A dilated causal convolutional model for surgical skill assessment using optical neuroimaging

Aseem Subedi; Fnu Rahul; Anirban Dutta; Jack Norfleet; Basiel Makled; Xavier R. Intes; Suvranu De

doi:10.1117/12.2610190

4 March 2022 A dilated causal convolutional model for surgical skill assessment using optical neuroimaging

Aseem Subedi, Fnu Rahul, Anirban Dutta, Jack Norfleet, Basiel Makled, Xavier R. Intes, Suvranu De

Proceedings Volume 11945, Clinical and Translational Neurophotonics 2022; 1194509 (2022) https://doi.org/10.1117/12.2610190
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Optical neuroimaging is a promising tool to assess motor skills execution. Especially, functional near-infrared spectroscopy (fNIRS) enables the monitoring of cortical activations in scenarios such as surgical task execution. fNIRS data sets are typically preprocessed to derive a few biomarkers that are used to provide a correlation between cortical activations and behavior. Meanwhile, Deep Learning methodologies have found great utility in the data processing of complex spatiotemporal data for classification or prediction tasks. Here, we report on a Deep Convolutional model that takes spatiotemporal fNIRS data sets as input to classify subjects performing a Fundamentals of Laparoscopic Surgery (FLS) task used in board certification of general surgeons in the United States. This convolutional neural network (CNN) uses dilated kernels paired with multiple stacks of convolution to capture long-range dependencies in the fNIRS time sequence. The model is trained in a supervised manner on 474 FLS trials obtained from seven subjects and assessed independently by stratified-10-fold cross-validation (CV). Results demonstrate that the model can learn discriminatory features between passed and failed trials, attaining 0.99 and 0.95 area under the Receiver Operating Characteristics (ROC) and Precision-Recall curves, respectively. The reported accuracy, sensitivity, and specificity are 97.7%, 81%, and 98.9%, respectively.

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Citation Download Citation

Aseem Subedi, Fnu Rahul, Anirban Dutta, Jack Norfleet, Basiel Makled, Xavier R. Intes, and Suvranu De "A dilated causal convolutional model for surgical skill assessment using optical neuroimaging", Proc. SPIE 11945, Clinical and Translational Neurophotonics 2022, 1194509 (4 March 2022); https://doi.org/10.1117/12.2610190

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