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Physiopathology, Diagnosis and Therapy of Primary Cephalalgia and Adaptive Disorders

Biomarker Identification to Predict the Evolution of Migraine From an Episodic to a Chronic Condition

The main aim of the present pilot study is to prove the possibility to use the Nitroglycerin (NTG) model to describe the pathophysiology of headache using task-free advanced Magnetic Resonance Imaging (MRI) techniques, in order to depict the static changes of the ictal and inter-ictal phase of migraine attacks vs the pain free state in healthy subjects and to compare that with the spontaneous headache attack experienced by chronic migraineurs.

Descripción general del estudio

Estado

Terminado

Condiciones

Descripción detallada

Resting state functional magnetic resonance imaging (rs-fMRI) has depicted cyclical functional connectivity changes during the ictal and inter-ictal phase of the migraine attack. In this pilot study, Functional Connectivity (FC) changes during nitroglycerin (NTG) induced migraine attacks were assessed vs the pain-free condition in healthy subjects.

To this end, subjects with episodic migraine (EM) without aura were enrolled. NTG-triggered a spontaneous-like migraine attack in the subjects. They underwent 4 rs-fMRI scan repetitions during different phases of the attack (baseline, prodromal, full blown, recovery phase) with a 3 Tesla MR scanner. According to the pain field literature, several regions of interests were studied, in particular the thalamic areas and the salience network (SN) were selected as primary areas of interest for the analyses. Subjects' rs-fMRI data were first processed with a seed-based correlation analysis (SCA) to assess the static changes in FC between the thalamus and the rest of the brain during the experiment. The wavelet coherence approach (WCA) were also applied to test the changes in time-in-phase coherence between the thalamus and the salience network (SN).

Healthy subject were administered nitroglycerin as well and scanned at a pain free baseline and after 3 hours in order to compare the response.

The rebound headache that followed acute drug withdrawal were used as a surrogate paradigm of spontaneous attack. Patients with chronic migraine and medication overuse were hospitalized for a supervised withdrawal program at the Mondino Foundation; during the program if they experienced a rebound headache attack, they were scanned with a rs-fMRI acquisition.

The acquired imagines were analyzed with the same procedure regarding the evaluation of static and dynamic functional connectivity fluctuation.

Tipo de estudio

De observación

Inscripción (Actual)

15

Contactos y Ubicaciones

Esta sección proporciona los datos de contacto de quienes realizan el estudio e información sobre dónde se lleva a cabo este estudio.

Ubicaciones de estudio

      • Pavia, Italia, 27100
        • Headache Science Center

Criterios de participación

Los investigadores buscan personas que se ajusten a una determinada descripción, denominada criterio de elegibilidad. Algunos ejemplos de estos criterios son el estado de salud general de una persona o tratamientos previos.

Criterio de elegibilidad

Edades elegibles para estudiar

18 años a 60 años (Adulto)

Acepta Voluntarios Saludables

Géneros elegibles para el estudio

Todos

Método de muestreo

Muestra no probabilística

Población de estudio

Subjects with episodic migraine without aura; patients with chronic migraine and medication overuse; healthy subjects

Descripción

Episodic migraineurs

Inclusion Criteria:

  • age between 18-60 years;
  • diagnosis of episodic migraine without aura developed before the age of 50;
  • no current prophylactic treatment for migraine prevention;
  • chronic migraineurs with medication overuse according to the ICHDIII criteria

Exclusion Criteria:

  • chronic or medication-overuse headache or cluster headache diagnosis;
  • any chronic pain condition or disorders other than migraine;
  • an alleged diagnosis of major psychiatric disorders such as depression, bipolar affective disorder and schizophrenia;
  • a diagnosis of tension type headache with a frequency of more than 5 days per month;
  • any cardiovascular diseases in which the NTG use could be contraindicated;
  • blood pressure hypotension, closed angle glaucoma, anaemia;
  • women in child bearing, breast feeding; continuous use of benzodiazepines;
  • any neuroradiological pathological findings at a previous MRI scan of the head.

Chronic migraineurs

Inclusion Criteria:

  • age between 18-60 years;
  • diagnosis of migraine without aura developed before the age of 50 according to the ICHD III criteria;
  • currently chronic migraineurs with medication overuse according to The International Classification of Headache Disorders 3rd edition (ICHDIII) criteria.

Exclusion Criteria:

  • any chronic pain condition or disorders other than migraine;
  • an alleged diagnosis of major psychiatric disorders such as depression, bipolar affective disorder and schizophrenia;
  • a diagnosis of tension type headache with a frequency of more than 5 days per month;
  • any cardiovascular diseases in which the NTG use could be contraindicated;
  • blood pressure hypotension, closed angle glaucoma, anaemia; women in child bearing, breast feeding;
  • continuous use of benzodiazepines;
  • any neuroradiological pathological findings at a previous MRI scan of the head.

Healthy subjects

Inclusion Criteria:

  • age between 18-60 years;
  • overall good clinical condition, no neurological findings at the physical examination.

