Osteoarthritis, KneeNCT06351059
Acoustic Emission Biomarkers for the Detection and Monitoring of Early Knee Osteoarthritis
An observational study of Osteoarthritis, Knee and Diagnosis, run by Schulthess Klinik at 1 site in Switzerland.
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. Read more about this study
- Who is it for?
- Ages 35 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Osteoarthritis, Knee, Diagnosis
- What is being tested?
- InModi acoustic emission analysis
- How many people
- 120 participants
- Where
- 1 siteSwitzerland
- Study dates
- 1 Jan 2023to 31 Dec 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 35 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: This study targets a population at risk of OA. The risk of knee OA after knee joint injury is up to five-fold that of non-injured patients. As much as 50% of individuals with an anterior cruciate ligament (ACL) or meniscus tear develop knee OA. Therefore, to represent the whole distribution of OA stages in the study sample, participants will be recruited from the Meniscus/ACL-surgery (MAC) registry of the Schulthess Klinik at 2 years and 5 years post-operative times. Additionally, a healthy control group and a late-stage OA group will be included.
Who may be able to join
- 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
Who cannot join
- 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
Show all 9Show fewer
- 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
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the detailed 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.
- Conditions
- Osteoarthritis, Knee, Diagnosis
- Being tested
- InModi acoustic emission analysis
- Keywords
- Acoustic emission, Knee Osteoarthritis
- Medical subject headings
- Osteoarthritis, Knee, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
InModi acoustic emission analysisDiagnostic test
Also called MRI / MOAKS, EOS / leg alignment, Functional tests, PROMs
All diagnosis tests
| Study group | Role | What they receive |
|---|---|---|
| A: healthy participants | 20 healthy participants judging themselves to be of good subjective health without any knee problems Receives: Diagnostic Test: InModi acoustic emission analysis | |
| B1: 2 years normal | 20 patients from the knee registry at 2 years post-op with normal outcomes Receives: Diagnostic Test: InModi acoustic emission analysis | |
| B2: 2 years poor | 20 patients from the knee registry at 2 years post-op with poor outcomes Receives: Diagnostic Test: InModi acoustic emission analysis | |
| C1: 5 years normal | 20 patients from the knee registry at 5 years post-op with normal outcomes Receives: Diagnostic Test: InModi acoustic emission analysis | |
| C2: 5 years poor | 20 patients from the knee registry at 5 years post-op with poor outcomes Receives: Diagnostic Test: InModi acoustic emission analysis | |
| D: TKA patients | 20 patients booked for unilateral TKA surgery for severe OA Receives: Diagnostic Test: InModi acoustic emission analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 1 year and 2 years
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).
Measured: 1 year and 2 years
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.
Measured: 1 year and 2 years
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).
Measured: 1 year and 2 years
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.
Measured: 1 year and 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Apr 2024
- Study start1 Jan 2023
- Primary completion31 Jul 2024 (estimated)
- Study completion31 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (9)Papers the sponsor has linked to this study.
- Other trials for Osteoarthritis, KneeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 120 participants (actual)
Sponsor and investigators
- Lead sponsor
- Schulthess Klinik
- Sponsor type
- University, hospital or other
- Collaborators
- Ecole Polytechnique Fédérale de Lausanne
- Responsible party
- Sponsor
- Investigators
- Vincent A Stadelmann, PhD, Principal investigator, Schulthess Klinik
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06351059
- Sponsor's protocol ID
- UE-0083
- Status last verified
- Apr 2024
- First submitted
- 25 Oct 2023
- Last updated
- 19 Apr 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 34023527KELLGREN 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.
PubMed 13498604Eckstein F, Wirth W. Quantitative cartilage imaging in knee osteoarthritis. Arthritis. 2011;2011:475684. doi: 10.1155/2011/475684. Epub 2010 Dec 8.
PubMed 22046518van 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.
PubMed 31887390Kalo 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.
PubMed 32807320Prior 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.
PubMed 20413570Shakya 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.
PubMed 31032989Bahador 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.
Leuthard L, Thevenot J, Teijeiro T, Atienza D, Stadelmann VA. Acoustic Emission Biomarkers for the Detection and Monitoring of Early Knee Osteoarthritis: Protocol for a Prospective, Single-Center, Exploratory Study. JMIR Res Protoc. 2026 Feb 26;15:e67032. doi: 10.2196/67032.
