23 Aug 2017 Austin - Cancer was first diagnosed 3,500 years ago in ancient Egypt. There, doctors removed tumours in a manner not dissimilar to what is done today: by surgically excising them from the body. Surgery remains the most frequently used approach to treat cancer, but it is not without its complications. Modern tools, from sterile, stainless steel scalpels to MRI imaging, have led to fewer complications and far better outcomes than in ancient Egypt, but haven't fundamentally altered the risks. Removing too little of a tumour can lead to a relapse; too much - especially in a critical area like the brain - can harm a patient.
A pioneering research project that ran from 2005 to 2012 used advanced computing resources to improve the precision with which doctors perform cancer surgery.
Researchers from the University of Texas at Austin, the University of Texas at San Antonio and the University of Texas MD Anderson Cancer Center - one of the USA's leading cancer research centres - developed a computer-driven, interactive system for planning, predicting and dynamically altering the course of a laser treatment for patients with cancer.
In 2008, after three years of research and development in algorithms, computer codes, imaging technology, and cyberinfrastructure, scientists used the Ranger supercomputer at the Texas Advanced Computing Center (TACC) to perform a minimally invasive laser treatment on a canine prostate without the intervention of a surgeon. The work was supported by a grant from the National Science Foundation's (NSF) Dynamic Driven Application Systems initiative.
At the heart of the technology was an adaptive-feedback control system based on mathematical and computational models that used Magnetic Resonance Temperature Imaging to determine the heat transferred by a laser to the tissue and the tissue's response.
The approach enabled the automated model to select the appropriate action, moment by moment, based on criteria determined in advance.
"It's a long process before these protocols are made robust and have wide-spread use in human subjects. But this is a step along a path that will be followed", J. Tinsley Oden, director of the Institute for Computation Engineering and Sciences at UT Austin, stated at the time.
David Fuentes, then a post-doctoral candidate at UT Austin and now a researcher and faculty member at MD Anderson, was also involved in the project.
With continuing support from NSF, Medtronic and others, David Fuentes has continued to develop treatment protocols for laser surgery on the brain. NSF-funded supercomputers at TACC have enabled David Fuentes to continue to simulate bioheat transfer in brain tissue and to calculate more accurate surgical outcomes.
Laser surgery on the brain involves many variables, including blood flow, optical properties, material properties, and thermal conductivity inside the body.
"The more data and images that can be acquired, the more confidence researchers and surgeons can have in planning surgical simulations", stated David Fuentes.
Working in collaboration with Rice University scientists, David Fuentes and his collaborators are currently adapting the methods they developed for supercomputers into a portable system for operating rooms.
Their early results suggest that someday soon, doctors may compute the results of surgeries as they occur using algorithms first tested at TACC.
Supercomputers, in this way, serve as testbeds for future medical technologies and harbingers for next-generation treatments.