Cancer cell
Cancer cell

Researchers at Johns Hopkins Medicine (Baltimore, MD) have created a new computer program designed to help scientists quantify the structural and functional changes in the blood flow networks feeding tumors. Because abnormal tumor hemodynamics is a critical determinant of a tumor’s microenvironment (TME), and profoundly affects drug delivery, therapeutic efficacy and the emergence of drug and radio-resistance, quantifying may be important in understanding the tumor and disease progression.

The development of the program, called HemoSYS, as well as an accompanying manual with instructions on how to use it, was supported by grants from the National Cancer Institute and a Kavli Neuroscience Distinguished Fellowship.

“Compared to blood flow in healthy tissues, tumor blood flow is abnormal, and these abnormalities can be captured with new imaging methods,” explained Arvind P. Pathak, Ph.D., associate professor of radiology and biomedical engineering at the Johns Hopkins University School of Medicine and a member of the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center.

“Therefore, we created a freely available toolkit called HemoSYS that enables scientists to quantify these abnormalities from imaging data acquired from tumors in live animals” Pathak added.

Providing insights
“Studying the architecture of blood vessels and their flow dynamics in tumors could provide insights into cancer progression and metastasis, noted Janaka Senarathna, Ph.D., a research fellow in Pathak’s lab and lead author of the paper.

Advertisement #3
Arvind P. Pathak, Ph.D., Associate Professor of Radiology and Radiological Science. Photo courtesy: The Johns Hopkins University, The Johns Hopkins Hospital, and The Johns Hopkins Health System Corporation.
Arvind P. Pathak, Ph.D., Associate Professor of Radiology and Radiological Science. Photo courtesy: The Johns Hopkins University, The Johns Hopkins Hospital, and The Johns Hopkins Health System Corporation.

“This approach could accelerate the development of new therapies that target a tumor’s blood vessels in order to limit its supply of nutrients and oxygen. HemoSYS could also lead to the more effective delivery of already available drugs by mapping blood flow fluctuations in the vessels feeding the tumor,” Senarathna further said.

Survival and growth
A tumor’s blood vessels are its lifeline for survival and growth, providing it with nutrients as well as an avenue for tumor cells to spread to other parts of the body. However, these vessels often grow irregularly and create abnormal blood flow patterns, making them a huge hurdle to the effective delivery of therapeutics.

“The abnormal blood flow makes it difficult to predict how effective therapies will be, and if an insufficient drug is delivered to the tumor, cancers may recur or develop resistance to treatment or advance harmful side effects,” Pathak noted.

The Johns Hopkins investigators caution that the research tool is not directly applicable to human tumors yet.

“As our ability to obtain high-resolution images in the clinic improves, we hope that this tool can be adapted to provide a noninvasive way to analyze the blood flow fluctuations in an individual patient’s cancer and help to customize their therapy,” Pathak said.

To develop the program, Pathak’s Laboratory recruited biomedical engineers and biophysicists to develop accurate, efficient ways to quantify “multivariable” data comprised of tumor blood flow, blood volume, and oxygenation images. A different type of light source was used to collect each of these data variables from tumors implanted in animals. The program was designed using the powerful image processing platform MATLAB (Mathworks, MA) and does not require any programming expertise to operate.

“Typically, a research lab studying these blood vessel systems would need to have extensive expertise in image processing to quantify the relationships between these measurements,” Pathak said.

“HemoSYS allows researchers without any programming expertise to conduct their analyses on these multivariable imaging data,” he added.

Multiple imaging systems
HemoSYS employs multivariable time-series data including in vivo tumor blood flow (BF), blood volume (BV) and intravascular oxygen saturation (Hbsat) acquired concurrently using a wide-field multi-contrast optical imaging system.

To analyze and integrate the different kinds of data, the HemoSYS program uses fundamental engineering principles.

“This data enables scientists to rigorously map the entire “hemodynamic landscape” of the tumor being studied,” Pathak explained.

The result is a colorful yet informative visualization that shows the relationships among blood flow, oxygenation and tumor cells in vivid reds, blues, and greens.

“The system lets researchers see that there may be an area in the tumor of low oxygen supply caused by poor blood flow, or see that an area is low on oxygen even though it’s exhibiting elevated blood volume,” Pathak noted.

Scientists and clinicians can download the toolkit at Pathak and his team have also made a customizable version for those who want to adapt HemoSYS for their own experiments or for data acquired with other imaging methods such as MRI, ultrasound and dynamic CT.

Senarathna J, Prasad A, Bhargava A, Gil S, Thakor NV, Pathak AP. HemoSYS: A Toolkit for Image-based Systems Biology of Tumor Hemodynamics. Sci Rep 10, 2372 (2020). [Article]

Advertisement #5