Researchers at Rice University, in collaboration with Oak Ridge National Laboratory, have developed a new model that could lead to sharper imaging and safer diagnostics using magnetic resonance imaging, or MRI.

In a study recently published in The Journal of Chemical Physics, the team of researchers showed how they used the Fokker-Planck equation to better understand how water molecules respond to contrast agents in a process known as “relaxation.” Previous models only approximated how water molecules relaxed around contrasting agents. However, through this new model, known as the NMR eigenmodes framework, the research team has uncovered the “full physical equations” to explain the process.

“The concept is similar to how a musical chord consists of many notes,” Thiago Pinheiro, the study’s first author, a Rice doctoral graduate in chemical and biomolecular engineering and postdoctoral researcher in the chemical sciences division at Oak Ridge National Laboratory, said in a news release. “Previous models only captured one or two notes, while ours picks up the full harmony.”

According to Rice, the findings could lead to the development and application of new contrast agents for clearer MRIs in medicine and materials science. Beyond MRIs, the NMR relaxation method could also be applied to other areas like battery design and subsurface fluid flow.

“In the present paper, we developed a comprehensive theory to interpret those previous molecular dynamics simulations and experimental findings,” Dilipkumar Asthagiri, a senior computational biomedical scientist in the National Center for Computational Sciences at Oak Ridge National Laboratory, said in the release. ”The theory, however, is general and can be used to understand NMR relaxation in liquids broadly.”

The team has also made its code available as open source to encourage its adoption and further development by the broader scientific community.

“By better modeling the physics of nuclear magnetic resonance relaxation in liquids, we gain a tool that doesn’t just predict but also explains the phenomenon,” Walter Chapman, a professor of chemical and biomolecular engineering at Rice, added in the release. “That is crucial when lives and technologies depend on accurate scientific understanding.”

The study was backed by The Ken Kennedy Institute, Rice Creative Ventures Fund, Robert A. Welch Foundation and Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory.