Fluorescence imaging has been used to evaluate the physiological features of renal ischemia in animal model. However, the fluorophore distribution details of the ischemia model could not be fully represented due to the limited dynamic range of the charged-couple device. A high-dynamic-range (HDR) strategy was adopted in renal ischemia fluorescence imaging, both ex vivo and in vivo. The HDR strategy successfully combined ischemia relevant biological features that could only be captured with different exposure times, and then presented these features in the HDR results. The HDR results effectively highlighted the renal ischemic areas with relatively better perfusion and diminished the saturation that resulted from long exposure time. The relative fluorescence intensities of the ischemic kidneys and the image entropy values were significantly higher in the HDR images than in the original images, therefore enhancing the visualization of the renal ischemia model. The results suggest that HDR could serve as a postprocessing strategy to enhance the assessment of in vivo renal ischemia, and HDR fluorescence molecular imaging could be a valuable imaging tool for future studies of clinical ischemia detection and evaluation.
Fluorescence molecular imaging has been used to target tumors in mice with xenograft tumors. However, tumor imaging is largely distorted by the aggregation of fluorescent probes in the liver. A principal component analysis (PCA)-based strategy was applied on the in vivo dynamic fluorescence imaging results of three mice with xenograft tumors to facilitate tumor imaging, with the help of a tumor-specific fluorescent probe. Tumor-relevant features were extracted from the original images by PCA and represented by the principal component (PC) maps. The second principal component (PC2) map represented the tumor-related features, and the first principal component (PC1) map retained the original pharmacokinetic profiles, especially of the liver. The distribution patterns of the PC2 map of the tumor-bearing mice were in good agreement with the actual tumor location. The tumor-to-liver ratio and contrast-to-noise ratio were significantly higher on the PC2 map than on the original images, thus distinguishing the tumor from its nearby fluorescence noise of liver. The results suggest that the PC2 map could serve as a bioimaging marker to facilitate in vivo tumor localization, and dynamic fluorescence molecular imaging with PCA could be a valuable tool for future studies of in vivo tumor metabolism and progression.
Dynamic fluorescence molecular tomography (DFMT) is a valuable method to evaluate the metabolic process of contrast agents in different organs in vivo, and direct reconstruction methods can improve the temporal resolution of DFMT. However, challenges still remain due to the large time consumption of the direct reconstruction methods. An acceleration strategy using graphics processing units (GPU) is presented. The procedure of conjugate gradient optimization in the direct reconstruction method is programmed using the compute unified device architecture and then accelerated on GPU. Numerical simulations and in vivo experiments are performed to validate the feasibility of the strategy. The results demonstrate that, compared with the traditional method, the proposed strategy can reduce the time consumption by ∼90% without a degradation of quality.