Canhua Xu

Real-time Imaging and Detection of Intracranial Haemorrhage by Electrical Impedance Tomography in a Piglet Model

The aim of this study was to use electrical impedance tomography (EIT) to detect and image acute intracranial haemorrhage (ICH) in an animal model. Blood was infused into the frontal lobe of the brains of anaesthetized piglets and impedance was measured using 16 electrodes placed in a circle on the scalp. The EIT images were constructed using a filtered back-projection algorithm. The mean of all the pixel intensities within a region of interest – the mean resistivity value (MRV) – was used to evaluate the relative impedance changes in the target region. A symmetrical index (SI), reflecting the relative impedance on both sides of the brain, was also calculated. Changes in MRV and SI were associated with the injection of blood, demonstrating that EIT can successfully detect ICH in this animal model. The unique features of EIT may be beneficial for diagnosing ICH early in patients after cranial surgery, thereby reducing the risk of complications and mortality.

Temporal lobe seizure prediction based on a complex Gaussian wavelet

OBJECTIVE Abnormal synchronisation change is closely associated with the process of seizure generation. The immediate and accurate detection of the changes in synchronisation may offer advantages in seizure prediction. Thus, we develop a phase synchronisation detection method for this purpose. METHODS An analysis of phase synchronisation based on the complex Gaussian wavelet transform (PSW) was conducted to detect synchronised phases of long-lasting scalp electroencephalograph (EEG) recordings from eight epilepsy patients with intractable temporal lobe epilepsy. Four assessment indicators, namely sensitivity, maximum false prediction rate, seizure occurrence period and seizure prediction horizon were used to assess and compare PSW with the analysis of phase synchronisation, based on the Hilbert transform (PSH) and a random predictor Poisson process. RESULTS An obvious decrease was found upon phase synchronisation prior to visual detection of electroencephalograph seizure onset, which was consistent with the EEG mechanism in the ictal events. The results suggest that PSW is the most effective among the three prediction methods. CONCLUSIONS The results confirm that the analysis of phase synchronisation based on the complex Gaussian wavelet transform can be used for seizure prediction. SIGNIFICANCE Phase synchronisation analysis may be a useful algorithm for clinical application in epileptic prediction.

An optimized strategy for real-time hemorrhage monitoring with electrical impedance tomography

Delayed detection of an internal hemorrhage may result in serious disabilities and possibly death for a patient. Currently, there are no portable medical imaging instruments that are suitable for long-term monitoring of patients at risk of internal hemorrhage. Electrical impedance tomography (EIT) has the potential to monitor patients continuously as a novel functional image modality and instantly detect the occurrence of an internal hemorrhage. However, the low spatial resolution and high sensitivity to noise of this technique have limited its application in clinics. In addition, due to the circular boundary display mode used in current EIT images, it is difficult for clinicians to identify precisely which organ is bleeding using this technique. The aim of this study was to propose an optimized strategy for EIT reconstruction to promote the use of EIT for clinical studies, which mainly includes the use of anatomically accurate boundary shapes, rapid selection of optimal regularization parameters and image fusion of EIT and computed tomography images. The method was evaluated on retroperitoneal and intraperitoneal bleeding piglet data. Both traditional backprojection images and optimized images among different boundary shapes were reconstructed and compared. The experimental results demonstrated that EIT images with precise anatomical information can be reconstructed in which the image resolution and resistance to noise can be improved effectively.

In Vivo Imaging of Twist Drill Drainage for Subdural Hematoma: A Clinical Feasibility Study on Electrical Impedance Tomography for Measuring Intracranial Bleeding in Humans

Intracranial bleeding is one of the most severe medical emergencies in neurosurgery. Early detection or diagnosis would largely reduce the rate of disability and mortality, and improve the prognosis of the patients. Electrical Impedance Tomography (EIT) can non-invasively image the internal resistivity distribution within a human body using a ring of external electrodes, and is thus a promising technique to promptly detect the occurrence of intracranial bleedings because blood differs from other brain tissues in resistivity. However, so far there is no experimental study that has determined whether the intracranial resistivity changes in humans could be repeatedly detected and imaged by EIT. Hence, we for the first time attempt to clinically validate this by in vivo imaging the influx and efflux of irrigating fluid (5% dextrose in water, D5W) during the twist-drill drainage operation for the patients with subdural hematoma (SDH). In this study, six patients (four male, two female) with subacute or chronic SDH received the surgical operation in order to evacuate the hematoma around subdural region, and EIT measurements were performed simultaneously on each patient’s head. The results showed that the resistivity significantly increased on the corresponding position of EIT images during the influx of D5W and gradually decreased back to baseline during the efflux. In the quantitative analysis, the average resistivity values demonstrated the similar results and had highly linear correlation (R2 = 0.93±0.06) with the injected D5W volumes, as well as the area of the resistivity gain(R2 = 0.94±0.05). In conclusion, it was clinically validated that intracranial resistivity changes in humans were detectable and quantifiable by the EIT method. After further technical improvements, EIT has the great potential of being a routine neuroimaging tool for early detection of intracranial bleedings.

