BACKGROUND AND PURPOSE: Few data on xenon computed tomography-based quantitative cerebral blood flow (CBF) in spontaneous intracerebral hemorrhage have been reported. We correlated perihematomal CBF in a retrospective series of 42 subacute spontaneous intracerebral hemorrhage patients undergoing xenon computed tomography with in-hospital discharge status and mortality. METHODS: We calculated 3 area-weighted mean CBF values: (1) within the computed tomography-visible rim of perihematomal edema, (2) within a 1-cm marginal radius around the hematoma, and (3) all cortical regions of interest immediately adjacent to the hematoma. Primary outcomes were in-hospital mortality and discharge status (ordinally as 0=home, 1=acute rehabilitation, 2=nursing home, 3=death). Discharge status was used as a surrogate for in-hospital functional outcome. RESULTS: Median hematoma volume was 14.4 cm(3) (range, 2 to 70). Median perihematomal (low-attenuation rim) CBF was 21.9 cm(3).100 g(-1).min(-1) (range, 6.1 to 81.1), and the median 1-cm marginal radius CBF was 26.8 cm(3).100 g(-1).min(-1) (range, 10.8 to 72.8). The median regional cortical CBF was 26.7 cm(3).100 g(-1).min(-1) (range, 6.9 to 72.6). Eight patients had 1-cm marginal radius or regional cortical CBF values <20 cm(3).100 g(-1).min(-1). Hematoma volume (odds ratio [OR], 1.68 per 10-cm(3) volume; P=0.036) and intraventricular hemorrhage (OR, 1.88 per grade of intraventricular hemorrhage; P=0.036) predicted mortality. Two CBF measures, hydrocephalus, and IVH predicted poor in-hospital functional outcome in bivariate analysis. Each CBF measure (OR, 0.34 to 0.43; P<0.001 to 0.003) and intraventricular hemorrhage (OR, 3.42; P<0.001) predicted in-hospital functional outcome in multivariable analyses. CONCLUSIONS: Most spontaneous intracerebral hemorrhage patients lack perihematomal penumbra. Perihematomal CBF independently predicts in-hospital discharge status but not in-hospital mortality. Further studies are warranted to determine whether perihematomal CBF predicts long-term functional outcomes.
BACKGROUND AND PURPOSE: Few data on xenon computed tomography-based quantitative cerebral blood flow (CBF) in spontaneous intracerebral hemorrhage have been reported. We correlated perihematomal CBF in a retrospective series of 42 subacute spontaneous intracerebral hemorrhagepatients undergoing xenon computed tomography with in-hospital discharge status and mortality. METHODS: We calculated 3 area-weighted mean CBF values: (1) within the computed tomography-visible rim of perihematomal edema, (2) within a 1-cm marginal radius around the hematoma, and (3) all cortical regions of interest immediately adjacent to the hematoma. Primary outcomes were in-hospital mortality and discharge status (ordinally as 0=home, 1=acute rehabilitation, 2=nursing home, 3=death). Discharge status was used as a surrogate for in-hospital functional outcome. RESULTS: Median hematoma volume was 14.4 cm(3) (range, 2 to 70). Median perihematomal (low-attenuation rim) CBF was 21.9 cm(3).100 g(-1).min(-1) (range, 6.1 to 81.1), and the median 1-cm marginal radius CBF was 26.8 cm(3).100 g(-1).min(-1) (range, 10.8 to 72.8). The median regional cortical CBF was 26.7 cm(3).100 g(-1).min(-1) (range, 6.9 to 72.6). Eight patients had 1-cm marginal radius or regional cortical CBF values <20 cm(3).100 g(-1).min(-1). Hematoma volume (odds ratio [OR], 1.68 per 10-cm(3) volume; P=0.036) and intraventricular hemorrhage (OR, 1.88 per grade of intraventricular hemorrhage; P=0.036) predicted mortality. Two CBF measures, hydrocephalus, and IVH predicted poor in-hospital functional outcome in bivariate analysis. Each CBF measure (OR, 0.34 to 0.43; P<0.001 to 0.003) and intraventricular hemorrhage (OR, 3.42; P<0.001) predicted in-hospital functional outcome in multivariable analyses. CONCLUSIONS: Most spontaneous intracerebral hemorrhagepatients lack perihematomal penumbra. Perihematomal CBF independently predicts in-hospital discharge status but not in-hospital mortality. Further studies are warranted to determine whether perihematomal CBF predicts long-term functional outcomes.
Authors: Robert A Knight; Yuxia Han; Tavarekere N Nagaraja; Polly Whitton; Jennifer Ding; Michael Chopp; Donald M Seyfried Journal: Stroke Date: 2008-07-17 Impact factor: 7.914
Authors: Peter B Sporns; Marios-Nikos Psychogios; Grégoire Boulouis; Andreas Charidimou; Qi Li; Enrico Fainardi; Dar Dowlatshahi; Joshua N Goldstein; Andrea Morotti Journal: J Clin Med Date: 2021-03-05 Impact factor: 4.241