Tianjin Polytechnic University to Transfer Local Cerebral Blood Flow Speckle Imaging Technology for RMB 600,000
Recently, Tiangong University released a public notice on the conversion of scientific and technological achievements, proposing to transfer its“Near-Infrared Diffuse Correlation Spectroscopy for Local Cerebral Blood Flow Speckle Imaging: Device and Detection Method”Transferred to Tianjin Baiwangda Technology Co., Ltd. via patent assignment, with a proposed transaction amount of600,000 yuan。
This patent is held byHan Guang, Chen Siqi, et al. (5 individuals)Joint R&D, belongs toBiomedical Testing Equipment Sectortechnical achievements. This patent overcomes the technical limitations of traditional cerebral blood flow detection methods. By employing an optical heterodyne detection structure and improved laser speckle imaging technology, it enables non-invasive detection of local cerebral blood flow in deep head tissues. It also facilitates the reconstruction of relative velocity indices and two-dimensional flow velocity imaging, effectively addressing issues such as insufficient sensitivity and interference from scalp blood flow encountered in conventional detection methods. This provides a novel technical solution for the medical assessment of cerebral diseases, including cerebrovascular disorders and Alzheimer’s disease.
Cerebrovascular DiseaseAs a major disease characterized by high incidence, high recurrence, high disability, and high mortality rates, there is an urgent need for precise and efficient cerebral blood flow detection technologies. However, traditional detection methods primarily rely on photon detection technology to amplify single-photon optical effects. The core components suffer from performance trade-offs: photomultiplier tubes offer high optical conversion gain but low quantum efficiency, while avalanche photodiodes provide high quantum efficiency but lower gain, making it difficult to balance detection efficiency with accuracy.
Furthermore, the single-photon counting rate of conventional techniques is temporally constrained, resulting in poor continuous monitoring performance and precluding dynamic tracking and detection of cerebral blood flow. These methods can only acquire one-dimensional, time-dependent hemodynamic information, making it difficult to achieve two-dimensional imaging of cerebral tissue blood flow with high temporal resolution. Consequently, they fail to meet the clinical demand for precise analysis of the spatial distribution and cross-sectional characteristics of cerebral blood flow.
Furthermore, conventional techniques struggle to mitigate interference from scalp blood flow, making it impossible to directly extract localized cerebral blood flow information from deep brain regions. This significantly compromises the specificity and accuracy of detection results and precludes hemodynamic probing of brain tissues at varying depths. These technical limitations hinder the effective application of traditional methods in early screening, disease assessment, and dynamic monitoring of neurological disorders, creating an urgent market demand for novel cerebral blood flow detection technologies capable of overcoming these constraints.
This patented technology centers on non-invasive cerebral blood flow detection, featuring multiple core innovations, ranging fromFrom Hardware Architecture and Detection Methods to Algorithm ApplicationsAchieving comprehensive technological breakthroughs to precisely address the various pain points of traditional testing.
The first is the modular and adjustable design innovation of hardware architecture,Build aLight Source Module, Optical Heterodyne Detection Module, Imaging Acquisition Modulean integrated detection device. The laser source employs a fiber Bragg grating semiconductor laser with a central wavelength of 851.1 nm, coupled with a temperature control system to ensure source stability. Meanwhile, the optical heterodyne detection module is equipped with a rotating adjustment rod to enable a flexible and adjustable source-detector distance ranging from 0 to 4 cm, accommodating detection requirements at various depths within the brain. Furthermore, precise allocation and combination of optical signals are achieved through a single-mode fiber splitter with a 1:9 splitting ratio and a multimode fiber coupler with a 1:1 splitting ratio, thereby balancing detection efficiency with signal accuracy.
Second, the innovative application of optical heterodyne detection technology,By abandoning the core approach of traditional photon detection technology and instead generating and acquiring beat-frequency signals through an optical heterodyne detection configuration, interference from scalp blood flow on detection results can be effectively avoided. This method directly extracts cerebral blood flow information from deep brain tissues, while significantly enhancing the sensitivity and detection accuracy of non-invasive spectroscopic measurements, thereby addressing the poor performance of conventional techniques in deep-tissue detection.
Third, process-oriented and standardized innovations in detection methodologies.A complete inspection workflow has been designed, encompassing laser emission, beam splitting and signal transmission, signal light acquisition, coherent beam combining, as well as speckle imaging and data processing. High-resolution laser speckle images are captured using a high-speed CMOS camera with a maximum resolution of 1088×2048 pixels. Imaging parameters can be preset via computer, thereby enhancing the controllability and reproducibility of the inspection process.
Fourth, improvements and innovations in algorithms and imaging technologies,Based on improved laser speckle imaging technology, we developed a near-infrared diffuse coherent spectral speckle contrast analysis algorithm to extract flow velocity eigenvalues by estimating and correcting system noise. This approach not only enables accurate reconstruction of the relative cerebral blood flow velocity index but also achieves two-dimensional flow velocity imaging with high temporal resolution. Furthermore, it allows for the calculation of blood flow volume based on vascular cross-sectional area, realizing a technological leap from one-dimensional information detection to two-dimensional visualized imaging and filling the gap left by traditional techniques in analyzing the spatial distribution of cerebral blood flow.
Currently, the global field of cerebral blood flow detection has witnessed mature technological development, forming a landscape where multiple technical pathways coexist and numerous products have been implemented in clinical practice. Different types of products are tailored to diverse clinical detection scenarios based on their respective technical characteristics.
Transcranial Doppler (TCD) Ultrasound Blood Flow Monitoring ProductsThis is the most widely used category in clinical practice. For example, Shenzhen Delikai’s EMS-9DPro/EMS-9F Transcranial Doppler (TCD) Blood Flow Analyzer has obtained multiple international certifications. Leveraging the ultrasonic Doppler effect, it enables precise detection of intracranial blood flow velocity, direction, and spectral morphology, making it suitable for various scenarios such as the diagnosis and treatment of neurological critical care and cerebrovascular diseases. However, its detection dimensions are limited; it can only acquire hemodynamic parameters and cannot achieve visualized imaging of cerebral tissue blood flow.
Imaging-Assisted Assessment ProductsIt leverages AI technology to achieve precise analysis of cerebral blood flow perfusion, such as Shukun Technology’s AI product for CT perfusion in cerebral ischemia. Certified by authoritative bodies in multiple countries, it can fully automate functional analysis of cerebral tissue perfusion, rapidly localize the infarct core and hypoperfused regions, and significantly improve the timeliness of cerebral blood flow analysis in the diagnosis and treatment of acute cerebral ischemia and stroke, serving as a critical tool for collaborative care between radiology and neurology departments. However, it exhibits strong dependence on upstream imaging equipment, provides only intermittent assessments, and lacks real-time monitoring capabilities.
Innovative Non-Invasive Imaging ProductsIt is also undergoing continuous development. For instance, Yi Ai Medical’s EIT-B300/B400 cerebral electrical impedance tomography system employs electrical impedance tomography technology to enable dynamic imaging and monitoring of cerebral blood flow. The company has also deployed warning headbands tailored for daily health management, thereby extending its applications from clinical testing to public health monitoring. However, its current focus remains primarily on monitoring blood flow trends, lacking the capability for precise pathological diagnosis, with its functionality still at an early stage.