After more than thirty years of development, laparoscopic surgery technology has become the main platform for surgery and has been widely applied in various fields of surgery. The safety, feasibility and efficacy of laparoscopic technique have already been confirmed in colorectal surgery. In recent years, with a deeper understanding of concepts such as laparoscopic fascial anatomy, laparoscopic colorectal surgery has made new explorations and advances in surgical approach selection, NOSES, lymph node dissection range, preservation of Denonvillier's fascia, functional protection, lateral lymph node dissection, selection of anal preservation techniques for ultra-low rectal cancer, and totally laparoscopic digestive tract reconstruction. In the field of laparoscopic gastric surgery, evidence-based medical evidence in China has entered a harvest period, moreover, functional preservation surgery, esophageal gastric junction adenocarcinoma, and total laparoscopic anastomosis have also become hot topics in this field with new progress. The medical equipment related to minimally invasive surgery has also been developping in recent years and has played an important role in improving minimally invasive surgery.

Laparoscopic colorectal surgery has been carried out in China for more than 30 years and has experienced a three-stage high-speed development of "exploring and designing,optimising and standardising, perfecting and re-innovating" at the technical level. Based on the support and assistance of laparoscopic technology, colorectal surgery has made rapid progress in sub-microscopic anatomy, surgical procedures, surgical concepts, instruments and equipment. Nowadays, the technology and efficacy of laparoscopic colorectal surgery have gradually reached the ceiling, and in view of the existing pain points and the future direction of development, where will we go? This article summarised the past three decades of experience and consolidate the results to guide the future practice and the way forward.

Colorectal cancer is the most common malignant tumor of digestive tract, and the incidence of colorectal cancer in China is especially characterized by middle and low rectal cancer. In recent years, with the progress of computer science, artificial intelligence technology has developed rapidly, and has achieved a lot of application results in the medical field. At present, artificial intelligence technology has covered various stages of colorectal cancer, including screening, individualized assessment, auxiliary diagnosis and treatment decision-making, refined surgery and prognosis judgment, providing help for the accurate and individualized treatment of rectal cancer. However, the lack of standardized, systematic, and scalable AI models remains a major pain point for the field. Therefore, it is necessary to carry out large-scale prospective clinical studies on artificial intelligence model to further confirm its application value in the clinical diagnosis and treatment of rectal cancer.

