Unraveling predictors affecting compliance to MRI in Parkinson's disease

Claudia Cacciari1, Clelia Pellicano2, Luca Cravello3

  • 1IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179 Rome, Italy.

Abstract

Insights

Predictors of magnetic resonance imaging (MRI) compliance in Parkinson's disease (PD) patients include older age, higher motor impairment, worse cognition, lower dopamine agonist doses, and increased anxiety. These factors are crucial for successful PD research and clinical MRI studies.

Area of Science:

  • Neurology
  • Medical Imaging

Background:

  • Magnetic resonance imaging (MRI) is a key tool for Parkinson's disease (PD) research and clinical practice.
  • Physical limitations and symptom severity in PD can hinder MRI completion.
  • Identifying factors influencing MRI compliance is essential for effective patient studies.

Purpose of the Study:

  • To investigate predictors of MRI compliance in Parkinson's disease patients.
  • To differentiate between physically incompatible and refusal groups for MRI scans.
  • To identify demographic, clinical, and psychological factors affecting MRI participation.

Main Methods:

  • 236 PD patients were assessed clinically, neuropsychologically, and neuropsychiatrically.
  • Patients were categorized into physically incompatible (PI), refusal (RR), and successful completion (SP) groups.
  • Multivariate/Univariate ANOVAs and logistic regression were used to analyze compliance predictors.

Main Results:

  • Physically incompatible patients were older, had higher motor scores (UPDRS-III), lower dopamine doses, and poorer cognition.
  • Patients who refused MRI (RR) exhibited higher anxiety levels.
  • Lower dopamine equivalents and higher anxiety scores significantly predicted non-compliance.

Conclusions:

  • Demographic, cognitive, and psychiatric factors significantly impact MRI compliance in PD.
  • Understanding these predictors aids in designing and interpreting PD MRI studies.
  • Addressing patient-specific factors can improve participation rates in neuroimaging research.