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  1. Article ; Online: Robotic surgery: a time of change.

    Marescaux, Jacques / Seeliger, Barbara

    Updates in surgery

    2023  Volume 75, Issue 4, Page(s) 793–794

    MeSH term(s) Humans ; Robotic Surgical Procedures ; Laparoscopy ; Operative Time
    Language English
    Publishing date 2023-06-13
    Publishing country Italy
    Document type Editorial
    ZDB-ID 2572692-4
    ISSN 2038-3312 ; 2038-131X
    ISSN (online) 2038-3312
    ISSN 2038-131X
    DOI 10.1007/s13304-023-01546-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 101: Show issues Location:
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  2. Book ; Online: Telesurgery

    Kumar, Sajeesh / Marescaux, Jacques

    2008  

    Author's details edited by Sajeesh Kumar, Jacques Marescaux
    Keywords Colon (Anatomy)/Heart_xEndoscopic surgery ; Surgery ; Thoracic surgery
    Language English
    Publisher Springer-Verlag
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    HBZ-ID TT050387798
    ISBN 978-3-540-72998-3 ; 978-3-540-72999-0 ; 3-540-72998-4 ; 3-540-72999-2
    DOI 10.1007/978-3-540-72999-0
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Article ; Online: Treatment of complete rectal prolapse using the TEO® platform (transanal endoscopic operation) - a video vignette.

    D'Urso, Antonio / Lapergola, Alfonso / Marescaux, Jacques / Mutter, Didier / Serra-Aracil, Xavier

    Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland

    2024  

    Language English
    Publishing date 2024-02-05
    Publishing country England
    Document type Letter
    ZDB-ID 1440017-0
    ISSN 1463-1318 ; 1462-8910
    ISSN (online) 1463-1318
    ISSN 1462-8910
    DOI 10.1111/codi.16910
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    Zs.A 5799: Show issues Location:
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  4. Article ; Online: Ten years of IRCAD, Barretos, SP, Brazil.

    Crema, Eduardo / Melani, Armando Geraldo Franchini / Romagnolo, Luís Gustavo Capochin / Marescaux, Jacques

    Acta cirurgica brasileira

    2022  Volume 37, Issue 6, Page(s) e370608

    Abstract: Minimally invasive surgery represented a significant milestone in modern surgery; however, continuous innovation and the emergence of new technologies pose new challenges in terms of surgical learning curves since new interventions are associated with ... ...

    Abstract Minimally invasive surgery represented a significant milestone in modern surgery; however, continuous innovation and the emergence of new technologies pose new challenges in terms of surgical learning curves since new interventions are associated with increased surgical complexity and a higher risk of complications. For this reason, surgeons are aware of the beneficial effects of "learning before doing" and the importance of safely implementing new surgical procedures in order to obtain better patient outcomes. Considered the largest Latin American training center in minimally invasive surgery, IRCAD Barretos, São Paulo, Brazil, makes it possible to acquire surgical skills through training in different and the most complex areas of medicine, providing the experience of real and simulated situations, with focus on innovation. The center possesses state-of-the-art infrastructure and technology, with a very high-level teaching staff and an affectionate and hospitable reception. Since its inauguration, in 2011, the center has already qualified numerous professionals and has placed the country in a privileged position in terms of surgical knowledge. The present article describes the activities developed over these ten years of the institute in Brazil as the largest training center for surgeons of the continent in order to address the importance of surgical skills training.
    MeSH term(s) Brazil ; Humans ; Learning Curve ; Minimally Invasive Surgical Procedures
    Language English
    Publishing date 2022-09-19
    Publishing country Brazil
    Document type Journal Article
    ZDB-ID 2012156-8
    ISSN 1678-2674 ; 1678-2674
    ISSN (online) 1678-2674
    ISSN 1678-2674
    DOI 10.1590/acb370608
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Live laparoscopic video retrieval with compressed uncertainty.

    Yu, Tong / Mascagni, Pietro / Verde, Juan / Marescaux, Jacques / Mutter, Didier / Padoy, Nicolas

    Medical image analysis

    2023  Volume 88, Page(s) 102866

    Abstract: Searching through large volumes of medical data to retrieve relevant information is a challenging yet crucial task for clinical care. However the primitive and most common approach to retrieval, involving text in the form of keywords, is severely limited ...

