• Danilo Cardim, Chiara Robba, Joseph Donnelly, Michal Bohdanowicz, Bernhard Schmidt, Maxwell Damian, Georgios V Varsos, Xiuyun Liu, Manuel Cabeleira, Gustavo Frigieri, Brenno Cabella, Peter Smielewski, Sergio Mascarenhas, and Marek Czosnyka.
• 1 Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge , Cambridge, United Kingdom .
• J. Neurotrauma. 2016 Apr 15; 33 (8): 792-802.

AbstractElevation of intracranial pressure (ICP) may occur in many diseases, and therefore the ability to measure it noninvasively would be useful. Flow velocity signals from transcranial Doppler (TCD) have been used to estimate ICP; however, the relative accuracy of these methods is unclear. This study aimed to compare four previously described TCD-based methods with directly measured ICP in a prospective cohort of traumatic brain-injured patients. Noninvasive ICP (nICP) was obtained using the following methods: 1) a mathematical "black-box" model based on interaction between TCD and arterial blood pressure (nICP_BB); 2) based on diastolic flow velocity (nICP_FVd); 3) based on critical closing pressure (nICP_CrCP); and 4) based on TCD-derived pulsatility index (nICP_PI). In time domain, for recordings including spontaneous changes in ICP greater than 7 mm Hg, nICP_PI showed the best correlation with measured ICP (R = 0.61). Considering every TCD recording as an independent event, nICP_BB generally showed to be the best estimator of measured ICP (R = 0.39; p < 0.05; 95% confidence interval [CI] = 9.94 mm Hg; area under the curve [AUC] = 0.66; p < 0.05). For nICP_FVd, although it presented similar correlation coefficient to nICP_BB and marginally better AUC (0.70; p < 0.05), it demonstrated a greater 95% CI for prediction of ICP (14.62 mm Hg). nICP_CrCP presented a moderate correlation coefficient (R = 0.35; p < 0.05) and similar 95% CI to nICP_BB (9.19 mm Hg), but failed to distinguish between normal and raised ICP (AUC = 0.64; p > 0.05). nICP_PI was not related to measured ICP using any of the above statistical indicators. We also introduced a new estimator (nICP_Av) based on the average of three methods (nICP_BB, nICP_FVd, and nICP_CrCP), which overall presented improved statistical indicators (R = 0.47; p < 0.05; 95% CI = 9.17 mm Hg; AUC = 0.73; p < 0.05). nICP_PI appeared to reflect changes in ICP in time most accurately. nICP_BB was the best estimator for ICP "as a number." nICP_Av demonstrated to improve the accuracy of measured ICP estimation.

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