Sample size estimation in acupuncture imaging research. / æ ·æœ¬é‡ä¼°ç®—åœ¨é’ˆç¸å½±åƒå­¦ç ”ç©¶ä¸­çš„åº”ç”¨ä¸Žæ€è€ƒ.

ABSTRACT

The size of the sample significantly impacts the accuracy of research outcomes. While preliminary results have been achieved in acupuncture imaging research, sample size estimation is often subjective and arbitrary, leading to insufficient reliability of study results. This article reviews the current application of sample size estimation in acupuncture imaging research, and provides recommendations to address existing issues. It is suggested that future researches should include the sample sizes that meet statistical power based on the characteristics of functional magnetic resonance imaging (fMRI) protocols, with group sizes of 12 and 20-30 cases having become the "minimum requirement" for confirmatory studies and a common choice. Additionally, the adoption of adaptive design approaches, which dynamically adjust sample sizes based on accumulated data, can be considered. Furthermore, efforts should be made to establish an open platform for sharing acupuncture imaging data to enhance data accessibility, and consequently, improve the quality and overall impact of acupuncture imaging research.