Acoustic Emission Biomarkers for the Detection and Monitoring of Early Knee Osteoarthritis

Osteoarthritis, Knee Clinical Trial

Official title:

Acoustic Emission Biomarkers for the Detection and Monitoring of Early Knee Osteoarthritis

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT06351059
• Other study ID #: UE-0083
• Status: Active, not recruiting
• Start date: January 1, 2023
• Est. completion date: December 31, 2024

Study information

• Verified date: April 2024
• Source: Schulthess Klinik
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The aim of this exploratory study is to further investigate the potential of acoustic emission biomarkers, assessed by the inmodi knee brace, to diagnose osteoarthritis (OA) at earlier stages. Therefore, 20 healthy participants and 100 patients with increased risk of knee OA will be recruited from the Schulthess Klinik in Zurich and examined twice with 9 ± 3 months' time interval. Anthropometric data, EOS radiographs and MR images of both knees, PROMs and acoustic emission data will be collected and evaluated. Artificial Intelligence algorithm will then be used to identify and validate the most promising acoustic emission biomarkers with a prognosis value in the prediction of knee osteoarthritis progress.

Description:

Disease background Osteoarthritis (OA) is a highly prevalent and disabling condition that affects over 7% of people globally (528 million people). It is significantly limiting their mobility and independent lifestyle. OA is mainly described by loss of cartilage, structural changes in bone, and inflammation of the synovium and joint capsule. Common risk factors include aging, obesity, prior joint injury and overuse. OA takes several years to develop, before the patient sees the doctor when pain intensifies. In early stages patients are asymptomatic or only experience activity related pain. The pain becomes constant over time with intermittent intense pain episodes. In regions around the world, the average annual cost of OA for an individual is estimated between USD $700-$15,600 (2019). Consequently, OA has a large socioeconomic impact due to its high medical costs, early retirements, and high absenteeism from work. OA typically affects the hips, knees, hands, feet, and spine, with a high prevalence of polyarticular involvement. This study focuses on OA of the knee. Current standard of assessment The current gold-standard assessment of the severity of knee OA is based on plain radiography, using the Kellgren-Lawrence (KL) grading system, which was accepted as a standard by the World Health Organization in 1961. This system does not evaluate the primary affected tissue - cartilage - but only the overall aspect of the joint. It is therefore unable to detect early stages of OA and the diagnosis is often established at a late stage, with few treatment options besides knee arthroplasty. Alternative assessment methods Earlier diagnostic and improved patient stratification is required to deploy preventive OA treatments. Possible early diagnostic options include Magnetic Resonance Imaging (MRI) and biochemical markers. MRI can be used to assess changes in cartilage volume, thickness or even quality, however, widespread use of MRI is limited by its high cost, availability, and the absence of a validated international score. Many biochemical markers are currently under investigation, but so far they lack specificity to joint tissues and to particular joints, and sensitivity and specificity are still not high enough for widespread clinical use. Recently, there has been a growing interest in acoustic analysis as an alternative to conventional biomarkers, particularly for the knee joint where poorly lubricated moving joint surfaces generate abnormal sounds that acoustic analysis could reveal. Relevance of the project The inmodi knee brace, developed at the ETH Lausanne is a device designed for an in-motion knee health assessment. Its core technology combines acoustic, thermal, and kinematic sensors and an artificial intelligence (AI)-based data analysis to extract relevant biomarkers of joint function. Preliminary data suggests that this combined approach may enable a non-invasive early diagnosis of OA. In horses, a strong association was found between the joint condition and the power of acoustic emission (AE) signals analysed. Combination of data (acoustic data/motion data) contains likely more information about the knee functional health, but such data is very heavy (computationally) and an algorithmic approach like AI seems the best option to extract meaningful parameters and combine them into clinically useful biomarkers. Recently, the investigators tested a prototype of inmodi knee brace in seventeen patients from the clinic shortly before total knee arthroplasty (TKA). These patients suffered from severe OA on the leg undergoing surgery and mild to moderate on the contralateral one. A machine learning algorithm was able to discriminate the leg states with a specificity of 0.96 (perfect = 1). The aim of this new project is to further explore the potential of the inmodi system to diagnose OA at earlier stages. For this the investigators will develop a preliminary reference database in a subpopulation at risk of developing OA. The identification and validation of novel biomarkers with an AI algorithm requires a training dataset and a test dataset, both with potential biomarkers and gold standard clinical outcomes for validation. This database will require a sample size large enough to be statistically sound to prevent statistical overfitting. Non-invasive knee health diagnostics should help identifying patients at risk at a relatively low cost and without radiation exposure and enable preventive measures to be implemented earlier than with standard radiographic measures. Risk category A (minimal): Imaging procedures contain (1) MRI of both knees, which is non-ionizing and (2) EOS full leg scan with much lower radiation dose of conventional radiography. Another procedure is the functional test with the inmodi knee brace of both legs. The probability that a biological effect on cells will occur from x-ray radiation is very low. Other risks are psychological, related to "screening overdiagnosis", or claustrophobic stress and noise discomfort in the MRI scanner. Further there is a risk on data privacy, which the investigators try to minimize by following the legal and internal data protection rules.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 120
• Est. completion date: December 31, 2024
• Est. primary completion date: July 31, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 35 Years to 75 Years

