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Monitoring Acupuncture Effects on Human Brain by fMRI

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Published on: April 8, 2010

Sample size estimation in acupuncture imaging research.

Yihao Zhou¹, Dongyan Wang², Xu Dong³

¹Second Clinical Medical College of Heilongjiang University of TCM, Harbin 150040, China. zyhacup@163.com.

Zhongguo Zhen Jiu = Chinese Acupuncture & Moxibustion

|January 8, 2024

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Accurate acupuncture imaging research requires adequate sample sizes. This review highlights issues with current methods and suggests statistically powered group sizes and data sharing for improved reliability.

Area of Science:

Neuroscience
Medical Imaging
Acupuncture Research

Background:

Sample size estimation in acupuncture imaging research is often subjective, impacting study reliability.
Preliminary results exist, but methodological rigor concerning sample size is lacking.
Insufficient sample sizes can lead to unreliable and inconclusive research outcomes.

Approach:

This article reviews current sample size estimation practices in acupuncture imaging.
It identifies limitations and proposes recommendations for future studies.
The review emphasizes statistical power and adaptive design methodologies.

Key Points:

Functional magnetic resonance imaging (fMRI) protocols require specific statistical power for sample sizes.
Group sizes of 12 are suggested for pilot studies, and 20-30 for confirmatory studies.

Keywords:

acupuncture functional magnetic resonance imaging (fMRI)imaging research sample size estimation

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Adaptive designs can dynamically adjust sample sizes based on accumulating data.

Conclusions:

Future acupuncture imaging research must prioritize statistically sound sample size estimations.
Establishing an open data-sharing platform will enhance data accessibility and research quality.
Implementing these recommendations will improve the overall impact and reliability of acupuncture imaging studies.