Prediction of tumor recurrence and therapy monitoring using ultrasound-guided photoacoustic imaging.

Abstract

Selection and design of individualized treatments remains a key goal in cancer therapeutics; prediction of response and tumor recurrence following a given therapy provides a basis for subsequent personalized treatment design. We demonstrate an approach towards this goal with the example of photodynamic therapy (PDT) as the treatment modality and photoacoustic imaging (PAI) as a non-invasive, response and disease recurrence monitor in a murine model of glioblastoma (GBM). PDT is a photochemistry-based, clinically-used technique that consumes oxygen to generate cytotoxic species, thus causing changes in blood oxygen saturation (StO2). We hypothesize that this change in StO2 can be a surrogate marker for predicting treatment efficacy and tumor recurrence. PAI is a technique that can provide a 3D atlas of tumor StO2 by measuring oxygenated and deoxygenated hemoglobin. We demonstrate that tumors responding to PDT undergo approximately 85% change in StO2 by 24-hrs post-therapy while there is no significant change in StO2 values in the non-responding group. Furthermore, the 3D tumor StO2 maps predicted whether a tumor was likely to regrow at a later time point post-therapy. Information on the likelihood of tumor regrowth that normally would have been available only upon actual regrowth (10-30 days post treatment) in a xenograft tumor model, was available within 24-hrs of treatment using PAI, thus making early intervention a possibility. Given the advances and push towards availability of PAI in the clinical settings, the results of this study encourage applicability of PAI as an important step to guide and monitor therapies (e.g. PDT, radiation, anti-angiogenic) involving a change in StO2.