Exclusion criteria:

  • history of episodic or chronic or medication-overuse headache or cluster headache diagnosis according to the International Chronic Headache Disease (ICHD) III criteria;
  • any chronic pain condition or disorders other than migraine;
  • an alleged diagnosis of major psychiatric disorders such as depression, bipolar affective disorder and schizophrenia;
  • a diagnosis of tension type headache with a frequency of more than 5 days per month;
  • any cardiovascular diseases in which the NTG use could be contraindicated;
  • blood pressure hypotension, closed angle glaucoma, anaemia;
  • women in child bearing, breast feeding;
  • continuous use of benzodiazepines;
  • any neuroradiological pathological findings at the baseline MRI scan of the head.

Plan de estudios

Esta sección proporciona detalles del plan de estudio, incluido cómo está diseñado el estudio y qué mide el estudio.

¿Cómo está diseñado el estudio?

Detalles de diseño

Cohortes e Intervenciones

Grupo / Cohorte
Chronic migraineurs
This group includes patients with chronic migraine.
Control group
This group includes healthy subjects.
Episodic migraineurs
This group includes patients with episodic migraine

¿Qué mide el estudio?

Medidas de resultado primarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Functional Connectivity (FC) changes
Periodo de tiempo: Up to 6 hours
Functional connectivity pattern of changes profiling the different condition of the migraine experience. To depict the static and dynamics changes of brain activity during a migraine attack; ii) To validate the use of the NTG-induced attacks paradigm as a reliable instrument combined with an fMRI approach to compare the induced vs the spontaneous attack; iii) To describe possible differences in brain activity between attacks in chronic and episodic migraineurs.
Up to 6 hours

Medidas de resultado secundarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Magnetic Resonance Imaging (MRI)
Periodo de tiempo: Up to 6 hours
To acquire sufficient MRI to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms. This can be achieved by combining clinical, psychological, biological, neurophysiological and MRI-derived features into a multimodal multi-parametric approach suitable for patient's classification. The ML and DL approaches could also be adopted to predict chronification, as well as the response to a withdrawal program for medication overuse headache.
Up to 6 hours
Monthly migraine frequency (day/month)
Periodo de tiempo: Up to 6 hours
To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Disease duration (years)
Periodo de tiempo: Up to 6 hours
To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Nausea (number)
Periodo de tiempo: Up to 6 hours
As a feature of the migraine attack.To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Vomiting (number)
Periodo de tiempo: Up to 6 hours
As a feature of the migraine attack.To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Photophobia (number)
Periodo de tiempo: Up to 6 hours
As a feature of the migraine attack.To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Phonophobia (number)
Periodo de tiempo: Up to 6 hours
To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Aggravation by movement (number)
Periodo de tiempo: Up to 6 hours
As a feature of the migraine attack. To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Throbbing pain (number)
Periodo de tiempo: Up to 6 hours
As a feature of the migraine attack. To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours
Abortive medication (number of intake/month)
Periodo de tiempo: Up to 6 hours
To acquire clinical data to identify feature patterns that can profile patient's condition using machine learning (ML) and deep learning (DL) algorithms.
Up to 6 hours

Colaboradores e Investigadores

Aquí es donde encontrará personas y organizaciones involucradas en este estudio.

Publicaciones y enlaces útiles

La persona responsable de ingresar información sobre el estudio proporciona voluntariamente estas publicaciones. Estos pueden ser sobre cualquier cosa relacionada con el estudio.

Publicaciones Generales

Fechas de registro del estudio

Estas fechas rastrean el progreso del registro del estudio y los envíos de resultados resumidos a ClinicalTrials.gov. Los registros del estudio y los resultados informados son revisados ​​por la Biblioteca Nacional de Medicina (NLM) para asegurarse de que cumplan con los estándares de control de calidad específicos antes de publicarlos en el sitio web público.

Fechas importantes del estudio

Inicio del estudio (Actual)

31 de agosto de 2018

Finalización primaria (Actual)

31 de marzo de 2019

Finalización del estudio (Actual)

15 de diciembre de 2020

Fechas de registro del estudio

Enviado por primera vez

21 de diciembre de 2020

Primero enviado que cumplió con los criterios de control de calidad

5 de enero de 2021

Publicado por primera vez (Actual)

6 de enero de 2021

Actualizaciones de registros de estudio

Última actualización publicada (Actual)

6 de enero de 2021

Última actualización enviada que cumplió con los criterios de control de calidad

5 de enero de 2021

Última verificación

1 de noviembre de 2020

Más información

Términos relacionados con este estudio

Información sobre medicamentos y dispositivos, documentos del estudio

Estudia un producto farmacéutico regulado por la FDA de EE. UU.

No

Estudia un producto de dispositivo regulado por la FDA de EE. UU.

No

Esta información se obtuvo directamente del sitio web clinicaltrials.gov sin cambios. Si tiene alguna solicitud para cambiar, eliminar o actualizar los detalles de su estudio, comuníquese con register@clinicaltrials.gov. Tan pronto como se implemente un cambio en clinicaltrials.gov, también se actualizará automáticamente en nuestro sitio web. .

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