This article presents a case study of a patient who visited the Geriatric Department of Peking Union Medical College Hospital due to "palpitations, shortness of breath for more than 2 years, limb weakness for 6 months, edema, and nocturnal dyspnea for 2 months". The patient exhibited decreased muscle strength in the limbs and involvement of swallowing and respiratory muscles, alongside complications of heart failure and various arrhythmias which were predominantly atrial. Laboratory tests revealed the presence of multiple autoantibodies and notably anti-mitochondrial antibodies. Following a comprehensive multidisciplinary evaluation, the patient was diagnosed with anti-mitochondrial antibody-associated inflammatory myopathy. Treatment involved a combination of glucocorticoids and immunosuppressants, along with resistance exercises for muscle strength and rehabilitation training for lung function, resulting in significant improvement of clinical symptoms. The case underscores the importance of collaborative multidisciplinary approaches in diagnosing and treating rare diseases in elderly patients, where careful consideration of clinical manifestations and subtle abnormal clinical data can lead to effective interventions.

Objective To study the clinical application of self-made specimen bags using intraoperative materials in single-port thoracoscopic lobectomy.Methods The clinical data of 40 patients who underwent single-port thoracoscopic lobectomy from October 2021 to July 2022 were retrospectively analyzed,and divided into two groups by different operation methods,the conventional method group and the new method group,20 cases each group.The conventional method group used a medical sterile protective sheath,leaving about 20 cm on one side,knotting the bottom and turning it inward.The mouth of the bag was held with two oval forceps and inserted into the chest cavity to remove the specimen.The new method group followed the same procedure,with the addition of a drainage tube inserted into the bag mouth.Intraoperative specimens were taken out from selfmade specimen bags.The specimen loading time,one-time success rate,wound healing status,and short-term prognosis were compared between the two groups.Results No specimens fell off in the new method group,and all were successfully retrieved on the first attempt.In the conventional method group,specimens fell off twice(2/20),but the difference between the two groups was not significant.The average completion time of specimen loading in the new method group was(36.20±6.08)s,which was significantly shorter in the conventional method group(57.95±6.59)s,with a statistically significant difference(t=10.85,P＜0.01).There were no ulcers in any specimen bags,and the surgical incisions of all patients healed well,with no incision infection,no tumor implantation,and no intrathoracic dissemination and metastasis within one year.Conclusion The selfmade thoracoscopic specimen bag is simple to make,low-cost,safe and convenient to use.It can save operation time and reduce medical costs.

Objective:To explore the value of three-dimensional automatic right ventricular quantitive analysis（3D Auto RVQ）technology in predicting the improvement of left ventricular ejection fraction（LVEF）in patients with heart failure with reduced ejection fraction（HFrEF）.Methods:A retrospective analysis was conducted on 89 HFrEF patients admitted to the Cardiology Department of Central China Fuwai Hospital of Zhengzhou University from April 2022 to June 2024. All patients received medication treatment and were further divided into heart failure with improved ejection fraction（HFimpEF）group and non HFimpEF group based on changes detected by echocardiography in LVEF after treatment. The clinical data，biological indicators，and medication treatment status of patients were collected，routine echocardiographic parameters and right ventricular strain parameters were measured，3D right ventricular ejection fraction（3D-RVEF），3D right ventricular stroke volume index（3D-RVSVI），3D right ventricular end-diastolic volume index（3D-RVEDVI），3D right ventricular end-systolic volume index（3D-RVESVI），3D tricuspid annular plane systolic excursion（3D-TAPSE），and 3D right ventricular fractional area change（3D-RVFAC）were measured using 3D Auto RVQ technology. The differences of the above parameters between the two groups were compared. The ROC curve was used to analyze the predictive efficiency of right ventricular parameters for HFimpEF，and the area under ROC curve（AUC）was calculated and compared. Logistic regression models were used to analyze the predictive value of right ventricular parameters for HFimpEF.Results:Compared with the non HFimpEF group，the HFimpEF group had a younger age，shorter heart failure course，a smaller proportion of males，New York Heart Association（NYHA）functional class ≥Ⅲ，and patients with concomitant coronary heart disease. The baseline LVEF，absolute value of two dimensional right ventricular global longitudinal strain（2D-RVGLS），3D-RVEF，3D-TAPSE，and 3D-RVSVI were higher in the HFimpEF group（all P<0.05）. ROC curve analysis showed that the AUC of 3D-RVEF for predicting HFimpEF was 0.858，and the predictive efficiency was higher than other right ventricular parameters. According to the Yoden index，the optimal cutoff value for predicting HFimpEF based on 3D-RVEF was 36.2%，with a corresponding sensitivity of 84.0% and specificity of 75.0%. After adjusting for clinical and other echocardiographic parameters，the logistic regression model showed that 3D-RVEF was an independent predictor of HFimpEF（ OR=1.435，95% CI=1.145-1.800， P<0.05）. Conclusions:The 3D-RVEF evaluated by 3D Auto RVQ technology has high predictive value for HFimpEF，which can provide a reference for clinical treatment，thereby improving the prognosis of HFrEF patients.

