Quantitative assessment of blood volume, blood flow, and permeability of the brain of clinically normal dogs by use of dynamic contrast-enhanced computed tomography

Kristi L. Peterson Veterinary Medical Teaching Hospital, School of Veterinary Medicine, University of California, Davis, CA 95616.

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Alexander G. MacLeod Veterinary Medical Teaching Hospital, School of Veterinary Medicine, University of California, Davis, CA 95616.

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Erik R. Wisner Department of Surgical and Radiological Sciences, School of Veterinary Medicine, University of California, Davis, CA 95616.

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Richard F. Larson Veterinary Medical Teaching Hospital, School of Veterinary Medicine, University of California, Davis, CA 95616.

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Rachel E. Pollard Department of Surgical and Radiological Sciences, School of Veterinary Medicine, University of California, Davis, CA 95616.

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Abstract

Objective—To determine effects of regional variation, interobserver variability, and vessel selection on quantitative vascular variables derived by dynamic contrast-enhanced computed tomography (DCE-CT) of the brain of clinically normal dogs.

Animals—14 adult dogs with no evidence of CNS dysfunction.

Procedures—Dogs were randomly assigned to 4 groups, and DCE-CT was performed at the level of the frontal lobe, rostral portion of the parietal-temporal lobes, caudal portions of the parietal-temporal lobes, or occipital lobe–cerebellum for groups 1 to 4, respectively. Cerebral blood flow (CBF), cerebral blood volume (CBV), and permeability in gray and white matter for both a large and small artery were calculated and compared. Values among 3 observers and 4 regions of the brain were calculated and compared.

Results—Significant interobserver variability was detected for CBF and permeability in white matter. Values calculated for large and small arteries were correlated for CBV and CBF but not for permeability. Overall mean ± SD for CBF, CBV, and permeability in gray matter was 53.5 ± 27.7 mL/min/100 g, 2.9 ± 1.4 mL/100 g, and 1.4 ± 2.2 mL/min/100 g, respectively. Mean for CBF, CBV, and permeability in white matter was 44.2 ± 28.5 mL/min/100 g, 2.5 ± 1.5 mL/100 g, and 0.9 ± 0.7 mL/min/100 g, respectively. Values did not differ significantly among brain regions.

Conclusions and Clinical Relevance—Significant regional variations were not detected for quantitative vascular variables in the brain of clinically normal dogs. However, interobserver variability and vessel selection have an important role in variable estimation.

Abstract

Objective—To determine effects of regional variation, interobserver variability, and vessel selection on quantitative vascular variables derived by dynamic contrast-enhanced computed tomography (DCE-CT) of the brain of clinically normal dogs.

Animals—14 adult dogs with no evidence of CNS dysfunction.

Procedures—Dogs were randomly assigned to 4 groups, and DCE-CT was performed at the level of the frontal lobe, rostral portion of the parietal-temporal lobes, caudal portions of the parietal-temporal lobes, or occipital lobe–cerebellum for groups 1 to 4, respectively. Cerebral blood flow (CBF), cerebral blood volume (CBV), and permeability in gray and white matter for both a large and small artery were calculated and compared. Values among 3 observers and 4 regions of the brain were calculated and compared.

Results—Significant interobserver variability was detected for CBF and permeability in white matter. Values calculated for large and small arteries were correlated for CBV and CBF but not for permeability. Overall mean ± SD for CBF, CBV, and permeability in gray matter was 53.5 ± 27.7 mL/min/100 g, 2.9 ± 1.4 mL/100 g, and 1.4 ± 2.2 mL/min/100 g, respectively. Mean for CBF, CBV, and permeability in white matter was 44.2 ± 28.5 mL/min/100 g, 2.5 ± 1.5 mL/100 g, and 0.9 ± 0.7 mL/min/100 g, respectively. Values did not differ significantly among brain regions.

Conclusions and Clinical Relevance—Significant regional variations were not detected for quantitative vascular variables in the brain of clinically normal dogs. However, interobserver variability and vessel selection have an important role in variable estimation.

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