Spectral correction for handheld optoacoustic imaging by means of near-infrared optical tomography in reflection mode.

In vivo imaging of tissue/vasculature oxygen saturation levels is of prime interest in many clinical applications. To this end, the feasibility of combining two distinct and complementary imaging modalities is investigated: optoacoustics (OA) and near-infrared optical tomography (NIROT), both operating noninvasively in reflection mode. Experiments were conducted on two optically heterogeneous phantoms mimicking tissue before and after the occurrence of a perturbation. OA imaging was used to resolve submillimetric vessel-like optical absorbers at depths up to 25 mm, but with a spectral distortion in the OA signals. NIROT measurements were utilized to image perturbations in the background and to estimate the light fluence inside the phantoms at the wavelength pair (760 nm, 830 nm). This enabled the spectral correction of the vessel-like absorbers' OA signals: the error in the ratio of the absorption coefficient at 830 nm to that at 760 nm was reduced from 60%-150% to 10%-20%. The results suggest that oxygen saturation (SO 2 ) levels in arteries can be determined with <10% error and furthermore, that relative changes in vessels' SO 2 can be monitored with even better accuracy. The outcome relies on a proper identification of the OA signals emanating from the studied vessels.

A New Method Based on Graphics Processing Units for Fast Near-Infrared Optical Tomography.

The accuracy of images obtained by Diffuse Optical Tomography (DOT) could be substantially increased by the newly developed time resolved (TR) cameras. These devices result in unprecedented data volumes, which present a challenge to conventional image reconstruction techniques. In addition, many clinical applications require taking photons in air regions like the trachea into account, where the diffusion model fails. Image reconstruction techniques based on photon tracking are mandatory in those cases but have not been implemented so far due to computing demands. We aimed at designing an inversion algorithm which could be implemented on commercial graphics processing units (GPUs) by making use of information obtained with other imaging modalities. The method requires a segmented volume and an approximately uniform value for the reduced scattering coefficient in the volume under study. The complex photon path is reduced to a small number of partial path lengths within each segment resulting in drastically reduced memory usage and computation time. Our approach takes advantage of wavelength normalized data which renders it robust against instrumental biases and skin irregularities which is critical for realistic clinical applications. The accuracy of this method has been assessed with both simulated and experimental inhomogeneous phantoms showing good agreement with target values. The simulation study analyzed a phantom containing a tumor next to an air region. For the experimental test, a segmented cuboid phantom was illuminated by a supercontinuum laser and data were gathered by a state of the art TR camera. Reconstructions were obtained on a GPU-installed computer in less than 2 h. To our knowledge, it is the first time Monte Carlo methods have been successfully used for DOT based on TR cameras. This opens the door to applications such as accurate measurements of oxygenation in neck tumors where the presence of air regions is a problem for conventional approaches.