The primary objective is the development of a computer-aided diagnosis tool (CAD-tool) that enables specialists to improve the diagnosis, treatment, and evaluation of hyperkinetic movement disorders. The secondary objectives is are: 1) To analyze…
ID
Source
Brief title
Condition
- Neurological disorders congenital
- Movement disorders (incl parkinsonism)
Synonym
Research involving
Sponsors and support
Intervention
Outcome measures
Primary outcome
During a single hospital visit or at an external location, participants will be
questioned about clinical parameters, such as age at onset, will fill out
several questionnaires on non-motor symptom severity, and will be asked to
perform several simple motor tasks with the arms. While executing these tasks,
participants will be recorded using 3D video, motion sensors, and muscle
activity sensors. Expert-based phenotype classification by three experts, based
on the video recordings and clinical parameters, will serve as input for
machine learning. Phenotype specific data clusters of the clinical parameters,
3D video, motion sensors, muscle activity sensors, FDG-PET imaging, fMRI, and
machine learning will be used to develop CAD models able to differentiate the
movement disorders. Algorithms, data quality assessment, discriminant feature
design, classifier training and validation will be applied using these data
clusters in machine learning.
Secondary outcome
Furthermore, the discrepancies between the phenotyping of the CAD-tool and the
clinical experts will be analyzed to improve the CAD-tool and gain further
understanding about clinical judgement.
Moreover, the pathophysiological brain process of dystonia, tremor, and
myoclonus will be analyzed by linking phenotypes to patterns of regional
changes in brain function.
Additionally, it will be analyzed whether regional change patterns in brain
function are phenotype- of genotype-specific in myoclonus-dystonia.
Background summary
Hyperkinetic movement disorders are defined as excessive involuntary movements,
including dystonia, myoclonus and tremor. Each single type of movement disorder
has its own clinical presentation, but frequently complex and variable mixed
forms occur. As a result, only highly specialized experts can classify movement
disorders correctly. However, even these experts are often not in agreement
about the diagnosis, leaving numerous patients without good clinical
description (phenotype). Incorrect phenotyping is a major problem which
precludes good diagnosis in patients, evaluating the natural course, delivering
tailored treatment, and evaluating treatment effects in hyperkinetic movement
disorders.
Study objective
The primary objective is the development of a computer-aided diagnosis tool
(CAD-tool) that enables specialists to improve the diagnosis, treatment, and
evaluation of hyperkinetic movement disorders.
The secondary objectives is are:
1) To analyze discrepancies between expert-based phenotype classification and
CAD-tool outcomes, to improve the CAD-tool and our knowledge of clinical
judgment.
2) To enable further optimization of the classification of the dystonia,
tremor, myoclonus, and mixed phenotypes by adding imaging patterns to the
machine learning.
3) To gain insight in pathophysiological brain processes of dystonia, tremor,
and myoclonus phenotypes by linking phenotypes to regional change patterns in
brain function.
4) To study whether regional change patterns in brain function are phenotype-
or genotype-specific in myoclonus-dystonia.
Study design
The study design is a cross-sectional translational study which aims to develop
a CAD-tool for hyperkinetic movement disorders. The study consists of a pilot,
and two three study parts: A, and B, and C. During the pilot the most
discriminating tasks will be selected for further use in part A and B. In part
A and B different groups of patients will be included. Part C consists of the
FDG-PET and MRI imaging.
Study burden and risks
The risk of the study parts A and B is considered minimal because no invasive
apparatuses are used and the tasks that are included in the study are not
burdensome. Subjects are not expected to experience direct clinical benefit
from participation in the study. However, in the future, this CAD-tool will
help provide fast and correct diagnosis for new patients. Additionally, the
CAD-tool can be used for evaluation of treatment, which could be beneficial for
the participants. The risk associated with participation in part C is
considered negligible and the burden can be considered acceptable since there
is great experience with the scans in normal diagnostic work up of patients
with movement disorders and significant side effects are not known.
Hanzeplein 1
Groningen 9700 RB
NL
Hanzeplein 1
Groningen 9700 RB
NL
Listed location countries
Age
Inclusion criteria
- >= 16 years of age.
- Patients with a clinically confirmed diagnosis of one of the included single
phenotypes (dystonia, tremor, myoclonus, tics, chorea, spasticity, ataxia) OR
mixed phenotyping OR healthy controls.
- For pediatric patients in part A and part B >= 6 years of age
Exclusion criteria
- Other neurological conditions that lead to movement problems other than
hyperkinetic movement disorders.
- Other conditions that lead to impaired hand or arm function.
- With regard to healthy subjects: no first degree family member of a patient
with a hyperkinetic movement disorder.
- Silver allergy
- Pace-makers
- For pediatric patients: not able to follow instructions
Design
Recruitment
Followed up by the following (possibly more current) registration
No registrations found.
Other (possibly less up-to-date) registrations in this register
No registrations found.
In other registers
| Register | ID |
|---|---|
| CCMO | NL67013.042.18 |