Predicting Tumor Recurrence Using Vevo LAZR
Submitted by Srivalleesha Mallidi, Ph.D., Research Fellow, Harvard Medical School, Wellman Center for Photomedicine, Boston, MA, USA
The unique feature of obtaining tumor structure and functional properties using the Vevo LAZR system enabled us to monitor therapies such as photodynamic therapy and predict tumor recurrence. By precisely monitoring the change in oxygen saturation within the 3D tumor volume, we could predict regions that did not have sufficient therapeutic effect and hence recurred at later time point. Information on the likelihood of tumor regrowth that normally would have been available only upon actual regrowth (10-30 days post treatment) in xenograft tumor model, was available within 24-hrs of treatment using PAI, thus making early intervention a possibility. We hope to extend this technique to guide and monitor various cancer targeted therapies. This work is recently published in Theranostics and was chosen for the cover feature.