Key Takeaways
- The Israel Institute of Technology has developed a noninvasive method to track cancer progression using chemical tomography.
- The method involves analyzing volatile organic compounds in exhaled breath, saliva, sweat, and other bodily fluids using a graphene-based sensor array.
- This approach has the potential to diagnose issues in various organs and transmit real-time health data to an external monitoring system, accelerating key advancements in personalised medicine and early disease detection.
Jerusalem: Israeli researchers have developed a new noninvasive method to monitor molecular processes deep within tissues in cancer and other diseases, the Israel Institute of Technology (Technion) said in a statement on Tuesday.
The approach, termed “chemical tomography,” allows researchers to track cancer progression at different stages, better understand cancer biology, and map biochemical pathways, metabolic markers, and molecular processes involved in cancer development.
Inspired by the compound eye of insects, the method provides insights into tissue function by analysing volatile organic compounds (VOCs) in exhaled breath, saliva, sweat, and other bodily fluids, using a graphene-based sensor array, with the graphene sensors acting as the eye and generative artificial intelligence as the brain to process data.
It allows for the continuous monitoring of structural and molecular changes in organoids and 3D cell-based models that replicate the characteristics of natural tissues, which are crucial in biomedical research. Unlike existing technologies that often damage tissues or fail to monitor deep-tissue processes, this method provides a “low-cost, accurate, and non-invasive” solution.
In study, VOC monitoring of a human breast tissue organoid revealed protein and genomic data linked to the transition of healthy tissues into cancerous ones.
Beyond cancer applications, the method has the potential to “diagnose issues in various organs” and “transmit real-time health data to an external monitoring system,” which is expected to accelerate key advancements in personalised medicine and early disease detection.
