Technique Combines Tumor Scans with Math Algorithms to Create Complex Tumor Models

Tumors can have a great deal of internal complexity, something which plays a central role in how cancer grow and protects themselves from attack. Understanding the structure of different types of tumors and how they come about may give researchers a way to address tumor growth. Currently, tumor models are fairly basic and don’t really provide a true picture of how tumors work on the insides, thereby remaining less useful than hoped for.

Now a team at Johns Hopkins has developed a tumor model that relies on real-world scans of tumors and data obtained from previously conducted studies. This model is unlike any other, since it was created by taking tumor specimens from animal models, making detailed scans of them using high-resolution MRI and micro-CT imaging, and applying various mathematical transformations, derived from experimental studies. The final result is a series of structural and functional maps, of things like oxygenation, vasculature, and blood velocity, that can be easily understood and made useful by researchers studying tumors.

The research was done on mice with human breast tumors and the blood vessel structures that were mapped were compared to similar structures studied previously. Using available scientific literature, the researchers applied data from previous studies to the structures in the scans, including parameters such as blood pressure, flow, and volume. This gave them the ability to use realistic, real-world numbers within a computer simulation based on real scans.

While the technology has no immediate clinical application, it will certainly help the research community better understand how tumors actually work.

Study in Nature Scientific Reports: Tumor Ensemble-Based Modeling and Visualization of Emergent Angiogenic Heterogeneity in Breast Cancer…

Via: Johns Hopkins Medicine