Closed cerebral hemorrhage (CCH) is a common symptom in traumatic brain injury (TBI) patients who suffer intracranial hemorrhage with the dura mater remaining intact. The diagnosis of CCH patients prior to hospitalization and in the early stage of the disease can help patients get earlier treatments that improve outcomes. In this study, a noncontact, portable system for early TBI-induced CCH detection was constructed that measures the magnetic induction phase shift (MIPS), which is associated with the mean brain conductivity caused by the ratio between the liquid (blood/CSF and the intracranial tissues) change. To evaluate the performance of this system, a rabbit CCH model with two severity levels was established based on the horizontal biological impactor BIM-II, whose feasibility was verified by computed tomography images of three sections and three serial slices. There were two groups involved in the experiments (group 1 with 10 TBI rabbits were simulated by hammer hit with air pressure of 600 kPa by BIM-II and group 2 with 10 TBI rabbits were simulated with 650 kPa). The MIPS values of the two groups were obtained within 30 min before and after injury. In group 1, the MIPS values showed a constant downward trend with a minimum value of −11.17 ± 2.91° at the 30th min after 600 kPa impact by BIM-II. After the 650 kPa impact, the MIPS values in group 2 showed a constant downward trend until the 25th min, with a minimum value of −16.81 ± 2.10°. Unlike group 1, the MIPS values showed an upward trend after that point. Before the injury, the MIPS values in both group 1 and group 2 did not obviously change within the 30 min measurement. Using a support vector machine at the same time point after injury, the classification accuracy of the two types of severity was shown to be beyond 90%. Combined with CCH pathological mechanisms, this system can not only achieve the detection of early functional changes in CCH but can also distinguish different severities of CCH.

The hemorrhagic and the ischemic types of stroke have similar symptoms in the early stage, but their treatments are completely different. The timely and effective discrimination of the two types of stroke can considerable improve the patients' prognosis. In this paper, a 16-channel and noncontact microwave-based stroke detection system was proposed and demonstrated for the potential differentiation of the hemorrhagic and the ischemic stroke. In animal experiments, 10 rabbits were divided into two groups. One group consisted of five cerebral hemorrhage models, and the other group consisted of five cerebral ischemia models. The two groups were monitored by the system to obtain the Euclidean distance transform value of microwave scattering parameters caused by pathological changes in the brain. The support vector machine was used to identify the type and the severity of the stroke. Based on the experiment, a discrimination accuracy of 96% between hemorrhage and ischemia stroke was achieved. Furthermore, the potential of monitoring the progress of intracerebral hemorrhage or ischemia was evaluated. The discrimination of different degrees of intracerebral hemorrhage achieved 86.7% accuracy, and the discrimination of different severities of ischemia achieved 94% accuracy. Compared with that with multiple channels, the discrimination accuracy of the stroke severity with a single channel was only 50% for the intracerebral hemorrhage and ischemia stroke. The study showed that the microwave-based stroke detection system can effectively distinguish between the cerebral hemorrhage and the cerebral ischemia models. This system is very promising for the prehospital identification of the stroke type due to its low cost, noninvasiveness, and ease of operation.

Timely reperfusion of ischemic tissues and hemodynamic reconstruction are key to the treatment of acute ischemic stroke. The low temporal resolution of current imaging methods commonly used in clinical practice have the risk of diagnostic delay. In this study, a noninvasive cerebral blood flow (CBF) monitoring device was established based on inductive sensing technology, aiming at rapid and real-time assessment of ischemic tissue blood flow reperfusion to improve the treatment conditions and assess the prognostic outcome of acute ischemic stroke. The noninvasive CBF monitoring device was constructed using an inductive sensor and the LDC1612 evaluation module. Based on a homemade physical model of CBF pulsation and a healthy volunteer test, the depth and range of the sensor were evaluated by the time-domain amplitude and frequency-domain variation characteristics of resonant frequency. The monitoring results were processed using wavelet transform, high and low pass filtering, and cubic spline interpolation to remove the baseline and extract the CBF signal components. Based on the cardiogenic CBF pulsation mechanism, the periodic amplitude and area of CBF signals in resting and carbon dioxide inhalation states were extracted from healthy volunteers, and the feasibility of noninvasive monitoring of CBF by inductive sensing technology was evaluated. The experimental results showed that the method can evaluate the periodic pulsation of CBF and the changes of CBF in real-time with high accuracy. Thus, the present study verifies that the noninvasive CBF monitoring device based on inductive sensing technology can effectively detect the cardiac pulsations of CBF, which is expected to break the time window effect caused by the imaging examination and provide a new technology for noninvasive real-time monitoring of CBF perfusion changes.

