A tri-modal (PET/CT/Optical) small animal tomographic imaging system was developed by integrating our advanced non-contact intensified CCD (ICCD) frequency-domain fluorescence imaging components into a Siemens Inveon scanner. We performed a performance evaluation of the developed imaging system by using the developed regularization-free high-order radiative-transfer-based reconstruction algorithm and custom solid phantoms. Our results show that frequency-domain photon migration (FDPM) fluorescence tomography can achieve better tomographic images with less artifacts and more precise fluorescent source localization compared to the continuous-wave counterpart. The developed multimodal tomographic imaging system provides a powerful tool for translational biomedical research.
IntroductionThe development of small animal fluorescence tomography has been the subject of intense research and development of the past decade [1,2]. For translational studies that seek to advance fluorescence with comparative assessment to nuclear imaging modalities, particular focus is on the development of multimodal fluorescence tomography imaging systems through integration of anatomical or/and functional (for example Positron Emission Tomography (PET) or Single-photon emission computed tomography (SPECT) imaging modalities.Non-contact CCD detection of emitted fluorescence can achieve high-resolution of spatial fluence distribution rapidly over large areas. Compared to continuous wave (CW) mode, time-dependent frequency-domain photon migration (FDPM) fluorescence tomography can acquire both the amplitude and phase information of fluorescent photons, that is less impacted by the optical property heterogeneity of intervening tissues, enable the monitoring of fluorescent lifetime, and result in improved the reconstruction quality with richer measurements. Our miniaturized intensified CCD (ICCD) camera imaging system provides a solution with high sensitivity and large-area photon collection [3].The information of fluorophores can be recovered by 3D reconstruction algorithms after acquiring fluorescent photon distribution information over the 2D mouse surface. Researchers have sought to develop more precise forward models because classic diffusion approximation (DA) to the radiative transfer equation (RTE) is inaccurate in cases that are common in small animal imaging [4]. Deriving from Diffuse Optical Tomography (DOT), fluorescence tomography can be realized by several nonlinear and linear approximation reconstruction algorithms. Generally, regularization strategies are used to acquire stable solutions. However, they suffer from the selection of regularization parameters [4] which gives the best match to the true imaging solution. Fluorescence tomography can be considered a linear problem since the absorption of trace deposition of fluorophore at excitation wavelengths can be neglected. Imaging reconstructions with rich linear optimization strategies significantly improve the numerical stability [3].In this paper, we use the linear regularizati...