In vivo active-targeting fluorescence molecular imaging with adaptive background fluorescence subtraction

Abstract

Using active tumor-targeting nanoparticles, fluorescence imaging can provide highly sensitive and specific tumor detection, and precisely guide radiation in translational radiotherapy study. However, the inevitable presence of non-specific nanoparticle uptake throughout the body can result in high levels of heterogeneous background fluorescence, which limits the detection sensitivity of fluorescence imaging and further complicates the early detection of small cancers. In this study, background fluorescence emanating from the baseline fluorophores was estimated from the distribution of excitation light transmitting through tissues, by using linear mean square error estimation. An adaptive masked-based background subtraction strategy was then implemented to selectively refine the background fluorescence subtraction. First, an in vivo experiment was performed on a mouse intratumorally injected with passively targeted fluorescent nanoparticles, to validate the reliability and robustness of the proposed method in a stringent situation wherein the target fluorescence was overlapped with the strong background. Then, we conducted in vivo studies on 10 mice which were inoculated with orthotopic breast tumors and intravenously injected with actively targeted fluorescent nanoparticles. Results demonstrated that active targeting combined with the proposed background subtraction method synergistically increased the accuracy of fluorescence molecular imaging, affording sensitive tumor detection.

Keywords: active targeting; contrast CT; fluorescence background subtraction; fluorescence molecular imaging; fluorescence molecular tomography; image-guided irradiation; multi-modality imaging; nanoparticle imaging.

Figure 1

Schematic diagram of the multimodal CT/FMT imaging and image-guided irradiation platform.

Figure 2

(A) Schematic structure of PLGA-anti-EGFR nanoparticles. (B) Longitudinal comparison of tumor accumulation for active (anti-EGFR) and passive targeting PLGA nanoparticles.

Figure 3

(A) Fluorescence image; red circle tumor signal, dotted circle gut uptake signal, left rectangle filter leakage animal holder signal, and right rectangle filter leakage mouse fur signal (B) Excitation image; Dotted circle gut excitation signal, right rectangle mouse fur reflection signal, left rectangle animal holder reflected signal. (C) white-light images of a mouse bearing a 4T1 tumor and received PLGA-anti-EGFR nanoparticle injection. The trans-illuminating point light source is overlapped onto (C), to indicate the light-source position.

Figure 4

(A) Workflow of the adaptive mask-based background subtraction strategy. (B) Representative example illustrating how to extract tumor fluorescence from background fluorescence based on workflow (A).

Figure 5

(A) Raw and AMBS-corrected fluorescence images before and after intratumoral injection of fluorescent GNRs. AMBS images were normalized to the maximum of the corresponding raw images. (B) Trans-illuminating light source is overlapped onto white-light image to indicate the excitation location. (C) Organ fluorescence imaging of the dissected animal, using Kodak In Vivo Multispectral Imaging system. (D, E) FMT reconstruction based on the raw and AMBS-corrected fluorescence images, respectively.

Figure 6

Contrast CT slices of 2 (out of 10) mice bearing orthotopic breast tumors of different sizes, in three orthogonal views. Arrows indicate the contrast enhanced tumor edge.

Figure 7

Comparison of fluorescence distribution before and after background subtraction for 10 mice bearing 4T1 breast tumors of different sizes. All the fluorescence images were obtained 1 day after intravenous injection of PLGA-anti-EGFR nanoparticles. (A) Raw and background-corrected fluorescence images, which were normalized by their own maximum. The circle marks the tumor differentiated from contrast CT. (B, C) Profiles across the 1.5 mm and 4 mm tumor, respectively (along the dotted lines in the 1st column of (A)). All the profiles were normalized to their own maximum.

Figure 8

Mean tumor-to-background ratios for the raw and background corrected fluorescence images.

Figure 9

Active-targeting FMT reconstruction respectively based on AMBS-corrected (A) and raw (B) fluorescence, for 2 (out of 10) mice bearing breast tumors with different sizes. Blue dotted line delineates the tumor edge obtained from CT. FMT (red colorwash) is superimposed on CT. Red line denotes the mouse contour used in FMT reconstruction. Bottom rows in (A, B) show the 3D rendering of FMT in the CT bony anatomy. Arrows in (A) point to the reconstructed residual uptake in gut. Arrows in (B) point to the artifacts caused by the nonspecific fluorophore update in abdomen. (C) Mean tumor center offset and (D) tumor volume overestimation for the 10 mice experiments.