Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

In 2025,the International Association of Pancreatology(IAP),in collaboration with the American Pancreatic Association,European Pancreatic Club,Indian Pancreas Club,and Japan Pancreas Society,released the International Association of Pancreatology revised guidelines on acute pancreatitis 2025.This edition represents a comprehensive revision of the 2013 guidelines,based on high-quality evidence accumulated over the past decade,particularly randomized controlled trials.The guidelines encompass 18 key areas-including pain management,fluid therapy,nutritional support,management of infected necrosis,complication control,discharge and follow-up,and recurrence prevention-offering a total of 96 recommendations that emphasize individualized treatment.These updates provide important guidance for standardizing clinical practice and improving outcomes in acute pancreatitis,while also indicating future research directions such as the development of targeted therapies.However,some recommendations remain limited by lower evidence quality,uncertain applicability in specific clinical settings,and insufficient consideration of economic burden and cost-effectiveness.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

Capturing and replicating experts'acupuncture manipulation techniques is a crucial aspect in inheriting acupuncture manipulation techniques.The precision,stability and real-time performance during the capturing process will directly impact the quality of the technique replication.This article summarized the methods and application status of acupuncture technique capturing from the aspects of acupuncture technique measuring instrument,visual collection,and tactile collection,and analyzed the shortcomings of current research,further explored the application prospect of motion capture technologies such as optical technology and electromagnetic navigation technology in acupuncture manipulation acquisition,and provided references for acupuncture manipulation acquisition research.

In 2025,the International Association of Pancreatology(IAP),in collaboration with the American Pancreatic Association,European Pancreatic Club,Indian Pancreas Club,and Japan Pancreas Society,released the International Association of Pancreatology revised guidelines on acute pancreatitis 2025.This edition represents a comprehensive revision of the 2013 guidelines,based on high-quality evidence accumulated over the past decade,particularly randomized controlled trials.The guidelines encompass 18 key areas-including pain management,fluid therapy,nutritional support,management of infected necrosis,complication control,discharge and follow-up,and recurrence prevention-offering a total of 96 recommendations that emphasize individualized treatment.These updates provide important guidance for standardizing clinical practice and improving outcomes in acute pancreatitis,while also indicating future research directions such as the development of targeted therapies.However,some recommendations remain limited by lower evidence quality,uncertain applicability in specific clinical settings,and insufficient consideration of economic burden and cost-effectiveness.

Capturing and replicating experts'acupuncture manipulation techniques is a crucial aspect in inheriting acupuncture manipulation techniques.The precision,stability and real-time performance during the capturing process will directly impact the quality of the technique replication.This article summarized the methods and application status of acupuncture technique capturing from the aspects of acupuncture technique measuring instrument,visual collection,and tactile collection,and analyzed the shortcomings of current research,further explored the application prospect of motion capture technologies such as optical technology and electromagnetic navigation technology in acupuncture manipulation acquisition,and provided references for acupuncture manipulation acquisition research.

This article reported a case of neurodevelopmental disorder accompanied by spastic diplegia and visual impairment with the manifestation of small fetal head circumference. Prenatal ultrasonography performed at 33 +5 weeks of pregnancy revealed small fetal head circumference (-2.61SD) and oligohydramnios. Whole-exome sequencing identified a heterozygous frameshift variation of c.1623_1624insA (p.R542Tfs*30) in the CTNNB1 gene (NM_001904.4) of the fetus. No phenotypic abnormalities or corresponding gene variations were detected in the parents, suggesting it was a de novo variation. Based on the clinical manifestations, the fetus was diagnosed with a neurodevelopmental disorder accompanied by spastic diplegia and visual defects. Following genetic counseling, the pregnant woman chose to terminate the pregnancy.

Background::Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods::In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort.Results::In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone.Conclusion::ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration::Chictr.org.cn: ChiCTR2200059599.

Objective To explore the effect of deep learning image reconstruction(DLIR)algorithm combined with"double low"[low voltage(kV)and low contrast agent dosage]technique on the image quality of coronary computed tomography angiography(CCTA)in overweight patients compared with adaptive statistical iterative reconstruction(ASIR-V)and filtered back projection(FBP).Methods Fifty-two patients with body mass index(BMI)between 25.1 kg/m2and 28 kg/m2 who underwent CCTA scanning were prospectively selected,all of whom scanned on a GE Revolution APEX-CT with a tube voltage of 80 kV,a smart mA(500-1 300 mA),a noise index of 30,and a contrast dosage of 0.5 mL/kg;four groups of images were reconstructed for each patient,FBP,50％ASIR-V,DLIR-M,and DLIR-H.The CT and SD values of the aorta(AO)root,the proximal segment of the right coronary artery(RCA),the left circumflex(LCX),the left anterior descending branch(LAD)and the pericardial fat were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.Two doctors experienced in the diagnosis of cardiovascular disease were selected to subjectively score the reconstructed images using a double-blind method.The SD value,SNR value,CNR value and subjective scores of images in the four groups were compared.Results In the objective image quality evaluation,there were statistically significant differences in SD value,SNR value and CNR value of reconstructed images in the four groups(P＜0.05).As the four groups of reconstruction algorithms FBP,50％ASIR-V,DLIR-M,and DLIR-H were changed sequentially,the image SD value gradually decreased,the SNR value and CNR value gradually increased,and the DLIR-H group had the lowest SD value and the highest SNR and CNR values.In the subjective image quality evaluation,the subjective scores of the two doctors had good consistency(Kappa value=0.900),and the difference between them was statistically significant(P＜0.001).The subjective scores of DLIR-M and DLIR-H groups were higher.Conclusion DLIR algorithm combined with"double-low"technique can significantly improve the CCTA image quality of overweight patients,which is better than 50％ASIR-V and FBP.

Malnutrition, as an independent predictor of incidence and mortality in patients with chronic heart failure (CHF), has a serious impact on the treatment effect of patients. Conducting nutritional risk assessment and providing nutritional interventions for CHF patients can effectively improve their quality of life. On the basis of elaborating on the risk factors for malnutrition in CHF patients, this paper reviews the assessment tools for malnutrition in CHF patients, aiming to promote the localization of malnutrition assessment tools and the research and clinical application of malnutrition specific assessment tools, making nutrition assessment a routine part of overall health assessment for CHF patients.