TSPE: Reconstruction of multi-morphological tumors of NIR-II fluorescence molecular tomography based on positional encoding

Abstract

Background and Objective

Fluorescence molecular tomography (FMT) is a noninvasive and highly sensitive imaging modality, which can display 3D visualization of tumors by reconstructing fluorescence probes’ distribution. However, existing methods mostly ignore positional information, which includes spatial structure information crucial for the reconstruction of light sources. This limits the reconstruction accuracy of light sources with multiple morphologies. Therefore, to our best knowledge, we for the first time integrated positional encoding into the FMT task, enabling the incorporation of high-frequency spatial structure information.

Methods

We proposed a three-stage network embedded with a positional encoding module (TSPE) to perform high reconstruction accuracy of tumors with multiple morphologies. Additionally, our study focused on NIR-II which had less severe scattering problems and higher imaging accuracy than NIR-I.

Results

The simulation experiments demonstrated that TSPE achieved high reconstruction accuracy in NIR-II FMT, with the barycenter error (BCE) for single-tumor reconstruction reaching 0.18 mm, representing a 14 % reduction compared to other methods. TSPE more accurately distinguished adjacent multi-morphological tumors with a minimal edge-to-edge distance (EED) of 0.3 mm. In vivo experiments also showed that TSPE could achieve more accurate reconstruction of tumors compared with other methods.

Conclusions

The proposed method can achieve the best reconstruction performance. It has potential to promote the development of NIR-II FMT and its preclinical application.