Time Is Brain—Quantified

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Abstract

The phrase "time is brain" emphasizes that human nervous tissue is rapidly lost as stroke progresses and emergent evaluation and therapy are required. Recent advances in quantitative neurostereology and stroke neuroimaging permit calculation of just how much brain is lost per unit time in acute ischemic stroke. Systematic literature-review identified consensus estimates of number of neurons, synapses, and myelinated fibers in the human forebrain; volume of large vessel, supratentorial ischemic stroke; and interval from onset to completion of large vessel, supratentorial ischemic stroke. The typical final volume of large vessel, supratentorial ischemic stroke is 54 mL (varied in sensitivity analysis from 19 to 100 mL). The average duration of nonlacunar stroke evolution is 10 hours (range 6 to 18 hours), and the average number of neurons in the human forebrain is 22 billion. In patients experiencing a typical large vessel acute ischemic stroke, 120 million neurons, 830 billion synapses, and 714 km (447 miles) of myelinated fibers are lost each hour. In each minute, 1.9 million neurons, 14 billion synapses, and 12 km (7.5 miles) of myelinated fibers are destroyed. Compared with the normal rate of neuron loss in brain aging, the ischemic brain ages 3.6 years each hour without treatment. Altering single input variables in sensitivity analyses modestly affected the estimated point values but not order of magnitude. Quantitative estimates of the pace of neural circuitry loss in human ischemic stroke emphasize the time urgency of stroke care. The typical patient loses 1.9 million neurons each minute in which stroke is untreated.

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Unbiased stereological estimation of the number of neurons in the human hippocampus.

M West, H J Gundersen (1990)

The total numbers of neurons in five subdivisions of human hippocampi were estimated using unbiased stereological principles and systematic sampling techniques. The method addresses the problems associated with the results and conclusions of previous quantitative studies, virtually all of which have been based on biased estimates of neuron densities. For each subdivision, the total number of neurons was calculated as the product of the estimate of the volume of the neuron-containing layers and the estimate of the numerical density of neurons in the layers. Each hippocampus was cut into 3-mm-thick slabs, transverse to the rostrocaudal axis. One 70-micron-thick section from each slab was used in the analysis. The volumes of the layers containing neurons in five major subdivisions of the hippocampus (granule cell layer, hilus, CA3-2, CA1, and subiculum) were estimated with point-counting techniques after delineation of the layers on each section. The numerical densities of neurons in each subdivision were estimated on the same sections with optical disectors. The sampling used in both estimates was performed systematically in all three dimensions. In an example of five hippocampi, the mean numbers of neurons (CV = SD/mean) in the different subdivisions were as follows: granule cells 15 X 10(6) (0.28), hilus 2.0 X 10(6) (0.16), CA3-2 2.7 X 10(6) (0.22), CA1 16 X 10(6) (0.32), subiculum 4.5 X 10(6) (0.19). The stereological measurements contributed approximately 25% of the observed variance. Among the five subjects there was a significant inverse relationship between age (which ranged from 47 to 85 years) and the total number of neurons in CA1 (which ranged from 24 to 11 X 10(6)). An optimized sampling scheme for studies of the number of neurons in the human hippocampus has been designed on the basis of an analysis of variance of the estimates at different levels of the sampling scheme. Counting neurons in the five subdivisions of the human hippocampus with the optimized sampling scheme takes less than 4 hours.

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Age and National Institutes of Health Stroke Scale Score within 6 hours after onset are accurate predictors of outcome after cerebral ischemia: development and external validation of prognostic models.

, H Diener, Melissa Ziegler … (2003)

To date, no validated, comprehensive, and practicable model exists to predict functional recovery within the first hours of cerebral ischemic symptoms. The purpose of this study was to externally validate 2 prognostic models predicting functional outcome and survival at 100 days within the first 6 hours after onset of acute cerebral ischemia. On admission to a participating hospital, patients were registered prospectively and included according to defined criteria. Follow-up was performed 100 days after the event. With the use of prospectively collected data, 2 prognostic models were developed and internally calibrated in 1079 patients and externally validated in 1307 patients. By means of age and National Institutes of Health Stroke Scale (NIHSS) score as independent variables, model I predicts incomplete functional recovery (Barthel Index <95) versus complete functional recovery, and model II predicts mortality versus survival. In the validation data set, model I correctly predicted 62.9% of the patients who were incompletely restituted or had died and 83.2% of the completely restituted patients, and model II correctly predicted 57.9% of the patients who had died and 91.5% of the surviving patients. Both models performed better than the treating physicians' predictions made within 6 hours after admission. The resulting prognostic models are useful to correctly stratify treatment groups in clinical trials and should guide inclusion criteria in clinical trials, which in turn increases the power to detect clinically relevant differences.