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Abstract

Objective

Based on histopathology, Edinburgh diagnostic criteria were proposed to consider a nontraumatic intracerebral lobar hemorrhage (ICH) as related to cerebral amyloid angiopathy (CAA) using the initial computed tomography (CT) scan and the APOE genetic status. We aimed to externally validate the Edinburgh prediction model, excluding the APOE genotyping and based on the modified Boston criteria on the MRI for CAA diagnosis

Methods

We included patients admitted for spontaneous lobar ICH in the emergency department between 2016 and 2019 who underwent noncontrast CT scan and MRI. According to the MRI, patients were classified into the CAA group or into the non-CAA group in the case of other causes of ICH. Two neuroradiologists, blinded to the final retained diagnosis, rated each radiological feature on initial CT scan described in the Edinburgh study on initial CT scan

Results

A total of 102 patients were included, of whom 36 were classified in the CAA group, 46 in the non-CAA causes group and 20 of undetermined cause (excluded from the primary analysis). The Edinburgh prediction model, including finger-like projections and subarachnoid extension showed an area under receiver operating characteristic curves (AUC) of 0.760 (95% confidence interval, CI: 0.660–0.859) for the diagnosis of CAA. The AUC reached 0.808 (95% CI: 0.714–0.901) in a new prediction model integrating a third radiologic variable: the ICH cortical involvement.

Conclusion

Using the Boston MRI criteria as a final assessment, we provided a new external confirmation of the radiological Edinburgh CT criteria, which are directly applicable in acute settings of spontaneous lobar ICH and further proposed an original 3‑set model considering finger-like projections, subarachnoid extension, and cortical involvement that may achieve a high discrimination performance.

Details

Title
Applicability of the Edinburgh CT Criteria for Lobar Intracerebral Hemorrhage Associated with Cerebral Amyloid Angiopathy
Author
Grangeon, Lou 1   VIAFID ORCID Logo  ; Roussel, Melanie 2 ; Gillibert, Andre 3 ; Verdalle-Cazes, Mikael 4 ; Dolores, Mickael 4 ; Ozkul-Wermester, Ozlem 5 ; Gilard, Vianney 6 ; Derrey, Stephane 6 ; Maltête, David 5 ; Gerardin, Emmanuel 4 ; Joly, Luc-Marie 2 ; Wallon, David 1 ; Magne, Nicolas 4 

 Rouen University Hospital, Department of Neurology, Rouen Cedex, France (GRID:grid.41724.34) (ISNI:0000 0001 2296 5231); Normandie Univ, UNIROUEN, Inserm U1245, Normandy Center for Genomic and Personalized Medicine, Rouen, France (GRID:grid.412043.0) (ISNI:0000 0001 2186 4076) 
 Rouen University Hospital, Emergency Department, Rouen, France (GRID:grid.41724.34) (ISNI:0000 0001 2296 5231) 
 University of Rouen, Department of Biostatistics, Rouen University Hospital, Rouen, France (GRID:grid.10400.35) (ISNI:0000 0001 2108 3034) 
 Rouen University Hospital, Department of Radiology, Rouen, France (GRID:grid.41724.34) (ISNI:0000 0001 2296 5231) 
 Rouen University Hospital, Department of Neurology, Rouen Cedex, France (GRID:grid.41724.34) (ISNI:0000 0001 2296 5231) 
 Rouen University Hospital, Department of Neurosurgery, Rouen, France (GRID:grid.41724.34) (ISNI:0000 0001 2296 5231) 
Pages
455-465
Publication year
2023
Publication date
Jun 2023
Publisher
Springer Nature B.V.
ISSN
18691439
e-ISSN
18691447
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2819537966
Copyright
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.