The Generic Error Rating Tool: A Novel Approach to Assessment of Performance and Surgical Education in Gynecologic Laparoscopy

Husslein, H; Shirreff, Lindsay; Shore, Eliane M.; Lefebvre, Guylaine; Grantcharov, Teodor P.

doi:10.1016/j.jsurg.2015.04.029

Cited by 37 publications

(41 citation statements)

References 26 publications

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“…This is particularly true for the field of laparoscopy, where the videos are used for technical quality assessment of the surgery. 7,8 The later use of recorded videos from endscopic procedures is, however, currently not well supported by software tools, and has not been addressed intensively in research. While there are several works that focus on on-the-fly processing of the video stream from the endoscope (e.g., for detection of abnormalities 9, 10 ), post-processing of the recorded videos has only attracted a few research works so far.…”

Section: Description Of Purposementioning

confidence: 99%

Content-based retrieval in videos from laparoscopic surgery

Schoeffmann

Beecks

Lux

et al. 2016

Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling

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In the field of medical endoscopy more and more surgeons are changing over to record and store videos of their endoscopic procedures for long-term archival. These endoscopic videos are a good source of information for explanations to patients and follow-up operations. As the endoscope is the "eye of the surgeon", the video shows the same information the surgeon has seen during the operation, and can describe the situation inside the patient much more precisely than an operation report would do. Recorded endoscopic videos can also be used for training young surgeons and in some countries the long-term archival of video recordings from endoscopic procedures is even enforced by law. A major challenge, however, is to efficiently access these very large video archives for later purposes. One problem, for example, is to locate specific images in the videos that show important situations, which are additionally captured as static images during the procedure. This work addresses this problem and focuses on contentbased video retrieval in data from laparoscopic surgery. We propose to use feature signatures, which can appropriately and concisely describe the content of laparoscopic images, and show that by using this content descriptor with an appropriate metric, we are able to efficiently perform content-based retrieval in laparoscopic videos. In a dataset with 600 captured static images from 33 hours recordings, we are able to find the correct video segment for more than 88% of these images.Feature signatures, as for instance investigated in the work of Beecks, 1 are a compact yet efficient way of describing the content of an image. They are obtained by clustering characteristic image features into a compact feature representation that adapts to individual image contents. In this paper, we propose to utilize feature signatures over a 7-dimensional feature space including position, color, and texture information for content-based retrieval in laparoscopic videos. To this end, we investigate different distance-based similarity measures including the Earth Mover's Distance, 2 the Signature Quadratic Form Distance, 3, 4 and the Signature Matching Distance. 5 Through a large evaluation with video data from 33 hours of laparoscopic surgery we show that the proposed signature-based approaches are able to efficiently perform content-based retrieval in laparoscopic videos. Description of PurposeIn endoscopic surgery, operating surgeons usually record video segments and capture static images during the operation, which they often need after the procedure. 6 However, while the static images can be used for later discussions with patients and colleagues, and can be easily integrated into operation reports, they lack of a complete and precise information, such as movements of operation instruments and the dynamics of performed actions. The recorded videos, on the other hand, contain all these important details, since they show exactly the same images that were visible on the monitors in the operation room, which were also used by the...

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Section: Description Of Purposementioning

confidence: 99%

Content-based retrieval in videos from laparoscopic surgery

Schoeffmann

Beecks

Lux

et al. 2016

Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling

View full text Add to dashboard Cite

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“…We have also shown that our dynamic extension of Feature Signatures (DFS) can achieve slightly better retrieval performance than static FS-which are known to work well for content-based retrieval in medical videos [8] -but cannot outperform HMG for our dataset. To the best of our knowledge, we are the first to focus on content similarity search in video archives of gynecologic laparoscopy, with the ultimate goal to support the surgical quality assessment process [11,22]. This work is only a first step in this domain, which would also benefit from semantic content classification approaches, which we want to investigate in the near future.…”

