Quantitative Texture and Blob Analyses on Patellar Tendon Sonographic Images of Collegiate Basketball Athletes

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Virginia Tech


Patellar Tendinopathy (PT), commonly called "Jumper's Knee", is a condition resulting from repetitive loading of the patellar tendon that presents as anterior knee pain, which is commonly seen in basketball players due to the maneuvers in the sport. Diagnosis of PT often involves a clinical exam followed by ultrasound images for confirmation of the diagnosis to look for key factors of PT. Clinical assessment of ultrasound images of tendons is subjective and requires a high level of experience for reliable interpretation. Thus, there is a need for objective, quantitative methods to assess tendon abnormalities associated with pathology. Ultrasound image texture analysis has emerged as a reliable technique to augment the utility of conventional US imaging, and has recently been shown to distinguish healthy from abnormal tendon and myofascial tissues. The objective of the present study was to conduct image texture analysis to evaluate patellar tendons of collegiate basketball athletes over two seasons. Under an IRB-approved protocol with informed consent, a total of 33 Division 1 collegiate basketball athletes (16 male, 17 female, age 19.9 +/- 1.4 years) underwent clinical evaluation and ultrasound imaging. Four imaging sessions were collected over the course of two years (pre- and post-season). Participants were imaged using a GE LOGIQ S8 (General Electric, USA) ultrasound machine equipped with ML6-15 linear probe. At each imaging session, power Doppler images were collected in the longitudinal and transverse axis, at the proximal, central, and distal regions of the patellar tendon of both knees. Image texture analysis was performed using a custom MATLAB (Mathworks, USA) program to obtain first order (mean, median, variance, skewness, kurtosis, entropy), second order (contrast, energy, and homogeneity), and blob analysis (blob count, BC, and blob area, BA, for 5%, 25%, 50%, 75%, and 95% thresholding values) texture parameters in each image, based upon borders manually drawn by a single researcher. Statistical analysis was conducted to compare imaging sessions (JMP Pro 16, SAS). P-values <0.05 were considered statistically significant. Quantitative texture parameters are able to distinguish characteristics in patellar tendon ultrasound images to distinguish between anatomic region, gender, dominance and pre- to post- season. The 25% and 75% thresholding percentiles effectively showed characteristics of collagen fibers in the patellar tendon. The abnormal diagnosis does not greatly effect texture parameters, which needs to be investigated with more incorporation of grading criteria distinctions and a larger sample size.



Ultrasound, Blob Analysis, Texture Analysis, Patellar Tendon