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International Journal of Computer Assisted Radiology and Surgery

Erschienen in:

18.05.2017 | Original Article

The minimally acceptable classification criterion for surgical skill: intent vectors and separability of raw motion data

verfasst von: Rodney L. Dockter, Thomas S. Lendvay, Robert M. Sweet, Timothy M. Kowalewski

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 7/2017

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Abstract

Purpose

Minimally invasive surgery requires objective methods for skill evaluation and training. This work presents the minimally acceptable classification (MAC) criterion for computational surgery: Given an obvious novice and an obvious expert, a surgical skill evaluation classifier must yield 100% accuracy. We propose that a rigorous motion analysis algorithm must meet this minimal benchmark in order to justify its cost and use.

Methods

We use this benchmark to investigate two concepts: First, how separable is raw, multidimensional dry laboratory laparoscopic motion data between obvious novices and obvious experts? We utilized information theoretic techniques to analytically address this. Second, we examined the use of intent vectors to classify surgical skill using three FLS tasks.

Results

We found that raw motion data alone are not sufficient to classify skill level; however, the intent vector approach is successful in classifying surgical skill level for certain tasks according to the MAC criterion. For a pattern cutting task, this approach yields 100% accuracy in leave-one-user-out cross-validation.

Conclusion

Compared to prior art, the intent vector approach provides a generalized method to assess laparoscopic surgical skill using basic motion segments and passes the MAC criterion for some but not all FLS tasks.

Vorheriger Artikel Hand-eye calibration for surgical cameras: a Procrustean Perspective-n-Point solution

Nächster Artikel Predicting surgical skill from the first N seconds of a task: value over task time using the isogony principle

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Titel: The minimally acceptable classification criterion for surgical skill: intent vectors and separability of raw motion data
verfasst von: Rodney L. Dockter
Thomas S. Lendvay
Robert M. Sweet
Timothy M. Kowalewski
Publikationsdatum: 18.05.2017
Verlag: Springer International Publishing
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 7/2017
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-017-1610-9

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Abstract

Purpose

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Conclusion

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