Scientists reach for the stars to find new radiation treatments

Compiled by BioPhotonics staff

Many have looked to the stars for inspiration, but could a new cancer therapy be up there as well?

Ohio State University astronomers think so. After studying how different chemical elements absorb and emit radiation in stars and around black holes, they found that heavy metals such as iron emit low-energy electrons when exposed to x-rays at specific energies. With the help of medical physicists and radiation oncologists, the team has developed a radiation treatment intended to be tougher on tumors but gentler on nearby healthy tissue.

The concept, called resonant nano-plasma theranostics (RNPT), uses x-rays to fire electrons at malignant cells to destroy them. The methodology could revolutionize both x-ray imaging and cancer therapy, the astronomers said.

Electrons orbit the nuclei of atoms at various distances, and when an electron closer to the nucleus is lost, a more distant one may drop in to take its place, releasing energy in a phenomenon known as the Auger effect.

The astronomers believe that K-alpha x-ray frequencies kick the close-in electrons out of heavy-metal atoms like platinum, causing many far-out electrons to fall in while many more are kicked out. The free Auger electrons are low in energy but great in number and could easily bombard malignant cells, shattering their DNA.

Typical therapeutic x-ray machines such as CT scanners generate full-spectrum x-rays, but with the new methodology, hospitals could employ RNPT using only K-alpha x-rays, greatly reducing a patient’s radiation exposure.

The scientists’ first experiment using the Auger effect demonstrated that it is possible to deliver specific frequencies of x-ray radiation to heavy-metal nanoparticles embedded in diseased tissue. The team is hopeful that, by targeting heavy-metal nanoparticles to certain sites in the body, x-ray imaging and therapy could become more precise and powerful, while radiation exposure would be reduced.

Research was funded by a Large Interdisciplinary Grant award from Ohio State, and computational resources were provided by the Ohio Supercomputer Center.