The destruction of blood vessels is a commonly used cancer therapeutic strategy. Bleeding consequently follows and leads to the accumulation of blood in the interstitium. Photoacoustic (PA) imaging is well positioned to detect bleeding due to its sensitivity to hemoglobin. After treatment vascular disruption can occur within just a few hours, which leads to bleeding which might be detected using PA to assess therapeutic effectiveness. Deep micro-vessels cannot typically be resolved using acoustic-resolution PA. However, spectral analysis of PA signals may still permit assessment of bleeding. This paper introduces a theoretical model to simulate the PA signals from disrupted vessels using a fractal model. The fractal model uses bifurcated-cylinder bases to represent vascular trees. Vessels have circular absorption cross-sections. To mimic bleeding from blood vessels, the diffusion of hemoglobin from micro-vessels was simulated. The PA signals were computed and in the simulations were detected using a linear array transducer (30 MHz center frequency) for four different vascular trees (at 256 axial spatial locations/tree). The Fourier Transform of each beam-formed PA signal was computed and the power spectra were fitted to a straight line within the -6 dB bandwidth of the receiving transducer. When comparing the power spectra before and after simulated bleeding, the spectral slope and mid-band fit (MBF) parameters decreased by 0.12 dB/MHz and 2.12 dB, while the y-intercept did not change after 1 hour of simulated bleeding. The results suggest that spectral PA analysis is sensitive to changes in the concentration and spatial distribution of hemoglobin in tissue, and changes due to bleeding can be detected without the need to resolve individual vessels. The simulations support the applicability of PA imaging in cancer treatment monitoring by detecting micro-vessel disruption.
|