The clinical burden of colorectal cancer (CRC) is high. Population-based screening and early detection are essential to improve the long-term clinical outcome. Nonetheless, a significant proportion of patients still present at an advanced stage, including with acute large bowel obstruction. Image-enhanced endoscopy and artificial intelligence can improve the detection and diagnosis of colonic adenomas and early cancer. Endoscopic resection is regarded as the preferred curative treatment option for colonic adenoma and T0 and T1 CRC limited to the superficial submucosa. Emergency colonic stenting as bridge to interval curative surgery is increasingly accepted as a first-line option when technically feasible. Minimally invasive resection techniques such as laparoscopic colectomy and robot-assisted colorectal surgery have also come of age. These techniques reduce post-treatment morbidity, shorten the recovery process and can be cost-effective while maintaining long-term oncological cure. These outcome measures are relevant to our patients; therefore, minimally invasive approaches to curative resection should be embraced.
Humans ; Colorectal Neoplasms/surgery* ; Minimally Invasive Surgical Procedures/methods* ; Laparoscopy/methods* ; Colectomy/methods* ; Robotic Surgical Procedures/methods* ; Treatment Outcome ; Colonoscopy/methods*

This study aims to develop an abdominal acupoint localization system based on computer vision and convolutional neural networks (CNNs). To address the challenge of abdominal acupoint localization, a multi-task CNNs architecture was constructed and trained to locate the Shenque (CV8) and human body boundaries. Based on the identified Shenque (CV8), the system further deduces key characteristics of four acupoints: Shangwan (CV13), Qugu (CV2), and bilateral Daheng (SP15). An affine transformation matrix is applied to accurately map image coordinates to an acupoint template space, achieving precise localization of abdominal acupoints. Testing has verified that this system can accurately identify and locate abdominal acupoints in images. The development of this localization system provides technical support for TCM remote education, diagnostic assistance, and advanced TCM equipment, such as intelligent acupuncture robots, facilitating the standardization and intelligent advancement of acupuncture.
Acupuncture Points ; Humans ; Deep Learning ; Abdomen/diagnostic imaging* ; Neural Networks, Computer ; Acupuncture Therapy ; Image Processing, Computer-Assisted

BACKGROUND: Telesurgery has the potential to overcome spatial limitations for surgeons, which depends on surgical robot and the quality of network communication. However, the influence of network latency and bandwidth on telesurgery is not well understood. METHODS: A telesurgery system capable of dynamically adjusting image compression ratios in response to bandwidth changes was established between Beijing and Sanya (Hainan province), covering a distance of 3000 km. In total, 108 animal operations, including 12 surgical procedures, were performed. Total latency ranging from 170 ms to 320 ms and bandwidth from 15-20 Mbps to less than 1 Mbps were explored using designed surgical tasks and hemostasis models for renal vein and internal iliac artery rupture bleeding. Network latency, jitter, frame loss, and bit rate code were systemically measured during these operations. National Aeronautics and Space Administration Task Load Index (NASA-TLX) and a self-designed scale measured the workload and subjective perception of surgeons. RESULTS: All 108 animal telesurgeries, conducted from January 2023 to June 2023, were performed effectively over a total duration of 3866 min. The operations were completed with latency up to 320 ms and bandwidths as low as 1-5 Mbps. Hemostasis for vein and artery rupture bleeding models was effectively achieved under these low bandwidth conditions. The NASA-TLX results indicated that latency significantly impacted surgical performance more than bandwidth and image clarity reductions. CONCLUSIONS This telesurgery system demonstrated safety and reliability. A total of 320 ms latency is acceptable for telesurgery operations. Reducing image clarity can effectively mitigate the potential latency increase caused by decreased bandwidth, offering a new method to reduce the impact of latency on telesurgery.
Animals ; Robotic Surgical Procedures/methods* ; Laparoscopy/methods*