    Abstract Searching through large volumes of medical data to retrieve relevant information is a challenging yet crucial task for clinical care. However the primitive and most common approach to retrieval, involving text in the form of keywords, is severely limited when dealing with complex media formats. Content-based retrieval offers a way to overcome this limitation, by using rich media as the query itself. Surgical video-to-video retrieval in particular is a new and largely unexplored research problem with high clinical value, especially in the real-time case: using real-time video hashing, search can be achieved directly inside of the operating room. Indeed, the process of hashing converts large data entries into compact binary arrays or hashes, enabling large-scale search operations at a very fast rate. However, due to fluctuations over the course of a video, not all bits in a given hash are equally reliable. In this work, we propose a method capable of mitigating this uncertainty while maintaining a light computational footprint. We present superior retrieval results (3%-4% top 10 mean average precision) on a multi-task evaluation protocol for surgery, using cholecystectomy phases, bypass phases, and coming from an entirely new dataset introduced here, surgical events across six different surgery types. Success on this multi-task benchmark shows the generalizability of our approach for surgical video retrieval.
    MeSH term(s) Humans ; Algorithms ; Cholecystectomy ; Laparoscopy ; Uncertainty
    Language English
    Publishing date 2023-06-15
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Video-Audio Media
    ZDB-ID 1356436-5
    ISSN 1361-8423 ; 1361-8431 ; 1361-8415
    ISSN (online) 1361-8423 ; 1361-8431
    ISSN 1361-8415
    DOI 10.1016/j.media.2023.102866
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 5206: Show issues Location:
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  6. Article ; Online: Design and preliminary validation of a high-fidelity vascular simulator for robot-assisted manipulation.

    Gamberini, Giulia / Maglio, Sabina / Mariani, Andrea / Mazzotta, Alessandro Dario / Forgione, Antonello / Marescaux, Jacques / Melfi, Franca / Tognarelli, Selene / Menciassi, Arianna

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 4779

    Abstract: The number of robot-assisted minimally invasive surgeries is increasing annually, together with the need for dedicated and effective training. Surgeons need to learn how to address the novel control modalities of surgical instruments and the loss of ... ...

    Abstract The number of robot-assisted minimally invasive surgeries is increasing annually, together with the need for dedicated and effective training. Surgeons need to learn how to address the novel control modalities of surgical instruments and the loss of haptic feedback, which is a common feature of most surgical robots. High-fidelity physical simulation has proved to be a valid training tool, and it might help in fulfilling these learning needs. In this regard, a high-fidelity sensorized simulator of vascular structures was designed, fabricated and preliminarily validated. The main objective of the simulator is to train novices in robotic surgery to correctly perform vascular resection procedures without applying excessive strain to tissues. The vessel simulator was integrated with soft strain sensors to quantify and objectively assess manipulation skills and to provide real-time feedback to the trainee during a training session. Additionally, a portable and user-friendly training task board was produced to replicate anatomical constraints. The simulator was characterized in terms of its mechanical properties, demonstrating its realism with respect to human tissues. Its face, content and construct validity, together with its usability, were assessed by implementing a training scenario with 13 clinicians, and the results were generally positive.
    MeSH term(s) Humans ; Robotics ; Computer Simulation ; Physical Examination ; Learning ; Feedback ; Clinical Competence
    Language English
    Publishing date 2024-02-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-55351-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Estado actual de la cirugía. Cirugía robótica y telecirugía.

    Marescaux, Jacques

    Cirugia y cirujanos

    2013  Volume 81, Issue 4, Page(s) 265–268

    Title translation State of the art of surgery. Robotic surgery and telesurgery.
    MeSH term(s) Computer Simulation ; General Surgery/trends ; Humans ; Miniaturization ; Minimally Invasive Surgical Procedures/instrumentation ; Minimally Invasive Surgical Procedures/methods ; Robotics/instrumentation ; Robotics/trends ; Surgical Instruments ; Telemedicine/trends
    Language Spanish
    Publishing date 2013-07
    Publishing country Spain
    Document type Editorial
    ZDB-ID 730699-4
    ISSN 0009-7411
    ISSN 0009-7411
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 797: Show issues Location:
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  8. Article ; Online: Comment on "Short-term Outcomes of Ambulatory Colectomy for 157 Consecutive Patients." Evaluation of Organizational Innovations: Reconciliation Between Patients' Expectations and Doctors' Duties.

    Pessaux, Patrick / Mutter, Didier / Marescaux, Jacques

    Annals of surgery

    2020  Volume 274, Issue 6, Page(s) e677–e678

    MeSH term(s) Colectomy ; Humans ; Motivation ; Physician-Patient Relations ; Physicians
    Language English
    Publishing date 2020-03-21
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 340-2
    ISSN 1528-1140 ; 0003-4932
    ISSN (online) 1528-1140
    ISSN 0003-4932
    DOI 10.1097/SLA.0000000000003810
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    Uk I Zs.35/1: Show issues Location:
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  9. Article ; Online: Intraoperative and postoperative complications in colorectal procedures: the role of continuous updating in medicine.

    Forgione, Antonello / Guraya, Salman Y / Diana, Michele / Marescaux, Jacques

    Minerva surgery

    2021  Volume 76, Issue 4, Page(s) 350–371

    Abstract: Accepting surgical complications, especially those related to the learning curve, as unavoidable events in colorectal procedures, is like accepting to fly onboard an aircraft with a 10% to 20% chance of not arriving at final destination. Under this ... ...

