Literature DB >> 28884750

Brain imaging tests for chronic pain: medical, legal and ethical issues and recommendations.

Karen D Davis1,2,3, Herta Flor4, Henry T Greely5, Gian Domenico Iannetti6, Sean Mackey7, Markus Ploner8, Amanda Pustilnik9,10, Irene Tracey11, Rolf-Detlef Treede12, Tor D Wager13,14.   

Abstract

Chronic pain is the greatest source of disability globally and claims related to chronic pain feature in many insurance and medico-legal cases. Brain imaging (for example, functional MRI, PET, EEG and magnetoencephalography) is widely considered to have potential for diagnosis, prognostication, and prediction of treatment outcome in patients with chronic pain. In this Consensus Statement, a presidential task force of the International Association for the Study of Pain examines the capabilities of brain imaging in the diagnosis of chronic pain, and the ethical and legal implications of its use in this way. The task force emphasizes that the use of brain imaging in this context is in a discovery phase, but has the potential to increase our understanding of the neural underpinnings of chronic pain, inform the development of therapeutic agents, and predict treatment outcomes for use in personalized pain management. The task force proposes standards of evidence that must be satisfied before any brain imaging measure can be considered suitable for clinical or legal purposes. The admissibility of such evidence in legal cases also strongly depends on laws that vary between jurisdictions. For these reasons, the task force concludes that the use of brain imaging findings to support or dispute a claim of chronic pain - effectively as a pain lie detector - is not warranted, but that imaging should be used to further our understanding of the mechanisms underlying pain.

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Year:  2017        PMID: 28884750     DOI: 10.1038/nrneurol.2017.122

Source DB:  PubMed          Journal:  Nat Rev Neurol        ISSN: 1759-4758            Impact factor:   42.937


  75 in total

1.  Progress in pain medicine: where are we now?

Authors:  Lesley A Colvin; Andrew S C Rice
Journal:  Br J Anaesth       Date:  2019-06-04       Impact factor: 9.166

2.  Identifying brain regions associated with the neuropathology of chronic low back pain: a resting-state amplitude of low-frequency fluctuation study.

Authors:  Binlong Zhang; Minyoung Jung; Yiheng Tu; Randy Gollub; Courtney Lang; Ana Ortiz; Joel Park; Georgia Wilson; Jessica Gerber; Ishtiaq Mawla; Suk-Tak Chan; Ajay Wasan; Robert Edwards; Jeungchan Lee; Vitaly Napadow; Ted Kaptchuk; Bruce Rosen; Jian Kong
Journal:  Br J Anaesth       Date:  2019-04-01       Impact factor: 9.166

3.  Developing Improved Translational Models of Pain: A Role for the Behavioral Scientist.

Authors:  Sarah L Withey; David R Maguire; Brian D Kangas
Journal:  Perspect Behav Sci       Date:  2020-01-03

Review 4.  Recent advances in objectifying pain using neuroimaging techniques.

Authors:  J Archibald; F M Warner; O Ortiz; M Todd; C R Jutzeler
Journal:  J Neurophysiol       Date:  2018-05-16       Impact factor: 2.714

Review 5.  Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment.

Authors:  Irene Tracey; Clifford J Woolf; Nick A Andrews
Journal:  Neuron       Date:  2019-03-06       Impact factor: 17.173

Review 6.  Employing pain and mindfulness to understand consciousness: a symbiotic relationship.

Authors:  Joshua A Grant; Fadel Zeidan
Journal:  Curr Opin Psychol       Date:  2019-01-09

Review 7.  Neuroimaging of Pain: Human Evidence and Clinical Relevance of Central Nervous System Processes and Modulation.

Authors:  Katherine T Martucci; Sean C Mackey
Journal:  Anesthesiology       Date:  2018-06       Impact factor: 7.892

8.  XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes.

Authors:  Byungjoo Noh; Changhong Youm; Eunkyoung Goh; Myeounggon Lee; Hwayoung Park; Hyojeong Jeon; Oh Yoen Kim
Journal:  Sci Rep       Date:  2021-06-09       Impact factor: 4.379

Review 9.  Representation, Pattern Information, and Brain Signatures: From Neurons to Neuroimaging.

Authors:  Philip A Kragel; Leonie Koban; Lisa Feldman Barrett; Tor D Wager
Journal:  Neuron       Date:  2018-07-25       Impact factor: 17.173

10.  Threat Prediction from Schemas as a Source of Bias in Pain Perception.

Authors:  Manyoel Lim; Christopher O'Grady; Douglas Cane; Amita Goyal; Mary Lynch; Steven Beyea; Javeria Ali Hashmi
Journal:  J Neurosci       Date:  2020-01-02       Impact factor: 6.167

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