Validation of AI for Personalized Assessment and Rehabilitation of Upper Limb in Children With Unilateral Cerebral Palsy

NCT ID: NCT06073522

Last Updated: 2023-10-10

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 500 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2023-10-10
• Study Completion Date: 2027-06-30

Brief Summary

Unilateral Cerebral palsy (UCP) is the most common neurological chronic disease in childhood with a significant burden on children, their families and health care system.

AInCP aims to develop evidence-based clinical Decision Support Tools (DST) for personalized functional diagnosis, Upper Limb (UpL) assessment and home-based intervention for children with UCP, by developing, testing and validating trustworthy Artificial Intelligence (AI) and cost-effective strategies. The AInCP approach will: i) establish a clinical diagnosis and accurate prognosis for treatment response of individual UCP profiles, by employing a multimodal approach including clinical phenotyping, advanced brain imaging and real-life monitoring of UpL function, and ii) provide personalized home-based treatment, from advanced ICT and AI technologies.

The AInCP will build upon personalized diagnostic and rehabilitative DST (dDST and rDST) to be developed and validated through large observational and rehabilitation studies, including at least 200 and 150 children with UCP, respectively. Using data driven and AI approach, dDST and rDST will be combined for developing a theranostic DST (tDST) that will allow the re-designing of an economical, ethical, sustainable decision-making process for delivering a personalized and validated approach, focused on the care, monitoring and rehabilitation of UpL in children with UCP. AInCP is a significant example of a transdisciplinary approach, where all project collaborators (clinicians, data scientists, physicists, engineers, economists, ethicists, SMEs, children and parent associations) will work closely together in building the AInCP approach. This approach will, therefore, hinge on transdisciplinary contributions, multi- dimensional data, sets of innovative devices and fair AI-based algorithms, clinically effective and able to reduce users? and market barriers of acceptability, reimbursability and adoption of the proposed solution.

Detailed Description

The project is configured as an international observational clinical non-profit study that aims to change the current management of care and intervention of children and adolescents with UCP, providing a new model of approach.

This study has international dimensions, in fact it involves 12 partners from 7 countries; children will be enrolled and tested by the four clinical centers, namely the IRCCS Stella Maris Foundation, the Universidad De Castilla - La Mancha (Spain), the Katholieke Universiteit of Leuven (Belgium) and the David Tvildiani Medical University (Georgia).

Enrollment and clinical and kinematic evaluations will be carried out by the centers involved in the study; as regards the analysis of all neuroimaging data, the Queensland Cerebral Palsy Research Centre of the University of Queensland (Australia) will be involved, as this center is an international expert on this.

Participation in the study will be voluntary and a signature of informed consent by the parent will be required.

For the group of children with UCP the inclusion criteria will be:

1. Confirmed diagnosis of CP with predominantly spastic hemiplegia

2. Mild to moderately severe impairment of upper limb function (MACS level I-III)

The exclusion criteria will be:

1. Severe impairment of the upper limbs (MACS level IV or V)

2. Botulinum toxin injection in the upper limb within 6 months prior to study entry

3. Upper limb surgery in the 6 months prior to study entry

4. Presence of severe comorbidities and/or severe intellectual disability For the sample of children with typical development, they will be defined with the exclusion criteria of clinically documented disorders.

Recruitment will take place only after the signature of the informed consent. Upon recruitment, some personal data will be acquired and a special database will be created built on the REDCap platform and processed anonymously.

The data will come from the following areas:

1. Multiaxial clinical assessments and questionnaires

Before the start of the evaluation, a screening of the clinical measures that are part of the protocol will be carried out, in order to report any recent administrations of the same tests, in order to, if necessary, choose a better time window in which to start participation in this study. The protocol is in fact composed of standardized tests and questionnaires usually used in clinical practice. The clinical evaluation, which will be organized in two consecutive days and will be divided into different tests, some directed to the child and others, such as questionnaires, carried out by / with the parents, included in the following areas:

• Clinical motor evaluation (strength, spasticity and mirror movements) and sensitivity;
• Evaluation of the functionality of the upper limbs with structured and semi-structured tests
• Cognitive and neuropsychological evaluation
• Classification systems and questionnaires for upper limb skills, independence in everyday life and aspects related to participation and quality of life

For the children with TD, only a very small part of the evaluations provided for children with UCP will be carried out, that is:

• Evaluation of upper limb function with a semi-structured assessment session
• Questionnaires for coordination skills, to define laterality and to explore aspects related to behavior

Finally, a survey will be proposed consisting of questionnaires on sleep quality, quality of life and familiarity and ability with technologies for all children (both those with UCP and those with TD) their parents and also health professionals.

2. Neuroimaging Structural Magnetic Resonance (MRI) images of the brain of children with UCP, commonly acquired for clinical purposes, will be collected and evaluated according to the semiquantitative evaluation scale, developed by the Stella Maris Foundation (FSM), in order to quantify the severity of brain injury. For children and/or adolescents who have already performed MRI, parental consent will be requested to access this data. Image evaluation will be carried out by anonymizing and transferring the images to the University of Queensland/CSIRO in Australia and then analysed by expert evaluators using automated software, producing quantitative measurements.

