Objective:To explore the diagnostic value of preoperative diffusion weighted imaging (DWI) histogram parameters in the depth of invasion of early rectal cancer.Methods:A total of 180 patients with early rectal cancer admitted to 904th Hospital of Joint Logistics Support Force of Chinese People's Liberation Army from August 2020 to August 2024 were selected as the study objects. Patients were divided into intramucosal cancer group ( n=102) and submucosal cancer group ( n=78) according to the depth of tumor invasion. The general data of the two groups were compared. The intraclass correlation coefficient (ICC) was used to analyze the consistency of DWI histogram parameters extracted by the two radiologists, and the differences between the two groups were compared. Receiver operator characteristic (ROC) curve was used to analyze the predictive value of each parameter to the depth of tumor invasion. Multivariate logistic regression was used to analyze the independent influencing factors of invasion depth, and a predictive model was constructed. The ROC curve was drawn to analyze the predictive value of the model for tumor invasion depth, and the Hosmer-Lemeshow test was used to analyze the goodness of fit of the model. Results:There were statistically significant differences in age ( t=8.15, P<0.001), maximum tumor diameter ( χ2=29.29, P<0.001), endoscopic type ( χ2=20.96, P<0.001), histological type ( χ2=24.93, P<0.001) and differentiation degree ( χ2=73.35, P<0.001) between intramucosal cancer group and submucosal cancer group. The mean, variance, skewness, kurtosis, the 1 st, 10 th, 50 th, 90 th, and 99 th percentiles of the histogram parameters of DWI had good consistency (all ICC>0.75). There were statistically significant differences in the mean ( t=5.69, P<0.001), variance ( t=9.75, P<0.001), skewness ( t=10.88, P<0.001), kurtosis ( t=10.06, P<0.001), the 1 st percentile ( t=3.43, P<0.001), 10 th percentile ( t=3.59, P<0.001), 50 th percentile ( t=9.97, P<0.001), 90 th percentile ( t=4.63, P<0.001), and 99 th percentile ( t=2.44, P=0.016) of the DWI histogram parameters between the intramucosal cancer group and the submucosal cancer group. ROC curve analysis results showed that mean [area under the curve (AUC) =0.77], variance (AUC=0.88), skewness (AUC=0.88), kurtosis (AUC=0.78), 50 th percentile (AUC=0.86) and 90 th percentile (AUC=0.82) had certain diagnostic value for submucous cancer. Multivariate analysis showed that age ( OR=9.98, 95% CI: 1.10-90.70, P=0.041), maximum tumor diameter ( OR=7.36, 95% CI: 1.08-50.23, P=0.042), and differentiation degree ( OR=19.88, 95% CI: 1.21-327.92, P=0.037), variance ( OR=16.24, 95% CI: 2.26-116.68, P=0.006), skewness ( OR=21.13, 95% CI: 2.80-59.61, P=0.003), 1 st percentile ( OR=9.78, 95% CI: 1.17-81.76, P=0.035) were independent factors in predicting tumor invasion depth in patients with early rectal cancer. The predictive model based on the above indicators was logit ( P) =1.51+2.30×age+2.00×maximum tumor diameter+2.99×differentiation degree+2.79×variance+3.05×skewness+ 2.28×the 1 st percentile. ROC curve analysis showed that the predictive model had an AUC of 0.97 (95% CI: 0.95-0.99) for judging the occurrence of submucosal cancer in patients with early rectal cancer, the sensitivity was 0.95, and the specificity was 0.88. The Hosmer-Lemeshow test results showed that the goodness of fit of the model was ideal ( P=0.823) . Conclusions:Age, maximum tumor diameter, differentiation degree, variance, skewness, and the 1 st percentile are independent factors in predicting tumor invasion depth in patients with early rectal cancer. The predictive model constructed based on these factors can effectively predict the risk of submucosal cancer in patients with early rectal cancer.