Definitive treatment of lung cancer with radiotherapy is challenging, as respiratory motion and anatomical changes can increase the risk of severe off-target effects during radiotherapy. Online adaptive radiotherapy (ART) is an evolving approach that enables timely modification of a treatment plan during the interfraction of radiotherapy, in response to physiologic or anatomic variations, aiming to improve the dose distribution for precise targeting and delivery in lung cancer patients. The effectiveness of online ART depends on the seamless integration of multiple components: sufficient quality of linear accelerator-integrated imaging guidance, deformable image registration, automatic recontouring, and efficient quality assurance and workflow. This review summarizes the present status of online ART for lung cancer, including key technologies, as well as the challenges and areas of active research in this field.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods*

Humans ; Laparoscopy/education* ; Female ; Gynecologic Surgical Procedures/education* ; Consensus ; Genital Diseases, Female/surgery* ; China ; Robotic Surgical Procedures/methods*

Pancreatoduodenectomy with portal-superior mesenteric vein resection and reconstruction can provide radical surgical opportunities for patients with venous invasion and enable them to benefit from the surgery. With the development of minimally invasive concepts and surgical techniques, laparoscopic and robot-assisted pancreatoduodenectomy with portal-superior mesenteric vein resection and reconstruction is being increasingly widely carried out. This surgical procedure is highly technically demanding, and the perioperative management of patients is complex. However, there is a lack of high-quality and high-level evidence-based clinical studies in this regard. In order to better standardize the clinical application of laparoscopic or robot-assisted pancreatoduodenectomy with portal-superior mesenteric vein resection and reconstruction in China, the Study Group of Minimally Invasive Treatment for Pancreatic Cancer in China Anti-Cancer Association, guided by problems and based on evidence, formed 17 recommendations through full discussions among experts. The recommendations involve the safety, oncological benefits, and perioperative patient management of the minimally invasive approach to pancreatoduodenectomy with portal-superior mesenteric vein resection and reconstruction.
Humans ; Pancreaticoduodenectomy/methods* ; Mesenteric Veins/surgery* ; Laparoscopy ; Portal Vein/surgery* ; Robotic Surgical Procedures ; Pancreatic Neoplasms/surgery* ; Consensus

Liver transplantation is an effective treatment for end-stage liver disease. Liver transplantation is technically complex and associated with significant trauma. In recent years,minimally invasive surgical techniques,such as laparoscopy and robotic surgery,have rapidly developed and been widely applied across various surgical fields. Minimally invasive surgery offers advantages including reduced trauma,less bleeding,and faster postoperative recovery,and has become a mainstream trend in surgical development. In the field of liver transplantation,laparoscopic and robotic donor hepatectomy techniques for living donor liver transplantation have made significant progress. However, due to difficulties in exposing the anastomotic sites of the donor liver and challenges in vascular anastomosis,the application of minimally invasive techniques in donor liver implantation has progressed relatively slowly. With advancements in laparoscopic and robotic surgical techniques and related instruments,laparoscopic donor liver implantation has gradually become feasible. Currently,multiple liver transplant centers worldwide have begun to progressively perform laparoscopic or robot-assisted liver transplantation in recipients,demonstrating potential advantages in reducing surgical trauma and accelerating postoperative recovery. However,there is currently a lack of guidelines or consensus on the application of minimally invasive surgery in liver transplant recipients. Therefore,Branch of Organ Transplantation of Chinese Medical Association,Surgery Group of Chinese Society of Surgery of Chinese Medical Association,and Branch of Organ Transplant Physicians of Chinese Medical Doctor Association invited experts in the field to discuss clinical issues. Combining published guidelines,consensus statements,and research advancements,they formulated the "Technical guidelines for minimally invasive surgery in liver transplant recipients（2025）", aiming to provide reasonable guidance and references for clinical practitioners in the field of liver transplantation.
Humans ; Liver Transplantation/methods* ; Minimally Invasive Surgical Procedures/methods* ; Laparoscopy ; Robotic Surgical Procedures ; Practice Guidelines as Topic

