Multi-site study of surgical practice in neurosurgery based on surgical process models

Abstract

Surgical Process Modelling (SPM) was introduced to improve understanding the different parameters that influence the performance of a Surgical Process (SP). Data acquired from SPM methodology is enormous and complex. Several analysis methods based on comparison or classification of Surgical Process Models (SPMs) have previously been proposed. Such methods compare a set of SPMs to highlight specific parameters explaining differences between populations of patients, surgeons or systems. In this study, procedures performed at three different international University hospitals were compared using SPM methodology based on a similarity metric focusing on the sequence of activities occurring during surgery. The proposed approach is based on Dynamic Time Warping (DTW) algorithm combined with a clustering algorithm. SPMs of 41 Anterior Cervical Discectomy (ACD) surgeries were acquired at three Neurosurgical departments; in France, Germany, and Canada. The proposed approach distinguished the different surgical behaviors according to the location where surgery was performed as well as between the categorized surgical experience of individual surgeons. We also propose the use of Multidimensional Scaling to induce a new space of representation of the sequences of activities. The approach was compared to a time-based approach (e.g. duration of surgeries) and has been shown to be more precise. We also discuss the integration of other criteria in order to better understand what influences the way the surgeries are performed. This first multi-site study represents an important step towards the creation of robust analysis tools for processing SPMs. It opens new perspectives for the assessment of surgical approaches, tools or systems as well as objective assessment and comparison of surgeon's expertise.

Optimal Sub-Sequence Matching for the Automatic Prediction of Surgical Tasks

“…We can see that our approach outperforms the state-of-the-art Euclidean approach, regardless of the considered configuration. The compact dispersion of the results for the senior case (compared the junior case) suggests that seniors have a more homogeneous behavior than junior surgeons, which is consistent with previous studies comparing junior and senior practices [12]. This result also illustrates the influence of the set of available recordings in the quality of the prediction.…”

“…The Dynamic Time Warping (DTW) similarity measure [11] makes it possible to find the optimal alignment of two sequences (and thus register them) in Θ(l 1 · l 2 ) operations (with l 1 and l 2 the respective lengths of the realigned sequences). The consistency of this measure has been demonstrated for surgical processes in [12,13].…”

“…Optimal registration of a partial surgery: We propose a method to optimally register the on-going surgery (partial surgery) to any complete pre-recorded surgery. Our approach is based on the Dynamic Time Warping similarity measure [11], which is consistent with surgical processes [12]. 2.…”

Non-linear temporal scaling of surgical processes

“…Similarity measures for surgeries were first studied in [19]. Dynamic Time Warping (DTW) is based on the Levenshtein distance and was introduced for speech recognition in the 1970s [20] We recently demonstrated that Dynamic Time Warping is sound for surgical processes comparison [6,21]. DTW operates non-linear distortions on the time-axis, in order to find the best alignment of the two sequences.…”

Language-Based Process Phase Detection in the Trauma Resuscitation

“…To avoid the labor-intensive manual logging of human observations, sensors (including cameras, wearable sensors, and machine recordings) have been used for data collection. Tool usage recordings [5], medical equipment signals [6], medical event logs [4][7], body-worn sensors [3], and multimodal Kinect sensors [1] have previously provided input data for surgical phase detection. However, human language has been overlooked as an input data source for process modeling.…”