High-tech Rehabilitation Impact on Muscle MRI

NCT ID: NCT06884956

Last Updated: 2025-03-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ENROLLING_BY_INVITATION

Total Enrollment

30 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-06-13

Study Completion Date

2025-12-31

Brief Summary

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The use of high-tech techniques is becoming increasingly popular in the rehabilitation field, where the use of exoskeletons, robots, virtual reality, etc. allow for customized rehabilitation protocols. Moreover, their combination with virtual reality systems improves the patient's involvement increasing the effectiveness of the treatment, especially in the pediatric context.

Several literature studies confirmed the effectiveness of rehabilitation treatments in the pediatric field in terms of functional and physiologic scores (e.g. GMFM).

This study aims to use MRI to identify biomarkers for the morpho-functional characterization of skeletal muscle and for the evaluation of the effect of high-tech rehabilitation treatment on it.

Detailed Description

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The use of high-tech techniques is becoming increasingly popular in the rehabilitation field, where the use of exoskeletons, robots, virtual reality, etc. allow for very refined control of the rehabilitation process, making it more repeatable and, at the same time, more customization on the needs of the individual patient. Furthermore, the use of virtual reality and applications with video game-style scenarios increase the patient's involvement and active participation, one of the crucial factors for maximizing the effectiveness of rehabilitation treatment, especially in the pediatric field. Studies also conducted at our institute have widely demonstrated the effectiveness of rehabilitation treatments in the pediatric field. In a study conducted at the Bosisio Parini center on 23 patients with acquired brain injuries, rehabilitation treatment with RAGT (Robotic-Aided Gait Training) and physiotherapy led to a general improvement in walking patterns and functional activities. The rehabilitation protocol included an intensive 4-week program with 20 sessions of RAGT and 20 sessions of traditional physiotherapy. The improvement in functionality was evaluated through the administration of the Gross Motor Function Measures GMFM scale, scales D and E) and the "6 Minutes Walk test", while the gait pattern was evaluated through gait analysis, highlighting an improvement regarding cadence, speed and stride length. Another study also conducted at the Bosisio Parini center demonstrated the effectiveness of the RAGT treatment also in a population of patients suffering from infantile cerebral palsy. In this second study, the effect of the rehabilitation process on the plasticity of the central nervous system was also evaluated using Magnetic Resonance Imaging (MRI). The analysis of Diffusion Tensor Imaging (DTI) and brain volumetric data on a group of 16 patients reported no significant effects at the group level; however, by stratifying the patients on the basis of the degree of clinical improvement achieved it was possible to observe an increase in the Fractional Anisotropy (FA) value at the level of some brain bundles, including the corticospinal tracts. To date, few studies have been carried out to study the effect of high-tech rehabilitation treatments directly on the patient's muscle tissue and, consequently, to better identify the categories of patients who respond better to rehabilitation treatment with the same initial clinical condition. In this context, MRI is a very promising tool, as it allows a completely non-invasive in-vivo measurement of the state of muscle tissue, which can be repeated several times even in a short time without risks for the patient. In another study conducted at the Bosisio Parini centre, muscle MRI was used to characterize patients suffering from two different types of limb-girdle muscular dystrophy (2A, 2B). In a subsequent study, muscle MRI was used to study the effect of Duchenne muscular dystrophy on respiratory muscles. A multicenter study which also involved our institute demonstrated that the use of a standardized acquisition and processing protocol for muscle MRI leads both to a high degree of repeatability of the measurements calculated from the MRI images and to their temporal stability, a an indispensable feature for any longitudinal studies. In this sense, the collaboration between our institute and the Institute of Biomedical Technologies (ITB) of the CNR has led to the development of a multimodal muscle MR image registration algorithm to improve data analysis in longitudinal studies. This study therefore aims to use MRI to identify biomarkers for the morpho-functional characterization of skeletal muscle and for the evaluation of the effect of high-tech rehabilitation treatment on it. For this purpose, it is planned to recruit a heterogeneous population of patients undergoing high-tech rehabilitation treatment in a clinical setting who will be asked to undergo a multimodal muscle MRI before and after the rehabilitation process. These measures can provide a useful tool both to better characterize the chain of events that lead to an improvement in the patient's functionality and to identify which patients can benefit most from this treatment.

