Machine Learning Algorithms Provide Greater Prediction of Response to Scs Than Lead Screening Trial: A Predictive AI-Based Multicenter Study

Abstract

Persistent Pain after Spinal Surgery can be successfully addressed by Spinal Cord Stimulation (SCS). International guidelines strongly recommend that a lead trial be performed before any permanent implantation. Recent clinical data highlight some major limitations of this approach. First, it appears that patient outcomes, WITH OR WITHOUT lead trial, are similar. In contrast, during trialing, infection rate drops drastically within time and can compromise the therapy. Using composite pain assessment experience and previous research, we hypothesized that ma-chine learning models could be robust screening tools and reliable predictors of long-term SCS efficacy. We developed several algorithms including logistic regression, Regularized Logistic Regression (RLR), naive Bayes classifier, artificial neural networks, random forest and gradient boosted trees to test this hypothesis and to perform internal and external validations, the objec-tive being to confront model predictions with lead trial results using a 1-year composite out-come from 103 patients. While almost all models have demonstrated superiority on lead trial-ing, the RLR model appears to represent the best compromise between complexity and inter-pretability in prediction of SCS efficacy. These results underscore the need to use AI based-predictive medicine, as a synergistic mathematical approach, aimed at helping implanters to optimize their clinical choices on daily practice.

Study on Automatic Multi-Classification of Spine Based on Deep Learning and Postoperative Infection Screening

“…Traditional machine learning algorithms mainly include two steps: feature extraction and classification. In the part of feature extraction, this study selects five most advanced global algorithms for texture representation, namely local binary patterns (LBPs) [ 2 ], local phase quantization (LPQ) [ 12 ], gray-level co-occurrence matrix (GLCM) [ 3 ], histogram of oriented gradient (HOG), and oriented fast and rotated brief (ORB) [ 4 ]. The feature dimensions of the five feature descriptors are shown in Table 3 .…”

“…The second type is the automatic segmentation or grading research directly based on the intervertebral foramen. Reference [ 11 ] realized the segmentation by detecting the center line of the vertebral body and the main boundary points of the intervertebral foramen; [ 12 ] used the AdaBoost detection algorithm and iterative normalization segmentation algorithm to detect MRI vertebral body images and locate and segment them at the same time; [ 13 ] realized the modeling and segmentation of spine and intervertebral foramen based on two scales by representing the global spine shape in a continuous local vertebral coordinate system and modeling the individual vertebrae as a triangular surface network; [ 14 ] used the super-pixel segmentation method to achieve an accuracy of 98.52% in the image location and benign and malignant classification of intervertebral foramen stenosis.…”

Patient Selection for Spinal Cord Stimulation in Treatment of Pain: Sequential Decision-Making Model — A Narrative Review

“…Recently, it was proposed that machine algorithms be used to predict response to SCS, based on clinical outcomes from 103 implanted patients. 53 , 54 The authors found that the sensitivity of the screening trial was greater than the machine-learning model (100% vs 83.3%), while specificity was significantly lower for the screening trial than the machine learning trial (33.3% vs 66.7%). Machine-learning and statistical models could be considered in future trials to delineate SCS-screening trial utility.…”

A Comprehensive Review of Pain Interference on Postural Control: From Experimental to Chronic Pain

“…Chronic pain is defined by the International Association for Study of Pain (IASP) as « an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage » [1] lasting more than 3 months [2]. By affecting more than 30% of population worldwide [3], chronic pain leads to economic burden and has dramatic impact on biological, psychological, sociological factors resulting in poor quality of life [4][5][6]. While medical care focused in pain perception, psychological and functional disability should be considered [6].…”

“…By affecting more than 30% of population worldwide [3], chronic pain leads to economic burden and has dramatic impact on biological, psychological, sociological factors resulting in poor quality of life [4][5][6]. While medical care focused in pain perception, psychological and functional disability should be considered [6]. It has been clearly demonstrated that pain interferes with sensorimotor control [7][8][9][10][11], and more especially with postural control [12][13][14][15][16][17][18][19][20].…”