Added value of multimodal MRI to the clinical diagnosis of primary progressive aphasia variants

Research output: Contribution to journalArticle

Abstract

Objective: To determine the added value of multimodal structural magnetic resonance imaging (MRI) to language assessment in the differential diagnosis of primary progressive aphasia (PPA) variants. Methods: 59 PPA patients [29 nonfluent (nfvPPA), 15 semantic (svPPA), 15 logopenic (lvPPA)] and 38 healthy controls underwent 3D T1-weighted and diffusion tensor (DT) MRI. PPA patients also performed a comprehensive language assessment. Cortical thickness measures and DT MRI indices of white matter tract integrity were obtained. A random forest analysis identified MRI features associated with each clinical variant. Using ROC curves, the discriminatory power of the language features alone (“language model”) and the added contribution of multimodal MRI variables were assessed (“language + MRI model”). Results: The ‘language model’ alone was able to differentiate svPPA from both nfvPPA and lvPPA patients with high accuracy (area under the curve [AUC] =.95 and.99, respectively). When left inferior parietal cortical thickness and DT MRI metrics of the genu of the corpus callosum and left frontal aslant tract were added to the “language model”, the ability to discriminate between nfvPPA and lvPPA cases increased from AUC.82 (“language model” only) to.94 (“language + MRI model”). Conclusions: Language measures alone are able to distinguish svPPA from the other two PPA variants with the highest accuracy. Multimodal structural MRI improves the distinction of nfvPPA and lvPPA, which is challenging in the clinical practice.

LanguageEnglish
Pages58-66
Number of pages9
JournalCortex
Volume113
DOIs
Publication statusPublished - Apr 1 2019

Keywords

  • Cortical thickness
  • Logopenic PPA variant
  • Nonfluent PPA variant
  • Primary progressive aphasia (PPA)
  • White matter tract damage

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience

Cite this

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title = "Added value of multimodal MRI to the clinical diagnosis of primary progressive aphasia variants",
abstract = "Objective: To determine the added value of multimodal structural magnetic resonance imaging (MRI) to language assessment in the differential diagnosis of primary progressive aphasia (PPA) variants. Methods: 59 PPA patients [29 nonfluent (nfvPPA), 15 semantic (svPPA), 15 logopenic (lvPPA)] and 38 healthy controls underwent 3D T1-weighted and diffusion tensor (DT) MRI. PPA patients also performed a comprehensive language assessment. Cortical thickness measures and DT MRI indices of white matter tract integrity were obtained. A random forest analysis identified MRI features associated with each clinical variant. Using ROC curves, the discriminatory power of the language features alone (“language model”) and the added contribution of multimodal MRI variables were assessed (“language + MRI model”). Results: The ‘language model’ alone was able to differentiate svPPA from both nfvPPA and lvPPA patients with high accuracy (area under the curve [AUC] =.95 and.99, respectively). When left inferior parietal cortical thickness and DT MRI metrics of the genu of the corpus callosum and left frontal aslant tract were added to the “language model”, the ability to discriminate between nfvPPA and lvPPA cases increased from AUC.82 (“language model” only) to.94 (“language + MRI model”). Conclusions: Language measures alone are able to distinguish svPPA from the other two PPA variants with the highest accuracy. Multimodal structural MRI improves the distinction of nfvPPA and lvPPA, which is challenging in the clinical practice.",
keywords = "Cortical thickness, Logopenic PPA variant, Nonfluent PPA variant, Primary progressive aphasia (PPA), White matter tract damage",
author = "Elisa Canu and Federica Agosta and Francesca Imperiale and Andrea Fontana and Francesca Caso and Spinelli, {Edoardo Gioele} and Giuseppe Magnani and Andrea Falini and Giancarlo Comi and Massimo Filippi",
year = "2019",
month = "4",
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doi = "10.1016/j.cortex.2018.11.025",
language = "English",
volume = "113",
pages = "58--66",
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AU - Canu, Elisa

AU - Agosta, Federica

AU - Imperiale, Francesca

AU - Fontana, Andrea

AU - Caso, Francesca

AU - Spinelli, Edoardo Gioele

AU - Magnani, Giuseppe

AU - Falini, Andrea

AU - Comi, Giancarlo

AU - Filippi, Massimo

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Objective: To determine the added value of multimodal structural magnetic resonance imaging (MRI) to language assessment in the differential diagnosis of primary progressive aphasia (PPA) variants. Methods: 59 PPA patients [29 nonfluent (nfvPPA), 15 semantic (svPPA), 15 logopenic (lvPPA)] and 38 healthy controls underwent 3D T1-weighted and diffusion tensor (DT) MRI. PPA patients also performed a comprehensive language assessment. Cortical thickness measures and DT MRI indices of white matter tract integrity were obtained. A random forest analysis identified MRI features associated with each clinical variant. Using ROC curves, the discriminatory power of the language features alone (“language model”) and the added contribution of multimodal MRI variables were assessed (“language + MRI model”). Results: The ‘language model’ alone was able to differentiate svPPA from both nfvPPA and lvPPA patients with high accuracy (area under the curve [AUC] =.95 and.99, respectively). When left inferior parietal cortical thickness and DT MRI metrics of the genu of the corpus callosum and left frontal aslant tract were added to the “language model”, the ability to discriminate between nfvPPA and lvPPA cases increased from AUC.82 (“language model” only) to.94 (“language + MRI model”). Conclusions: Language measures alone are able to distinguish svPPA from the other two PPA variants with the highest accuracy. Multimodal structural MRI improves the distinction of nfvPPA and lvPPA, which is challenging in the clinical practice.

AB - Objective: To determine the added value of multimodal structural magnetic resonance imaging (MRI) to language assessment in the differential diagnosis of primary progressive aphasia (PPA) variants. Methods: 59 PPA patients [29 nonfluent (nfvPPA), 15 semantic (svPPA), 15 logopenic (lvPPA)] and 38 healthy controls underwent 3D T1-weighted and diffusion tensor (DT) MRI. PPA patients also performed a comprehensive language assessment. Cortical thickness measures and DT MRI indices of white matter tract integrity were obtained. A random forest analysis identified MRI features associated with each clinical variant. Using ROC curves, the discriminatory power of the language features alone (“language model”) and the added contribution of multimodal MRI variables were assessed (“language + MRI model”). Results: The ‘language model’ alone was able to differentiate svPPA from both nfvPPA and lvPPA patients with high accuracy (area under the curve [AUC] =.95 and.99, respectively). When left inferior parietal cortical thickness and DT MRI metrics of the genu of the corpus callosum and left frontal aslant tract were added to the “language model”, the ability to discriminate between nfvPPA and lvPPA cases increased from AUC.82 (“language model” only) to.94 (“language + MRI model”). Conclusions: Language measures alone are able to distinguish svPPA from the other two PPA variants with the highest accuracy. Multimodal structural MRI improves the distinction of nfvPPA and lvPPA, which is challenging in the clinical practice.

KW - Cortical thickness

KW - Logopenic PPA variant

KW - Nonfluent PPA variant

KW - Primary progressive aphasia (PPA)

KW - White matter tract damage

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