Objective To study the clinical application of self-made specimen bags using intraoperative materials in single-port thoracoscopic lobectomy.Methods The clinical data of 40 patients who underwent single-port thoracoscopic lobectomy from October 2021 to July 2022 were retrospectively analyzed,and divided into two groups by different operation methods,the conventional method group and the new method group,20 cases each group.The conventional method group used a medical sterile protective sheath,leaving about 20 cm on one side,knotting the bottom and turning it inward.The mouth of the bag was held with two oval forceps and inserted into the chest cavity to remove the specimen.The new method group followed the same procedure,with the addition of a drainage tube inserted into the bag mouth.Intraoperative specimens were taken out from selfmade specimen bags.The specimen loading time,one-time success rate,wound healing status,and short-term prognosis were compared between the two groups.Results No specimens fell off in the new method group,and all were successfully retrieved on the first attempt.In the conventional method group,specimens fell off twice(2/20),but the difference between the two groups was not significant.The average completion time of specimen loading in the new method group was(36.20±6.08)s,which was significantly shorter in the conventional method group(57.95±6.59)s,with a statistically significant difference(t=10.85,P＜0.01).There were no ulcers in any specimen bags,and the surgical incisions of all patients healed well,with no incision infection,no tumor implantation,and no intrathoracic dissemination and metastasis within one year.Conclusion The selfmade thoracoscopic specimen bag is simple to make,low-cost,safe and convenient to use.It can save operation time and reduce medical costs.

Objective:To explore the value of three-dimensional automatic right ventricular quantitive analysis（3D Auto RVQ）technology in predicting the improvement of left ventricular ejection fraction（LVEF）in patients with heart failure with reduced ejection fraction（HFrEF）.Methods:A retrospective analysis was conducted on 89 HFrEF patients admitted to the Cardiology Department of Central China Fuwai Hospital of Zhengzhou University from April 2022 to June 2024. All patients received medication treatment and were further divided into heart failure with improved ejection fraction（HFimpEF）group and non HFimpEF group based on changes detected by echocardiography in LVEF after treatment. The clinical data，biological indicators，and medication treatment status of patients were collected，routine echocardiographic parameters and right ventricular strain parameters were measured，3D right ventricular ejection fraction（3D-RVEF），3D right ventricular stroke volume index（3D-RVSVI），3D right ventricular end-diastolic volume index（3D-RVEDVI），3D right ventricular end-systolic volume index（3D-RVESVI），3D tricuspid annular plane systolic excursion（3D-TAPSE），and 3D right ventricular fractional area change（3D-RVFAC）were measured using 3D Auto RVQ technology. The differences of the above parameters between the two groups were compared. The ROC curve was used to analyze the predictive efficiency of right ventricular parameters for HFimpEF，and the area under ROC curve（AUC）was calculated and compared. Logistic regression models were used to analyze the predictive value of right ventricular parameters for HFimpEF.Results:Compared with the non HFimpEF group，the HFimpEF group had a younger age，shorter heart failure course，a smaller proportion of males，New York Heart Association（NYHA）functional class ≥Ⅲ，and patients with concomitant coronary heart disease. The baseline LVEF，absolute value of two dimensional right ventricular global longitudinal strain（2D-RVGLS），3D-RVEF，3D-TAPSE，and 3D-RVSVI were higher in the HFimpEF group（all P<0.05）. ROC curve analysis showed that the AUC of 3D-RVEF for predicting HFimpEF was 0.858，and the predictive efficiency was higher than other right ventricular parameters. According to the Yoden index，the optimal cutoff value for predicting HFimpEF based on 3D-RVEF was 36.2%，with a corresponding sensitivity of 84.0% and specificity of 75.0%. After adjusting for clinical and other echocardiographic parameters，the logistic regression model showed that 3D-RVEF was an independent predictor of HFimpEF（ OR=1.435，95% CI=1.145-1.800， P<0.05）. Conclusions:The 3D-RVEF evaluated by 3D Auto RVQ technology has high predictive value for HFimpEF，which can provide a reference for clinical treatment，thereby improving the prognosis of HFrEF patients.

