Simulated outcomes for durotomy repair in minimally invasive spine surgery

Minimally invasive spine surgery (MISS) is increasingly performed using endoscopic and microscopic visualization, and the captured video can be used for surgical education and development of predictive artificial intelligence (AI) models. Video datasets depicting adverse event management are also va...

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Bibliographic Details
Published inScientific data Vol. 11; no. 1; p. 62
Main Authors Balu, Alan, Kugener, Guillaume, Pangal, Dhiraj J., Lee, Heewon, Lasky, Sasha, Han, Jane, Buchanan, Ian, Liu, John, Zada, Gabriel, Donoho, Daniel A.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 10.01.2024
Nature Publishing Group
Nature Portfolio
Subjects
692/308
692/308/2778
692/700
Artificial Intelligence
Back surgery
Bone surgery
Cadavers
Data Descriptor
Educational Status
Humanities and Social Sciences
Humans
Models, Anatomic
multidisciplinary
Neurosurgery
Prediction models
Science
Science (multidisciplinary)
Spine - surgery
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Summary:Minimally invasive spine surgery (MISS) is increasingly performed using endoscopic and microscopic visualization, and the captured video can be used for surgical education and development of predictive artificial intelligence (AI) models. Video datasets depicting adverse event management are also valuable, as predictive models not exposed to adverse events may exhibit poor performance when these occur. Given that no dedicated spine surgery video datasets for AI model development are publicly available, we introduce Simulated Outcomes for Durotomy Repair in Minimally Invasive Spine Surgery (SOSpine). A validated MISS cadaveric dural repair simulator was used to educate neurosurgery residents, and surgical microscope video recordings were paired with outcome data. Objects including durotomy, needle, grasper, needle driver, and nerve hook were then annotated. Altogether, SOSpine contains 15,698 frames with 53,238 annotations and associated durotomy repair outcomes. For validation, an AI model was fine-tuned on SOSpine video and detected surgical instruments with a mean average precision of 0.77. In summary, SOSpine depicts spine surgeons managing a common complication, providing opportunities to develop surgical AI models.
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-023-02744-5