Objective

2

To screen the population for acupuncture treatment of neck pain

using functional magnetic resonance imaging (fMRI) technology and based on machine learning algorithms.

Methods

2

Eighty patients with neck pain were recruited. Using FPX25 handheld pressure algometer

the tender points were detected in the areas with high-frequent onset of neck pain and high degree of acupoint sensitization. Acupuncture was delivered at 4 tender points with the lowest pain threshold

once every two days; and the treatment was given 3 times a week and for 2 consecutive weeks. The amplitude of low-frequency fluctuation (ALFF) of the brain before treatment was taken as a predictive feature to construct support vector machine (SVM)

logistic regression (LR)

and K-nearest neighbors (KNN) models to predict the responses of neck pain patients to acupuncture treatment. A longitudinal analysis of the ALFF features was performed before and after treatment to reveal the potential biological markers of the reactivity to the acupuncture therapy.

Results

2

The SVM model could successfully distinguish high responders (48 cases) and low responders (32 cases) to acupuncture treatment

and its accuracy rate reached 82.5%. Based on the SVM model

the ALFF values of 4 brain regions were identified as the consistent predictive features

including the right middle temporal gyrus

the right superior occipital gyrus

and the bilateral posterior cingulate gyrus. In the patients with high acupuncture response

the ALFF value in the left posterior cingulate gyrus decreased after treatment (

P

<

0.05)

whereas in the patients with low acupuncture response

the ALFF value in the right superior occipital gyrus increased after treatment (

P

<

0.01). The longitudinal functional connectivity (FC) analysis found that compared with those before treatment

t

he high responders showed the enhanced FC after treatment between the left posterior cingulate gyrus and various regions

including the bilateral Crus1 of the cerebellum

the right insula

the bilateral angular gyrus

the left medial superior frontal gyrus

and the left middle cingulate gyrus (GRF: corrected

voxel level:

P

<

0.05

mass level:

P

<

0.05). In contrast

the low responders exhibited the enhanced FC between the left posterior cingulate gyrus and the left Crus2 of the cerebellum

the left middle temporal gyrus

the right posterior cingulate gyrus

and the left angular gyrus; besides

FC was reduced in low responders between the left posterior cingulate gyrus and the right supramarginal gyrus (GRF: corrected

voxel level:

P

<

0.05

mass level:

P

<

0.05).

Conclusion

2

This study validates the practicality of pre-treatment ALFF feature prediction for acupuncture efficacy on neck pain. The therapeutic effect of acupuncture on neck pain is potentially associated with its impact on the default mode network

and then

alter the pain perception and emotional regulation.