Section: Discussionmentioning

confidence: 99%

“…While many works have been proposed for the first two categories mentioned above, content similarity search for supporting surgical quality assessment has been addressed only sparsely in the literature so far. De facto standards for objective assessment methods are just starting to establish [10,22], and related research in this medical field is a niche area. However, it has been shown in recent work that manual post-hoc analysis of video recordings of laparoscopic surgeries can adequately categorize surgeons according to skill and training level.…”

Section: Related Workmentioning

confidence: 99%

“…The reasons behind are manifold -among some other motivations the videos are used for: (1) teaching purposes; e.g., to train surgery techniques with inexperienced surgeons, (2) post-operative explanations to the patients, (3) detailed visual information for follow-up surgeries, and (4) evidence in case of lawsuits from patients [34,43]. Another, more recently emerged purpose for usage of the recorded endoscopic video footage is surgical quality assessment (SQA) [10,22]. Through the recorded video the surgery can be revisited, the surgeon's level of skill can be assessed, and the video can be thoroughly checked for the occurrence of technical errors, which is especially important in medical endoscopy.…”

Section: Introductionmentioning

confidence: 99%

“…This situation could lead to inadvertent injuries as well as extensive complications. Therefore, surgeons are advised to revisit their video recordings of laparoscopic surgeries after the intervention and look for surgical errors in order to increase the subjective awareness and thereby improve patient safety [1,12,22].…”

Section: Introductionmentioning

confidence: 99%

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Video retrieval in laparoscopic video recordings with dynamic content descriptors

Schoeffmann

Husslein

Kletz

et al. 2017

Multimed Tools Appl

Self Cite

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In the domain of gynecologic surgery an increasing number of surgeries are performed in a minimally invasive manner. These laparoscopic surgeries require specific psychomotor skills of the operating surgeon, which are difficult to learn and teach. This is the reason why an increasing number of surgeons promote checking video recordings of laparoscopic surgeries for the occurrence of technical errors with surgical actions. This manual surgical quality assessment (SQA) process, however, is very cumbersome and timeconsuming when carried out without any support from content-based video retrieval. Appl (2018) 77:16813-16832 Descriptor) that can be effectively used to find similar segments in a laparoscopic video database and thereby help surgeons to more quickly inspect other instances of a given error scene. We evaluate the retrieval performance of MIDD with surgical actions from gynecologic surgery in direct comparison to several other dynamic content descriptors. We show that the MIDD descriptor significantly outperforms the state-of-the-art in terms of retrieval performance as well as in terms of runtime performance. Additionally, we release the manually created video dataset of 16 classes of surgical actions from medical laparoscopy to the public, for further evaluations.

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Analysis of the video motion tracking system “Kinovea” to assess surgical movements during robot‐assisted radical prostatectomy

Beulens

Namba

Brinkman

et al. 2020

Robotics Computer Surgery

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Backgrounds Robot‐assisted surgery facilitated the possibility to evaluate the surgeon's skills by recording and evaluating the robot surgical images. The aim of this study was to investigate the possibility of using a computer programme (Kinovea) for objective assessment of surgical movements in previously recorded in existing robot‐assisted radical prostatectomy (RARP) videos. Methods Twelve entire RARP procedures were analysed by a trained researcher using the computer programme “Kinovea” to perform semi‐automated assessment of surgical movements. Results Data analysis showed Kinovea was on average able to automatically assess only 22% of the total surgical duration per video of the robot‐assisted surgery. On average, it lasted 4 hours of continued monitoring by the researcher to assess one RARP using Kinovea. Conclusion Although we proved it is technically possible to use the Kinovea system in retrospective analysis of surgical movement in robot‐assisted surgery, the acquired data do not give a comprehensive enough analysis of the video to be used in skills assessment.

show abstract

The Generic Error Rating Tool: A Novel Approach to Assessment of Performance and Surgical Education in Gynecologic Laparoscopy

Cited by 37 publications

References 26 publications

Content-based retrieval in videos from laparoscopic surgery

Content-based retrieval in videos from laparoscopic surgery

Video retrieval in laparoscopic video recordings with dynamic content descriptors

Analysis of the video motion tracking system “Kinovea” to assess surgical movements during robot‐assisted radical prostatectomy

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