Predicting language improvement in acute stroke patients presenting with aphasia: a multivariate logistic model using location-weighted atlas-based analysis of admission CT perfusion scans.
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Predicting language improvement in acute stroke patients presenting with aphasia: a multivariate logistic model using location-weighted atlas-based analysis of admission CT perfusion scans. / Payabvash, S; Kamalian, S; Fung, S; Wang, Y; Passanese, J; Souza, L C S; Kemmling, A; Kemmling, Andre; Halpern, E F; González, R G; Furie, K L; Lev, M H.
In: AM J NEURORADIOL, Vol. 31, No. 9, 9, 2010, p. 1661-1668.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Predicting language improvement in acute stroke patients presenting with aphasia: a multivariate logistic model using location-weighted atlas-based analysis of admission CT perfusion scans.
AU - Payabvash, S
AU - Kamalian, S
AU - Fung, S
AU - Wang, Y
AU - Passanese, J
AU - Souza, L C S
AU - Kemmling, A
AU - Kemmling, Andre
AU - Halpern, E F
AU - González, R G
AU - Furie, K L
AU - Lev, M H
PY - 2010
Y1 - 2010
N2 - Prediction of functional outcome immediately after stroke onset can guide optimal management. Most prognostic grading scales to date, however, have been based on established global metrics such as total NIHSS score, admission infarct volume, or intracranial occlusion on CTA. Our purpose was to construct a more focused, location-weighted multivariate model for the prediction of early aphasia improvement, based not only on traditional clinical and imaging parameters, but also on atlas-based structure/function correlation specific to the clinical deficit, using CT perfusion imaging.
AB - Prediction of functional outcome immediately after stroke onset can guide optimal management. Most prognostic grading scales to date, however, have been based on established global metrics such as total NIHSS score, admission infarct volume, or intracranial occlusion on CTA. Our purpose was to construct a more focused, location-weighted multivariate model for the prediction of early aphasia improvement, based not only on traditional clinical and imaging parameters, but also on atlas-based structure/function correlation specific to the clinical deficit, using CT perfusion imaging.
KW - Humans
KW - Male
KW - Female
KW - Multivariate Analysis
KW - Reproducibility of Results
KW - Sensitivity and Specificity
KW - Prognosis
KW - Logistic Models
KW - Algorithms
KW - Models, Neurological
KW - Computer Simulation
KW - Tomography, X-Ray Computed/methods
KW - Pattern Recognition, Automated/methods
KW - Radiographic Image Interpretation, Computer-Assisted/methods
KW - Brain/radiography
KW - Aphasia/diagnosis/etiology
KW - Perfusion Imaging/methods
KW - Stroke/complications/radiography
KW - Subtraction Technique
KW - Humans
KW - Male
KW - Female
KW - Multivariate Analysis
KW - Reproducibility of Results
KW - Sensitivity and Specificity
KW - Prognosis
KW - Logistic Models
KW - Algorithms
KW - Models, Neurological
KW - Computer Simulation
KW - Tomography, X-Ray Computed/methods
KW - Pattern Recognition, Automated/methods
KW - Radiographic Image Interpretation, Computer-Assisted/methods
KW - Brain/radiography
KW - Aphasia/diagnosis/etiology
KW - Perfusion Imaging/methods
KW - Stroke/complications/radiography
KW - Subtraction Technique
M3 - SCORING: Journal article
VL - 31
SP - 1661
EP - 1668
JO - AM J NEURORADIOL
JF - AM J NEURORADIOL
SN - 0195-6108
IS - 9
M1 - 9
ER -
