ForceLoss: Part I - Healthy Volunteers. Development and Validation of Methods to Generate Personalised Models for the Differential Diagnosis of the Loss of Muscle Force
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Istituto Ortopedico Rizzoli
- Enrollment
- 20
- Locations
- 1
- Primary Endpoint
- Co-contraction index (CCI)
Study Overview
Brief Summary
The ForceLoss study aims to develop personalised modeling and simulation procedures to enable the differential diagnosis for the loss of muscle force, namely dynapenia. Dynapenia can be caused by diffuse or selective sarcopenia, lack of activation, or improper motor control. Each of these causes requires different interventions, but a reliable differential diagnosis is currently impossible. While instrumental methods can provide information on each of these possible causes, it is left to the experience of the single clinician to integrate such information into a complete diagnostic picture. But an accurate diagnosis for dynapenia is important in a number of pathologies, including neurological diseases, age-related frailty, diabetes, and orthopaedic conditions. The hypothesis is that the use of a mechanistic, subject-specific model of maximum isometric knee extension, informed by a number of instrumental information can provide a robust differential diagnosis of dynapenia.
In this preliminary study, on healthy volunteers, the investigators will develop and optimize (i) the experimental protocol and (ii) the modeling and simulation framework, assessing both feasibility and reliability of the proposed procedures. Medical imaging, electromyography (EMG) and dynamometry data will be collected and combined to inform a personalised musculoskeletal model of each participant. Biomechanical computer simulations of a Maximal Voluntary Isometric Contraction (MVIC) task will then be performed. To validate the proposed approach, the models' estimates will be compared to in vivo dynamometry measurements and experimental EMG data.
Study Design
- Study Type
- Interventional
- Allocation
- Na
- Intervention Model
- Single Group
- Primary Purpose
- Diagnostic
- Masking
- None
Eligibility Criteria
- Ages
- 20 Years to 40 Years (Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Body mass index (BMI) between 15 and 30 kg / m²
Exclusion Criteria
- •Neurological, rheumatic or tumoral diseases;
- •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, pregnancy);
- •Previous interventions or traumas to the joints of the lower limb.
Arms & Interventions
Healthy volunteers
Intervention: Personalised musculoskeletal modeling (Diagnostic Test)
Outcomes
Primary Outcomes
Co-contraction index (CCI)
Time Frame: at baseline (Day 0)
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). EMG patterns (mV) will additionally be stored and will constitute a normative dataset, for qualitative comparisons to identify suboptimal muscle control or altered muscle activation patterns in dynapenic patients in future studies that aim to assess (the severity of) dynapenia in a patient population.
MVIC Torque
Time Frame: at baseline (Day 0)
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. Such data will serve as normative dataset/threshold in future studies that aim to assess (the severity of) dynapenia in a patient population.
Muscle volume
Time Frame: at baseline (Day 0)
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. Such data will serve as normative dataset/threshold in future studies that aim to assess (the severity of) sarcopenia in a patient population.
Secondary Outcomes
No secondary outcomes reported