Publications by authors named "Jennifer A Eckhoff"

The most common functional challenge after Ivor-Lewis esophagectomy is delayed emptying of the gastric conduit. One of the primary endoscopic treatment strategies is performing a pyloric dilatation. However, the effects of dilation have never been scientifically proven.

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Background: The ergonomic advantages and potential challenges that robotic surgery poses to the well-being of surgeons are mainly unexplored. The most recent surgical robot introduced on the European market is the Hugo™ RAS System by Medtronic. This study aims to evaluate the ergonomic benefits of the Hugo™ RAS System, which is available in our training laboratory, CeMIT (Center for Medical Innovation and Technology Cologne).

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Previous studies have shown that surgical residents can safely perform a variation of complex abdominal surgeries when provided with adequate training, proper case selection, and appropriate supervision. Their outcomes are equivalent when compared to experienced board-certified surgeons. Our previously published training curriculum for robotic assisted minimally invasive esophagectomy already demonstrated a possible reduction in time to reach proficiency.

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Objective: Develop a pioneer surgical anonymization algorithm for reliable and accurate real-time removal of out-of-body images validated across various robotic platforms.

Background: The use of surgical video data has become a common practice in enhancing research and training. Video sharing requires complete anonymization, which, in the case of endoscopic surgery, entails the removal of all nonsurgical video frames where the endoscope can record the patient or operating room staff.

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Background: Postesophagectomy diaphragmatic prolapse (PDP) is a major complication after esophagectomy with significant mortality and morbidity. However, in the current literature, treatment and outcomes are not evaluated for patients undergoing an Ivor Lewis Robot-assisted minimally invasive esophagectomy (IL-RAMIE). The aim of this study is to evaluate the incidence of PDP after IL-RAMIE.

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Article Synopsis
  • Robotic-assisted minimally invasive esophagectomy (RAMIE) has improved postoperative recovery since its introduction in 2003, and this study aimed to evaluate a proficiency-based training pathway for surgeons at a high-volume center in Germany.
  • A total of 154 patients who underwent RAMIE between 2017 and 2022 were analyzed to observe the necessary case numbers for surgeons to reach expert performance levels in various metrics such as operating time and complication rates.
  • Results indicated that significant improvements in surgical performance were seen after specific case milestones, with varying stabilization points for hospital stay and anastomotic leak rates, highlighting the importance of structured training in developing surgical expertise.
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Article Synopsis
  • Surgery generates extensive video data that is crucial for research, clinical outcomes, and education, but the entire data lifecycle requires standardized frameworks to ensure quality and compliance with ethical regulations.
  • Working groups comprised of clinicians and data experts collaborated to develop structured recommendations across key areas: Data Use, Structure, Exploration, and Governance using a modified Delphi process.
  • The consensus offers clear guidelines for standardized surgical video data management, emphasizing transparency, diversity, and attention to legal and ethical issues, aiming to improve data utilization for all stakeholders involved.
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Analysis of relations between objects and comprehension of abstract concepts in the surgical video is important in AI-augmented surgery. However, building models that integrate our knowledge and understanding of surgery remains a challenging endeavor. In this paper, we propose a novel way to integrate conceptual knowledge into temporal analysis tasks using temporal concept graph networks.

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Article Synopsis
  • The study explores the use of near-infrared light fluorescence (NIR) with indocyanine green (ICG) for mapping lymph nodes during esophageal cancer surgery, a method not yet established in this field.
  • It involved 20 patients with advanced esophageal cancer undergoing robotic-assisted minimally invasive esophagectomy (RAMIE), where ICG was injected around the tumor prior to surgery to visualize lymphatic drainage.
  • Initial findings indicate that using NIR imaging is feasible and safe for detecting lymph node metastases during RAMIE, with plans for further research on ICG-positive tissue and long-term outcomes.
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Background: Artificial intelligence (AI) holds tremendous potential to reduce surgical risks and improve surgical assessment. Machine learning, a subfield of AI, can be used to analyze surgical video and imaging data. Manual annotations provide veracity about the desired target features.

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Background: Caroli Disease (CD) and Caroli Syndrome (CS) are rare disorders presenting with dilation of the intrahepatic bile ducts. CD/CS are associated with cholangiocarcinoma (CCA). However, the true incidence of CCA is still unclear, although it may serve as an indication for surgery.

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