Cerenkov luminescence tomography (CLT) is a highly sensitive and promising imaging modality for three-dimensional visualization of radiopharmaceuticals. However, the approximate error generated by the simplified radiation transfer equation and the ill-posedness of the inverse problem limit the improvement of CLT reconstruction. In this research, a residual learning network (RLN) was proposed to improve morphological restorability. By learning the relationship between surface photon intensity and internal source, the errors from the inverse process could be avoided. RLN comprised two fully connected sub-networks: one was used to provide the coarse reconstruction result. The other optimized the final reconstruction result by learning the residual between the coarse reconstruction result and the true source. Monte Carlo method was used to generate the dataset. Furthermore, multilayer fully connected neural network (MFCNN) was used as baselines and compared. Single-source simulation and robustness experiments were conducted to evaluate the reconstruction performance. The experimental results show RLN achieved accurate localization and morphological reconstruction, which will promote the application of machine learning in optical tomography reconstruction.
Fluorescence molecular imaging is a promising tool for molecular tracking, and thus can visualize the vascular structure of small animal. However, with the strong scattering in biological tissues, traditional fluorescence molecular imaging in the visible spectrum or the first near-infrared spectrum (NIR-I, 700-900 nm) has a limitation for high-resolution vascular imaging. Recently, the novel in vivo fluorescence molecular imaging in the longer second near-infrared window (NIR-IIb, 1500-1700 nm) is successfully developed for small animal imaging. The NIR-IIb window affords high imaging resolution and deep tissue penetration because of the diminished photon scattering effect, which is suitable for vascular imaging. However, the clinical applications of NIR-IIb fluorescence molecular imaging have been severely limited for lack of the clinical fluorophores. Here, we show that the clinically available dye, indocyanine green (ICG), can also emit the NIR-IIb signal, which provides high-resolution vascular imaging of small animal. We construct a novel imaging system for NIR-I and NIR-IIb imaging simultaneously and perform two vascular imaging experiments. The results demonstrate that the NIR-IIb imaging using ICG shows great superiority for high-resolution vascular imaging of small animal compared with NIR-I imaging. It is believed that this study will facilitate the preclinical and clinical applications of NIR-IIb molecular imaging using ICG in the future.
Background: Cherenkov luminescence (CL) has been used in the field of biomedical imaging since 2009 and has attracted more and more attentions in recent years. However, the weak signal intensity and the spectrum distribution whose energy mainly located at 400-500 nm limited the widespread application of CLI. In this study, a novel nanoparticle which contained europium atoms doped into gadolinium oxide (GdO: Eu) was used to be excited by radiopharmaceuticals to convert the weak blue light into stronger long-wavelength fluorescence for improving imaging performance.
Methods: First, both EO nanoparticles and GdO: Eu nanoparticles of the same mass in two Eppendorf (EP) tubes were excited simultaneously by 18F-FDG with the activity of 466 µCi and and the emitted fluorescence intensity of two EP tubes ßwere compared. Next, a series of in vitro experiments were desinged and conducted to investigate the cause of production of the long wavelength fluorescence of GdO: Eu under radiopharmaceutical excitation. Lastly, the tumor mouse models (n=6) were constructed, injected with the novel nanoparticles through the tail vein, and received the in vivo fluorescence imaging.
Results: Compared with EO, the novel nanoparticle had a better performance in emitted fluorescence intensity. The fluorescence intensity increased with the decreasing distance between the nanoparticle and the radiopharmaceutical, or the increasing activity of 18F-FDG.
Conclusion: The results showed that gadolinium oxide nanoparticle doped with europium atoms can convert the short-wavelength Cerenkov light of 18F-FDG into a long-wavelength light with better performance for in vivo imaging compared with CLI. This imaging strategy showed great potential for tumor imaging and detection.
Cherenkov luminescence tomography (CLT) has become a novel three-dimensional (3D) non-invasive technology for biomedical applications such as tumor detection, pharmacodynamics evaluation, etc. However, the reconstruction of CLT still remains a challenging task because of the strong absorbing effect and scattering effect of Cherenkov photon transport process. In this study, we proposed a novel robust sparse reconstruction method named look ahead orthogonal matching pursuit (LAOMP) algorithm to improve the robustness and accuracy of reconstruction for CLT instead of traditional OMP algorithm based on a look ahead strategy. To validate the reconstruction performance of LAOMP method, a series of numerical simulations were conducted. The results showed that LAOMP method obtained the higher robustness and accuracy in locating the optical sources compared with the OMP and StOMP algorithms.
