Ultrasound Imaging of the Superficial Fascial System Can Predict the Subcutaneous Strength of Abdominal Tissue Using Mean Gray Value Quantification

Background: This study is the first to correlate sonographic findings of subcutaneous tissue to structural and biomechanical properties. Methods: Precisely sized tissue specimens (59 samples) were collected from five abdominoplasty procedures. A Philips Lumify L12-4 linear array probe, connected to an Android tablet, was used to obtain ultrasound images of the superficial fascial system. A no. 1 Vicryl suture on a CTX needle placed though a needle guide within a three-dimensionally printed template ensured equal bites of subcutaneous tissue across specimens. Suture pull-out strength was measured until failure at a displacement rate of 2.12 mm/second using an Admet MTEST Quattro. Mean gray value for the superficial fascial system in associated ultrasonographic images was quantified by CellProfiler. Results: Superficial fascial system visualization can be accomplished using high-resolution portable ultrasound. Comparing multiple specimens' imaging, interpatient and intrapatient variability of superficial fascial system quantity and structural characteristics are apparent. The superficial fascial system is highly abundant in some patients, but has limited presence in others. Individual-specimen mean gray value and whole-patient mean gray value positively correlated with tissue tensile strength (p = 0.006) and patient-average tissue tensile strength (p = 0.036), respectively. Whole-patient mean gray value accounted for 98.5 percent of the variance seen in patient-average tensile strength, making it a strong predictor for tensile strength. Conclusions: Portable ultrasound and image-processing technology can visualize, quantify, and predict subcutaneous tissue strength of the superficial fascial system. The superficial fascial system quantity correlates with suture tensile strength. Clinically, preoperative superficial fascial system quantification may aid in outcome predictions, manage patient expectations, and potentially lower complication rates.