Technology Overview

This technology is a system and method for ultrasound image and data analysis and ultrasound with contrast medium of human pancreatic tissues to automatically diagnose acute pancreatitis of the pancreas and identify pancreatic non-viable tissues at an early stage. It is one of the most accessible, safest (without ionizing radiation) and cheapest imaging methods to assess the condition of the pancreas and surrounding tissues, and other abdominal organs.

We are looking for companies to collaborate on research and development to further improve this system and also for companies keen to license this technology.

Technology Features, Specifications and Advantages

Our invention includes a specialized software for contrast studies (ultrasound) for in vivo ultrasound examinations of human internal organs, recording reflected ultrasound signals from pancreatic tissues (without contrast material and when contrast material is injected) and an image and data processing algorithm with artificial intelligence (neural network) elements providing a diagnostic estimate of a recommendatory nature.

Our solution is compatible with most ultrasound systems available in the market and have currently achieved more than 90% accuracy for our system.

Potential Applications

The invention is suitable for manufacturers of non-invasive contrast ultrasound diagnostic equipment and manufacturers of software for medical image analysis.

There is an opportunity to transfer the invention to alternative markets for non-invasive medical diagnostic technologies: magnetic resonance imaging (MRI) and computed tomography (CT)

Users: hospital radiology departments and radiologists

Buyers: Medical diagnostic equipment companies and hospitals

Customer Benefits

• Application of artificial intelligence algorithms for automated detection of problems in the pancreas in contrast-enhanced ultrasound diagnostic images. Until now, this is done manually based on the experience of the radiologist.
• Application of artificial intelligence algorithms for automated detection of problems in the pancreas by adaptive adjustment of the contour of the data selection area. Until now, this is done manually based on the experience of the radiologist.
• Quantification of pancreatic perfusion dynamics by comparative analysis of pancreatic volume, aorta and superior iliac artery. To date, no such assessment has been made.
• Spatial quantification of pancreatic parenchymal tissue viability in pancreatic volume by assessing the percentage of viable tissue areas and areas with tissues damaged by pathology (e.g., necrosis due to acute pancreatitis or malignancy). To date, contrast-enhanced ultrasound has no such functionality.
• Automated clinical decision support information for contrast-enhanced ultrasound examination for the radiologist, providing faster diagnosis of acute pancreatitis and other pathologies of the pancreas. Until now, there has been no such functionality.