Objective:To investigate the correlation between plasma fibrinogen/serum albumin ratio (FAR) and the degree of cerebral artery stenosis in patients with acute cerebral infarction (ACI).Methods:Clinical data of 189 patients with acute cerebral infarction diagnosed and treated in the Department of Neurology of the First Affiliated Hospital of Hainan Medical College from January 2021 to March 2023 were selected for retrospective analysis. Digital subtraction angiography (DSA) was improved, and they were divided into four groups according to the degree of intracranial vascular stenosis according to NASCET grading method: no stenosis group (47 cases), mild stenosis group (45 cases), moderate stenosis group (39 cases) and severe stenosis and occlusion group (58 cases). The differences of basic data, plasma fibrinogen/serum albumin ratio (FAR) and other inflammatory indicators among all groups were compared, and the correlation between FAR level and the severity of cerebral artery stenosis was analyzed. Multivariate Logistic regression was used to explore the factors influencing to cerebral artery stenosis and ROC curve was used to evaluate the diagnostic value of FAR in the degree of cerebral artery stenosis in cerebral infarction patients.Results:There were significant differences in blood neutrophil (NEU), mean platelet volume (MPV), fibrinogen (FIB), fibrinogen (FIB), albumin (ALB) and FAR among the 4 groups (statistical values were H=11.50, H=8.44, F=5.16, H=30.93, H=40.38; all P<0.05). Correlation analysis showed a positive correlation between FAR and the degree of cerebral artery stenosis ( r=0.455, P<0.05). Multivariate Logistic regression showed that FAR was an independent risk factor for the degree of cerebral artery stenosis ( OR=1.445, 95% CI=1.261-1.655, P<0.001). Conclusion:FAR is an independent risk factor for cerebral artery stenosis in patients with acute cerebral infarction (ACI), and may be a new biomarker for predicting cerebral artery stenosis.

Chronic internal carotid artery occlusion, a common clinical lesion caused by atherosclerosis, was also one of the common vascular diseases in the middle and old age. It could slow down the blood flow rate of blood vessels, which leaded to changes in the blood supply of brain tissue, and secondary causes abnormal metabolism of brain nerves and brain tissue. At the same time, long-term cerebral hypoperfusion would induce cognitive impairment, which would seriously affect the quality of life of patients. At present, there were two main treatment methods: drug conservative treatment and intravascular intervention, but there was still a great controversy about the survival of the fittest in these two treatment methods. This paper reported the clinical, imaging, therapeutic strategy and prognosis of a case of severe intracranial and extracranial multiple vessel stenosis and occlusion, in order to provide reference for the early diagnosis and treatment of such patients.

Objective:To evaluate the right ventricular function in patients with dilated cardiomyopathy (DCM) by four-dimensional automatic right ventricular quantitative analysis (4D Auto RVQ), and compare with the right ventricular ejection fraction measured by cardiac magnetic resonance (CMR-RVEF), and to explore the clinical application value of 4D Auto RVQ technique in evaluating the right ventricular function of patients with DCM.Methods:A prospective study was conducted to select 52 patients with DCM who were treated in Fuwai Central China Cardiovascular Hospital of Zhengzhou University from March to October 2022 as DCM group, and 52 healthy volunteers were selected as the control group during the same period. The four-dimensional right ventricular ejection fraction (4D-RVEF), right ventricular stroke volume index (RVSVI), right ventricular end-diastolic volume index (RVEDVI), right ventricular end-systolic volume index (RVESVI), four-dimensional right ventricular basal diameter (4D-RVDd-base), four-dimensional right ventricular middle diameter (4D-RVDd-mid), four-dimensional right ventricular long axis diameter (4D-RVLd), four-dimensional tricuspid annular plane systolic excursion (4D-TAPSE) and four-dimensional right ventricular fractional area change (4D-RVFAC) were obtained by 4D Auto RVQ technique. The differences of the above parameters between DCM group and control group were compared.Pearson linear correlation analysis was used to evaluate the correlation between echocardiographic parameters and CMR-RVEF. The ROC curve was used to find the most sensitive parameters for evaluating right ventricular function, and the area under the ROC curve ( AUC ) was calculated and compared.Results:Compared with the control group, RVEDVI, RVESVI, 4D-RVDd-base and 4D-RVDd-mid in the DCM group were increased, and the absolute values of 4D-RVEF, 4D-TAPSE, 4D-RVFAC, right ventricular global longitudinal strain(RVGLS) and right ventricular free wall longitudinal strain(RVFWLS) were decreased (all P<0.05). Correlation analysis showed that 4D-RVEF was positively correlated with CMR-RVEF ( r=0.711, P<0.05). ROC curve analysis showed that 4D-RVEF was superior to other parameters in evaluating right ventricular function in DCM patients (AUC: 0.916). Conclusions:4D Auto RVQ technique can quantitatively evaluate right ventricular function in DCM patients. 4D-RVEF has a significant correlation with CMR-RVEF, and 4D-RVEF has the best efficacy in evaluating right ventricular function in DCM patients.