Objective:To investigate the prognosis and the factors that influence it in patients with non-gastric gastrointestinal stromal tumors (GISTs) who are at low risk of recurrence.Methods:This was a retrospective cohort study. Clinicopathologic and prognostic data from patients with non-gastric GISTs and at low risk of recurrence (i.e., very low-risk or low-risk according to the 2008 version of the Modified NIH Risk Classification), who attended 18 medical centers in China between January 2000 and June 2023, were collected. We excluded patients with a history of prior malignancy, concurrent primary malignancy, multiple GISTs, and those who had received preoperative imatinib. The study cohort comprised 1,571 patients with GISTs, 370 (23.6%) of whom were at very low-risk and 1,201 (76.4%) at low-risk of recurrence. The cohort included 799 (50.9%) men and 772 (49.1%) women of median age 57 (16–93) years. Patients were followed up to July 2024. The prognosis and its influencing factors were analyzed. Receiver operating characteristic curves for tumor diameter and Ki67 were established, and the sensitivity, specificity, area under the curve (AUC) and optimal cut-off value with 95% confidence intervals were calculated. Propensity score matching was implemented using the 1:1 nearest neighbor matching method with a matching tolerance of 0.02.Results:With a median follow-up of 63 (12–267) months, the 5- and 10-year overall survival (OS) rates of the 1,571 patients were 99.5% and 98.0%, respectively, and the 5- and 10-year disease-free survival (DFS) rates were 96.3% and 94.4%, respectively. During postoperative follow-up, 3.8% (60/1,571) patients had disease recurrence or metastasis, comprising 0.8% (3/370) in the very low-risk group and 4.7% (57/1,201) in the low-risk group. In the low-risk group, recurrence or metastasis occurred in 5.5% (25/457) of patients with duodenal GISTs, 3.9% (25/645) of those with small intestinal GISTs, 9.2% (6/65) of those with rectal GISTs, and 10.0% (1/10) of those with colonic GISTs. Among the 60 patients with metastases, 56.7% (34/60) of the metastases were located in the abdominal cavity, 53.3% (32/60) in the liver, and 3.3% (2/60) in bone. During the follow-up period, 13 patients (0.8%) died of disease. Receiver operating characteristic curves were plotted for tumor diameter and Ki67 and assessed using the Jordon index. This showed that the difference in DFS between the two groups was statistically significant when the cutoff value for tumor diameter was 3.5 cm (AUC 0.731, 95% CI: 0.670–0.793, sensitivity 77.7%, specificity 64.1%). Furthermore, the difference in DFS between the two groups was statistically significant when the cutoff value for Ki67 was 5% (AUC 0.693, 95% CI: 0.624–0.762, sensitivity 60.7%, specificity 65.3%). Multifactorial analysis revealed that tumor diameter ≥3.5 cm, Ki67 ≥5%, and R1 resection were independent risk factors for DFS in patients with non-gastric GISTs at low risk of recurrence (all P<0.05). Furthermore, age >57 years, Ki67 ≥5%, and R1 resection were also independent risk factors for OS in patients with non-gastric GISTs at low risk of recurrence (all P<0.05). We also grouped the patients according to whether they had received postoperative adjuvant treatment with imatinib for 1 or 3 years. This yielded 137 patients in the less than 1-year group, 139 in the 1-year plus group; and 44 in both the less than 3 years and 3-years plus group. After propensity score matching for age, tumor diameter, Ki67, and resection status, the differences in survival between the two groups were not statistically significant (all P>0.05). The 10-year DFS and OS were 87.5% and 95.5%, respectively, in the group treated with imatinib for less than 1 year and 88.5% and 97.8%, respectively, in the group treated for more than 1 year. The 10-year DFS and OS were 89.6% and 92.6%, respectively, in the group treated with imatinib for less than 3 years and 88.0% and 100.0%, respectively, in the group treated with imatinib for more than 3 years. Conclusion:The overall prognosis of primary, non-gastric, low recurrence risk GISTs is relatively favorable; however, recurrences and metastases do occur. Age, tumor diameter, Ki67, and R1 resection may affect the prognosis. For some patients with low risk GISTs, administration of adjuvant therapy with imatinib for an appropriate duration may help prevent recurrence and improve survival.

Laparoscopic colorectal surgery has been carried out in China for more than 30 years and has experienced a three-stage high-speed development of "exploring and designing,optimising and standardising, perfecting and re-innovating" at the technical level. Based on the support and assistance of laparoscopic technology, colorectal surgery has made rapid progress in sub-microscopic anatomy, surgical procedures, surgical concepts, instruments and equipment. Nowadays, the technology and efficacy of laparoscopic colorectal surgery have gradually reached the ceiling, and in view of the existing pain points and the future direction of development, where will we go? This article summarised the past three decades of experience and consolidate the results to guide the future practice and the way forward.

Colorectal cancer is the most common malignant tumor of digestive tract, and the incidence of colorectal cancer in China is especially characterized by middle and low rectal cancer. In recent years, with the progress of computer science, artificial intelligence technology has developed rapidly, and has achieved a lot of application results in the medical field. At present, artificial intelligence technology has covered various stages of colorectal cancer, including screening, individualized assessment, auxiliary diagnosis and treatment decision-making, refined surgery and prognosis judgment, providing help for the accurate and individualized treatment of rectal cancer. However, the lack of standardized, systematic, and scalable AI models remains a major pain point for the field. Therefore, it is necessary to carry out large-scale prospective clinical studies on artificial intelligence model to further confirm its application value in the clinical diagnosis and treatment of rectal cancer.

