Multivariate decoding of cerebral blood flow measures in a clinical model of on‐going postsurgical pain

Abstract

Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pain. However, applications to date have focussed on acute experimental nociceptive stimuli rather than clinically relevant pain states. These reports have coincided with others describing the application of arterial spin labeling (ASL) to detect changes in regional cerebral blood flow (rCBF) in patients with on-going clinical pain. We combined these acquisition and analysis methodologies in a well-characterized postsurgical pain model. The principal aims were (1) to assess the classification accuracy of rCBF indices acquired prior to and following surgical intervention and (2) to optimise the amount of data required to maintain accurate classification. Twenty male volunteers, requiring bilateral, lower jaw third molar extraction (TME), underwent ASL examination prior to and following individual left and right TME, representing presurgical and postsurgical states, respectively. Six ASL time points were acquired at each exam. Each ASL image was preceded by visual analogue scale assessments of alertness and subjective pain experiences. Using all data from all sessions, an independent Gaussian Process binary classifier successfully discriminated postsurgical from presurgical states with 94.73% accuracy; over 80% accuracy could be achieved using half of the data (equivalent to 15 min scan time). This work demonstrates the concept and feasibility of time-efficient, probabilistic prediction of clinically relevant pain at the individual level. We discuss the potential of ML techniques to impact on the search for novel approaches to diagnosis, management, and treatment to complement conventional patient self-reporting. Hum Brain Mapp 36:633–642, 2015. © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Co-crystal of Tramadol–Celecoxib in Patients with Moderate to Severe Acute Post-surgical Oral Pain: A Dose-Finding, Randomised, Double-Blind, Placebo- and Active-Controlled, Multicentre, Phase II Trial

“…The extraction of two or more impacted third molars requiring bone removal is considered a gold standard model for measuring the efficacy of new medications in moderate to severe acute pain [ 14 ]. Although tramadol has been demonstrated to be more effective than placebo in acute moderate to severe pain models in several clinical trials [ 15 , 16 ], it has not always been so [ 17 ].…”

Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment

“…The data need to be split into ''training'' groups, used to obtain a provisional brain marker, and ''test'' groups, which evaluate predictive accuracy. Early ML studies in pain relied on single datasets (Brodersen et al, 2012;Marquand et al, 2010;O'Muircheartaigh et al, 2015), but more recent ones have drawn on multiple datasets that include a range of pain experiences both from healthy individuals (Wager et al, 2013) and those subjected to experimental models of pain (e.g., the capsaicin model of secondary hyperalgesia) and from patients (Duff et al, 2015). Robust regional networks modulated by analgesics can be identified using this approach from multiple studies and can be tested for utility as diagnostic, prognostic, predictive, and pharmacodynamic biomarkers.…”

Evidence against pain specificity in the dorsal posterior insula

“…Hopefully, these technical problems can be easily addressed (e.g., in future experiments) or challenged by an understanding of the field and its limitations (as Davis et al so eloquently do - see First and Second Arguments in their paper). What is still unclear is why Segerdahl and colleagues, seem to have overlooked considerable prior work using ASL in experimental pain 6 - 8 , post-surgical pain 9 - 11 , and chronic pain 12 - 16 . There is also a noticeable lack of consideration for the limitations of both the imaging technique and the experimental pain model 5 , which itself in healthy volunteers, has some issues relating to reproducibility and its clinical relevance 4 .…”