- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05795348
Personalised Modeling and Simulations for the Differential Diagnosis of Dynapenia: Study on Patients With Osteoarthritis (ForceLoss II)
ForceLoss: Part II - Osteoarthritic Patients. Development and Validation of Methods to Generate Personalised Models for the Differential Diagnosis of the Loss of Muscle Force
The ForceLoss study aims to develop personalised modeling and simulation procedures to enable the differential diagnosis for the loss of muscle force, namely dynapenia. The primary causes of dynapenia can be identified in a diffuse or selective sarcopenia, a lack of activation (inhibition), or suboptimal motor control. Each of these causes requires different interventions, but a reliable differential diagnosis is currently impossible. While biomedical instruments and tools can provide valuable information, it is often left to the experience of the single clinican to integrate such information into a complete diagnostic picture. An accurate diagnosis for dynapenia is important for a number of pathologies, including neurological diseases, age-related frailty, diabetes, and orthopaedic conditions.
The hypothesis is that the use of mechanistic, subject-specific models (digital twins) to simulate a maximal isometric knee extension task, informed by experimental measures may be employed to conduct a robust differential diagnosis for dynapenia.
In this study, on patients candidate for knee arthroplasty, the investigators will expand (i) the experimental protocol previously developed and tested on healthy volunteers with a measure of involuntary muscle contraction (superimposed neuromuscular electrical stimulation, SNMES), a hand-grip test, measures of bio-impedance and clinical questionnaires, and (ii) the modeling and simulation framework to include one additional step (to check for muscle inhibition).
Medical imaging, electromyography (EMG) and dynamometry data will be collected and combined to inform a digital twin of each participant. Biomechanical computer simulations of a Maximal Voluntary Isometric Contraction (MVIC) task will then be performed. Comparing the models' estimates to in vivo dynamometry measurements and EMG data, the investigators will test one by one the three possible causes of dynapenia, and, through a process of hypothesis falsification will exclude those that do not explain the observed loss of muscle force.
Study Overview
Status
Conditions
Intervention / Treatment
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Bologna, Italy, 40136
- IRCCS Istituto Ortopedico Rizzoli
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Diagnosis of Primary Arthrosis at the knee (according to the American College of Rheumatology criteria), subjects elected for tota knee arthroplasty
- Body Mass Index between 18.5 and 30 kg/m2
- Health status (according to the American Society of Anesthesiology classification) equal to 1 or 2
- Suspected systemic sarcopenia due to aging or localized sarcopenia due to disuse
Exclusion Criteria:
- Neurological, rheumatic or tumoral diseases
- Inguinal or abdominal hernia
- Diabetes
- Severe Hypertension (Level 3)
- Severe Cardio-pulmonary insufficiency
- Diagnosis of Osteonecrosis in the lower limb joints
- Pathologies or physical conditions incompatible with the use of magnetic resonance imaging and electrostimulation (i.e., active and passive implanted biomedical devices, epilepsy, severe venous insufficiency in the lower limbs)
- Previous interventions or traumas to the joints of the lower limb
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
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Other: Knee Osteoarthritic Patients
Patients candidate for knee arthroplasty; Age: 65-80 years; Body Mass Index: 18.5-30 kg/m²; ASA Classification: 1 or 2; Diagnosis of primary osteoarthritis at the knee; Suspect sarcopenia.
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Magnetic resonance images, electromyography and dynamometry data will be used to develop and inform personalised musculoskeletal models
Other Names:
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Muscle volume
Time Frame: at baseline (Day 0)
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Full lower limb MRI data will be acquired with subjects in supine position.
Individual muscle volumes (in cm3) will be segmented using commercial software and stored in anonymized form.
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at baseline (Day 0)
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MVIC Torque
Time Frame: at baseline (Day 0)
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Dynamometry data will be acquired while participants perform a MVIC leg extension test.
The maximum torque values (Nm) measured over three repetitions will be recorded.
These correspond to the values observed in correspondence of the plateaux of force, developed over a sustained contraction.
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at baseline (Day 0)
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Muscle Inhibition level
Time Frame: at baseline (Day 0)
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The difference between the maximal force exerted during the MVIC test (voluntary contraction) and that achieved when the muscles are electrically stimulated (involuntary contraction) will be computed.
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at baseline (Day 0)
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Co-contraction index (CCI)
Time Frame: at baseline (Day 0)
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Experimental EMG data will be recorded from the major lower limb muscles involved in the knee extension, while participants perform a maximal voluntary isometric contraction on a dynamometer (i.e., MVIC test to quantify muscle strength). The co-contraction index, defined as the relative activation of agonist and antagonist muscles (for this task: quadriceps and hamstrings) in the act of kicking (MVIC test), will be computed according to Li et al (2020). |
at baseline (Day 0)
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Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Marco Viceconti, Professor, IRCCS Istituto Ortopedico Rizzoli
Publications and helpful links
General Publications
- Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol. 2000 Oct;10(5):361-74. doi: 10.1016/s1050-6411(00)00027-4.
- Pons C, Borotikar B, Garetier M, Burdin V, Ben Salem D, Lempereur M, Brochard S. Quantifying skeletal muscle volume and shape in humans using MRI: A systematic review of validity and reliability. PLoS One. 2018 Nov 29;13(11):e0207847. doi: 10.1371/journal.pone.0207847. eCollection 2018.
- Rice DA, McNair PJ. Quadriceps arthrogenic muscle inhibition: neural mechanisms and treatment perspectives. Semin Arthritis Rheum. 2010 Dec;40(3):250-66. doi: 10.1016/j.semarthrit.2009.10.001. Epub 2009 Dec 2.
- Fernandez J, Zhang J, Heidlauf T, Sartori M, Besier T, Rohrle O, Lloyd D. Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling. Interface Focus. 2016 Apr 6;6(2):20150084. doi: 10.1098/rsfs.2015.0084.
- Petterson SC, Barrance P, Buchanan T, Binder-Macleod S, Snyder-Mackler L. Mechanisms underlying quadriceps weakness in knee osteoarthritis. Med Sci Sports Exerc. 2008 Mar;40(3):422-7. doi: 10.1249/MSS.0b013e31815ef285.
- Manini TM, Clark BC. Dynapenia and aging: an update. J Gerontol A Biol Sci Med Sci. 2012 Jan;67(1):28-40. doi: 10.1093/gerona/glr010. Epub 2011 Mar 28.
- O'Brien TD, Reeves ND, Baltzopoulos V, Jones DA, Maganaris CN. The effects of agonist and antagonist muscle activation on the knee extension moment-angle relationship in adults and children. Eur J Appl Physiol. 2009 Aug;106(6):849-56. doi: 10.1007/s00421-009-1088-4. Epub 2009 May 27.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- ForceLoss II
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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