Objective:To investigate the prognosis and the factors that influence it in patients with non-gastric gastrointestinal stromal tumors (GISTs) who are at low risk of recurrence.Methods:This was a retrospective cohort study. Clinicopathologic and prognostic data from patients with non-gastric GISTs and at low risk of recurrence (i.e., very low-risk or low-risk according to the 2008 version of the Modified NIH Risk Classification), who attended 18 medical centers in China between January 2000 and June 2023, were collected. We excluded patients with a history of prior malignancy, concurrent primary malignancy, multiple GISTs, and those who had received preoperative imatinib. The study cohort comprised 1,571 patients with GISTs, 370 (23.6%) of whom were at very low-risk and 1,201 (76.4%) at low-risk of recurrence. The cohort included 799 (50.9%) men and 772 (49.1%) women of median age 57 (16–93) years. Patients were followed up to July 2024. The prognosis and its influencing factors were analyzed. Receiver operating characteristic curves for tumor diameter and Ki67 were established, and the sensitivity, specificity, area under the curve (AUC) and optimal cut-off value with 95% confidence intervals were calculated. Propensity score matching was implemented using the 1:1 nearest neighbor matching method with a matching tolerance of 0.02.Results:With a median follow-up of 63 (12–267) months, the 5- and 10-year overall survival (OS) rates of the 1,571 patients were 99.5% and 98.0%, respectively, and the 5- and 10-year disease-free survival (DFS) rates were 96.3% and 94.4%, respectively. During postoperative follow-up, 3.8% (60/1,571) patients had disease recurrence or metastasis, comprising 0.8% (3/370) in the very low-risk group and 4.7% (57/1,201) in the low-risk group. In the low-risk group, recurrence or metastasis occurred in 5.5% (25/457) of patients with duodenal GISTs, 3.9% (25/645) of those with small intestinal GISTs, 9.2% (6/65) of those with rectal GISTs, and 10.0% (1/10) of those with colonic GISTs. Among the 60 patients with metastases, 56.7% (34/60) of the metastases were located in the abdominal cavity, 53.3% (32/60) in the liver, and 3.3% (2/60) in bone. During the follow-up period, 13 patients (0.8%) died of disease. Receiver operating characteristic curves were plotted for tumor diameter and Ki67 and assessed using the Jordon index. This showed that the difference in DFS between the two groups was statistically significant when the cutoff value for tumor diameter was 3.5 cm (AUC 0.731, 95% CI: 0.670–0.793, sensitivity 77.7%, specificity 64.1%). Furthermore, the difference in DFS between the two groups was statistically significant when the cutoff value for Ki67 was 5% (AUC 0.693, 95% CI: 0.624–0.762, sensitivity 60.7%, specificity 65.3%). Multifactorial analysis revealed that tumor diameter ≥3.5 cm, Ki67 ≥5%, and R1 resection were independent risk factors for DFS in patients with non-gastric GISTs at low risk of recurrence (all P<0.05). Furthermore, age >57 years, Ki67 ≥5%, and R1 resection were also independent risk factors for OS in patients with non-gastric GISTs at low risk of recurrence (all P<0.05). We also grouped the patients according to whether they had received postoperative adjuvant treatment with imatinib for 1 or 3 years. This yielded 137 patients in the less than 1-year group, 139 in the 1-year plus group; and 44 in both the less than 3 years and 3-years plus group. After propensity score matching for age, tumor diameter, Ki67, and resection status, the differences in survival between the two groups were not statistically significant (all P>0.05). The 10-year DFS and OS were 87.5% and 95.5%, respectively, in the group treated with imatinib for less than 1 year and 88.5% and 97.8%, respectively, in the group treated for more than 1 year. The 10-year DFS and OS were 89.6% and 92.6%, respectively, in the group treated with imatinib for less than 3 years and 88.0% and 100.0%, respectively, in the group treated with imatinib for more than 3 years. Conclusion:The overall prognosis of primary, non-gastric, low recurrence risk GISTs is relatively favorable; however, recurrences and metastases do occur. Age, tumor diameter, Ki67, and R1 resection may affect the prognosis. For some patients with low risk GISTs, administration of adjuvant therapy with imatinib for an appropriate duration may help prevent recurrence and improve survival.

