Photoacoustic Spectral Analysis for Evaluating the Aggressiveness of Prostate Cancer Labeled by Methylene Blue Polyacrylamide Nanoparticles.

Evaluating the aggressiveness of prostate cancer (PCa) is crucial for PCa diagnosis and prognosis. Previously, studies have shown that photoacoustic spectral analysis (PASA) can assess prostate tissue microarchitecture for evaluating the aggressiveness of PCa. In this study, in a transgenic mouse (TRAMP) model of PCa, we utilized methylene blue polyacrylamide nanoparticles (MB PAA NPs) to label the cancer cells in prostate in vivo. MB PAA NPs can specifically target proliferating cancer cells as a contrast agent, allowing photoacoustic (PA) imaging to better detect PCa tumors, and also assessing prostate glandular architecture. With the PA signals from the prostates measured simultaneously by a needle hydrophone and a PA and ultrasound (US) dual-imaging system, we conducted PASA and correlated the quantified spectral parameter slopes with the cancer grading from histopathology. The PASA results from 18 mice showed significant differences between normal and cancer, and also between low-score cancer and high-score cancer. This study in the clinically relevant TRAMP model of PCa demonstrated that PA imaging and PASA, powered by MB PAA NPs that can label the PCa microarchitectures in vivo after systemic administration, can detect PCa and, more importantly, evaluate cancer aggressiveness.

Personalized Oncology by In Vivo Chemical Imaging: Photoacoustic Mapping of Tumor Oxygen Predicts Radiotherapy Efficacy.

We hereby apply the approach of photoacoustic chemical imaging, performing an in vivo chemical analysis that is spatially resolved (200 µm) and in real time, to predict a given tumor's response to therapy. Using triple negative breast cancer as a model, we took photoacoustic images of tumors' oxygen distributions in patient-derived xenografts (PDXs) in mice using biocompatible, oxygen-sensitive tumor-targeted chemical contrast nanoelements (nanosonophores), which function as contrast agents for photoacoustic imaging. Following radiation therapy, we established a quantitatively significant correlation between the spatial distribution of the initial oxygen levels in the tumor and its spatial distribution of the therapy's efficacy: the lower the local oxygen, the lower the local radiation therapy efficacy. We thus provide a simple, noninvasive, and inexpensive method to both predict the efficacy of radiation therapy for a given tumor and identify treatment-resistant regions within the tumor's microenvironment.