Structural brain connectivity predicts early acute pain after mild traumatic brain injury

Paulo Branco, Noam Bosak, Jannis Bielefeld, Olivia Cong, Yelena Granovsky, Itamar Kahn, David Yarnitsky, A. Vania Apkarian*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Mild traumatic brain injury (mTBI), is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute postinjury pain is important because it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6 months after the collision still predicted mTBI pain at that timepoint (n = 36). These white matter connections were associated with 2 nociceptive psychophysical outcomes tested at a remote body site - namely, conditioned pain modulation and magnitude of suprathreshold pain - and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

Original languageEnglish (US)
Pages (from-to)1312-1320
Number of pages9
JournalPain
Volume164
Issue number6
DOIs
StatePublished - Jun 1 2023

Keywords

  • Acute pain
  • Diffusion tensor imaging
  • Mild traumatic brain injury
  • Pain sensitivity
  • Whiplash

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Anesthesiology and Pain Medicine

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