After nearly 40 years of development, minimally invasive techniques have been widely applied in curative surgeries for various types of tumors. The safety and efficacy of minimally invasive surgery has being fully validated. With the continuous iteration and updating of medical equipments, the convenience and precision of surgeries have been significantly enhanced, marking the advancement of minimally invasive surgery into a phase of high-level platform. With the rapid development of information technology, we have gradually entered the era of intelligent medicine, where the integration of technologies such as artificial intelligence will inject new vitality into the development of minimally invasive surgery. Combined with the latest research trends, the authors provide an in-depth analysis of how artificial intelligence plays a unique role in key aspects of minimally invasive surgery, including preoperative assessment and planning, intraoperative moni-toring and alerting, and comprehensive postoperative management. Additionally, the authors discuss how to utilize these innovative technologies to further promote reforms in medical education and prospects for the development of telemedicine service. In the era of intelligent medicine, the develop-ment of minimally invasive surgery should adhere to the principle of "bold innovation, cautious practice", guided by the concept of "patient-centeredness". By promoting interdisciplinary collabora-tion between medicine and engineering, accelerating the translation of scientific and technological achievements into clinical practice, we can ensure that minimally invasive surgical techniques better serve the health and well-being of the people.

Objective:To investigate the clinical value of magnetic resonance imaging (MRI) based integrated deep learning model for predicting the times of linear staplers used in double stapling technique for middle-low rectal cancer resection.Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients who underwent low anterior resection (LAR) for middle-low rectal cancer in Ruijin Hospital of Shanghai Jiaotong University School of Medicine from January 2018 to December 2022 were collected as training dataset. There were 183 males and 80 females, aged 63(55,68)years. The clinicopathological data of 128 patients with middle-low rectal cancer were collected as validation dataset, including 83 males and 45 females, with age as 65(57,70)years. The training dataset was used to construct the prediction model, and the validation dataset was used to validate the prediction model. Observation indicators: (1) clinicopathological features of patients in the training dataset; (2) influencing factors for ≥3 times using of linear staplers in the operation; (3) prediction model construction; (4) efficiency evaluation of prediction model; (5) validation of prediction model. Measurement data with skewed distribution were represented as M( Q1, Q3), and Mann-Whitney U test was used for comparison between groups. Count data were expressed as absolute numbers, and comparison between groups was conducted using the chi-square test. Wilcoxon rank sum test was used for non-parametric data analysis. Univariate analysis was conducted using the Logistic regression model, and multivariate analysis was conducted using the Logistic stepwise regression model. The receiver operating characteristic (ROC) curve was draw and the area under the curve (AUC) was calculated. The AUC of the ROC curve >0.75 indicated the prediction model as acceptable. Comparison of AUC was conducted using the Delong test. Results:(1) Clinicopathological features of patients in the training dataset. Of the 263 patients, there were 48 cases with linear staplers used in the operation ≥3 times and 215 cases with linear staplers used in the operation ≤2 times. Cases with preoperative serum carcinoembryonic antigen (CEA) >5 μg/L, cases with anastomotic leakage, cases with tumor diameter ≥5 cm were 20, 12, 13 in the 48 cases with linear staplers used ≥3 times in the operation, versus 56, 26, 21 in the 215 cases with linear staplers used ≤2 times in the operation, showing significant differences in the above indicators between them ( χ2=4.66, 5.29, 10.45, P<0.05). (2) Influencing factors for ≥3 times using of linear staplers in the operation. Results of multivariate