    Abstract Accepting surgical complications, especially those related to the learning curve, as unavoidable events in colorectal procedures, is like accepting to fly onboard an aircraft with a 10% to 20% chance of not arriving at final destination. Under this condition, it is very likely that the aviation industry and the concurrent reshaping of the world and of our lives would have not been possible in the absence of high reliability and reproducibility of safe flights. It is hard to imagine surgery without any intraoperative and/or postoperative complications. Nevertheless, there is a plenty of room for improvement by simply adopting what has been explicitly and scientifically demonstrated; training outside of the operating room (OR), usage of modern information technologies and application of evidence-based perioperative care protocols. Additionally, the possibility to objectively measure and monitor the technical and even non-technical skills and competencies of individual surgeons and even of OR teams through the application of structured and validated assessment tools can finally put an end to the self-referential, purely hierarchical, and indeed extremely unreliable process of being authorized or not to perform operations on patients. Last but not least, a wide range of new technologies spanning from augmented imaging modalities, virtual reality for intraoperative guidance, improved robotic manipulators, artificial intelligence to assist in preoperative patient specific risk assessment, and intraoperative decision-making has the potential to tackle several hidden roots of surgical complications.
    MeSH term(s) Artificial Intelligence ; Clinical Competence ; Colorectal Neoplasms ; Humans ; Postoperative Complications/prevention & control ; Reproducibility of Results
    Language English
    Publishing date 2021-05-04
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 3067899-7
    ISSN 2724-5438
    ISSN (online) 2724-5438
    DOI 10.23736/S2724-5691.21.08638-X
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 25: Show issues Location:
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  10. Article ; Online: Machine learning models to predict success of endoscopic sleeve gastroplasty using total and excess weight loss percent achievement: a multicentre study.

    Vannucci, Maria / Niyishaka, Patrick / Collins, Toby / Rodríguez-Luna, María Rita / Mascagni, Pietro / Hostettler, Alexandre / Marescaux, Jacques / Perretta, Silvana

    Surgical endoscopy

    2023  Volume 38, Issue 1, Page(s) 229–239

    Abstract: Background: The large amount of heterogeneous data collected in surgical/endoscopic practice calls for data-driven approaches as machine learning (ML) models. The aim of this study was to develop ML models to predict endoscopic sleeve gastroplasty (ESG) ...

    Abstract Background: The large amount of heterogeneous data collected in surgical/endoscopic practice calls for data-driven approaches as machine learning (ML) models. The aim of this study was to develop ML models to predict endoscopic sleeve gastroplasty (ESG) efficacy at 12 months defined by total weight loss (TWL) % and excess weight loss (EWL) % achievement. Multicentre data were used to enhance generalizability: evaluate consistency among different center of ESG practice and assess reproducibility of the models and possible clinical application. Models were designed to be dynamic and integrate follow-up clinical data into more accurate predictions, possibly assisting management and decision-making.
    Methods: ML models were developed using data of 404 ESG procedures performed at 12 centers across Europe. Collected data included clinical and demographic variables at the time of ESG and at follow-up. Multicentre/external and single center/internal and temporal validation were performed. Training and evaluation of the models were performed on Python's scikit-learn library. Performance of models was quantified as receiver operator curve (ROC-AUC), sensitivity, specificity, and calibration plots.
    Results: Multicenter external validation: ML models using preoperative data show poor performance. Best performances were reached by linear regression (LR) and support vector machine models for TWL% and EWL%, respectively, (ROC-AUC: TWL% 0.87, EWL% 0.86) with the addition of 6-month follow-up data. Single-center internal validation: Preoperative data only ML models show suboptimal performance. Early, i.e., 3-month follow-up data addition lead to ROC-AUC of 0.79 (random forest classifiers model) and 0.81 (LR models) for TWL% and EWL% achievement prediction, respectively. Single-center temporal validation shows similar results.
    Conclusions: Although preoperative data only may not be sufficient for accurate postoperative predictions, the ability of ML models to adapt and evolve with the patients changes could assist in providing an effective and personalized postoperative care. ML models predictive capacity improvement with follow-up data is encouraging and may become a valuable support in patient management and decision-making.
    MeSH term(s) Humans ; Gastroplasty/methods ; Obesity/surgery ; Reproducibility of Results ; Treatment Outcome ; Weight Loss ; Machine Learning ; Obesity, Morbid/surgery
    Language English
    Publishing date 2023-11-16
    Publishing country Germany
    Document type Multicenter Study ; Journal Article
    ZDB-ID 639039-0
    ISSN 1432-2218 ; 0930-2794
    ISSN (online) 1432-2218
    ISSN 0930-2794
    DOI 10.1007/s00464-023-10520-0
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