AI-Assisted Knee Infrared Imaging Based Acupuncture for Treating Knee Osteoarthritis: A Randomized Controlled Study Protocol

Abstract

Background: The variability in acupoint selection limits the standardization of acupuncture for knee osteoarthritis (KOA) and is one of the important factors affecting treatment efficacy. Recent advancements in artificial intelligence (AI) and infrared imaging provide opportunities to enhance the precision and standardization of acupuncture. Methods: This multicenter, single-blind, randomized controlled trial aims to evaluate whether AI-assisted personalized acupuncture is superior to traditional acupuncture and sham acupuncture in alleviating pain and improving joint function in patients with KOA. A total of 120 participants will be recruited from four hospitals in China and randomly assigned to three groups: the specific acupoint group (n=40), the conventional acupoint group (n=40), and the sham acupuncture group (n=40). All groups will receive acupuncture treatment twice a week for 8 weeks, with a total of 16 sessions. Outcome assessments will be conducted at baseline, week 8, and week 12. The AI system utilizes infrared imaging to identify heat-sensitive knee surface areas, and generates individualized acupoint prescriptions through internal decision analysis. Discussion: The primary outcomes are knee pain (Numeric Rating Scale, NRS) and function (WOMAC subscale). Secondary outcomes include knee pain and stiffness (Western Ontario and McMaster Universities Osteoarthritis Index subscale, WOMAC subscale), quality of life (Short Form 12, SF-12), knee range of motion, Traditional Chinese Medicine (TCM) clinical efficacy, and inflammatory indicators (IL-1β, IL-6, and TNF-α). This trial is expected to provide high-quality evidence for the clinical value and standardization of AI-assisted acupuncture. Trial Registration: This study has been registered with the Chinese Clinical Trial Registry (ChiCTR2400087106, July 19, 2024).