Conditions

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Movement Disorders Treatment

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients

Patients undergoing a motion rehabilitation treatment by using high tech devices, i.e. GRAIL and/or Lokomat

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* patients undergoing high-tech rehabilitation treatment of the lower limb
* able to remain in a supine position for 30 minutes without moving
* able to follow instructions and communicate effectively with operators (e.g communicating fear and/or pain)

Exclusion Criteria

* any contraindication to MRI examination
* presence of metal nails/protheses or objects near the thighs which will disrupt and/or induce distortion on the MR images
Minimum Eligible Age

8 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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IRCCS Eugenio Medea

OTHER

Sponsor Role lead

Responsible Party

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Denis Peruzzo

Head of Neuroimaging Unit

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Denis Peruzzo, PhD

Role: PRINCIPAL_INVESTIGATOR

Scientific Institute IRCCS Eugenio Medea

Locations

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IRCCS Eugenio Medea - La Nostra Famiglia

Bosisio Parini, LC, Italy

Site Status

Countries

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Italy

References

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Mastropietro A, Peruzzo D, Taccogna MG, Sanna N, Casali N, Nossa R, Biffi E, Ambrosini E, Pedrocchi A, Rizzo G. Multiparametric MRI Assessment of Morpho-Functional Muscle Changes Following a 6-Month FES-Cycling Training Program: Pilot Study in People With a Complete Spinal Cord Injury. JMIR Rehabil Assist Technol. 2025 Jan 16;12:e64825. doi: 10.2196/64825.

Reference Type BACKGROUND
PMID: 39819652 (View on PubMed)

Beretta E, Storm FA, Strazzer S, Frascarelli F, Petrarca M, Colazza A, Cordone G, Biffi E, Morganti R, Maghini C, Piccinini L, Reni G, Castelli E. Effect of Robot-Assisted Gait Training in a Large Population of Children With Motor Impairment Due to Cerebral Palsy or Acquired Brain Injury. Arch Phys Med Rehabil. 2020 Jan;101(1):106-112. doi: 10.1016/j.apmr.2019.08.479. Epub 2019 Sep 25.

Reference Type BACKGROUND
PMID: 31562873 (View on PubMed)

Piccinini L, Cimolin V, Storm F, Di Girolamo G, Biffi E, Galli M, Condoluci C. Quantification of the effects of robotic-assisted gait training on upper and lower body strategy during gait in diplegic children with Cerebral Palsy using summary parameters. Comput Methods Biomech Biomed Engin. 2022 Feb;25(2):140-147. doi: 10.1080/10255842.2021.1938009. Epub 2021 Jun 14.

Reference Type BACKGROUND
PMID: 34121521 (View on PubMed)

Biffi E, Beretta E, Storm FA, Corbetta C, Strazzer S, Pedrocchi A, Ambrosini E. The Effectiveness of Robot- vs. Virtual Reality-Based Gait Rehabilitation: A Propensity Score Matched Cohort. Life (Basel). 2021 Jun 11;11(6):548. doi: 10.3390/life11060548.

Reference Type BACKGROUND
PMID: 34208009 (View on PubMed)

Castelli E, Beretta E, De Tanti A, Arduini F, Biffi E, Colazza A, Di Pede C, Guzzetta A, Lucarini L, Maghini I, Mandala M, Nespoli M, Pavarelli C, Policastro F, Polverelli M, Rossi A, Sgandurra G, Boldrini P, Bonaiuti D, Mazzoleni S, Posteraro F, Benanti P, Draicchio F, Falabella V, Galeri S, Gimigliano F, Grigioni M, Mazzon S, Molteni F, Morone G, Petrarca M, Picelli A, Senatore M, Turchetti G, Saviola D. Robot-assisted rehabilitation for children with neurological disabilities: Results of the Italian consensus conference CICERONE. NeuroRehabilitation. 2022;51(4):665-679. doi: 10.3233/NRE-220036.

Reference Type BACKGROUND
PMID: 36530098 (View on PubMed)

Peri E, Turconi AC, Biffi E, Maghini C, Panzeri D, Morganti R, Pedrocchi A, Gagliardi C. Effects of dose and duration of Robot-Assisted Gait Training on walking ability of children affected by cerebral palsy. Technol Health Care. 2017 Aug 9;25(4):671-681. doi: 10.3233/THC-160668.

Reference Type BACKGROUND
PMID: 28436398 (View on PubMed)

Arrigoni F, De Luca A, Velardo D, Magri F, Gandossini S, Russo A, Froeling M, Bertoldo A, Leemans A, Bresolin N, D'angelo G. Multiparametric quantitative MRI assessment of thigh muscles in limb-girdle muscular dystrophy 2A and 2B. Muscle Nerve. 2018 Oct;58(4):550-558. doi: 10.1002/mus.26189. Epub 2018 Aug 22.

Reference Type BACKGROUND
PMID: 30028523 (View on PubMed)

Schlaffke L, Rehmann R, Rohm M, Otto LAM, de Luca A, Burakiewicz J, Baligand C, Monte J, den Harder C, Hooijmans MT, Nederveen A, Schlaeger S, Weidlich D, Karampinos DC, Stouge A, Vaeggemose M, D'Angelo MG, Arrigoni F, Kan HE, Froeling M. Multi-center evaluation of stability and reproducibility of quantitative MRI measures in healthy calf muscles. NMR Biomed. 2019 Sep;32(9):e4119. doi: 10.1002/nbm.4119. Epub 2019 Jul 17.

Reference Type BACKGROUND
PMID: 31313867 (View on PubMed)

Other Identifiers

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RC1020

Identifier Type: -

Identifier Source: org_study_id

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