Pain management is a global challenge, due to the high prevalence, disabling effects, large medical burden, and unsatisfactory medication choices so far. With the opioid crisis for pain management emerging in the US in recent years and drug abuse in many other regions worldwide, various federal regulatory and oversight agencies have started to advise or mandate that healthcare systems and providers offer other treatment options for pain control. Acupuncture, which is green and safe, stands as the potential choice to fulfil these calls.
Acupuncture is an important component of traditional Chinese medicine. As an oriental ancient treatment technology, acupuncture has been practised for various disorders in East Asian counties for thousands of years. Now it is also gradually accepted for pain control in many other regions in the world, due to the accumulating high quality evidence supporting the use of it. However, the underlying scientific mechanisms of acupuncture for pain are not fully illustrated and the translational research from neural mechanisms to clinical applications are limited, which restricts its use for clinical practice in a wider range. In recent decades, with the development of advanced neuroimaging techniques (such as PET-CT, fMRI, EEG, MEG, fNIRS, etc.), acupuncture neuroimaging studies are increasing. These techniques allow us to see the human brain’s responses to acupuncture in vivo. Some researchers have also combined innovative research strategies such as machine learning (ML) with neuroimaging techniques, which could not only assist in diagnosing diseases but also help predict acupuncture treatment outcomes.
Therefore, in this context, researchers are welcome to contribute original, as well as in-depth review articles, to this Research Topic that may improve our understanding of the use of acupuncture for pain management. We are particularly interested in articles combining innovative strategies such as machine learning to evaluate the molecular and neuroimaging mechanisms of acupuncture treatment for pain, in order to facilitate translational research from neural mechanisms to clinical applications of acupuncture for pain management.
Potential topics include but are not limited to the following:
- Neuroimaging mechanisms involved in pain modulation of acupuncture
- Innovative techniques, such as machine learning, combing neuroimaging and genetics/biochemical indicators, or clinical features of acupuncture for pain
- Narrative and systematic reviews of acupuncture for pain management
Pain management is a global challenge, due to the high prevalence, disabling effects, large medical burden, and unsatisfactory medication choices so far. With the opioid crisis for pain management emerging in the US in recent years and drug abuse in many other regions worldwide, various federal regulatory and oversight agencies have started to advise or mandate that healthcare systems and providers offer other treatment options for pain control. Acupuncture, which is green and safe, stands as the potential choice to fulfil these calls.
Acupuncture is an important component of traditional Chinese medicine. As an oriental ancient treatment technology, acupuncture has been practised for various disorders in East Asian counties for thousands of years. Now it is also gradually accepted for pain control in many other regions in the world, due to the accumulating high quality evidence supporting the use of it. However, the underlying scientific mechanisms of acupuncture for pain are not fully illustrated and the translational research from neural mechanisms to clinical applications are limited, which restricts its use for clinical practice in a wider range. In recent decades, with the development of advanced neuroimaging techniques (such as PET-CT, fMRI, EEG, MEG, fNIRS, etc.), acupuncture neuroimaging studies are increasing. These techniques allow us to see the human brain’s responses to acupuncture in vivo. Some researchers have also combined innovative research strategies such as machine learning (ML) with neuroimaging techniques, which could not only assist in diagnosing diseases but also help predict acupuncture treatment outcomes.
Therefore, in this context, researchers are welcome to contribute original, as well as in-depth review articles, to this Research Topic that may improve our understanding of the use of acupuncture for pain management. We are particularly interested in articles combining innovative strategies such as machine learning to evaluate the molecular and neuroimaging mechanisms of acupuncture treatment for pain, in order to facilitate translational research from neural mechanisms to clinical applications of acupuncture for pain management.
Potential topics include but are not limited to the following:
- Neuroimaging mechanisms involved in pain modulation of acupuncture
- Innovative techniques, such as machine learning, combing neuroimaging and genetics/biochemical indicators, or clinical features of acupuncture for pain
- Narrative and systematic reviews of acupuncture for pain management
