Investigation of the optimal near-infrared wavelength for photoacoustic tomography in early submucosal gastric cancer diagnosis using finite element analysis and in vitro experiments

Near-infrared photoacoustic tomography (NIR-PAT) is a robust biomedical imaging modality that provides structural and functional information with superior resolution and high contrast, making it particularly suitable for cancer diagnosis. In this study, we utilized a commercial finite element simulation package to determine the optimal near-infrared wavelength for photoacoustic tomography of simulated early submucosal gastric cancer. Ex vivo experiments were conducted to validate the effectiveness of the proposed approach. Our findings indicate that 720 nm is the optimal wavelength, as it yields the maximum photoacoustic amplitude for simulated submucosal gastric tumors. The results demonstrate that the FE-based simulation model for photoacoustic signal generation can be effectively employed to rapidly select appropriate wavelengths for in vivo diagnosis of various types of submucosal gastric cancer.