Fluorescence molecular imaging (FMI) has been widely used in many medical fields with small molecule indocyanine green (ICG). However, low signal-background ratio and limited specificity to tumor remain big challenges for FMI. In this study, a novel excitation strategy is proposed on the basis of clinical approved ICG and 18F-FDG. A series of in vitro experiments are designed to reveal the mechanism and results show obvious decreasing of ICG fluorescence intensity with the increasing distance to excitation source. Meanwhile, the ICG fluorescence intensity is proportional to the activity of radiopharmaceutical. Results from different respects illustrate the promising of this proposed excitation strategy.
Cerenkov luminescence tomography (CLT), as a promising optical molecular imaging modality, can be applied
to cancer diagnostic and therapeutic. Most researches about CLT reconstruction are based on the finite element
method (FEM) framework. However, the quality of FEM mesh grid is still a vital factor to restrict the accuracy
of the CLT reconstruction result. In this paper, we proposed a multi-grid finite element method framework,
which was able to improve the accuracy of reconstruction. Meanwhile, the multilevel scheme adaptive algebraic
reconstruction technique (MLS-AART) based on a modified iterative algorithm was applied to improve the
reconstruction accuracy. In numerical simulation experiments, the feasibility of our proposed method were
evaluated. Results showed that the multi-grid strategy could obtain 3D spatial information of Cerenkov source
more accurately compared with the traditional single-grid FEM.
Cerenkov luminescence tomography (CLT) is a promising tool that enables three-dimensional noninvasive in vivo detection of radiopharmaceuticals. Conventionally, multispectral information and diffusion theory were introduced to achieve whole-body tomographic reconstruction. However, the diffusion theory inevitably causes systematic error in blue bands of the electromagnetic spectrum due to high-tissue absorption, and CL has a blue-weighted broad spectrum. Therefore, it is challenging to improve the accuracy of CLT. The performance of the n-order simplified spherical harmonics approximation (SPn) in different spectra is evaluated, and a multispectral hybrid CLT based on the combination of different SPn models is proposed to handle the Cerenkov photon transport problem in complex media. The in vivo xenograft experiment shows that this approach can effectively improve the quality and accuracy of the reconstructed light source. We believe that the new reconstruction method will advance the development of CLT for more in vivo imaging applications.
Cerenkov luminescence imaging (CLI) is a novel optical imaging method and has been proved to be a potential substitute of the traditional radionuclide imaging such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). This imaging method inherits the high sensitivity of nuclear medicine and low cost of optical molecular imaging. To obtain the depth information of the radioactive isotope, Cerenkov luminescence tomography (CLT) is established and the 3D distribution of the isotope is reconstructed. However, because of the strong absorption and scatter, the reconstruction of the CLT sources is always converted to an ill-posed linear system which is hard to be solved. In this work, the sparse nature of the light source was taken into account and the preconditioning orthogonal matching pursuit (POMP) method was established to effectively reduce the ill-posedness and obtain better reconstruction accuracy. To prove the accuracy and speed of this algorithm, a heterogeneous numerical phantom experiment and an in vivo mouse experiment were conducted. Both the simulation result and the mouse experiment showed that our reconstruction method can provide more accurate reconstruction result compared with the traditional Tikhonov regularization method and the ordinary orthogonal matching pursuit (OMP) method. Our reconstruction method will provide technical support for the biological application for Cerenkov luminescence.
Background: Cerenkov luminescence imaging (CLI) provides a great potential for clinical translation of optical molecular imaging techniques through using clinical approved radiotracers. However, it is difficult to obtain the Cerenkov luminescence signal of deeper biological tissues due to the small magnitude of the signal. To efficiently acquire the weak Cerenkov luminescence, we developed an endoscopic Cerenkov luminescence imaging (ECLI) system to reduce the in vivo imaging depth with minimum invasion, and validated the system on small animal tumor models. Methods: For the ECLI system, the laparoscope was connected to a high sensitive charge-couple device (CCD) camera (DU888+, Andor, UK) by a custom made adapter. We conducted a series of in vitro and in vivo experiments by use of the system. In the in vitro experiment, the endoscopic luminescence images of the 18F-FDG with various activities in EP tubes were acquired using ECLI system, and the sensitivity was compared with conventional CLI system. In the in vivo tumor experiment, 18F-FDG with the activity of 200μCi were intravenously injected into 3 tumor mice. Then the ECLI system was used to acquire the optical images for both non-invasive and invasive conditions. Conclusion: Experimental data showed the ECLI system could detect the 18F-FDG with the activity as low as 1μCi. Furthermore, our preliminary results indicated the possibility of ECLI technique for detecting Cerenkov signals inside the tumor tissue with deeper depth and guiding the surgical operation of tumor excision. We believe that this technique can help to accelerate the clinical translation of CLI.
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