were measured on 70 keV single-energy images and iodine-based images,respectively.The single-factor variance and Kruskal-Wallis H rank sum test were used to analyze and compare the differences.Results The short diameter of metastatic lymph nodes was larger than that of non-metastatic lymph nodes and reactive hyperplastic lymph nodes(P<0.001).The plain scan density of reactive hyperplastic lymph nodes was higher than that of metastatic lymph nodes(P<0.001),but there was no significant difference between non-metastatic lymph nodes(P=0.325).The CT values of reactive hyperplastic lymph nodes in arterial phase and venous phase were higher than those of metastatic and non-metastatic lymph nodes(P<0.05).Except for NIC in arterial phase,IC,NIC and λHU in plain scan,IC and λHU in arterial phase,IC,NIC and λHU in venous phase of reactive hyperplastic lymph nodes and metastatic lymph nodes were statistically significant(all P<0.05).There was no significant difference in IC,NIC and λHU between reactive hyperplastic lymph nodes and non-metastatic lymph nodes in plain scan,arterial phase and venous phase(all P>0.05).Conclusion The quantitative and spectral curve slope of iodine in mediastinal metastatic lymph nodes of lung cancer were basically lower than those in reactive hyperplastic lymph nodes.The quantitative parameters of spectral CT had certain diagnostic efficacy in differentiating metastatic lymph nodes and reactive hyperplastic lymph nodes,while the spectral parameters of non-metastatic lymph nodes and reactive hyperplastic lymph nodes were not statistically significant.

Objective To develop deep learning-based auxiliary diagnostic models for diverse pulmonary diffuse cystic diseases,and subsequently evaluate their classification performance to identify the optimal model for clinical diagnosis.Methods A total of 288 patients diagnosed with idiopathic pulmonary fibrosis(IPF),pulmonary lymphangioleiomyomatosis(PLAM),and pulmonary Langerhans cell histiocytosis(PLCH)were prospectively enrolled from the First Affiliated Hospital of Guangzhou Medical University between January 2010 and October 2022,comprising 76 cases of IPF,179 cases of PLAM,and 33 cases of PLCH.A total of 877 CT cases were collected,comprising 232 cases of IPF,557 cases of PLAM,and 88 cases of pulmonary PLCH.Based on the cutoff date of December 31,2019,the CT scans were divided into two datasets:dataset A consisted of 500 CT scans including 185 IPF cases,265 PLAM cases,and 50 PLCH cases;while dataset B comprised 377 CT scans with a distribution of 47 IPFcases,292 PLAMcases,and 38 PLCH cases.The Dataset A was randomly partitioned into training set,validation set,and test set in a ratio of 7∶1∶2.Subsequently,six distinct deep learning neural networks were employed for training after preprocessing and data augmentation.Receiver operating characteristic curves were generated to assess the model performance using metrics such as area under the curve(AUC),accuracy,sensitivity,specificity,and F1 score in order to identify the optimal model.Furthermore,a test set B comprising 30 randomly selected cases from dataset B for each disease type was utilized to evaluate the trained optimal model by employing the same aforementioned metrics.Results In test A,six well-established diagnostic models demonstrated superior classification performance for IPF and LAM,with an AUC greater than 0.9.For LCH,EfficientNet exhibited low classification efficiency with an AUC between 0.6 and 0.7,while Vgg11 showed an AUC between 0.8 and 0.9;the other four models displayed excellent classification efficiency with an AUC greater than 0.9.Except for Inception V3,the remaining five diagnostic models performed poorly in identifying and classifying LCH lesions.Considering multiple indicators,the InceptionV3 model showcased optimal comprehensive performance among the six models,achieving high evaluation parameters such as overall accuracy(94.90%),precision(93.49%),recall(90.84%),and specificity(96.91%).TestB was conducted using the trained InceptionV3 model resulting in an accuracy of 81%,precision of 82%,recall of 81%,and specificity of 90%.Conclusions Six recognition and classification models,developed using deep learning technology in conjunction with pulmonary CT images,demonstrate effective discrimination between LAM,LCH,and IPF.Notably,the model constructed utilizing the InceptionV3 neural network exhibits superior efficiency in accurately recognizing and classifying IPF and LAM.

Objective:To explore the caregiving feelings and needs of caregivers of children with β-thalassemia major.Methods:A semi-structured interview was conducted with 14 caregivers of children with β-thalassemia major who were treated at the Affiliated Hospital of Youjiang Medical University for Nationalities from December 2022 to March 2023, and the data were analyzed using the Colaizzi 7-step analysis method.Results:Caregivers of children with β-thalassemia major felt a greater burden of care, including declining physical and mental health, disruption of daily life rhythms and heavy financial burden. And their caregiving needs included psychological and emotional support, guidance on the physical and mental health of children, assurance of a stable blood supply and medical and social support.Conclusions:Caregivers of children with β-thalassemia major have a heavy burden of care and face various nursing difficulties in the daily care of children. Medical staff should actively take measures to meet their care needs and improve their care quality and quality of life.

