Primary Objective:

To explore changes in shear wave elastography (SWE) and microvascular flow imaging (MFI) measurements from time of injury through the recovery phase of lower extremity musculoskeletal injuries to determine if a correlation exists with functional impairment.

Secondary Objective:

To develop a deep learning AI system for automated region of interest (ROI) determination for measurement of average SWE and MFI.

Methodology:

Eligible subjects with lower extremity injuries will undergo SWE and MFI measurements and complete the Lower Extremity Functional Scale questionnaire at each study visit. Clinical data related to the evaluation of the injury acquired during standard medical care of the injury will be collected from the patients' medical record such as CT or MRI scans, X-rays, physical exams and tests as well as laboratory measurements. Subjects will undergo serial SWE and MFI imaging throughout their rehabilitation episode of care to assess changes over time, status in rehabilitation and comparison to the contralateral extremity.

Inclusion Criteria:

• Subjects age 18 - 89 years;
• Able to sign an informed consent document;
• Suspected MSK injury of the lower extremity (i.e. hamstring injuries and soft tissue injuries involving the ankle).

Exclusion Criteria:

• Prior fasciotomy of same limb;
• Hemodialysis grafts of involved extremity;
• Extremity wounds preventing ultrasound imaging.

All SWE and MFI images are evaluated for quality and analyzed by qualified study physicians that are blinded to the clinical data. The analysis includes but is not limited to reading images, identifying the regions of interest, and making measurements. Clinical data will then be reviewed to validate the clinical diagnosis.