A newly developed technique leverages integrin imaging and multi-bed-position dynamic PET acquisition to create advanced whole-body parametric maps, which could help evaluate tumors and metastases throughout the body, according to research presented at the Society of Nuclear Medicine and Molecular Imaging (SNMMI) 2015 annual meeting in Baltimore.
Ning Guo, PhD, a research fellow in the department of radiology at Massachusetts General Hospital and Harvard Medical School in Boston, showcased a study in which they used the radiotracer gallium-68 (Ga-68) and a peptide called arginine-glycine-aspartic acid (RGD), which has a natural affinity for integrin. Since integrin facilitates cellular signaling, it can be used to image tumors that have spread to other organs in the body.
Sixteen lung cancer patients were imaged used whole-body dynamic RGD-PET. Guo and colleagues used a technique in which the imaging bed shuttles between four different positions during an hour-long scan to provide quantitative analysis and parametric maps covering primary lung tumors and distant metastases.
Kinetic parameters used to build the parametric maps of binding potential showed a six-fold higher volume of distribution in tumors compared with muscle. “Comparing with static images, parametric maps showed substantial increase of tumor-background ratio and pixel-wise quantification of integrin expression in primary and metastatic lesions all over the body,” wrote the authors.
There was little difference between the standardized uptake value of primary and metastasis lesions on either RGD or FDG static images, according to Guo and colleagues.
If further research confirms the results and the technique is approved, the method could be used for lung cancer and, potentially, to detect a range of other cancers.
“For patients with multiple tumors, this technology could significantly improve the contrast and quantitation of their PET scans and, therefore, the quality of their care,” said Guo in a press release. “RGD imaging could contribute to earlier diagnosis and more accurate prognosis by not only discriminating between benign tumors, inflammation and malignancy but also providing insight about malignant lesions that are atypical or unclear – a common challenge when using FDG-PET.”