Eligibility

Inclusion Criteria:

• Group A: persons judging themselves to be of good subjective health without any knee problems, aged 35-65 years
• Groups B&C: participant in MAC registry, completed patient reported-outcome measurements (PROM) questionnaires at 2y or 5y within the last 6 months, aged 35-65 years, unilateral knee surgery (another side as internal control), B1/C1: the normal group is defined as patients closely around the median COMI scores of their respective group (determined medians are: 2yr females: 0.9 / 2yr males: 0.7 / 5yr females: 0.5 / 5yr males: 0.5), B2/C2: the poor outcomes group consists of patients with scores = 2.
• Group D: patient booked for TKA due to severe OA, aged 35-75 years

Exclusion Criteria:

• inability to give consent or follow procedures
• no understanding of German language
• open wounds or tissue injuries
• irritated or infected sections on the limbs
• Class II obesity defined by Body Mass Index (BMI) = 35 kg/m2 (comorbidities associated with obesity should be investigated in future studies)
• uncooperative patients who disregard or cannot follow instructions, including those who abuse drugs and/or alcohol
• Pregnant or with intention to get pregnant (x-rays)
• Current address outside of Switzerland
• Groups B&C: revision surgeries at the operated knee, death, known pathologies or former injuries of the comparator knee

Related Conditions & MeSH terms

• Diagnosis
• Osteoarthritis
• Osteoarthritis, Knee

Intervention

Diagnostic Test:
• InModi acoustic emission analysis
All diagnosis tests

Locations

Country	Name	City	State
Switzerland	Schulthess Klinik	Zürich	ZH

Sponsors (2)

Lead Sponsor	Collaborator
Schulthess Klinik	Ecole Polytechnique Fédérale de Lausanne

Country where clinical trial is conducted

Switzerland, 

References & Publications (8)

Bahador N, Pfeifle J, Thevenot J, et al. Evaluating the Potential of Novel Biomarkers for Characterizing Deviation of Acoustic Dynamics from Self-similarity in Osteoarthritic Knees (Manuscript in preparation). Published online 2021.