Real-time imaging of subarachnoid hemorrhage in piglets with electrical impedance tomography

Subarachnoid hemorrhage (SAH) is one of the most severe medical emergencies in neurosurgery. Early detection or diagnosis would significantly reduce the rate of disability and mortality, and improve the prognosis of the patients. Although the present medical imaging techniques generally have high sensitivity to identify bleeding, the use of an additional, non-invasive imaging technique capable of continuously monitoring SAH is required to prevent contingent bleeding or re-bleeding. In this study, electrical impedance tomography (EIT) was applied to detect the onset of SAH modeled on eight piglets in real time, with the subsequent process being monitored continuously. The experimental SAH model was introduced by one-time injection of 5 ml fresh autologous arterial blood into the cisterna magna. Results showed that resistivity variations within the brain caused by the added blood could be detected using the EIT method and may be associated not only with the resistivity difference among brain tissues, but also with variations of cerebrospinal fluid dynamics. In conclusion, EIT has unique potential for use in clinical practice to provide invaluable real-time neuroimaging data for SAH after the improvement of electrode design, anisotropic realistic modeling and instrumentation.

A New Head Phantom With Realistic Shape and Spatially Varying Skull Resistivity Distribution

Brain electrical impedance tomography (EIT) is an emerging method for monitoring brain injuries. To effectively evaluate brain EIT systems and reconstruction algorithms, we have developed a novel head phantom that features realistic anatomy and spatially varying skull resistivity. The head phantom was created with three layers, representing scalp, skull, and brain tissues. The fabrication process entailed 3-D printing of the anatomical geometry for mold creation followed by casting to ensure high geometrical precision and accuracy of the resistivity distribution. We evaluated the accuracy and stability of the phantom. Results showed that the head phantom achieved high geometric accuracy, accurate skull resistivity values, and good stability over time and in the frequency domain. Experimental impedance reconstructions performed using the head phantom and computer simulations were found to be consistent for the same perturbation object. In conclusion, this new phantom could provide a more accurate test platform for brain EIT research.

Exploratory Study on the Methodology of Fast Imaging of Unilateral Stroke Lesions by Electrical Impedance Asymmetry in Human Heads

Stroke has a high mortality and disability rate and should be rapidly diagnosed to improve prognosis. Diagnosing stroke is not a problem for hospitals with CT, MRI, and other imaging devices but is difficult for community hospitals without these devices. Based on the mechanism that the electrical impedance of the two hemispheres of a normal human head is basically symmetrical and a stroke can alter this symmetry, a fast electrical impedance imaging method called symmetrical electrical impedance tomography (SEIT) is proposed. In this technique, electrical impedance tomography (EIT) data measured from the undamaged craniocerebral hemisphere (CCH) is regarded as reference data for the remaining EIT data measured from the other CCH for difference imaging to identify the differences in resistivity distribution between the two CCHs. The results of SEIT imaging based on simulation data from the 2D human head finite element model and that from the physical phantom of human head verified this method in detection of unilateral stroke.

Real-time imaging of cerebral infarction in rabbits using electrical impedance tomography

Objective To investigate the possible use of electrical impedance tomography (EIT) in monitoring focal cerebral infarction in a rabbit model. Methods A model of focal cerebral infarction was established in eight New Zealand rabbits using a photochemical method without craniectomy. Focal cerebral infarction was confirmed by histopathological examination. Intracranial impedance variation was measured using 16 electrodes placed in a circle on the scalp. EIT images were obtained using a damped least-squares reconstruction algorithm. The average resistivity value (ARV) of the infarct region on EIT images was calculated to quantify relative resistivity changes. A symmetry index was calculated to evaluate the relative difference in resistivity between the two sides of the cerebrum. Results EIT images and ARV curves showed that impedance changes caused by cerebral infarction increased linearly with irradiation time. A difference in ARV was found between measurements taken before and after infarct induction. Conclusions Focal cerebral infarction can be monitored by EIT in the proposed animal model. The results are sufficiently encouraging that the authors plan to extend this study to humans, after further technical improvements.

Comparison of Drive Patterns for Single Current Source EIT in Computational Phantom

Electrical impedance tomography (EIT) estimated the electrical conductivity distribution within a body. Bipolar drive pattern appeared in most EIT studies that the current was injected with a single current source and sink. In the present study, we built a computational phantom and compared the quality of dynamic EIT image in terms of data quality, resolution and anti-noise performance associated with three different bipolar drive patterns: polar drive pattern, pseudo-polar drive pattern and adjacent drive pattern. The results demonstrated that the pseudo-polar drive pattern is optimal.

Ex-Vivo Characterization of Bioimpedance Spectroscopy of Normal, Ischemic and Hemorrhagic Rabbit Brain Tissue at Frequencies from 10 Hz to 1 MHz

Stroke is a severe cerebrovascular disease and is the second greatest cause of death worldwide. Because diagnostic tools (CT and MRI) to detect acute stroke cannot be used until the patient reaches the hospital setting, a portable diagnostic tool is urgently needed. Because biological tissues have different impedance spectra under normal physiological conditions and different pathological states, multi-frequency electrical impedance tomography (MFEIT) can potentially detect stroke. Accurate impedance spectra of normal brain tissue (gray and white matter) and stroke lesions (ischemic and hemorrhagic tissue) are important elements when studying stroke detection with MFEIT. To our knowledge, no study has comprehensively measured the impedance spectra of normal brain tissue and stroke lesions for the whole frequency range of 1 MHz within as short as possible an ex vivo time and using the same animal model. In this study, we established intracerebral hemorrhage and ischemic models in rabbits, then measured and analyzed the impedance spectra of normal brain tissue and stroke lesions ex vivo within 15 min after animal death at 10 Hz to 1 MHz. The results showed that the impedance spectra of stroke lesions significantly differed from those of normal brain tissue; the ratio of change in impedance of ischemic and hemorrhagic tissue with regard to frequency was distinct; and tissue type could be discriminated according to its impedance spectra. These findings further confirm the feasibility of detecting stroke with MFEIT and provide data supporting further study of MFEIT to detect stroke.