PubMed 41747224
Study at a glance
From the registry record, last updated by the sponsor on 19 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Acoustic Emission Biomarkers for the Detection and Monitoring of Early Knee Osteoarthritis
- ClinicalTrials.gov ID
- NCT06351059
- Acronym / sponsor ID
- UE-0083
- Conditions
- Osteoarthritis, Knee, Diagnosis
- Keywords
- Acoustic emission, Knee Osteoarthritis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 120 participants (actual)
- Lead sponsor
- Schulthess KlinikUniversity, hospital or other
- Collaborators
- Ecole Polytechnique Fédérale de Lausanne
- Study start
- 1 Jan 2023 (actual)
- Primary completion
- 31 Jul 2024 (estimated)
- Study completion
- 31 Dec 2024 (estimated)
- First posted
- 8 Apr 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 6
| Arm | Type | Receives |
|---|---|---|
| A: healthy participants | – | Diagnostic Test: InModi acoustic emission analysis20 healthy participants judging themselves to be of good subjective health without any knee problems |
| B1: 2 years normal | – | Diagnostic Test: InModi acoustic emission analysis20 patients from the knee registry at 2 years post-op with normal outcomes |
| B2: 2 years poor | – | Diagnostic Test: InModi acoustic emission analysis20 patients from the knee registry at 2 years post-op with poor outcomes |
| C1: 5 years normal | – | Diagnostic Test: InModi acoustic emission analysis20 patients from the knee registry at 5 years post-op with normal outcomes |
| C2: 5 years poor | – | Diagnostic Test: InModi acoustic emission analysis20 patients from the knee registry at 5 years post-op with poor outcomes |
| D: TKA patients | – | Diagnostic Test: InModi acoustic emission analysis20 patients booked for unilateral TKA surgery for severe OA |
Who may qualify
- Ages
- 35 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- This study targets a population at risk of OA. The risk of knee OA after knee joint injury is up to five-fold that of non-injured patients. As much as 50% of individuals with an anterior cruciate ligament (ACL) or meniscus tear develop knee OA. Therefore, to represent the whole distribution of OA stages in the study sample, participants will be recruited from the Meniscus/ACL-surgery (MAC) registry of the Schulthess Klinik at 2 years and 5 years post-operative times. Additionally, a healthy control group and a late-stage OA group will be included.
Key inclusion criteria (3 listed)
- 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
Key exclusion criteria (9 listed)
- 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)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| InModi acoustic emission analysisAlso: MRI / MOAKS, EOS / leg alignment, Functional tests, PROMsAll diagnosis tests | Diagnostic test | A: healthy participants, B1: 2 years normal, B2: 2 years poor, C1: 5 years normal, C2: 5 years poor, D: TKA patients |
Primary outcome
acoustic emissions
Time frame: 1 year and 2 years
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.
kinematic data
Time frame: 1 year and 2 years
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).
MRI / MOAKS
Time frame: 1 year and 2 years
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.
EOS / leg alignment
Time frame: 1 year and 2 years
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).
PROMS
Time frame: 1 year and 2 years
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.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Apr 2024.
- Background: PubMed 34023527Leifer 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.
- Background: PubMed 13498604KELLGREN 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.
- Background: PubMed 22046518Eckstein F, Wirth W. Quantitative cartilage imaging in knee osteoarthritis. Arthritis. 2011;2011:475684. doi: 10.1155/2011/475684. Epub 2010 Dec 8.
- Background: PubMed 31887390van 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.
- Background: PubMed 32807320Kalo 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.
- Background: PubMed 20413570Prior 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.
- Background: PubMed 31032989Shakya 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.
- BackgroundBahador 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.
- Derived from this study: PubMed 41747224Leuthard L, Thevenot J, Teijeiro T, Atienza D, Stadelmann VA. Acoustic Emission Biomarkers for the Detection and Monitoring of Early Knee Osteoarthritis: Protocol for a Prospective, Single-Center, Exploratory Study. JMIR Res Protoc. 2026 Feb 26;15:e67032. doi: 10.2196/67032.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Vincent A Stadelmann, PhD principal investigator
Schulthess Klinik
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Osteoarthritis, Knee and Diagnosis, run by Schulthess Klinik at 1 site in Switzerland.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 19 Apr 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
acoustic emissions (time frame: 1 year and 2 years). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06351059, which also lists 9 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Apr 2024.