Combining quantitative susceptibility mapping to the morphometric index in differentiating between progressive supranuclear palsy and Parkinson's disease. Academic Article uri icon

Overview

abstract

  • PURPOSE: To determine whether the susceptibility value in the deep gray matter obtained by quantitative susceptibility mapping (QSM) provides additive value to the morphometric index for differentiating progressive supranuclear palsy (PSP) from Parkinson's disease (PD). MATERIALS AND METHODS: PSP- (n = 8) and PD patients (n = 18) and 18 age-matched healthy controls who underwent QSM and 3D magnetization-prepared rapid gradient echo (MPRAGE) sequences. The mean susceptibility values (MSVs) of the deep gray matter structures on QSM- and areas of the midbrain (morphometric index, MI) on 3D MPRAGE images were measured by two neuroradiologists. Analysis of variance, the Scheffe test and receiver operating characteristic (ROC) analysis were conducted to assess differences and discriminate among PSP, PD and controls by the MSVs and the MI. Using the MSV of a structure with the best area under the curve (AUC) and the MI, we created a decision tree to differentiate between PSP and PD. RESULTS: The MSVs of the globus pallidus (GP) and substantia nigra (SN) were significantly higher in PSP than PD and the controls (p < .05). By ROC analysis (PSP vs PD), AUC was greatest (0.903) for the GP. The MI was significantly smaller in PSP than PD and the controls (p < .05); AUC (PSP vs PD) was 0.917. The decision tree using cutoff values of 244 parts per billion for MSV of the GP and 74.0 mm2 for MI served to completely differentiate between PSP and PD. CONCLUSION: The MSV in the GP on QSM images adds value to the MI for differentiating PSP from PD.

publication date

  • August 31, 2019

Research

keywords

  • Brain Mapping
  • Globus Pallidus
  • Parkinson Disease
  • Supranuclear Palsy, Progressive
  • Tegmentum Mesencephali

Identity

Scopus Document Identifier

  • 85073344205

Digital Object Identifier (DOI)

  • 10.1016/j.jns.2019.116443

PubMed ID

  • 31634718

Additional Document Info

volume

  • 406