Prediction of clinical outcome in subacute subarachnoid hemorrhage using diffusion tensor imaging.

clinical outcome diffusion tensor imaging subarachnoid hemorrhage vascular disorders

Journal

Journal of neurosurgery
ISSN: 1933-0693
Titre abrégé: J Neurosurg
Pays: United States
ID NLM: 0253357

Informations de publication

Date de publication:
01 02 2019
Historique:
received: 22 07 2017
accepted: 16 10 2017
medline: 14 4 2018
pubmed: 14 4 2018
entrez: 14 4 2018
Statut: epublish

Résumé

Clinical outcome in nontraumatic subarachnoid hemorrhage (SAH) is multifactorial and difficult to predict. Diffusion tensor imaging (DTI) findings are a prognostic marker in some diseases such as traumatic brain injury. The authors hypothesized that DTI parameters measured in the subacute phase of SAH can be associated with a poor clinical outcome. Diffusion tensor imaging was prospectively performed in 54 patients at 8-10 days after nontraumatic SAH. Logistic regression analysis was performed to evaluate the association of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values with a poor clinical outcome (modified Rankin Scale score ≥ 3) at 3 months. At 8-10 days post-SAH, after adjusting for other variables associated with a poor outcome, an increased ADC at the frontal centrum semiovale was associated with a poor prognosis (OR estimate 1.29, 95% CI 1.04-1.60, p = 0.020). Moreover, an increase of 0.1 in the FA value at the corpus callosum at 8-10 days after SAH corresponded to 66% lower odds of having a poor outcome (p = 0.002). Decreased FA and increased ADC values in specific brain regions were independently associated with a poor clinical outcome after SAH. This preliminary exploratory study supports a potential role for DTI in predicting the outcome of SAH.

Identifiants

pubmed: 29652228
pii: 2017.10.JNS171793
doi: 10.3171/2017.10.JNS171793
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

550-558

Auteurs

Isabel Fragata (I)

1Neuroradiology Department.
2Nova Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa.

Marta Alves (M)

3Centro de Investigação.

Ana Luísa Papoila (AL)

3Centro de Investigação.
4Biostatistics Department.

Patrícia Ferreira (P)

5Cerebrovascular Unit, Centro Hospitalar Lisboa Central.

Ana Paiva Nunes (AP)

5Cerebrovascular Unit, Centro Hospitalar Lisboa Central.

Nuno Canto Moreira (NC)

6Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden.

Patrícia Canhão (P)

7Neurology Department, Centro Hospitalar Lisboa Norte.
8Faculdade de Medicina, University of Lisbon, Portugal; and.

Classifications MeSH