BACKGROUND AND PURPOSE: A mathematical model has previously been introduced to estimate noninvasively intracranial pressure (nICP). In the present multicenter study, we investigated the ability of model to adapt to the state of cerebral autoregulation (SCA). This modification was intended to improve the quality of nICP estimation and noninvasive assessment of pressure reactivity of the cerebrovascular system. METHODS: We studied 145 patients after severe head injuries or stroke. All patients had direct ICP, arterial blood pressure (ABP), and transcranial Doppler middle cerebral artery blood flow velocity (FV) monitored. The SCA was assessed by moving correlation (Mx index) of cerebral perfusion pressure (CPP=ABP-ICP) and cerebral blood flow velocity and correlation of ABP and ICP (PRx index). nICP was calculated from ABP and FV waveforms. When nICP was used instead of ICP, the SCA was continuously estimated, and the model was dynamically adapted to the SCA. RESULTS: High and moderate correlations between invasively (Mx, PRx) and noninvasively (nMx, nPRx) estimated autoregulation indexes were observed (Mx: R=0.90, P<0.001; PRx: R=0.62, P<0.001). Values of Mx and nMx indicated contradictory SCA in 4 of 167 evaluated recordings; values of PRx and nPRx were contradictory in 27 recordings. When the model was adapted to the SCA, the mean error of ICP estimation decreased significantly (P<0.005). CONCLUSIONS: Continuous adaptation of the model to SCA improves the accuracy of noninvasive estimation of ICP and ICP dynamics. The same model provides a noninvasive and continuous assessment of SCA.
BACKGROUND AND PURPOSE: A mathematical model has previously been introduced to estimate noninvasively intracranial pressure (nICP). In the present multicenter study, we investigated the ability of model to adapt to the state of cerebral autoregulation (SCA). This modification was intended to improve the quality of nICP estimation and noninvasive assessment of pressure reactivity of the cerebrovascular system. METHODS: We studied 145 patients after severe head injuries or stroke. All patients had direct ICP, arterial blood pressure (ABP), and transcranial Doppler middle cerebral artery blood flow velocity (FV) monitored. The SCA was assessed by moving correlation (Mx index) of cerebral perfusion pressure (CPP=ABP-ICP) and cerebral blood flow velocity and correlation of ABP and ICP (PRx index). nICP was calculated from ABP and FV waveforms. When nICP was used instead of ICP, the SCA was continuously estimated, and the model was dynamically adapted to the SCA. RESULTS: High and moderate correlations between invasively (Mx, PRx) and noninvasively (nMx, nPRx) estimated autoregulation indexes were observed (Mx: R=0.90, P<0.001; PRx: R=0.62, P<0.001). Values of Mx and nMx indicated contradictory SCA in 4 of 167 evaluated recordings; values of PRx and nPRx were contradictory in 27 recordings. When the model was adapted to the SCA, the mean error of ICP estimation decreased significantly (P<0.005). CONCLUSIONS: Continuous adaptation of the model to SCA improves the accuracy of noninvasive estimation of ICP and ICP dynamics. The same model provides a noninvasive and continuous assessment of SCA.
Authors: Sunghan Kim; Fabien Scalzo; Marvin Bergsneider; Paul Vespa; Neil Martin; Xiao Hu Journal: IEEE Trans Biomed Eng Date: 2010-11-22 Impact factor: 4.538
Authors: Matthias Reinhard; Florian Neunhoeffer; Thomas A Gerds; Wolf-Dirk Niesen; Klaus-Juergen Buttler; Jens Timmer; Bernhard Schmidt; Marek Czosnyka; Cornelius Weiller; Andreas Hetzel Journal: Intensive Care Med Date: 2009-10-17 Impact factor: 17.440