Objective To explore the feasibility,effectiveness,and safety of balloon catheter-assisted total hepatic vascular exclusion.Methods We designed and manufactured an endovascular catheter with three lumens and double balloons,which can be inserted into the retrahepatic inferior vena cava through the femoral vein.The superior and inferior vena cava of the liver can be blocked by filling balloon,and the total hepatic vascular exclusion was achieved by combining with pringle method.In animal experiments,total hepatic vascular exclusion was performed by balloon catheter-assist method(experimental group)or traditional methods(control group),and the complete time was compared between the two groups.Blood flow blocking effect was observed by angiography and incision of retrahepatic inferior vena cava under direct vision.The complications were recorded.Results Total hepatic vascular exclusion was successfully completed in both groups.The completion time in the experimental group was significantly shorter than that in the control group([12.5±1.2]min vs.[35.8±4.9]min,P<0.05).CT angiography,DSA,and direct vision of blood vessels all confirmed the effectiveness of balloon catheter-assisted hepatic blood flow exclusion.No catheter displacement,balloon rupture,or air embolism occurred.Conclusion The balloon catheter-assisted hepatic total vascular exclusion is simpler and more feasible than traditional method.

Coronavirus disease 2019 (COVID-19) is a multi-system disease that can lead to various severe complications. Acute limb ischemia (ALI) has been increasingly recognized as a COVID-19-associated complication that often predicts a poor prognosis. However, the pathophysiology and molecular mechanisms underlying COVID-19-associated ALI remain poorly understood. Hypercoagulability and thrombosis are considered important mechanisms, but we also emphasize the roles of vasospasm, hypoxia, and acidosis in the pathogenesis of the disease. The angiotensin-converting enzyme 2 (ACE2) pathway, inflammation, and platelet activation may be important molecular mechanisms underlying these pathological changes induced by COVID-19. Furthermore, we discuss the hypotheses of risk factors for COVID-19-associated ALI from genetic, age, and gender perspectives based on our analysis of molecular mechanisms. Additionally, we summarize therapeutic approaches such as use of the interleukin-6 (IL-6) blocker tocilizumab, calcium channel blockers, and angiotensin-converting enzyme inhibitors, providing insights for the future treatment of coronavirus-associated limb ischemic diseases.
Humans ; COVID-19/physiopathology* ; Ischemia/etiology* ; SARS-CoV-2 ; Extremities/blood supply* ; Risk Factors ; Interleukin-6/antagonists & inhibitors* ; Acute Disease ; Angiotensin-Converting Enzyme 2