Objective:To understand the performance of public health risk assessment in emergencies of institutions for disease control and prevention at different levels in China, and provide suggestions for the improvement of public health risk assessment.Methods:A self-administered survey was conducted in professionals involved in public health risk assessment in emergencies from national institution, provincial institutions and some prefectural institutions for disease control and prevention (1-2 prefectural institutions were selected using convenience sampling in each province) between March and April in 2021.Results:A total of 79 institutions for disease control and prevention were investigated, including 1 national institution, 32 provincial institutions and 46 prefectural institutions. By April 2021, all the 79 institutions surveyed had conducted risk assessment of public health emergencies, in which 61 (77.2%) had established departments responsible for the public health risk assessment, i.e. emergency management office or communicable disease prevention and control office (section), and regular risk assessment mechanisms. The main sources of information for public health risk assessment were public health surveillance systems, including the National Notifiable Diseases Reporting System (100.0%) and Public Health Emergencies Management Information System (97.5%). Compared with the provincial institutions, the prefectural institutions were more likely to use specific disease surveillance systems (84.8% vs. 62.5%; χ2=5.09, P=0.024). The risk management recommendations made by 43 institutions for disease control and prevention (54.4%) after the risk assessment were accepted by the superior health administrative departments and used in epidemic prevention and control. Conclusions:Public health risk assessment in emergencies has been widely carried out by national, provincial and prefectural institutions for disease control and prevention in China. Specialized departments and mechanisms have been established, but the information sources are still confined to public health surveillance systems and the application of the risk assessment results still needs to be further improved.

Background::Familial hypercholesterolemia (FH) is underrecognized, and its association with coronary artery disease (CAD) remains limited, especially in China. We aimed to investigate the prevalence of FH and its relationship with CAD in a large Chinese cohort.Methods::FH was defined using the Make Early Diagnosis to Prevent Early Death (MEDPED) criteria. The crude and age-sex standardized prevalence of FH were calculated based on surveys of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project during 2007-2008. The associations of FH with incident CAD and its major subtypes were estimated with the cohort-stratified multivariate Cox proportional hazard models based on the data from the baseline to the last follow-up (2018-2020).Results::Among 98,885 included participants, 190 participants were defined as FH. Crude and age-sex standardized prevalence and 95% confidence interval (CI) of FH were 0.19% (0.17%–0.22%) and 0.13% (0.10%–0.16%), respectively. The prevalence varied across age groups and peaked in the group of 60–<70 years (0.28%), and the peak prevalence (0.18%) in males was earlier, yet lower than the peak crude prevalence in females (0.41%). During a mean follow-up of 10.7 years, 2493 cases of incident CAD were identified. After multivariate adjustment, FH patients had a 2.03-fold greater risk of developing CAD compared to non-FH participants.Conclusions::The prevalence of FH was estimated to be 0.19% in the participants, and it was associated with an elevated risk of incident CAD. Our study suggests that early screening of FH has certain public health significance for the prevention of CAD.

Background::Population-based epidemiological evidence regarding the association between fruit and vegetable intake and the incidence of hypertension is inconsistent. This prospective cohort study aimed to investigate the association between fruit and vegetable intake and the risk of new-onset hypertension.Methods::Based on the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR), 58,981 Chinese adults without hypertension at baseline were included. Information on fruit and vegetable intake was collected using a food-frequency questionnaire. Cox proportional hazards models were performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of incident hypertension.Results::During 640,795 person-years of follow-up, 21,008 new cases of hypertension were recorded. Compared with participants in the lowest quintile (Q1) of total fruit and vegetable (TFV) intake, the HRs (95% CIs) of incident hypertension were 0.90 (0.86-0.95), 0.85 (0.81-0.90), 0.82 (0.78-0.86), and 0.83 (0.78-0.88) for the Q2 to Q5 group ( ptrend < 0.001), respectively. In further analyses categorizing participants according to the recommended intake level (500 g/day), we found that increasing the intake of TFV, even though it was still insufficient for the recommendation, also had a protective effect against the incident hypertension. When considering the intake of fruit or vegetable separately, we found similar trends as the TFV intake. Conclusion::These results suggest that a higher intake of fruit and vegetable is beneficial for preventing hypertension in Chinese adults.

Background::Familial hypercholesterolemia (FH) is underrecognized, and its association with coronary artery disease (CAD) remains limited, especially in China. We aimed to investigate the prevalence of FH and its relationship with CAD in a large Chinese cohort.Methods::FH was defined using the Make Early Diagnosis to Prevent Early Death (MEDPED) criteria. The crude and age-sex standardized prevalence of FH were calculated based on surveys of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project during 2007-2008. The associations of FH with incident CAD and its major subtypes were estimated with the cohort-stratified multivariate Cox proportional hazard models based on the data from the baseline to the last follow-up (2018-2020).Results::Among 98,885 included participants, 190 participants were defined as FH. Crude and age-sex standardized prevalence and 95% confidence interval (CI) of FH were 0.19% (0.17%–0.22%) and 0.13% (0.10%–0.16%), respectively. The prevalence varied across age groups and peaked in the group of 60–<70 years (0.28%), and the peak prevalence (0.18%) in males was earlier, yet lower than the peak crude prevalence in females (0.41%). During a mean follow-up of 10.7 years, 2493 cases of incident CAD were identified. After multivariate adjustment, FH patients had a 2.03-fold greater risk of developing CAD compared to non-FH participants.Conclusions::The prevalence of FH was estimated to be 0.19% in the participants, and it was associated with an elevated risk of incident CAD. Our study suggests that early screening of FH has certain public health significance for the prevention of CAD.