BACKGROUND: Hemorrhagic stroke and ischemic stroke have similar symptoms at the onset of the disease, but their clinical treatment is completely different. The early, effective identification of stroke types can effectively improve the cure rate. OBJECTIVE: In this study, an early, noncontact identification of the stroke type, i.e., hemorrhagic or ischemic, based on a microwave measurement technique was investigated. METHODS: This study was based on animal models of cerebral hemorrhage and cerebral ischemia and the design of a microwave scattering parameter measurement system. RESULTS: The accuracy of the cerebral hemorrhage model with a blood loss interval of 2 ml reached 93.75%. While the accuracy of the cerebral ischemia model with an ischemic interval of 42 minutes reached 91.7%. CONCLUSION: The experimental results show that the system for identifying cerebral stroke based on microwaves can distinguish between cerebral hemorrhage and cerebral ischemia models and effectively distinguish between different degrees of cerebral hemorrhage or different durations of cerebral ischemia. This experimental system is inexpensive, portable, noninvasive, simple, and rapid and thus has good potential as a method for identifying the stroke type prior to hospitalization.

The purpose of this article is to improve the detection sensitivity and quantitative assessment of different levels of cerebral hemorrhage (CH), and a high-sensitivity and shielding-free rabbit brain magnetic induction phase shift (MIPS) scanner was developed and validated. First, a uniform rotating magnetic field generated by a birdcage coil was utilized instead of the divergent magnetic field for the first time, and the birdcage structure has inherent characteristics of shielding external interference. Furthermore, the primary field was canceled, and the axial and tangential magnetic field components of the secondary magnetic field were synchronously detected and then synthesized for the first time using a magnetron sensor coil and a circular solenoid coil. Specifically, a field-programmable gate array-based spectrometer was used to guarantee the two-channel signal of high-precision quadrature excitation for birdcage coil, signal acquisition, and data processing. Experimental results indicated that the phase shift difference decreases linearly with the volume increase of blood injection, and the average MIPS caused by a 3-mL blood injection of rabbit inner capsule hemorrhage was 2.709°, which was 7.7 times higher than that of the traditional single excitation coil and single receiving coil (single coil–coil) method. The results have proven that this scanner has high sensitivity, strong anti-interference ability, and potential to realize the quantitative detection of hematoma volume.

Acute cerebral ischemia is an important clinical disease that is usually detected by magnetic resonance imaging or computed tomography. The magnetic inductive phase shift (MIPS) is a new method for detecting cerebral diseases, which is non-invasive, miniaturized, and low-cost. A total of 25 rabbits were studied using a two-coil sensor with a 0.3-200 MHz frequency range, and all the subjects were measured for 1 hour. Based on the rabbit acute cerebral ischemia model, the rabbits were divided into unilateral ligation, bilateral ligation, and non-ligation groups. The results showed that the average MIPS values of the non-ligation, unilateral ligation, and bilateral ligation group were -0.195 ± 0.079°, -4.873 ± 1.042°, and -9.165 ± 2.862° respectively. MIPS distinguished different severities of cerebral ischemia in rabbits with statistical significance (p <; 0.05). Laser Doppler flowmetry (LDF) was used as the gold standard for collecting cerebral blood flow data. The strong correlation between the LDF measurements and the phase shift suggested that the phase shift reflects blood flow changes in the brain. Overall, these results suggest that the MIPS detection method has the potential to provide early detection of global cerebral ischemia. Furthermore, this method effectively distinguished different severities of cerebral ischemia.