Diagnostic Development Services for Brain Tumors

Magnetic resonance imaging (MRI) can detect brain tumors, but most cases require biopsy sections to determine the type and severity of the tumor. Removal of brain tissue not only causes discomfort to the patient but in 2% of cases can cause stroke, paralysis, or even death. Therefore there is an urgent need to develop some new methods to enable researchers to diagnose brain tumors faster and more comprehensively.

We offer services for the development of diagnostic methods for brain tumors

More accurate diagnosis may improve the high mortality and low survival rates of brain tumors. However, tissue biopsies are invasive and may miss important information about tumor composition. Alfa Cytology is actively developing diagnostic methods for brain tumors, including artificial intelligence (AI) optical imaging systems, brain tumor blood tests, brain tumor fingerprint libraries, and biosensors. These non-invasive diagnostics allow researchers to monitor the development of brain tumors over time and obtain more definitive findings.

• AI optical imaging system

Stimulated Raman histology (SRH) provides fast, label-free, submicron-resolution images of unprocessed biological tissue. SRH uses the inherent vibrational properties of lipids, proteins, and nucleic acids to produce image contrast, revealing diagnostic microscopic features and histological findings that are difficult to visualize with HE-stained images, while eliminating the artifacts inherent in frozen or smear tissue preparations.
We distinguish tumors from the non-infiltrating brain and non-diagnostic areas by identifying SRH images in a short time with a system that incorporates AI. This simplifies the practice of analyzing tissue samples while the patient is still on the operating table and helps guide brain surgery and subsequent treatment. The automated approach predicts the diagnosis in near real-time, creating a complementary pathway for brain tumor diagnosis independent of the traditional pathology laboratory.

• Brain tumor blood testing

We have been refining a method for brain tumor diagnosis based on the detection of circulating oncogenes (ctDNA) in tiny volumes in blood samples. to make it very sensitive in picking up even small amounts of highly specific tumor-derived signals in the blood. This strategy for detecting and differentiating common brain tumors in a non-invasive way gives you a more complete picture of the altered characteristics of tumors and offers the possibility for more specific, sensitive, and tumor-agnostic detection.

• Brain tumor fingerprinting library

Tumors contain higher levels of certain chemicals than normal tissue and are distributed differently in different types of tumors. Using nuclear magnetic resonance spectroscopy, we can identify the "chemical fingerprints" of a variety of brain tumors. This can be used to diagnose brain tumors without the need for a biopsy. We are actively promoting the use of this technique in combination with MRI scans for brain tumor detection.

• Biosensors

We use a high-intensity laser beam to form three-dimensional nickel-nickel oxide nanolayers on nickel chips. This process produces an ultra-sensitive biosensor that allows us to detect trace amounts of tumor-derived substances, such as nucleic acids, proteins, and lipids, that cross the blood-brain barrier into circulation. The sensor uses surface-enhanced Raman spectroscopy to detect these components and generates a molecular profile or fingerprint for each sample. Can help you find evidence of a brain tumor, determine its type, and predict its location in the brain.

• Deep learning model

We utilize a deep learning approach to achieve efficient and accurate brain tumor recognition using multi-scale deep convolutional neural networks. Not only does it improve the accuracy of recognition compared to traditional methods, but it also drastically increases processing speed, providing you with faster and more accurate classification results.

Please feel free to contact us to customize a brain tumor diagnostic strategy for your research needs.