Minimally invasive esophagectomy (MIE) is technically challenging. Da Vinci Robotic system could improve surgical dissection with additional degree of freedom from robotic arms. This study aimed to assess the feasibility and safety of performing MIE using Da Vinci Robotic system among patients with esophageal cancers. From 2009 to 2013, consecutive patients with esophageal cancers who received robotic-assisted MIE were recruited. We excluded tumors with suspected invasion to adjacent organs. Preoperative staging included EUS, CT thorax and abdomen and bronchoscopy. We perform mobilization of thoracic esophagus with two-field lymphadenectomy using robotic system, followed by laparoscopic gastric mobilization and hand-sewn cervical esophagogastric anastomosis. A total of 20 patients were recruited (16 male and 4 female) with mean age of 64.2 ± 8.8 years. All patients were successfully treated with robotic-assisted MIE with mean operative time of 499.5 ± 70 min and blood loss of 355.7 ± 329.6 mls. There was no pulmonary complication, while three patients sustained anastomotic leakage and managed conservatively. The mean hospital stay was 13 ± 6 days. Five patients had stage I tumors, five had stage II, and nine had stage III disease. One patient had complete response after neoadjuvant chemoradiotherapy. The number of lymph node dissection was 18.2 ± 13.2, and 2.8 ± 5.7 nodes involved. The follow-up period was 21 ± 9 months, and the overall survival was 75 %. Robotic-assisted MIE is feasible and safe for treatment of esophageal cancers. The surgical dissection can be enhanced by improved ergonomics from robotic arms and sense of depth from 3D images.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s11701-016-0644-2 | DOI Listing |
Nat Commun
January 2025
Guangxi Key Laboratory of Clean Pulp & Papermaking and Pollution Control, School of Light Industry and Food Engineering, Guangxi University, Nanning, 530004, PR China.
Skin-like sensors capable of detecting multiple stimuli simultaneously have great potential in cutting-edge human-machine interaction. However, realizing multimodal tactile recognition beyond human tactile perception still faces significant challenges. Here, an extreme environments-adaptive multimodal triboelectric sensor was developed, capable of detecting pressure/temperatures beyond the range of human perception.
View Article and Find Full Text PDFPathol Res Pract
December 2024
Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy.
Pathology laboratories are currently facing remarkable issues in the management of their archives due to the ongoing increase in the production of formalin-fixed paraffin-embedded (FFPE) blocks, which is often coupled with inadequate spatial and environmental storing conditions. The manual process of storage and retrieving further increases the likelihood of human-based mistakes, wastes professionals' working time, and, ultimately, widens reports signing turn-around times. In the present work, we outline the strategies underlying the development of an automated archive at the pathology services of the University of Modena.
View Article and Find Full Text PDFSci Rep
January 2025
Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal do Paraná (UTFPR), Curitiba, 80230-901, Brazil.
Modeling the Digital Twin (DT) is an important resource for accurately representing the physical entity, enabling it to deliver functional services, meet application requirements, and address the disturbances between the physical and digital realms. This article introduces the Log Mean Kinematics Difference Synchronization (SyncLMKD) to measure the kinematic variations distributed among Digital Twin elements to ensure symmetric values relative to a reference. The proposed method employs abductive reasoning and draws inspiration from the Log Mean Temperature Difference (LMTD).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Engineering, California Polytechnic State University, San Luis Obispo, California, USA.
Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet traditional finger pricking methods are often inconvenient and painful. To address this issue, photoplethysmography (PPG) presents a promising non-invasive alternative for estimating blood glucose levels. In this study, we propose an innovative 1-second signal segmentation method and evaluate the performance of three advanced deep learning models using a novel dataset to estimate blood glucose levels from PPG signals.
View Article and Find Full Text PDFSci Rep
January 2025
Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Humans exploit motor synergies for motor control; however, how they emerge during motor learning is not clearly understood. Few studies have dealt with the computational mechanism for generating synergies. Previously, optimal control generated synergistic motion for the upper limb; however, it has not yet been applied to the high-dimensional whole-body system.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!