3. Analysis of upper limb movement during clinical evaluation and daily life All children and/or adolescents enrolled will be asked to wear sensors on both wrists, during clinical evaluations and for 2 weeks in order to investigate upper limb activity also during daily life. During this period, parents will have to fill out a diary reporting the main daily activities (for example the time of wake-up, falling asleep, lunch and dinner, any sporting activity, etc.). Questionnaires will also be administered to evaluate the feasibility and acceptability of the sensors by children and/or adolescents and their parents, with a short daily form and a more extensive form at the end of the period of recording. At the end of the 2 weeks, parents will be contacted to pick up the sensors directly from their home.

To protect privacy and anonymity, each subject will be assigned a numerical code that will be kept separately. In this way the database will not contain any identification data of the subject. Access to such data will be limited only to personnel directly involved in the study and all data will be processed anonymously.

Once all the data coming from the three domains (clinical assessment, neuroimaging and kinematic analysis), together with the questionnaires, will be collected, they will be inserted in a dedicated RedCap database.

Investigators of UNIPI will use AI algorithms to process and analyze all data collected at the Green Data Center: clinical outcome measures, trackers' data, results of the questionnaires and the outcome from neuroimaging analysis. The results of analysis will be packaged into the diagnostic Decision Support Tool (dDST), a software tool that will support clinicians in managing functional diagnosis. This tool will be accessed by the clinicians through a specifically designed dashboard. The purpose of the AI analysis is to understand how these data are correlated with the different clinical features and treatment responses that distinguish one individual from another. The clinician can be supported both in diagnostic and rehabilitative processes, positively impacting both the clinical decision-making and the subject healthcare.

Conditions

Unilateral Cerebral Palsy

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

Typically developing children

Children aged 5 to 15 years old with no clinically documented disorders.

Artificial Intelligence for combining multi-domain data acquisition

Intervention Type: OTHER

Artificial Intelligence and machine learning techniques to combine data coming from multidomains data collection (such as clinical multiaxial assessments and questionnaires, Neuroimaging, Upper limb movement analysis during clinical assessment and daily life )

Children with Unilateral Cerebral Palsy

Children aged 5 to 15 years old with a diagnosis of Unilateral Cerebral Palsy

Artificial Intelligence for combining multi-domain data acquisition

Intervention Type: OTHER

Artificial Intelligence and machine learning techniques to combine data coming from multidomains data collection (such as clinical multiaxial assessments and questionnaires, Neuroimaging, Upper limb movement analysis during clinical assessment and daily life )

Interventions

Artificial Intelligence for combining multi-domain data acquisition

Artificial Intelligence and machine learning techniques to combine data coming from multidomains data collection (such as clinical multiaxial assessments and questionnaires, Neuroimaging, Upper limb movement analysis during clinical assessment and daily life )

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Children with confirmed diagnosis of UCP mainly spastic form
• Ages from 5 to 15 years old

Exclusion Criteria

• Severe Upper Limb (UpL) impairment (MACS ≥ level IV: inability to grasp)
• Botulinum toxin-A injections in UpL within 6 months prior to study entry
• UpL surgery within 12 months prior to study entry
• Severe comobordities and/or severe cognitive disability

For Typically developing children:

• Ages from 5 to 15 years old
• No documented clinically relevant disorders

• Minimum Eligible Age: 5 Years
• Maximum Eligible Age: 15 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Pisa

OTHER

Sponsor Role: collaborator

University of Castilla-La Mancha

OTHER

Sponsor Role: collaborator

Fight The Stroke

UNKNOWN

Sponsor Role: collaborator

SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO S ANNA

OTHER

Sponsor Role: collaborator

Noldus Information Technology Bv

UNKNOWN

Sponsor Role: collaborator

Khymeia

UNKNOWN

Sponsor Role: collaborator

Tyromotion GMBH

UNKNOWN

Sponsor Role: collaborator

The University of Queensland

OTHER

Sponsor Role: collaborator

University of Salento

OTHER

Sponsor Role: collaborator

IRCCS Fondazione Stella Maris

OTHER

Sponsor Role: lead

Responsible Party

Giuseppina Sgandurra

MD, PhD

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Giuseppina Sgandurra, Md, PhD

Role: PRINCIPAL_INVESTIGATOR

IRCCS Fondazione Stella Maris

Locations

IRCCS Fondazione Stella Maris

Pisa, , Italy

Universidad de Castilla - La Mancha

Toledo, , Spain

Countries

Italy; Spain

Central Contacts

Giuseppina Sgandurra, PhD, MD

Role: CONTACT

g.sgandurra@fsm.unipi.it

3392472874

Elena Beani, PhD

Role: CONTACT

e.beani@fsm.unipi.it

Facility Contacts

Giuseppina Sgandurra, MD, PhD

Role: primary

g.sgandurra@fsm.unipi.it

3392472874 ext. 0039

Elena Beani, PhD

Role: backup

e.beani@fsm.unipi.it

3475823890 ext. 0039

Rocio Palomo Carrion

Role: primary

Other Identifiers

IRCCS Fondazione Stella Maris

Identifier Type: -

Identifier Source: org_study_id