Abstract
Intraoperative multispectral photoacoustic pathology assessment presents a promising approach to guide biopsy resection. In this study, we developed and validated a novel photoacoustic technique to differentiate between healthy and cancerous tissues. Our method consisted of photoacoustic contrast calculations as a function of wavelength, followed by projections of the resulting spectra from training data into a two-dimensional space using principal component analysis to create representative spectra, then calculation of the average cosine similarity between the spectrum of each pixel in test data and the representative spectra. The test healthy tissue region had a 0.967 mean correlation with the representative healthy tissue spectrum and a lower mean correlation (0.801) with the cancer tissue spectrum. The test cancer tissue region had a 0.954 mean correlation with the cancer tissue spectrum and a lower mean correlation (0.762) with the healthy tissue spectrum. Our method was further validated through qualitative comparison with high-resolution hematoxylin and eosin histopathology scans. Healthy tissue was primarily correlated with the optical absorption of blood (i.e., deoxyhemoglobin), while invasive ductal carcinoma breast cancer tissue was primarily correlated with the optical absorption of lipids. Our label-free histopathology approach utilizing multispectral photoacoustic imaging has the potential to enable real-time tumor margin determination during biopsy or surgery.