A New Quantitative Tool for the Ultrasonographic Assessment of Tendons: A Reliability and Validity Study on the Patellar Tendon

Abstract

Ultrasound is widely used for tendon assessment due to its safety, affordability, and portability, but its subjective nature poses challenges. This study aimed to develop a new quantitative analysis tool based on artificial intelligence to identify statistical patterns of healthy and pathological tendons. Furthermore, we aimed to validate this new tool by comparing it to experts’ subjective assessments. A pilot database including healthy controls and patients with patellar tendinopathy was constructed, involving 14 participants with asymptomatic (n = 7) and symptomatic (n = 7) patellar tendons. Ultrasonographic images were assessed twice, utilizing both the new quantitative tool and the subjective scoring method applied by an expert across five regions of interest. The database contained 61 variables per image. The robustness of the clinical and quantitative assessments was tested via reliability analyses. Lastly, the prediction accuracy of the quantitative features was tested via cross-validated generalized linear mixed-effects logistic regressions. These analyses showed high reliability for quantitative variables related to “Bone” and “Quality”, with ICCs above 0.75. The ICCs for “Edges” and “Thickness” varied but mostly exceeded 0.75. The results of this study show that certain quantitative variables are capable of predicting an expert’s subjective assessment with generally high cross-validated AUC scores. A new quantitative tool for the ultrasonographic assessment of the tendon was designed. This system is shown to be a reliable and valid method for evaluating the patellar tendon structure.

Keywords

• mathematical modeling
• psychometric properties
• quantification
• tendinopathy
• texture analysis
• ultrasound