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Physiopathology, Diagnosis and Therapy of Primary Cephalalgia and Adaptive Disorders

5. Januar 2021 aktualisiert von: IRCCS National Neurological Institute "C. Mondino" Foundation

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.

Studienübersicht

Status

Abgeschlossen

Bedingungen

Detaillierte Beschreibung

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.

Studientyp

Beobachtungs

Einschreibung (Tatsächlich)

15

Kontakte und Standorte

Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.

Studienorte

  • Italien
      • Pavia, Italien, 27100
        • Headache Science Center

Teilnahmekriterien

Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.

Zulassungskriterien

Studienberechtigtes Alter

18 Jahre bis 60 Jahre (Erwachsene)

Akzeptiert gesunde Freiwillige

Ja

Studienberechtigte Geschlechter

Alle

Probenahmeverfahren

Nicht-Wahrscheinlichkeitsprobe

Studienpopulation

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

Beschreibung

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.

Studienplan

Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.

Wie ist die Studie aufgebaut?

Designdetails

Kohorten und Interventionen

Gruppe / Kohorte
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

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Functional Connectivity (FC) changes
Zeitfenster: 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

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Magnetic Resonance Imaging (MRI)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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)
Zeitfenster: 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

Mitarbeiter und Ermittler

Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.

Sponsor

IRCCS National Neurological Institute "C. Mondino" Foundation

Publikationen und hilfreiche Links

Die Bereitstellung dieser Publikationen erfolgt freiwillig durch die für die Eingabe von Informationen über die Studie verantwortliche Person. Diese können sich auf alles beziehen, was mit dem Studium zu tun hat.

Allgemeine Veröffentlichungen

Studienaufzeichnungsdaten

Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.

Haupttermine studieren

Studienbeginn (Tatsächlich)

31. August 2018

Primärer Abschluss (Tatsächlich)

31. März 2019

Studienabschluss (Tatsächlich)

15. Dezember 2020

Studienanmeldedaten

Zuerst eingereicht

21. Dezember 2020

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

5. Januar 2021

Zuerst gepostet (Tatsächlich)

6. Januar 2021

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

6. Januar 2021

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

5. Januar 2021

Zuletzt verifiziert

1. November 2020

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Schlüsselwörter

Zusätzliche relevante MeSH-Bedingungen

Andere Studien-ID-Nummern

  • IMAGO2020

Arzneimittel- und Geräteinformationen, Studienunterlagen

Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt

Nein

Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt

Nein

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