Appendix300: Surgical video and patient metadata of 330 laparoscopic appendectomy cases from five institutions

Kolbinger, Fiona R; Kirchner, Max; Pfeiffer, Kevin; Bodenstedt, Sebastian; Jenke, Alexander C; Barthel, Julia; Carstens, Matthias; Dehlke, Karolin; Dietz, Sophia; Emmanouilidis, Sotirios; Fitze, Guido; Freitag, Martin; Holderried, Fabian; Jacobi, Thorsten; Kanjo, Weam; Leitermann, Linda; Mees, Sören Torge; Pistorius, Steffen; Prudlo, Conrad; Seiberth, Astrid; Schultz, Jurek; Thiel, Karolin; Ziehn, Daniel; Speidel, Stefanie; Kather, Jakob Nikolas; Distler, Marius; Saldanha, Oliver Lester

Appendix300: Surgical video and patient metadata of 330 laparoscopic appendectomy cases from five institutions

References to related material datacite.relatedItem.IsSupplementTo	10.1101/2025.09.05.25335174
Type of the data datacite.resourceTypeGeneral	Dataset
Type of the data datacite.resourceTypeGeneral	Image
Type of the data datacite.resourceTypeGeneral	Other
Total size of the dataset datacite.size	1692471372638
Author dc.contributor.author	Kolbinger, Fiona R
Author dc.contributor.author	Kirchner, Max
Author dc.contributor.author	Pfeiffer, Kevin
Author dc.contributor.author	Bodenstedt, Sebastian
Author dc.contributor.author	Jenke, Alexander C
Author dc.contributor.author	Barthel, Julia
Author dc.contributor.author	Carstens, Matthias
Author dc.contributor.author	Dehlke, Karolin
Author dc.contributor.author	Dietz, Sophia
Author dc.contributor.author	Emmanouilidis, Sotirios
Author dc.contributor.author	Fitze, Guido
Author dc.contributor.author	Freitag, Martin
Author dc.contributor.author	Holderried, Fabian
Author dc.contributor.author	Jacobi, Thorsten
Author dc.contributor.author	Kanjo, Weam
Author dc.contributor.author	Leitermann, Linda
Author dc.contributor.author	Mees, Sören Torge
Author dc.contributor.author	Pistorius, Steffen
Author dc.contributor.author	Prudlo, Conrad
Author dc.contributor.author	Seiberth, Astrid
Author dc.contributor.author	Schultz, Jurek
Author dc.contributor.author	Thiel, Karolin
Author dc.contributor.author	Ziehn, Daniel
Author dc.contributor.author	Speidel, Stefanie
Author dc.contributor.author	Kather, Jakob Nikolas
Author dc.contributor.author	Distler, Marius
Author dc.contributor.author	Saldanha, Oliver Lester
Upload date dc.date.accessioned	2026-04-29T14:13:14Z
Publication date dc.date.available	2026-04-29T14:13:14Z
Publication date dc.date.issued	2026-04-29
Abstract of the dataset dc.description.abstract	The limited availability of diverse and representative training data poses a critical barrier to the development of clinically relevant computational tools for intraoperative surgical decision support. Surgical procedures are not routinely recorded, and data annotation requires domain expertise, resulting in a scarcity of open-access surgical video datasets with high-quality annotations. Existing datasets are typically limited to single institutions and specific procedures, such as cholecystectomy, and rarely comprise patient-level metadata like demographic characteristics, disease history, or laboratory parameters. The Appendix300 dataset comprises 330 laparoscopic surgery recordings, including 325 full-length laparoscopic appendectomies and 5 control recordings from non-appendectomy procedures in pediatric and adult patients treated at five German centers. The dataset includes patient-level clinical metadata (demographics, medical history, clinical symptoms, preoperative laboratory parameters, and histopathological findings, as well as standardized expert annotations of the laparoscopic grade of appendicitis. This dataset enables novel validation tasks for computer vision in laparoscopic surgery and facilitates simulation of decentralized learning approaches, overall enhancing the breadth and translational relevance of AI-based surgical video analysis.
Public reference to this page dc.identifier.uri	https://opara.zih.tu-dresden.de/handle/123456789/2223
Public reference to this page dc.identifier.uri	https://doi.org/10.25532/OPARA-1173
Publisher dc.publisher	Technische Universität Dresden
Licence dc.rights	Attribution 4.0 International	en
URI of the licence text dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
Specification of the discipline(s) dc.subject.classification	2::22::205::205-07
Specification of the discipline(s) dc.subject.classification	2::22::205::205-25
Title of the dataset dc.title	Appendix300: Surgical video and patient metadata of 330 laparoscopic appendectomy cases from five institutions
Funding Acknowledgement opara.project.fundingAcknowledgement	The authors gratefully acknowledge administrative support from Sandra Korn, Ulrike Neckmann, Christian Praetorius, and Anika Stützer (Clinical Trial Center, Department of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine Carl Gustav Carus Dresden, Dresden, Germany) and technical support from all participating institutions in locally setting up data collection infrastructure. This work was supported by the German Cancer Research Center (CoBot 2.0) and the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) as part of Germany’s Excellence Strategy (EXC 2050/1, Project ID 390696704) within the Cluster of Excellence ”Centre for Tactile Internet with Human-in-the-Loop” (CeTI) of the Dresden University of Technology. FRK receives support from the Joachim Herz Foundation (Add-On Fellowship for Interdisciplinary Life Science), the Central Indiana Corporate Partnership AnalytiXIN Initiative, the Evan and Sue Ann Werling Pancreatic Cancer Research Fund, and the Indiana Clinical and Translational Sciences Institute (EPAR4157) funded, in part, by Grant Number UM1TR004402 from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award. MK and ACJ are supported by the European Union through NEARDATA under grant agreement ID 101092644. JNK is supported by the German Cancer Aid (DECADE, 70115166), the German Federal Ministry of Education and Research (PEARL, 01KD2104C; CAMINO, 01EO2101; SWAG, 01KD2215A; TRANSFORM LIVER, 031L0312A; TANGERINE, 01KT2302 through ERA-NET Transcan; Come2Data, 16DKZ2044A; DEEP-HCC, 031L0315A), the German Academic Exchange Service (SECAI, 57616814), the German Federal Joint Committee (TransplantKI, 01VSF21048) the European Union’s Horizon Europe and innovation programme (ODELIA, 101057091; GENIAL, 101096312), the European Research Council (ERC; NADIR, 101114631), the National Institutes of Health (EPICO, R01 CA263318) and the National Institute for Health and Care Research (NIHR, NIHR203331) Leeds Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the National Institutes of Health, the NIHR, or the Department of Health and Social Care. This work was funded by the European Union. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor other granting authorities can be held responsible for them. Competing Interests FRK declares advisory roles for Radical Healthcare, USA; and the Surgical Data Science Collective (SDSC), USA. JNK declares consulting services for Bioptimus, France; Owkin, France; DoMore Diagnostics, Norway; Panakeia, UK; AstraZeneca, UK; Scailyte, Switzerland; Mindpeak, Germany; and MultiplexDx, Slovakia. Furthermore, he holds shares in StratifAI, Synagen, and Ignition Labs, Germany, has received a research grant by GSK, and has received honoraria by AstraZeneca, Bayer, Eisai, Janssen, MSD, BMS, Roche, Pfizer and Fresenius. MD declares advisory roles for AESCULAP AG, Germany; and Intuitive Surgical, USA, and has received honoraria from Medtronic. All other authors declare no competing interests.