Idiopathic Normal-Pressure Hydrocephalus: Diagnostic Accuracy of Automated Sulcal Morphometry in Patients With Ventriculomegaly.


Journal

Neurosurgery
ISSN: 1524-4040
Titre abrégé: Neurosurgery
Pays: United States
ID NLM: 7802914

Informations de publication

Date de publication:
01 10 2019
Historique:
received: 27 07 2018
accepted: 17 03 2019
pubmed: 23 5 2019
medline: 31 3 2020
entrez: 23 5 2019
Statut: ppublish

Résumé

Idiopathic normal-pressure hydrocephalus (iNPH) is a treatable cause of gait and cognitive impairment. iNPH should be differentiated from ventriculomegaly secondary to brain atrophy to choose the best therapeutic option (ventriculoperitoneal shunt vs medical management). To determine the diagnostic accuracy of automated sulcal morphometry to differentiate patients with iNPH from patients with ventriculomegaly of neurodegenerative origin. Thirty-eight consecutive patients with iNPH (shunt responsive n = 31, nonresponsive n = 7), 35 with vascular cognitive disorder, and 25 age- and sex-matched healthy controls were prospectively included and underwent cognitive evaluation and 3T brain magnetic resonance imaging. Sulcal opening of 10 sulci of interest was retrospectively measured using an automated surface-based approach from the 3-dimensional T1-weighted images. Receiver-operating characteristic curve analyses determined the best parameter to identify iNPH patients. The best parameter to discriminate shunt-responsive iNPH from patients with vascular cognitive disorder and healthy controls was the ratio between calcarine sulcus and cingulate sulcus opening with an area under the curve of 0.94 (95% CI: 0.89, 0.99). A cut-off value of 0.95 provided the highest sensitivity (96.8%) and specificity (83.3%). This preliminary study showed that automated sulcal morphometry may help the neurosurgeon to identify iNPH patients and to exclude other causes of ventriculomegaly.

Sections du résumé

BACKGROUND
Idiopathic normal-pressure hydrocephalus (iNPH) is a treatable cause of gait and cognitive impairment. iNPH should be differentiated from ventriculomegaly secondary to brain atrophy to choose the best therapeutic option (ventriculoperitoneal shunt vs medical management).
OBJECTIVE
To determine the diagnostic accuracy of automated sulcal morphometry to differentiate patients with iNPH from patients with ventriculomegaly of neurodegenerative origin.
METHODS
Thirty-eight consecutive patients with iNPH (shunt responsive n = 31, nonresponsive n = 7), 35 with vascular cognitive disorder, and 25 age- and sex-matched healthy controls were prospectively included and underwent cognitive evaluation and 3T brain magnetic resonance imaging. Sulcal opening of 10 sulci of interest was retrospectively measured using an automated surface-based approach from the 3-dimensional T1-weighted images. Receiver-operating characteristic curve analyses determined the best parameter to identify iNPH patients.
RESULTS
The best parameter to discriminate shunt-responsive iNPH from patients with vascular cognitive disorder and healthy controls was the ratio between calcarine sulcus and cingulate sulcus opening with an area under the curve of 0.94 (95% CI: 0.89, 0.99). A cut-off value of 0.95 provided the highest sensitivity (96.8%) and specificity (83.3%).
CONCLUSION
This preliminary study showed that automated sulcal morphometry may help the neurosurgeon to identify iNPH patients and to exclude other causes of ventriculomegaly.

Identifiants

pubmed: 31115469
pii: 5494815
doi: 10.1093/neuros/nyz121
doi:

Types de publication

Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

E747-E755

Commentaires et corrections

Type : CommentIn
Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2019 by the Congress of Neurological Surgeons.

Auteurs

Grégory Kuchcinski (G)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.
CHU Lille, Department of Neuroradiology, Lille, France.

Caroline Jacquiez (C)

CHU Lille, Department of Neuroradiology, Lille, France.

Marc Baroncini (M)

CHU Lille, Department of Neurosurgery, Lille, France.

François Machuron (F)

Univ Lille, CHU Lille, EA 2694 - Santé publique: épidémiologie et qualité des soins, Unité de Biostatistiques, Lille, France.

Hélène Béhal (H)

Univ Lille, CHU Lille, EA 2694 - Santé publique: épidémiologie et qualité des soins, Unité de Biostatistiques, Lille, France.

Julien Dumont (J)

CHU Lille, Department of Neuroradiology, Lille, France.

Renaud Lopes (R)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.
CHU Lille, Department of Neuroradiology, Lille, France.

Christine Delmaire (C)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.
CHU Lille, Department of Neuroradiology, Lille, France.

Thibaud Lebouvier (T)

CHU Lille, Department of Neurology, Lille, France.
Memory Center, DISTALZ, Lille, France.

Michel Bottlaender (M)

Laboratoire Imagerie Moléculaire In Vivo (IMIV), UMR 1023 Inserm/CEA/Université Paris Sud - ERL 95218 CNRS, CEA/I2BM/Service Hospitalier Frédéric Joliot, Orsay, France.
UNIACT, Neurospin, Direction de la Recherche Médicale, CEA, Gif-sur-Yvette, France.

Regis Bordet (R)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.

Luc Defebvre (L)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.
CHU Lille, Department of Neurology, Lille, France.

Jean-Pierre Pruvo (JP)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.
CHU Lille, Department of Neuroradiology, Lille, France.

Xavier Leclerc (X)

Univ Lille, Inserm, UMR_S 1171 'Degenerative and vascular cognitive disorders', Lille, France.
CHU Lille, Department of Neuroradiology, Lille, France.

Jérôme Hodel (J)

Department of Neuroradiology, Hôpital Henri Mondor, Créteil, France.

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Classifications MeSH