Diffuse optical tomography (DOT) as a new functional imaging has important clinical applications in many aspects such as benign and malignant breast tumor detection, tumor staging and so on. For quantitative detection of breast tumor, a three-wavelength continuous-wave DOT prototype system combined the ultra-high sensitivity of the photon-counting detection and the measurement parallelism of the lock-in technique was developed to provide high temporal resolution, high sensitivity, large dynamic detection range and signal-to-noise ratio. Additionally, a CT-analogous scanning mode was proposed to cost-effectively increase the detection data. To evaluate the feasibility of the system, a series of assessments were conducted. The results demonstrate that the system can obtain high linearity, stability and negligible inter-wavelength crosstalk. The preliminary phantom experiments show the absorption coefficient is able to be successfully reconstructed, indicating that the system is one of the ideal platforms for optical breast tumor detection.
Real-time and continuous monitoring of drug release in vivo is an important task in pharmaceutical development. Here, we devoted to explore a real-time continuous study of the pharmacokinetics of free indocyanine green (ICG) and ICG loaded in the shell-sheddable nanoparticles in tumor based on a dynamic diffuse fluorescence tomography (DFT) system: A highly-sensitive dynamic DFT system of CT-scanning mode generates informative and instantaneous sampling datasets; An analysis procedure extracts the pharmacokinetic parameters from the reconstructed time curves of the mean ICG concentration in tumor, using the Gauss-Newton scheme based on two-compartment model. Compared with the pharmacokinetic parameters of free ICG in tumor, the ICG loaded in the shell-sheddable nanoparticles shows efficient accumulation in tumor. The results demonstrate our proposed dynamic-DFT can provide an integrated and continuous view of the drug delivery of the injected agents in different formulations, which is helpful for the development of diagnosis and therapy for tumors.
Proc. SPIE. 10486, Design and Quality for Biomedical Technologies XI
KEYWORDS: Modulation, Imaging systems, Field programmable gate arrays, Dynamical systems, Signal detection, Fluorescence tomography, Current controlled current source
Pharmacokinetic diffuse fluorescence tomography (DFT) can describe the metabolic processes of fluorescent agents in biomedical tissue and provide helpful information for tumor differentiation. In this paper, a dynamic DFT system was developed by employing digital lock-in-photon-counting with square wave modulation, which predominates in ultra-high sensitivity and measurement parallelism. In this system, 16 frequency-encoded laser diodes (LDs) driven by self-designed light source system were distributed evenly in the imaging plane and irradiated simultaneously. Meanwhile, 16 detection fibers collected emission light in parallel by the digital lock-in-photon-counting module. The fundamental performances of the proposed system were assessed with phantom experiments in terms of stability, linearity, anti-crosstalk as well as images reconstruction. The results validated the availability of the proposed dynamic DFT system.
In vivo tomographic imaging of the fluorescence pharmacokinetic parameters in tissues can provide additional specific and quantitative physiological and pathological information to that of fluorescence concentration. This modality normally requires a highly-sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic parameters from the measured pharmacokinetics-associated temporally-varying boundary intensity. This paper is devoted to preliminary experimental validation of our proposed direct reconstruction scheme of instantaneous sampling based pharmacokinetic-DFT: A highly-sensitive DFT system of CT-scanning mode working with parallel four photomultiplier-tube photon-counting channels is developed to generate an instantaneous sampling dataset; A direct reconstruction scheme then extracts images of the pharmacokinetic parameters using the adaptive-EKF strategy. We design a dynamic phantom that can simulate the agent metabolism in living tissue. The results of the dynamic phantom experiments verify the validity of the experiment system and reconstruction algorithms, and demonstrate that system provides good resolution, high sensitivity and quantitativeness at different pump speed.
KEYWORDS: Fluorescence tomography, Data modeling, Tissues, Signal to noise ratio, Instrument modeling, Performance modeling, In vivo imaging, Digital filtering, Image filtering, Electronic filtering
We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.
The underdeterminedness of the inverse problems encountered in diffuse optical tomography (DOT) becomes especially severe when detecting breast cancers, because much more variables are needed to be reconstructed due to the big-size. With the addition of ill-condition caused by the diffusive nature of light propagation, the ill-posedness makes it very difficult to improve the image reconstruction. Fortunately, from the anatomy viewpoint, we have known that the cancer is distributed locally and only amounts to a small percentage of the whole breast. This makes it possible to employ the compressive sensing theory to mitigate the ill-posedness, based on the prior knowledge about the sparsity of the signal to be reconstructed. Specifically speaking, sparsity regularizations can be used in DOT to improve the image reconstruction under the premise that un-increase the number of measurements required in the reconstruction. In this paper, we primarily focus on comparing the performances of different kinds of Lp-norm-based regularizations in terms of theory and real effects, respectively. The numerical and phantom experiments have proven that the sparsity regularizations can dramatically improve the image reconstruction. Furthermore, as the p in the Lp-norm decreasing to zero, the solutions become sparser and the corresponding image quality gets higher, with smooth L0-norm-based regularization providing the highest image quality.
Of the three measurement schemes established for diffuse fluorescence tomography (DFT), the time-domain scheme is well known to provide the richest information about the distribution of the targeting fluorophore in living tissues. However, the explicit use of the full time-resolved data usually leads to a considerably lengthy time for image reconstruction, limiting its applications to three-dimensional or small-volume imaging. To cope with the adversity, we propose herein a computationally efficient scheme for DFT image reconstruction where the time-dependent photon density is expanded to a Fourier-series and calculated by solving the independent frequency-domain diffusion equations at multiple sampling frequencies with the support of a combined multicore CPU-based coarse-grain and multithread GPU-based fine-grain parallelization strategy. With such a parallelized Fourier-series truncated diffusion approximation, both the time- and frequency-domain inversion procedures are developed and validated for their effectiveness and accuracy using simulative and phantom experiments. The results show that the proposed method can generate reconstructions comparable to the explicit time-domain scheme, with significantly reduced computational time.