Researchers at the UC Davis Health department of radiology have introduced a new method that significantly reduces the time required for total-body PET imaging in cancer detection.

The approach, published in the Journal of Nuclear Medicine, uses a variation of the Patlak plot — called the relative Patlak plot — to generate high-quality parametric images in 20 minutes, down from the typical one-hour scan.

“Parametric PET imaging for cancer often provides better lesion contrast and quantification than conventional static PET imaging, but it typically requires a time of up to one hour, which poses challenges for widespread use,” said Guobao Wang, professor of radiology and senior author of the study. “However, with the method detailed in the paper, we can now make parametric imaging feasible for routine clinical PET scans in 20 minutes or less.”

The imaging was performed using EXPLORER, a total-body PET scanner co-developed by UC Davis and Shanghai-based United Imaging Healthcare. The scanner, first approved for clinical use at UC Davis, tracks the distribution of radioactive glucose tracers throughout the body. These tracers tend to accumulate in tumors due to their elevated metabolic activity, helping identify and assess cancer.

In a study involving 22 participants — 12 healthy and 10 with cancer — the research team tested the relative Patlak approach and found it provided results comparable to traditional parametric scans, despite the shorter acquisition time. A key challenge was reducing noise in the faster scans, which was addressed using a deep learning method called “deep kernel noise reduction,” developed by first author Siqi Li.

“We found the relative Patlak method is both feasible and accurate,” said Li. “Our images showed excellent lesion contrast and allowed us to better visualize the heart.”

Li is continuing to refine the method with support from a new research grant and is working with specialists at the UC Davis Comprehensive Cancer Center to adapt it for pediatric oncology.