Eckstein F, Wirth W. Quantitative cartilage imaging in knee osteoarthritis. Arthritis. 2011;2011:475684. doi: 10.1155/2011/475684. Epub 2010 Dec 8. — View Citation

Kalo K, Niederer D, Stief F, Wurzberger L, van Drongelen S, Meurer A, Vogt L. Validity of and recommendations for knee joint acoustic assessments during different movement conditions. J Biomech. 2020 Aug 26;109:109939. doi: 10.1016/j.jbiomech.2020.109939. Epub 2020 Jul 8. — View Citation

KELLGREN JH, LAWRENCE JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957 Dec;16(4):494-502. doi: 10.1136/ard.16.4.494. No abstract available. — View Citation

Leifer VP, Katz JN, Losina E. The burden of OA-health services and economics. Osteoarthritis Cartilage. 2022 Jan;30(1):10-16. doi: 10.1016/j.joca.2021.05.007. Epub 2021 May 20. — View Citation

Prior J, Mascaro B, Shark LK, Stockdale J, Selfe J, Bury R, Cole P, Goodacre JA. Analysis of high frequency acoustic emission signals as a new approach for assessing knee osteoarthritis. Ann Rheum Dis. 2010 May;69(5):929-30. doi: 10.1136/ard.2009.112599. No abstract available. — View Citation

Shakya BR, Tiulpin A, Saarakkala S, Turunen S, Thevenot J. Detection of experimental cartilage damage with acoustic emissions technique: An in vitro equine study. Equine Vet J. 2020 Jan;52(1):152-157. doi: 10.1111/evj.13132. Epub 2019 Jun 6. — View Citation

van Spil WE, Szilagyi IA. Osteoarthritis year in review 2019: biomarkers (biochemical markers). Osteoarthritis Cartilage. 2020 Mar;28(3):296-315. doi: 10.1016/j.joca.2019.11.007. Epub 2019 Dec 27. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	acoustic emissions	Acoustic sensors are embedded in the hardware of the inmodi knee brace, allowing the non-invasively collection of acoustic data at frequencies between 100Hz and 20 kHz. During data analysis, signals will be segmented and frequency components of low interest will be removed. Specific sound features, such as spectral, fractality, peak amplitude or click patters will be extracted.; Data of both knees will be assessed at the same time with the inmodi knee brace (v2) during four different tests, based on recommendations by the Osteoarthritis Research Society International (OARSI) for people with knee OA: - unloaded flexion-extension (F/E) of the knee in a seated position, - Sit-to-Stand test (STS), - One-step test (OST), - Walk test.; Associations between the extracted sound parameters and kinematic data, MOAKS grading, KL grading, leg alignment angles and PROMS will be studied to identify biomarkers with a prognosis value in the prediction of OA progress.	1 year and 2 years
Primary	kinematic data	Inertial sensors, also embedded in the hardware, do collect movement trajectories at the same time during the four different tests. This kinematic data will be combined with the acoustic emissions to analyze which sound features appear at specific ranges of motion (knee flexion/extension).	1 year and 2 years
Primary	MRI / MOAKS	Patients will be scanned using a 3T MRI scanner (Magnetom Prisma, Siemens). MRI allow to visualize and assess structural changes in joint tissues, such as cartilage, meniscus and subchondral bone. Semi-quantitative scoring of these degenerative structures in OA will be done using the MRI Osteoarthritis Knee Score (MOAKS) system by a radiologist.	1 year and 2 years
Primary	EOS / leg alignment	Bilateral long-leg radiographic images will be acquired in a standing position as stereoradiography using the EOS Edge (EOS X-Ray Imaging Acquisition System, Paris, France). Images will be analyzed for OA grading (Kellgren-Lawrence grade 0 - 4) and leg alignment parameters (hip-knee-ankle angle, mechanical axis length and deviation, proximal tibia width and compartmental joint space width).	1 year and 2 years
Primary	PROMS	Five different patient reported outcome measures are used: Oxford Knee Score: contains 12 questions about individual's activities of daily living and how they have been affected by pain over the last 4 weeks.; Core Outcome Measures Index Knee: assesses the main outcomes of importance to patients with knee problems (pain, function, symptom-specific well-being, quality of life, disability).; University of California at Los Angeles: an activity rating scale, which rates the activity level of joint replacement patients globally in one out of 10.; Knee injury and osteoarthritis outcome score: an instrument to assess the patient's opinion about their knee and associated problems.; Forgotten Joint Score 12 is a concise 12-item PROM that evaluates patients' ability to forget their joint in daily life.	1 year and 2 years