analysis showed that preoperative serum CEA >5 μg/L and tumor diameter ≥5 cm were independent risk factors for ≥3 times using of linear staplers in the operation ( odds ratio=2.26, 3.39, 95% confidence interval as 1.15-4.43, 1.50-7.65, P<0.05). (3) Prediction model construction. According to the results of multivariate analysis, the clinical prediction model was established as Logit(P)=-2.018+0.814×preoperative serum CEA (>5 μg/L as 1, ≤5 μg/L as 0)+ 1.222×tumor diameter (≥5 cm as 1, <5 cm as 0). The image data segmented by the Mask region convolutional neural network (MASK R-CNN) was input into the three-dimensional convolutional neural network (C3D), and the image prediction model was constructed by training. The image data segmented by the MASK R-CNN and the clinical independent risk factors were input into the C3D, and the integrated prediction model was constructed by training. (4) Efficiency evaluation of prediction model. The sensitivity, specificity and accuracy of the clinical prediction model was 70.0%, 81.0% and 79.4%, respectively, with the Yoden index as 0.51. The sensitivity, specificity and accuracy of the image prediction model was 50.0%, 98.3% and 91.2%, respectively, with the Yoden index as 0.48. The sensitivity, specificity and accuracy of the integrated prediction model was 70.0%, 98.3% and 94.1%, respectively, with the Yoden index as 0.68. The AUC of clinical prediction model, image prediction model and integrated prediction model was 0.72(95% confidence interval as 0.61-0.83), 0.81(95% confidence interval as 0.71-0.91) and 0.88(95% confidence interval as 0.81-0.95), respectively. There were significant differences in the efficacy between the integrated prediction model and the image prediction model or the clinical prediction model ( Z=2.98, 2.48, P<0.05). (5) Validation of prediction model. The three prediction models were externally validated by validation dataset. The sensitivity, specificity and accuracy of the clinical prediction model was 62.5%, 66.1% and 65.6%, respectively, with the Yoden index as 0.29. The sensitivity, specificity and accuracy of the image prediction model was 58.8%, 95.5% and 92.1%, respectively, with the Yoden index as 0.64. The sensitivity, specificity and accuracy of the integrated prediction model was 68.8%, 97.3% and 93.8%, respectively, with the Yoden index as 0.66. The AUC of clinical prediction model, image prediction model and integrated prediction model was 0.65(95% confidence interval as 0.55-0.75), 0.75(95% confidence interval as 0.66-0.84) and 0.84(95% confidence interval as 0.74-0.93), respec-tively. There was significant differences in the efficacy between the clinical prediction model and the integrated prediction model ( Z=3.24, P<0.05). Conclusion:The MRI-based deep-learning model can help predicting the high-risk population with ≥3 times using of linear staplers in resection of middle-low rectal cancer with double stapling technique.

Represented by colorectal cancer, gastrointestinal malignancies have unique clinical characteristics and biological behaviors, ranking high in the incidence and mortality rates in China. In recent years, with technological innovations and continuous optimization of disease management models, the concept of "precision surgery" has been driving the transformation of colorectal cancer surgery from traditional empirical surgical paradigms to modern precision surgical paradigms. Rapid advancements have been made in colorectal surgical treatment, including surgical techniques, instrument platforms, various novel targeted therapies, and immune combination therapies, which have demonstrated significant efficacy in colorectal cancer treatment. Meanwhile, with 30 years of development in laparoscopic colorectal surgery in China, the surgical approach for colorectal cancer has shifted from traditional open-bellied surgery to minimally invasive surgery. The diagnostic and therapeutic models for colorectal cancer patients have gradually transitioned from experience-driven to precision-based and individualized care. Guided by the concept of "precision surgery", this article combines the current status and trends in colorectal cancer surgery to discuss relevant molecular subtyping and precision treatment strategies, aiming to promote precise surgery and comprehensive treatment for colorectal cancer.