In recent years， significant progress has been made in the standardized diagnosis and treatment of pancreatic cancer in China. From the lack of treatment options and poor drug efficacy at the beginning to the current comprehensive treatment modality integrating surgery， chemotherapy， radiotherapy， immunotherapy， and targeted therapy under multidisciplinary decision-making， the diagnosis and treatment of pancreatic cancer has gradually achieved higher levels of individualization， refinement， and precision. With reference to the latest evidence-based medical data， this article discusses the hot topics in the diagnosis and treatment of pancreatic cancer and explores the future development directions of this field.

This article reviews the research advances in the characteristics and application progress of various new models for preclinical cancer research on pancreatic cancer， analyzes and discusses the history， current research status， and advantages and disadvantages of new models of pancreatic cancer， including patient-derived tissue xenograft， conditional reprogramming， and patient derived organoids， and it also reviews the studies that have achieved clinical transformation from preclinical models and proposes possible research prospects in the future.

ObjectiveTo compare and analyze the clinical application of robot-assisted parenchymal-sparing pancreatectomy （R-PSP） and laparoscopic parenchymal-sparing pancreatectomy （L-PSP） in the treatment of pancreatic neuroendocrine neoplasm （pNEN）， and to evaluate the safety and efficacy of the R-PSP procedure. MethodsA retrospective analysis was performed for the clinical data of pNEN patients who underwent parenchymal-sparing pancreatectomy in Department of General Surgery， Peking Union Medical College Hospital， Peking Union Medical College， Chinese Academy of Medical Sciences， from December 2017 to August 2023， and according to the minimally invasive surgical procedure， they were divided into R-PSP group and L-PSP group. R-PSP and L-PSP were compared in terms of the efficacy of minimally invasive procedure， the outcome of postoperative complications， and oncological efficacy. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups； the Mann-Whitney U test was used for comparison of ranked data between two groups. ResultsA total of 45 pNEN patients were included， with 9 in the R-PSP group and 36 in the L-PSP group， and there were no significant differences in baseline data between the two groups （all P>0.05）. There were no significant differences between the two groups in time of operation， intraoperative blood loss， intraoperative blood transfusion， and the rate of conversion to laparotomy （all P>0.05）. Compared with the L-PSP group， the R-PSP group had a significantly longer length of postoperative hospital stay ［10.00 （9.00‍ ‍—‍ ‍15.00） days vs 7.50 （6.00‍ ‍—‍ ‍10.00） days， Z=-2.356， P=0.017］ and significantly higher hospital costs ［86 610.44 （81 905.39‍ ‍—‍ ‍114 401.24） yuan vs 38 781.20 （31 708.39‍ ‍—‍ ‍50 514.76） yuan， Z=-4.001， P<0.001］. There were no significant differences between the two groups in the incidence rates of serious postoperative complications （Clavien-Dindo grade ≥Ⅲ）， clinically relevant pancreatic fistula， delayed gastric emptying， and intra-abdominal infection （all P>0.05）. The postoperative 90-day mortality rate was 0% for both groups. ConclusionR-PSP has acceptable safety and efficacy in pNEN patients in clinical practice.

Objective To explore the application value of deep learning image reconstruction(DLIR)with coronary computed tomography angiography(CCTA)using 100 kV.Methods Sixty patients who underwent CCTA were selected.The tube voltage of 100 kV,noise index of 24 were applied.The 60％adaptive statistical iterative reconstruction-Veo(ASIR-V)and DLIR-low(DLIR-L),DLIR-medium(DLIR-M)and DLIR-high(DL1R-H)were reconstructed.The CT values and standard deviation(SD)values of the aortic root,left main artery,left anterior descending artery,left circumflex artery,right coronary artery and pericardial fat of the four groups of images were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.Two radiologists with five-year working experience subjectively evaluated the image quality using a five-point method double-blindly.Results The differences in noise(SD values),SNR values and CNR values among the four groups of images were statistically significant(P＜0.001).As the reconstruction gradually changed of 60％ASIR-V,DLIR-L,DLIR-M and DLIR-H,the coronary SD values gradually decreased,while the SNR values and CNR values gradually increased,among which the DLIR-H had the lowest SD values and the highest SNR values and CNR values.The subjective scores of the four groups of images by two radiologists showed good consistency(Kappa value=0.929,P＜0.001),and the subjective scores were all above 3 points which met the clinical diagnosis criteria.The subjective scores of DLIR-L,DLIR-M and DLIR-H were significantly higher than those of 60％ASIR-V(P＜0.001),with the DLIR-H achieving the highest subjective score.Conclusion DLIR can significantly reduce image SD value and improve image quality of CCTA with 100 kV,among which DLIR-H has the best effect on improving CCTA image quality.