Objective:To explore the value of Alberta stroke program early CT Score (ASPECTS) regional net water intake (NWU) based on plain CT in evaluating the neurological outcome of patients with acute large vessel occlusive stroke (ALVOS) after mechanical thrombectomy.Methods:The study was a prospective cross-sectional study. The clinical and imaging data of patients with ALVOS who underwent mechanical thrombectomy in the 904 Hospital of the PLA Joint Service Support Force from June 2022 to June 2024 were prospectively collected. Clinical data analysis included age, gender distribution, National Institutes of Health Stroke Scale (NIHSS) score and Glasgow Coma Scale (GCS) score at admission. All patients underwent plain CT and CT angiography (CTA). Automated processing software quantified ischemic brain edema by calculating ASPECTS and measuring the ASPECTS regional NWU rate (CT-ASPECTS-NWU) based on plain CT. Cerebral collateral circulation was assessed using CTA images. According to the modified Rankin Scale score of patients with mechanical thrombectomy 90 days after the telephone follow-up, 0-2 points were defined as good neurological outcome, and 3-6 points were defined as poor neurological outcome. Independent samples t test, Mann-Whitney U test and χ2 test were used to analyze the differences of clinical and imaging indicators between patients with good and poor neurological outcome, indicators with statistically significant differences were included in multivariate logistic regression analysis to screen out the independent influencing factors that predicted the neurological outcome of patients with ALVOS after mechanical thrombectomys. The efficacy of related indicators to predict neurological outcomes after mechanical thrombectomy in patients with ALVOS was evaluated using receiver operating characteristic (ROC) curve analysis, with the area under the curve (AUC) calculated. Results:A total of 122 patients with ALVOS were included, including 101 patients with good neurological outcome and 21 patients with poor neurological outcome after mechanical thrombectomy. There were statistically significant differences in preoperative GCS score, collateral circulation status, NIHSS score at admission, preoperative ASPECTS and CT-ASPECTS-NWU between patients with good neurological outcome and patients with poor neurological outcome ( P<0.05). Multivariate logistic regression analysis showed that the status of collateral circulation ( OR=3.450, 95% CI 1.158-10.277, P=0.026), preoperative ASPECTS ( OR=0.510, 95% CI 0.274-0.952, P=0.034) and CT-ASPECTS-NWU ( OR=2.131, 95% CI 1.301-3.493, P=0.003) were independent predictors of neurological outcome in patients with ALVOS after mechanical thrombectomy. ROC curve analysis showed that CT-ASPECTS-NWU had the highest predictive value, with an AUC of 0.881, a sensitivity of 85.7%, a specificity of 85.1%, and an optimal cutoff value of 7.55. Conclusion:CT-ASPECTS-NWU demonstrates high diagnostic value in evaluating the neurological outcome of patients with ALVOS after mechanical thrombectomy, and can provide an objective imaging biomarker to guide clinical decision-making.

This paper aims to discuss the application value and progress of artificial intelligence (AI) in the diagnosis and treatment of gastrointestinal tumors and teaching practice of gastrointestinal oncology. Through a comprehensive analysis of the current clinical research status and literature, this paper summarizes the application practice and exploratory thinking of AI and deep learning technologies in gastrointestinal oncology. In diagnosis, AI technologies have improved the early detection and diagnosis efficiency for gastrointestinal tumors by optimizing medical image analysis, especially in the recognition of liver metastases. Applications of AI in pathological diagnosis include automatic recognition of tumor cells and tissue structure, as well as improving diagnostic sensitivity and specificity through feature extraction and pattern recognition. In treatment, the application scenarios of AI include rapid diagnosis, accurate staging, personalized treatment plan formulation, drug development, and surgical assistance. In surgical assistance, AI technology improves the safety and effectiveness of surgery through preoperative evaluation, surgical navigation, and postoperative evaluation. In teaching, AI technology facilitates knowledge acquisition and clinical skill enhancement of medical students by providing a multidisciplinary learning platform, simulating clinical environment and case details, and establishing a remote learning platform. The application of AI technology in teaching also includes deep learning and assessment feedback, providing personalized teaching and real-time assessment for students. This paper discusses the application prospects for AI technology in the teaching practice of gastrointestinal oncology. Although AI technology shows great potential in the diagnosis and treatment of gastrointestinal tumors and teaching gastrointestinal oncology, it also has limitations and needs to be combined with traditional teaching methods to achieve the best teaching results.

This paper aims to discuss the application value and progress of artificial intelligence (AI) in the diagnosis and treatment of gastrointestinal tumors and teaching practice of gastrointestinal oncology. Through a comprehensive analysis of the current clinical research status and literature, this paper summarizes the application practice and exploratory thinking of AI and deep learning technologies in gastrointestinal oncology. In diagnosis, AI technologies have improved the early detection and diagnosis efficiency for gastrointestinal tumors by optimizing medical image analysis, especially in the recognition of liver metastases. Applications of AI in pathological diagnosis include automatic recognition of tumor cells and tissue structure, as well as improving diagnostic sensitivity and specificity through feature extraction and pattern recognition. In treatment, the application scenarios of AI include rapid diagnosis, accurate staging, personalized treatment plan formulation, drug development, and surgical assistance. In surgical assistance, AI technology improves the safety and effectiveness of surgery through preoperative evaluation, surgical navigation, and postoperative evaluation. In teaching, AI technology facilitates knowledge acquisition and clinical skill enhancement of medical students by providing a multidisciplinary learning platform, simulating clinical environment and case details, and establishing a remote learning platform. The application of AI technology in teaching also includes deep learning and assessment feedback, providing personalized teaching and real-time assessment for students. This paper discusses the application prospects for AI technology in the teaching practice of gastrointestinal oncology. Although AI technology shows great potential in the diagnosis and treatment of gastrointestinal tumors and teaching gastrointestinal oncology, it also has limitations and needs to be combined with traditional teaching methods to achieve the best teaching results.

