High-Resolution Reconstruction of FMT Based on Elastic Net Optimized by Relaxed ADMM.

Fluorescence Molecular Tomography (FMT), providing thethree-dimensional fluorescent distribution information of specific molecular probes in tumors, is widely applied to detect in vivo tumors. However, the ill-posedness of reconstruction greatly affects the resolution of FMT. Traditional methods have introduced different regularization terms to solve this problem, but there are still challenges for the high-resolution reconstruction of small tumors under complex conditions. In this paper, we proposed an elastic net method optimized by the relaxed Alternating Direction Method of Multipliers (EN-RADMM) to improve the reconstruction resolution for small tumors. The objective function consisted of the Least-Square term and elastic net regularization. Relaxation, equivalent deformation directing at ill-posed equations, and LU decomposition were applied to accelerate algorithm convergence and improve solution accuracy. Thereby, the light from small tumors can be precisely reconstructed. We designed a series of digital tumor models with different distances, sizes, and shapes to verify the performance of EN-RADMM, and utilized the real glioma-bearing mouse models to further verify its feasibility and accuracy. The simulation results demonstrated that EN-RADMM can achieve significantly higher resolution and reconstruction accuracy of morphology and position with less time compared with other advanced methods. Furthermore, in vivo experiments proved the broad prospect of EN-RADMM in pre-clinical application of FMT reconstruction.

A Fast and Automated FMT/XCT Reconstruction Strategy Based on Standardized Imaging Space.

The traditional finite element method-based fluorescence molecular tomography (FMT)/ X-ray computed tomography (XCT) imaging reconstruction suffers from complicated mesh generation and dual-modality image data fusion, which limits the application of in vivo imaging. To solve this problem, a novel standardized imaging space reconstruction (SISR) method for the quantitative determination of fluorescent probe distributions inside small animals was developed. In conjunction with a standardized dual-modality image data fusion technology, and novel reconstruction strategy based on Laplace regularization and L1-fused Lasso method, the in vivo distribution can be calculated rapidly and accurately, which enables standardized and algorithm-driven data process. We demonstrated the method's feasibility through numerical simulations and quantitatively monitored in vivo programmed death ligand 1 (PD-L1) expression in mouse tumor xenografts, and the results demonstrate that our proposed SISR can increase data throughput and reproducibility, which helps to realize the dynamically and accurately in vivo imaging.

Low-Grade Nasopharyngeal Papillary Adenocarcinoma.

Low-grade nasopharyngeal papillary adenocarcinoma is a rare tumor, and only a limited number of cases are reported in the literature. The case reported in this study had long-term nasal catarrh with a runny nose and was admitted to the hospital. Computed tomography (CT) examination revealed polypoid mass in the nasopharynx. Pathological examination revealed typical papillary growth pattern of glandular epithelial cells. Immunohistochemical (IHC) staining showed the tumor cells to be diffusely positive for cytokeratin 7 (CK7), vimentin, and thyroid transcription factor 1 (TTF-1). The Ki-67 proliferation index was approximately 1%. In situ hybridization for latent Ebstein-virus (EBV) injection was negative. The patient did not exhibit recurrence or metastasis of the tumor.