Facilitating in vivo tumor localization by principal component analysis based on dynamic fluorescence molecular imaging

Multi-target reconstruction strategy based on blind source separation of surface measurement signals in FMT

Fluorescence molecular tomography (FMT) is a promising molecular imaging technique for tumor detection in the early stage. High-precision multi-target reconstructions are necessary for quantitative analysis in practical FMT applications. The existing reconstruction methods perform well in retrieving a single fluorescent target but may fail in reconstructing a multi-target, which remains an obstacle to the wider application of FMT. In this paper, a novel multi-target reconstruction strategy based on blind source separation (BSS) of surface measurement signals was proposed, which transformed the multi-target reconstruction problem into multiple single-target reconstruction problems. Firstly, by multiple points excitation, multiple groups of superimposed measurement signals conforming to the conditions of BSS were constructed. Secondly, an efficient nonnegative least-correlated component analysis with iterative volume maximization (nLCA-IVM) algorithm was applied to construct the separation matrix, and the superimposed measurement signals were separated into the measurements of each target. Thirdly, the least squares fitting method was combined with BSS to determine the number of fluorophores indirectly. Lastly, each target was reconstructed based on the extracted surface measurement signals. Numerical simulations and in vivo experiments proved that it has the ability of multi-target resolution for FMT. The encouraging results demonstrate the significant effectiveness and potential of our method for practical FMT applications.

Enhancing in vivo renal ischemia assessment by high-dynamic-range fluorescence molecular imaging

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.

Methods for detecting host genetic modifiers of tumor vascular function using dynamic near-infrared fluorescence imaging

Vascular supply is a critical component of the tumor microenvironment (TME) and is essential for tumor growth and metastasis, yet the endogenous genetic modifiers that impact vascular function in the TME are largely unknown. To identify the host TME modifiers of tumor vascular function, we combined a novel genetic mapping strategy [Consomic Xenograft Model] with near-infrared (NIR) fluorescence imaging and multiparametric analysis of pharmacokinetic modeling. To detect vascular flow, an intensified cooled camera based dynamic NIR imaging system with 785 nm laser diode based excitation was used to image the whole-body fluorescence emission of intravenously injected indocyanine green dye. Principal component analysis was used to extract the spatial segmentation information for the lungs, liver, and tumor regions-of-interest. Vascular function was then quantified by pK modeling of the imaging data, which revealed significantly altered tissue perfusion and vascular permeability that were caused by host genetic modifiers in the TME. Collectively, these data demonstrate that NIR fluorescent imaging can be used as a non-invasive means for characterizing host TME modifiers of vascular function that have been linked with tumor risk, progression, and response to therapy.