A systematic review of annotation for surgical process model analysis in minimally invasive surgery based on video

Abstract

Background

Annotated data are foundational to applications of supervised machine learning. However, there seems to be a lack of common language used in the field of surgical data science.

The aim of this study is to review the process of annotation and semantics used in the creation of SPM for minimally invasive surgery videos.

Methods

For this systematic review, we reviewed articles indexed in the MEDLINE database from January 2000 until March 2022. We selected articles using surgical video annotations to describe a surgical process model in the field of minimally invasive surgery. We excluded studies focusing on instrument detection or recognition of anatomical areas only. The risk of bias was evaluated with the Newcastle Ottawa Quality assessment tool. Data from the studies were visually presented in table using the SPIDER tool.

Results

Of the 2806 articles identified, 34 were selected for review. Twenty-two were in the field of digestive surgery, six in ophthalmologic surgery only, one in neurosurgery, three in gynecologic surgery, and two in mixed fields. Thirty-one studies (88.2%) were dedicated to phase, step, or action recognition and mainly relied on a very simple formalization (29, 85.2%). Clinical information in the datasets was lacking for studies using available public datasets. The process of annotation for surgical process model was lacking and poorly described, and description of the surgical procedures was highly variable between studies.

Conclusion

Surgical video annotation lacks a rigorous and reproducible framework. This leads to difficulties in sharing videos between institutions and hospitals because of the different languages used. There is a need to develop and use common ontology to improve libraries of annotated surgical videos.

Appendix: Risk of bias and the Newcastle–Ottawa quality assessment scale

Study	Selection	Outcome
	Ascertainment of exposure	Assessment of outcome
	Secure record (e.g., surgical records)	Independent blind assessment, record linkage
Blum et al. [32]	*	*
Bodenstedt et al. [19]	*	*
Bodenstedt et al. [20]	*	*
Cheng et al. [13]	*	*
Derathé et al. [16]	*	*
Dergachyova et al. [21]	*	*
Guedon et al. [31]	*	*
	*	*
Hashimoto et al. [14]	*	*
Huaulmé et al. [18]	*	*
Jalal et al. [56]	*	*
Jin et al. [22]	*	*
Katic et al. [37]	*	*
Khan et al. [11]	*	*
Kitugachi et al. [12]	*	*
Kitugachi et al. [29]	*	*
Pangal et al. [55]	*	*
Lalys et al. [39]	*	*
Lalys et al. [40]	*	*
Lecuyer et al. [23]	*	*
	*	*
Malpani et al. [30]	*	*
Mascagani et al. [38]	*	*
Mascagani et al. [41]	*	*
Meuwssen et al. [28]	*	*
Nespolo et al. [17]	*	*
Guerin et al. [56]	*	*
Quellec et al. [33]	*	*
Ramesh et al. [24]	*	*
Shi et al. [25]	*	*
	*	*
Twinanda et al. [26]	*	*
	*	*
Twinanda et al. [27]	*	*
	*	*
Yeh et al. [15]	*	*
Yu et al. [42]	*	*
Zhang et al. [35]	*	*
Zhang et al. [34]	*	*