Objective:To evaluate left atrial(LA) function and its value in predicting left ventricular(LV) remodeling in patients with coronary heart disease (CHD) by four dimensional automatic left atrial quantitation (4D Auto LAQ).Methods:A total of 176 patients with CHD were prospectively enrolled in Fuwai Central China Cardiovascular Hospital from October 2021 to September 2022. They were divided into two groups according to left ventricular mass index: LV remodeling group (female>95 g/m 2, male>115 g/m 2, n=88) and Non-LV remodeling group (female≤95 g/m 2, male≤115 g/m 2, n=88). The 3D dynamic image of LA was analyzed by 4D Auto LAQ on machine to obtain the LA parameters, including the minimum, maximum, pre-systolic and emptying volumes of LA (LAVmin, LAVmax, LAVpreA, LAEV), LA ejection fraction (LAEF), LA reservoir longitudinal and circumferential strains (LASr, LASr-c), LA conduit longitudinal and circumferential strains (LAScd, LAScd-c) and LA contraction longitudinal and circumferential strains (LASct, LASct-c). Logistic regression models were used to analyze the value of LA parameters in predicting LV remodeling in patients with CHD. ROC curve was used to evaluate LA parameters and left atrial volume index (LAVI) to predict the diagnostic efficiency of LV remodeling. Results:Compared with the Non-LV remodeling group, LAVmin, LAVmax, LAVpreA were significantly increased and LAEF, LASr, LAScd, LASct, LASr-c, LAScd-c, LASct-c were significantly decreased in the LV remodeling group ( P<0.05). Logistic regression model showed that LASct-c was an independent risk factor for LV remodeling in patients with CHD after adjustment( OR=2.018, 95% CI=1.214-3.355). ROC curve analysis showed that the area under the curve of LASct-c for predicting LV remodeling in CHD patients was 0.844, the sensitivity was 0.784, and the specificity was 0.761. Conclusions:4D Auto LAQ can effectively evaluate LA function in patients with CHD.LASct-c can be used as a reference index to predict LV remodeling in patients with CHD, which provides a new evaluation method in prognosis evaluation of CHD patients.

Objective:To develop a multi-scale fusion and attention mechanism based image automatic segmentation method of organs at risk (OAR) from head and neck carcinoma radiotherapy.Methods:We proposed a new OAR segmentation method for medical images of heads and necks based on the U-Net convolution neural network. Spatial and channel squeeze excitation (csSE) attention block were combined with the U-Net, aiming to enhance the feature expression ability. We also proposed a multi-scale block in the U-Net encoding stage to supplement characteristic information. Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD) were used as evaluation criteria for deep learning performance.Results:The segmentation of 22 OAR in the head and neck was performed according to the medical image computing computer assisted intervention (MICCAI) StructSeg2019 dataset. The proposed method improved the average segmentation accuracy by 3%-6% compared with existing methods. The average DSC in the segmentation of 22 OAR in the head and neck was 78.90% and the average 95%HD was 6.23 mm.Conclusion:Automatic segmentation of OAR from the head and neck CT using multi-scale fusion and attention mechanism achieves high segmentation accuracy, which is promising for enhancing the accuracy and efficiency of radiotherapy in clinical practice.