Clinical trial NCT05521126: Micro-Doppler Radar: A Gold Standard Comparison
Official title: The Use of Micro-Doppler Radar to Identify Service Members at Risk for Musculoskeletal Injury: A Gold Standard Comparison
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Musculoskeletal Injury
Anterior Cruciate Ligament Injuries
Keywords: musculoskeletal injury
anterior cruciate ligament injury
anterior cruciate ligament repair
micro-Doppler radar
motion capture
Lead sponsor: Milton S. Hershey Medical Center
Sponsor class: OTHER
Collaborators: name: United States Department of Defense
name: Lebanon Valley College
First posted: 2022-08-30
Enrollment: 250
Sex: ALL
Minimum age (years): 18
Maximum age (years): 40
Standard ages: ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: ACL repair cohort: Penn State Health Bone and Joint clinic

control cohort: Penn State University/College of Medicine students and employees, Lebanon Valley College students, community sample

Brief summary: The purpose of this study is to see if the study team can use micro-Doppler signal (MDS) technology to determine if someone has had an anterior cruciate ligament (ACL) reconstruction. The investigators will do this by comparing the movement data from a group of people who have had the surgery with a group who has not had the surgery to see if the micro-Doppler radar technology can accurately and predictably tell the difference.

Detailed description: The objective of this research is to validate that radar MDS can accurately and predictably differentiate individuals at high-risk for MSKI from those who are low risk. The investigators hypothesize that MDS will identify individuals at a high-risk for MSKI more accurately than the gold-standard MC technologies. To test this hypothesis, the investigators propose a case control study that will compare adults who have undergone ACL reconstruction to a control group of healthy adults that has not. Patients who have undergone ACL reconstruction have a 6-24% chance of either re-tearing their ACL or having a subsequent knee surgery on either side within two years of successful completion of surgery and post-surgical rehabilitation. Despite being released for full activities, little is known about what makes this group at high-risk for re-tear. As such, the investigators will use this patient population as a model for identifying an at-risk population for musculoskeletal injury (MSKI). The researchers will simultaneously collect radar micro-Doppler signals and biomechanical motion capture (MC) data in a state-of-the-art human movement lab. Participants will be asked to perform a series of functional activities that will be captured by both the MDS radar and MC systems. The data sets will then be analyzed independently.

Eligibility criteria: Inclusion Criteria:

High risk cohort

* age 18-40
* history of ACL reconstruction
* no current musculoskeletal injuries
* ACL repair between 9 and 24 months prior to recruitment

Control cohort

* age 18-40
* never had lower extremity surgery

Exclusion Criteria:

High risk cohort

* age \<18 or \>40
* pregnancy
* institutionalization
* history of cerebral vascular accident
* unable to provide informed consent
* inability to perform study activities
* history of hip or knee replacement
* inability to walk or jump without a limp
* current neuromuscular disease
* any surgery in the last 6 months

Control cohort

* age \< 18 or \> 40
* pregnancy
* institutionalization
* history of Cerebral Vascular Accident
* unable to provide informed consent
* inability to perform study activities
* history of knee or hip replacement
* inability to walk or jump without a limp
* current neuromuscular disease
* history of lower extremity surgery
* any surgery in the last 6 months

Primary outcomes:
measure: accuracy and predictability of MDS differentiation between ACL repair and control group
timeFrame: Day 1
Secondary outcomes:
measure: accuracy of MDS differentiation between ACL repair and control groups versus the motion capture system
timeFrame: Day 1
measure: ability of micro-Doppler radar and deep learning algorithms to automatically produce predictive data
timeFrame: Day 1
Other outcomes:
Locations:
city: Annville
country: United States
facility: Lebanon Valley College
state: Pennsylvania
city: Hershey
country: United States
facility: Pennsylvania State University College of Medicine
state: Pennsylvania
Study officials:
affiliation: Milton S. Hershey Medical Center
name: Cayce A Onks, DO, MS
role: PRINCIPAL_INVESTIGATOR
References: