Abstract: Objective To evaluate the use of online self-learning application(APP) for precision teaching in joint diagnostic ultrasound. Methods Twelve sonographers were divided into three groups(4 in each) based on their experience in ultrasound diagnosis. At first, all of them were approached to the training courses in self-learning APP to study “the joint diagnostic ultrasound scoring system”. After that, they were admitted to “the ultrasound images assessment platform” in-APP to perform the ultrasound score on 140 small joints with inflammatory rheumatic diseases. The overall agreement rate(%) and intraclass correlation coefficients(ICC) values were calculated to analyze the assessment results among the three groups(%/ICC). A questionnaire survey was also administered at the end of the study via the APP to determine the ease of use of self-learning APP. Results A good interobserver agreement was reached among the three groups(65.2%～67.7%/0.49～0.97). In detail, the best interobserver results were found for the detection of Power Doppler Ultrasound(PDUS) synovitis(74.40%～81.70%/0.91～0.94) and tenosynovitis/paratenonitis in all joints(87.50%～93.80%/0.97～0.98). Good ICC values was found for the detection of Grayscale Ultrasound(GSUS) synovitis, but the agreement rate in this region was poor(45.10%～47.80%/0.58～0.74). For the presence or absence of erosions, moderate agreement rate was calculated, however, the ICC values among the three groups were poor(66.70%～77.80%/0.44～0.58). Regarding agreements in the finger joint regions, lower agreement results were found in both of MCP3(61.1%～71.3%) and PIP2/3 joints(57.4%～63.9%), and a variable agreement rates were found for wrist joints (64%～80%). The majority of survey respondents indicated favorable receptivity to the online self-learning APP(75%) including finding it helpful to improve the learning efficiency and interests (91.7%). Furthermore, a more accurate definition about the joint ultrasound score, standardization of image acquisition and adequate dynamic ultrasonography were advised to further improve interobserver agreements. Conclusions The online self-learning APP can be used as an effective tool in joint ultrasound training. A detailed analysis of the assessment results based on the feedback information from the trainees can help to further optimize and improve the teaching process to realize the precision teaching in joint diagnostic ultrasound.

Key words: ultrasonography, joint diagnostic ultrasound, ultrasound score, self-learning, precision teaching