Contribution of mathematical modelling to the interpretation of bedside tests of cerebrovascular autoregulation. Issue 6 (1st December 1997) - Czosnyka, Marek; Piechnik, Stefan; Richards, Hugh K; Kirkpatrick, Peter; Smielewski, Piotr; Pickard, John D
Abstract : OBJECTIVES: Cerebral haemodynamic responses to short and longlasting episodes of decreased cerebral perfusion pressure contain information about the state of autoregulation of cerebral blood flow. Mathematical simulation may help to elucidate which of the indices, that can be derived using transcranial Doppler ultrasonography and trends of intracranial pressure and blood pressure, are useful in clinical tests of autoregulatory reserve. METHODS: Time dependent interactions between pressure, flow, and volume of cerebral blood and CSF were modelled using a set of non-linear differential equations. The model simulates changes in arterial blood inflow and storage, arteriolar and capillary blood flow controlled by cerebral autoregulation, venous blood storage and venous outflow modulated by changes in ICP, and CSF storage and reabsorption. The model was used to simulate patterns of blood flow during either short or longlasting decreases in cerebral perfusion pressure. These simulations can be considered as clinically equivalent to a short compression of the common carotid artery, systemic hypotension, and intracranial hypertension. Simulations were performed in autoregulating and non-autoregulating systems and compared with recordings obtained in patients. RESULTS: After brief compression of the common carotid artery, a subsequent transient hyperaemia can be interpreted as evidence of intact autoregulation. During longlasting sustained hypoperfusion, a gradual increase in the systolic value of the blood flow velocity waveform along with a decrease in the diastolic value is specific for an autoregulating cerebrovascular system. CONCLUSION: Modelling studies help to interpret both clinical and experimental cerebral haemodynamic phenomena and their dependence on the state of autoregulation.