Objective:To explore the value of Alberta stroke program early CT Score (ASPECTS) regional net water intake (NWU) based on plain CT in evaluating the neurological outcome of patients with acute large vessel occlusive stroke (ALVOS) after mechanical thrombectomy.Methods:The study was a prospective cross-sectional study. The clinical and imaging data of patients with ALVOS who underwent mechanical thrombectomy in the 904 Hospital of the PLA Joint Service Support Force from June 2022 to June 2024 were prospectively collected. Clinical data analysis included age, gender distribution, National Institutes of Health Stroke Scale (NIHSS) score and Glasgow Coma Scale (GCS) score at admission. All patients underwent plain CT and CT angiography (CTA). Automated processing software quantified ischemic brain edema by calculating ASPECTS and measuring the ASPECTS regional NWU rate (CT-ASPECTS-NWU) based on plain CT. Cerebral collateral circulation was assessed using CTA images. According to the modified Rankin Scale score of patients with mechanical thrombectomy 90 days after the telephone follow-up, 0-2 points were defined as good neurological outcome, and 3-6 points were defined as poor neurological outcome. Independent samples t test, Mann-Whitney U test and χ2 test were used to analyze the differences of clinical and imaging indicators between patients with good and poor neurological outcome, indicators with statistically significant differences were included in multivariate logistic regression analysis to screen out the independent influencing factors that predicted the neurological outcome of patients with ALVOS after mechanical thrombectomys. The efficacy of related indicators to predict neurological outcomes after mechanical thrombectomy in patients with ALVOS was evaluated using receiver operating characteristic (ROC) curve analysis, with the area under the curve (AUC) calculated. Results:A total of 122 patients with ALVOS were included, including 101 patients with good neurological outcome and 21 patients with poor neurological outcome after mechanical thrombectomy. There were statistically significant differences in preoperative GCS score, collateral circulation status, NIHSS score at admission, preoperative ASPECTS and CT-ASPECTS-NWU between patients with good neurological outcome and patients with poor neurological outcome ( P<0.05). Multivariate logistic regression analysis showed that the status of collateral circulation ( OR=3.450, 95% CI 1.158-10.277, P=0.026), preoperative ASPECTS ( OR=0.510, 95% CI 0.274-0.952, P=0.034) and CT-ASPECTS-NWU ( OR=2.131, 95% CI 1.301-3.493, P=0.003) were independent predictors of neurological outcome in patients with ALVOS after mechanical thrombectomy. ROC curve analysis showed that CT-ASPECTS-NWU had the highest predictive value, with an AUC of 0.881, a sensitivity of 85.7%, a specificity of 85.1%, and an optimal cutoff value of 7.55. Conclusion:CT-ASPECTS-NWU demonstrates high diagnostic value in evaluating the neurological outcome of patients with ALVOS after mechanical thrombectomy, and can provide an objective imaging biomarker to guide clinical decision-making.