This paper aims to propose a noninvasive radiotherapy patient positioning system based on structured light surface imaging, and evaluate its clinical feasibility. First, structured light sensors were used to obtain the panoramic point clouds during radiotherapy positioning in real time. The fusion of different point clouds and coordinate transformation were realized based on optical calibration and pose estimation, and the body surface was segmented referring to the preset region of interest (ROI). Then, the global-local registration of cross-source point cloud was achieved based on algorithms such as random sample consensus (RANSAC) and iterative closest point (ICP), to calculate 6 degrees of freedom (DoF) positioning deviation and provide guidance for the correction of couch shifts. The evaluation of the system was carried out based on a rigid adult phantom and volunteers' body, which included positioning error, correlation analysis, and receiver operating characteristic (ROC) analysis. Using Cone Beam CT (CBCT) as the gold standard, the maximum translation and rotation errors of this system were (1.5 ± 0.9) mm along Vrt direction (chest) and (0.7 ± 0.3) ° along Pitch direction (head and neck). The Pearson correlation coefficient between results of system outputs and CBCT verification distributed in an interval of [0.80, 0.84]. Results of ROC analysis showed that the translational and rotational AUC values were 0.82 and 0.85, respectively. In the 4D freedom accuracy test on the human body of volunteers, the maximum translation and rotation errors were (2.6 ± 1.1) mm (Vrt direction, chest and abdomen) and (0.8 ± 0.4)° (Rtn direction, chest and abdomen) respectively. In summary, the positioning system based on structured light body surface imaging proposed in this article can ensure positioning accuracy without surface markers and additional doses, and is feasible for clinical application.
Humans ; Patient Positioning/methods* ; Phantoms, Imaging ; Cone-Beam Computed Tomography ; Algorithms ; Radiotherapy, Image-Guided/methods* ; Radiotherapy Planning, Computer-Assisted/methods*

To address the issues of difficulty in preserving anatomical structures, low realism of generated images, and loss of high-frequency image information in medical image cross-modal translation, this paper proposes a medical image cross-modal translation method based on diffusion generative adversarial networks. First, an unsupervised translation module is used to convert magnetic resonance imaging (MRI) into pseudo-computed tomography (CT) images. Subsequently, a nonlinear frequency decomposition module is used to extract high-frequency CT images. Finally, the pseudo-CT image is input into the forward process, while the high-frequency CT image as a conditional input is used to guide the reverse process to generate the final CT image. The proposed model is evaluated on the SynthRAD2023 dataset, which is used for CT image generation for radiotherapy planning. The generated brain CT images achieve a Fréchet Inception Distance (FID) score of 33.159 7, a structure similarity index measure (SSIM) of 89.84%, a peak signal-to-noise ratio (PSNR) of 35.596 5 dB, and a mean squared error (MSE) of 17.873 9. The generated pelvic CT images yield an FID score of 33.951 6, a structural similarity index of 91.30%, a PSNR of 34.870 7 dB, and an MSE of 17.465 8. Experimental results show that the proposed model generates highly realistic CT images while preserving anatomical accuracy as much as possible. The transformed CT images can be effectively used in radiotherapy planning, further enhancing diagnostic efficiency.
Humans ; Tomography, X-Ray Computed/methods* ; Magnetic Resonance Imaging/methods* ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Brain/diagnostic imaging* ; Algorithms ; Radiotherapy Planning, Computer-Assisted ; Generative Adversarial Networks

Dynamic navigation technology can "real-time guide" the implantologist to place the implant in the alveolar bone of the missing tooth area according to the preoperative design of the optimal site and path, making the whole implant surgery process more safe and precise. In order to further promote the standardized application of oral implant dynamic navigation technology, China Association of Gerontology and Geriatrics has convened distinguished experts to engage in deliberations and develop the standard. This standard covers the basic requirements, indications and contraindications, operation procedures, common complications and treatment measures, and accuracy verification. This standard can be used as a reference for the use of dynamic navigation technology in implant surgery.
Humans ; Dental Implantation, Endosseous/standards* ; Surgery, Computer-Assisted/standards* ; Dental Implants ; Surgical Navigation Systems/standards*