Virtual imaging trials to investigate impact of skin color on three-dimensional optoacoustic tomography of the breast

Abstract

Optoacoustic tomography (OAT), also known as photoacoustic computed tomography, is being actively developed for breast imaging applications. The endogenous optical contrast in OAT images is associated with oxygen saturation and concentrations of chromophores, such as hemoglobin, melanin, fat, and water, within the tissue. In OAT breast imaging, near-infrared light propagates through the skin, where the optical energy is absorbed primarily by melanin. The photoacoustic effect results in the generation of a pressure wavefield, and the propagated pressure wavefield is measured by ultrasonic transducers located on a measurement aperture surrounding the breast. Thus, the melanin concentration influences lesion contrast in OAT images. However, the extent to which skin color affects lesion detectability in OAT breast imaging remains unexplored. To address this, we generate realistic optoacoustic 3D numerical breast phantoms containing a lesion at different locations (three depths and two polar angles) with five skin colors and virtually acquire optoacoustic data employing them. To assess the skin color impact on lesion detectability, we quantify numerical observer performance for a signal-known-exactly and background-known-exactly detection task. The results confirm that the signal-to-noise ratio of the test statistic is degraded in darker skin, and the extent depends on lesion locations and the light delivery system design.