Acral melanoma(AM)is the most common histologic subtype of melanoma in dark-skinned patients and is associated with a worse prognosis and a high mortality rate,largely due to the inconspicuous nature of early-stage lesions,which can lead to late diagnosis.Because of the overlapping clinical and histopathological features of AM with other forms of cutaneous melanomas,early detection of AM requires a multidisciplinary approach that integrates various diagnostic modalities,including clinical examination,dermoscopy,histopathology,molecular testing,radiological imaging,and blood tests.While surgery is the preferred method of treatment for AM,other therapeutic options may be employed based on the stage and underlying etiology of the disease.Immune checkpoint inhibitors,molecular targeted therapy,radiotherapy,chemotherapy,and oncolytic virotherapy represent promising advanced treatment options for AM.In this review,we provide an overview of the latest advancements in diagnostic and therapeutic methods for AM,highlighting the importance of early detection and the prompt,individualized management of this challenging disease.

Objective:To investigate the status of cognition and clinical management of prolonged mechanical ventilation(PMV) among medical staffs in pediatric intensive care unit(PICU) in China, and in order to improve the awareness of PICU medical staffs on PMV and standardize the management of PMV.Methods:The cross-sectional study was conducted with doctors and nurses in PICUs of the collaborative group as the survey objects from July 12 to September 12, 2020.The questionnaire was issued, collected and checked by the Children′s Hospital of Fudan University.Results:(1) PMV related settings: Nine out of eleven hospitals had established PMV multidisciplinary teams, respiratory techniques such as diaphragm ultrasound and airway peak flow monitoring could be respectively executed in 72.7% and 36.4% of PICU.Pulmonary rehabilitation techniques such as airway clearance techniques, induced spirometer exercise, external diaphragm pacemaker stimulation, transfer bed exercise, balloon blowing, hyperbaric oxygen therapy could be respectively executed in 100.0%, 9.1%, 9.1%, 9.1%, 27.3% and 27.3% of PICU, respectively.(2) The cognitive status quo of children′s PMV: The most medical staffs agreed with the view that PMV referred to the children′s continuous mechanical ventilation for more than two weeks.Sixty percent of medical staffs believed that children with PMV had basic central nervous system diseases, and 62.7% of medical staffs believed that the most common causes of difficulty in PMV weaning was abnormal brain function.(3) The cognitive status quo of the children′s PMV management in PICU: Respondents believed that the most commonly used mechanical ventilation mode was synchronized intermittent mandatory ventilation+ pressure support ventilation in children′s PMV during stable disease.Ninety-two percent of medical staffs performed the spontaneous breathing test when weaning.And 58.7% of the respondents agreed to perform tracheotomy for the children during 3 to 4 weeks of mechanical ventilation.More than half of medical staffs would execute diaphragm function assessment, bedside rehabilitation training, nutritional assessment, analgesia and sedation assessment for children with PMV.(4) The cognitive status quo of the children′s PMV management of transition from hospital to family: 54.5% of PICU provided family care training to the family members before the children were discharged from the hospital.One center established the PMV specialized outpatient clinic.45.5% of PICU would follow up these discharged children one month later.Conclusion:At present, PICU medical staffs have different awareness of children′s PMV related problems in China.And children′s PMV lacks a systematic plan regarding diagnosis, treatment and management.

Effective methods for visualizing neurovascular morphology are essential for understanding the normal spinal cord and the morphological alterations associated with diseases. However, ideal techniques for simultaneously imaging neurovascular structure in a broad region of a specimen are still lacking. In this study, we combined Golgi staining with angiography and synchrotron radiation micro-computed tomography (SRμCT) to visualize the 3D neurovascular network in the mouse spinal cord. Using our method, the 3D neurons, nerve fibers, and vasculature in a broad region could be visualized in the same image at cellular resolution without destructive sectioning. Besides, we found that the 3D morphology of neurons, nerve fiber tracts, and vasculature visualized by SRμCT were highly consistent with that visualized using the histological method. Moreover, the 3D neurovascular structure could be quantitatively evaluated by the combined methodology. The method shown here will be useful in fundamental neuroscience studies.