Clinical trial NCT05091502: Personalised Modeling and Simulation Procedures for the Differential Diagnosis of Dynapenia: a Study on Healthy Volunteers
Official title: ForceLoss: Part I - Healthy Volunteers. Development and Validation of Methods to Generate Personalised Models for the Differential Diagnosis of the Loss of Muscle Force
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Healthy
Keywords: Musculoskeletal modeling
In silico medicine
Maximal Voluntary Isometric Contraction
Electromyography
Healthy volunteers
Dynapenia
Dynamometry
Lead sponsor: Istituto Ortopedico Rizzoli
Sponsor class: OTHER
First posted: 2021-10-25
Enrollment: 20
Sex: ALL
Minimum age (years): 20
Maximum age (years): 40
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: DIAGNOSTIC

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.


Eligibility criteria: 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.

Primary outcomes:
measure: Muscle volume
timeFrame: at baseline (Day 0)
measure: Co-contraction index (CCI)
timeFrame: at baseline (Day 0)
measure: MVIC Torque
timeFrame: at baseline (Day 0)
Secondary outcomes:
Other outcomes:
Locations:
city: Bologna
country: Italy
facility: IRCCS Istituto Ortopedico Rizzoli
state: Emilia-Romagna
Study officials:
affiliation: IRCCS Istituto Ortopedico Rizzoli
name: Marco Viceconti, Professor
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: Nishikawa Y, Watanabe K, Takahashi T, Hosomi N, Orita N, Mikami Y, Maruyama H, Kimura H, Matsumoto M. Sex differences in variances of multi-channel surface electromyography distribution of the vastus lateralis muscle during isometric knee extension in young adults. Eur J Appl Physiol. 2017 Mar;117(3):583-589. doi: 10.1007/s00421-017-3559-3. Epub 2017 Feb 20.