As a systemic disease,pancreatic cancer is highly malignant and has a high rate of recurrence and metastasis,which makes it particularly difficult in diagnosis,treatment and management.In recent years,with the concept of neoadjuvant therapy deeply rooted in the hearts of the people,the treatment of pancreatic cancer has increasingly emphasized the development of comprehensive and individualized treatment schemes in the whole process and multi-dimensional management of pancreatic cancer patients.However,there still remain many controversies about the application of neoadjuvant therapy for resectable pancreatic cancer.This review intended to discuss the hot topics and related controversies in the implementation of neoadjuvant therapy for patients with resectable pancreatic cancer based on domestic and foreign guidelines and the latest research progress,which may vastly promote the standardized application of neoadjuvant therapy for resectable pancreatic cancer.

As pancreatic cancer (PC) is highly malignant, its patients tend to develop metastasis at an early stage and show a poor response to conventional chemotherapies. First-line chemotherapies for PC, according to current guidelines, include fluoropyrimidine- and gemcitabine-based regimens. Accumulating research on drug resistance has shown that biochemical metabolic aberrations in PC, especially those involving glycolysis and glutamine metabolism, are highly associated with chemoresistance. Additionally, lipid metabolism is a major factor in chemoresistance. However, emerging compounds that target these key metabolic pathways have the potential to overcome chemoresistance. This review summarizes how PC develops chemoresistance through aberrations in biochemical metabolism and discusses novel critical targets and pathways within cancer metabolism for new drug research.

Pancreatic cancer, a highly malignant digestive system tumor, presents significant challenges in surgical treatment and generally has a poor prognosis. Luckily, the rapid development of medical artificial intelligence has facilitated its application in areas related to pancreatic cancer, including preoperative imaging diagnostics, rapid pathological diagnosis, surgical robotic systems, and the training of pancreatic surgery specialists. In this paper, we review the latest advancements in the application of medical artificial intelligence in pancreatic cancer, aiming to promote the deep integration of artificial intelligence in the field of pancreatic cancer surgery.

Pancreatic cancer is a common malignant tumor in the digestive tract, and the difficulty of early diagnosis and the lack of effective treatment means are the main reasons for the poor prognosis of pancreatic cancer. In recent years, multidisciplinary treatment (MDT) has become an important means to break through the bottleneck of diagnosis and treatment of pancreatic cancer and improve clinical prognosis. Besides providing patients with high-quality diagnosis and treatment services, this treatment model helps to improve the clinical diagnosis and treatment level of specialists and cultivate high-quality compound medical talents. It also highlights clinical research groups and high-quality case resource sharing, and promotes the clinical application of innovative drugs and new diagnostic and therapeutic technologies, which plays an essential role in increasing the core competence of hospitals. This paper reviews and summarizes the origin, status quo, and deficiencies of the MDT diagnosis and treatment model of pancreatic cancer in China, and examines the prospects for future development, with the aim to provide reference for domestic and foreign counterparts.

To investigate the differences in postoperative short-term complications and long-term prognosis of pancreatic cancer(PC) patients after total pancreatectomy(TP) and pancreaticoduodenectomy(PD).

Pancreatic surgery is one of the most challenging specialties in general surgery. Due to the variety of pancreatic diseases, the difficulty of surgery, and the differences in diagnosis and treatment among different diseases, treatment strategies for these diseases remain controversial. From the aspects of surgical treatment such as pancreatitis, pancreatic cystic neoplasms, pancreatic neuroendocrine neoplasms, and pancreatic cancer, as well as neoadjuvant therapy, adjuvant therapy, immunotherapy, and targeted therapy. We review and summarize the frontier progress of clinical and translational research in pancreatic surgery in 2023, in order to further standardize the diagnosis and treatment of pancreatic surgery.