OBJECTIVE: Total brain water content changes in several cerebral pathological conditions and the measurement of brain water content are important for the selection of appropriate therapeutic procedures. We present a quantitative, in vivo, bioelectrical impedance analysis (BIA) method and propose its use for the accurate assessment of brain water content among human subjects. METHODS: Cerebral BIA is based on the conduction of an applied current in the brain parenchyma. Application of an excitatory current of 800 microA at 50 kHz, via two electrodes placed on the eyelids with the eyes closed, and detection of the voltage drop with two electrodes placed in the suboccipital region allow brain resistance and reactance to be measured. By means of an equation that considers cranial circumference and resistance, it is possible to quantify the total brain water content, expressed as the bioelectrical volume. Cerebral BIA was performed with a series of healthy volunteers (n = 100), for determination of average brain water content values. The method was then applied to 50 patients with brain tumors (n = 20), intracranial hemorrhage (n = 16), or hydrocephalus (n = 14), for assessment of changes in global brain water contents. Data were compared with those obtained for healthy volunteers. RESULTS: Statistically significant differences (P < 0.001) were observed between the two groups. Mean brain water content values (expressed as bioelectrical volume values) were 38.2 +/- 3.9 cm2/Omega for healthy volunteers and 67.7 +/- 13.1 cm2/Omega for patients with cerebral pathological conditions. Statistically significant differences (P < 0.05) were also observed among patients with cerebral pathological conditions. CONCLUSION: The results of this study suggest that BIA, applied to the cerebral parenchyma, is a valid method for the prediction of brain water contents under both normal and pathological conditions. However, further studies are needed to establish whether it is sensitive and reliable enough for future clinical applications.
OBJECTIVE: Total brain water content changes in several cerebral pathological conditions and the measurement of brain water content are important for the selection of appropriate therapeutic procedures. We present a quantitative, in vivo, bioelectrical impedance analysis (BIA) method and propose its use for the accurate assessment of brain water content among human subjects. METHODS: Cerebral BIA is based on the conduction of an applied current in the brain parenchyma. Application of an excitatory current of 800 microA at 50 kHz, via two electrodes placed on the eyelids with the eyes closed, and detection of the voltage drop with two electrodes placed in the suboccipital region allow brain resistance and reactance to be measured. By means of an equation that considers cranial circumference and resistance, it is possible to quantify the total brain water content, expressed as the bioelectrical volume. Cerebral BIA was performed with a series of healthy volunteers (n = 100), for determination of average brain water content values. The method was then applied to 50 patients with brain tumors (n = 20), intracranial hemorrhage (n = 16), or hydrocephalus (n = 14), for assessment of changes in global brain water contents. Data were compared with those obtained for healthy volunteers. RESULTS: Statistically significant differences (P < 0.001) were observed between the two groups. Mean brain water content values (expressed as bioelectrical volume values) were 38.2 +/- 3.9 cm2/Omega for healthy volunteers and 67.7 +/- 13.1 cm2/Omega for patients with cerebral pathological conditions. Statistically significant differences (P < 0.05) were also observed among patients with cerebral pathological conditions. CONCLUSION: The results of this study suggest that BIA, applied to the cerebral parenchyma, is a valid method for the prediction of brain water contents under both normal and pathological conditions. However, further studies are needed to establish whether it is sensitive and reliable enough for future clinical applications.
Authors: Min Zhou; Yue Zhou; Huijun Liao; Benjamin C Rowland; Xiangquan Kong; Nils D Arvold; David A Reardon; Patrick Y Wen; Alexander P Lin; Raymond Y Huang Journal: Neuro Oncol Date: 2018-08-02 Impact factor: 12.300
Authors: Laurent Koessler; Sophie Colnat-Coulbois; Thierry Cecchin; Janis Hofmanis; Jacek P Dmochowski; Anthony M Norcia; Louis G Maillard Journal: Hum Brain Mapp Date: 2016-10-11 Impact factor: 5.038
Authors: Matthew T Harting; Carter T Smith; Ravi S Radhakrishnan; Kevin R Aroom; Pramod K Dash; Brijesh Gill; Charles S Cox Journal: J Surg Res Date: 2008-11-27 Impact factor: 2.192
Authors: Cesar A Gonzalez; Jose A Valencia; Alfredo Mora; Fernando Gonzalez; Beatriz Velasco; Martin A Porras; Javier Salgado; Salvador M Polo; Nidiyare Hevia-Montiel; Sergio Cordero; Boris Rubinsky Journal: PLoS One Date: 2013-05-14 Impact factor: 3.240