BACKGROUND AND PURPOSE: Clinical stroke trials require objective and reproducible end point variables. Morphometry of cerebral structures, including infarct volume, provides numerical measures that represent the amount of tissue damaged and potentially salvaged by therapy. However, morphometry may be time-consuming and labor-intensive, and it requires standardization across multiple centers, which may be difficult to achieve in large multicenter trials. We developed a brain morphometry method that is unbiased, rapid, reliable, and based on well-accepted stereological techniques. We now extend this method to analysis of routine computed tomographic (CT) scans such as might be obtained during a clinical stroke trial. METHODS: We studied CT scans from 18 stroke patients and 14 asymptomatic control patients obtained over 5 years at the San Diego Veterans Administration Medical Center. Three observers independently measured the volume of the cranial vault, cerebrum, cortex, white matter, deep gray structures, ventricle, sulcal cerebrospinal fluid space, visible infarction, and cerebellum/brain stem. RESULTS: The two patient groups were well matched demographically. The intracranial volume of 1400 +/- 40 mL in control subjects was not different from the 1311 +/- 41 mL in patients. Cerebral volume was 1250 +/- 36 mL compared with 1070 +/- 36 mL (control subjects versus patients, P < .001), and infarction volume was 55 +/- 16 mL in patients. For all structures, intraclass correlation coefficients among the observers ranged from 0.87 to 0.03; the best agreement was found for lesion, ventricle, and intracranial volume. White matter and cortex volume predicted the National Institutes of Health Stroke Scale score but not the late outcome scores on the Barthel Index or Rankin Scale. Each scan required 70 to 90 minutes for analysis. CONCLUSIONS: We developed a stereological method for cerebral morphometry from CT scans that is reliable, rapid, and simple. The measurements are unbiased, can be made on slices of any known thickness, and are independent of machine variables. Our results are remarkably similar to values obtained with more labor-intensive methods. This method should be of use in large-scale, multicenter trials of stroke therapy.
BACKGROUND AND PURPOSE: Clinical stroke trials require objective and reproducible end point variables. Morphometry of cerebral structures, including infarct volume, provides numerical measures that represent the amount of tissue damaged and potentially salvaged by therapy. However, morphometry may be time-consuming and labor-intensive, and it requires standardization across multiple centers, which may be difficult to achieve in large multicenter trials. We developed a brain morphometry method that is unbiased, rapid, reliable, and based on well-accepted stereological techniques. We now extend this method to analysis of routine computed tomographic (CT) scans such as might be obtained during a clinical stroke trial. METHODS: We studied CT scans from 18 strokepatients and 14 asymptomatic control patients obtained over 5 years at the San Diego Veterans Administration Medical Center. Three observers independently measured the volume of the cranial vault, cerebrum, cortex, white matter, deep gray structures, ventricle, sulcal cerebrospinal fluid space, visible infarction, and cerebellum/brain stem. RESULTS: The two patient groups were well matched demographically. The intracranial volume of 1400 +/- 40 mL in control subjects was not different from the 1311 +/- 41 mL in patients. Cerebral volume was 1250 +/- 36 mL compared with 1070 +/- 36 mL (control subjects versus patients, P < .001), and infarction volume was 55 +/- 16 mL in patients. For all structures, intraclass correlation coefficients among the observers ranged from 0.87 to 0.03; the best agreement was found for lesion, ventricle, and intracranial volume. White matter and cortex volume predicted the National Institutes of Health Stroke Scale score but not the late outcome scores on the Barthel Index or Rankin Scale. Each scan required 70 to 90 minutes for analysis. CONCLUSIONS: We developed a stereological method for cerebral morphometry from CT scans that is reliable, rapid, and simple. The measurements are unbiased, can be made on slices of any known thickness, and are independent of machine variables. Our results are remarkably similar to values obtained with more labor-intensive methods. This method should be of use in large-scale, multicenter trials of stroke therapy.
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