The major therapy for ischemic stroke is thrombolytic treatment, but severe consequences occur when this method is used to treat hemorrhagic stroke. Currently, computed tomography and magnetic resonance imaging are used to differentiate between two types of stroke, but these two methods are ineffective for pre-hospital care. We developed a new brain diagnostic device for rabbits based on electromagnetic induction to non-invasively differentiate two types of stroke. The device includes two coils and a phase difference measurement system that detects the magnetic inductive phase shift (MIPS) value to reflect the tissue’s condition. The hemorrhage model was established through the injection of autologous blood into the internal capsule of a rabbit’s brain. Ischemia was induced in the brain of a rabbit by bilateral carotid artery occlusion. Two types of animal models were measured with our device. The MIPS value gradually decreased with increasing injected blood and increased with ischemia time. The MIPS changes induced by the two types of strokes were exact opposites, and the absolute values of MIPS variation in the hemorrhagic and the ischemic groups were significantly larger than those of the normal control group (P < 0.05). The tested technique can differentiate ischemic stroke from hemorrhagic stroke on rabbit brain in a non-invasive, continuous, and bulk monitoring manner by using a simple and inexpensive apparatus.

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.

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.

A 62-year-old man with situs inversus totalis and non-small-cell lung cancer underwent a right lower lobectomy by video-assisted thoracoscopic surgery. Lobectomy in a situs inversus totalis patient can be performed safely using this minimally invasive procedure. Preoperative evaluation of the pulmonary artery and veins by three-dimensional computed tomography and the bronchial tree by bronchoscopy, is essential to avoid unanticipated complications during the procedure.

Microwave detection is a prospective method in promptly identifying strokes, thereby facilitating clinical intervention and improved prognosis. We aimed to explore the factors affecting microwave stroke detection results, including brain tissue volume, composition, and motion artifacts. Various brain tissue conductivities were simulated using different concentrations of sodium chloride solutions. Physical experiments were conducted utilizing a microwave detection system, with observations focused on changes in S-parameters. Eigenvalue changes are most notable for volume alterations and motion artifacts. The eigenvalues of motion artifacts and volumes exhibit distinctions at specific frequencies. At 1.85 GHz, differences in the imaginary part of S 11 depend solely on volume variation. The study reveals that volume changes and motion artifacts significantly impact microwave detection outcomes. Motion artifacts can be initially mitigated by targeting specific frequency points. The optimal eigenvalues for characterizing volume changes are differences in imaginary parts of S 11 , and real parts of differences in S 21 serve as the optimal feature for characterizing composition changes.