Resolving tissue chromophore concentration at MRI resolution using multi-wavelength photo-magnetic imaging

Abstract

Photo-magnetic imaging (PMI) is an emerging optical imaging modality that showed great performance on providing absorption maps with high resolution and quantitative accuracy. As a multi-modality technology, PMI warms up the imaged object using a near infrared laser while temperature variation is measured using magnetic resonance imaging. By probing tissue at multiple wavelengths, concentration of the main tissue chromophores such as oxy- and deoxy-hemoglobin, lipid, and water are obtained then used to derive functional parameters such as total hemoglobin concentration and relative oxygen saturation. In this paper, we present a multi-wavelength PMI system that was custom-built to host five different laser wavelengths. After recovering the high-resolution absorption maps, a least-squared minimization process was used to resolve the different chromophore concentration. The performance of the system was experimentally tested on a phantom with two different dyes. Their concentrations were successfully assessed with high spatial resolution and average accuracy of nearly 80%.

Self-Guided Algorithm for Fast Image Reconstruction in Photo-Magnetic Imaging: Artificial Intelligence-Assisted Approach

“…Since the training data require a variety of cases, different inclusions were embedded into this background to mimic the presence of tumors. A set of 3927 cases was obtained by varying the size, location, and absorption coefficient of these inclusions [18,23,40]. Due to their higher concentration of hemoglobin, tumors are generally characterized with a higher optical absorption coefficient.…”

“…PMI is able to achieve higher spatial resolution than conventional DOI methods thanks to the utilization of magnetic resonance thermometry (MRT) for the measurement of the laser-induced internal spatiotemporal temperature [19,20]. Following data acquisition, the high-resolution optical absorption maps are obtained using a dedicated PMI reconstruction algorithm [21,22]. The image reconstruction is based on the minimization of the difference between the measured and synthetic spatiotemporal temperature maps, which are simulated by solving the combined diffusion and Pennes' bio-heat equations using the finite element method (FEM) [23][24][25].…”

“…Following data acquisition, the high-resolution optical absorption maps are obtained using a dedicated PMI reconstruction algorithm [21,22]. The image reconstruction is based on the minimization of the difference between the measured and synthetic spatiotemporal temperature maps, which are simulated by solving the combined diffusion and Pennes' bio-heat equations using the finite element method (FEM) [23][24][25]. This conventional FEM-based algorithm performs highly but remains limited by its relatively long computation time.…”

Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks

“…Diffuse Optical Imaging (DOT) is a non-invasive imaging technique that uses near-infrared (NIR) light to recover tissue chromophore concentrations, enabling the distinction between diseased and normal tissues [1][2][3][4][5]. However, DOT is limited by its inherent poor spatial resolution, hindering its use in clinical practice [6].…”

“…A dedicated finite element method (FEM)based solver is used to model light propagation and temperature diffusion in tissue [2,10,11]. Then, the difference between these modeled temperature maps and the measured MRT maps is minimized to obtain the high resolution optical absorption map of the tissue [3,4]. PMI identifies abnormalities in bio-tissues based on their higher absorption of NIR light.…”