Viewing Study NCT05091502


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Study NCT ID: NCT05091502
Status: COMPLETED
Last Update Posted: 2023-01-23
First Post: 2021-09-23
Is NOT Gene Therapy: False
Has Adverse Events: False

Brief Title: Personalised Modeling and Simulation Procedures for the Differential Diagnosis of Dynapenia: a Study on Healthy Volunteers
Sponsor: Istituto Ortopedico Rizzoli
Organization:

Study Overview

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
Status: COMPLETED
Status Verified Date: 2022-09
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: None
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.
Detailed Description: None

Study Oversight

Has Oversight DMC: False
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: