In minimally invasive surgery, the white-light thoracoscope as a standard imaging tool is facing challenges of the low contrast between important anatomical or pathological regions and surrounding tissues. Recently, the near-infrared (NIR) fluorescence imaging shows superior advantages over the conventional white-light observation, which inspires researchers to develop imaging systems to improve overall outcomes of endoscopic imaging. We developed an NIR and white-light dual-channel thoracoscope system, which achieved high-fluorescent signal acquisition efficiency and the simultaneously optimal visualization of the NIR and color dual-channel signals. The system was designed to have fast and accurate image registration and high signal-to-background ratio by optimizing both software algorithms and optical hardware components for better performance in the NIR spectrum band. The system evaluation demonstrated that the minimally detectable concentration of indocyanine green (ICG) was 0.01 μM, and the spatial resolution was 35 μm. The in vivo feasibility of our system was verified by the preclinical experiments using six porcine models with the intravenous injection of ICG. Furthermore, the system was successfully applied for guiding the minimally invasive segmentectomy in three lung cancer patients, which revealed that our system held great promise for the clinical translation in lung cancer surgeries.
Fluorescence molecular tomography (FMT) is developing rapidly in the field of molecular imaging. FMT has been
used in surgical navigation for tumor resection and has many potential applications at the physiological, metabolic, and
molecular levels in tissues. Due to the ill-posed nature of the problem, many regularized methods are generally adopted.
In this paper, we propose a region reconstruction method for FMT in which the trace norm regularization. The trace
norm penalty was defined as the sum of the singular values of the matrix. The proposed method adopts a priori
information which is the structured sparsity of the fluorescent regions for FMT reconstruction. In order to improve the
solution efficiency, the accelerated proximal gradient algorithms was used to accelerate the computation. The
numerical phantom experiment was conducted to evaluate the performance of the proposed trace norm regularization
method. The simulation study shows that the proposed method achieves accurate and is able to reconstruct image
effectively.
KEYWORDS: Luminescence, Tomography, Fluorescence tomography, In vivo imaging, Inverse problems, Finite element methods, Tissues, Tumors, Imaging systems, 3D modeling
Fluorescence molecular tomography (FMT) is a promising tool in the study of cancer, drug discovery, and disease diagnosis, enabling noninvasive and quantitative imaging of the biodistribution of fluorophores in deep tissues via image reconstruction techniques. Conventional reconstruction methods based on the finite-element method (FEM) have achieved acceptable stability and efficiency. However, some inherent shortcomings in FEM meshes, such as time consumption in mesh generation and a large discretization error, limit further biomedical application. In this paper, we propose a meshless method for reconstruction of FMT (MM-FMT) using compactly supported radial basis functions (CSRBFs). With CSRBFs, the image domain can be accurately expressed by continuous CSRBFs, avoiding the discretization error to a certain degree. After direct collocation with CSRBFs, the conventional optimization techniques, including Tikhonov, L1-norm iteration shrinkage (L1-IS), and sparsity adaptive matching pursuit, were adopted to solve the meshless reconstruction. To evaluate the performance of the proposed MM-FMT, we performed numerical heterogeneous mouse experiments and in vivo bead-implanted mouse experiments. The results suggest that the proposed MM-FMT method can reduce the position error of the reconstruction result to smaller than 0.4 mm for the double-source case, which is a significant improvement for FMT.
Fluorescence molecular tomography (FMT) has many successful applications which has been considered as a promising tomographic method for invivo small animal imaging. However, most of the reconstruction methods, which are used to solve the forward model and inverse model of FMT, are carried out based on MATLAB or other separate subprogram tools. It is inconvenient to adjust the same parameters in different programs and to apply in multi-modality imaging reconstructions. To solve this problem, a robust simulation and reconstruction platform of FMT is proposed in this paper. The proposed platform is based on Windows, and the development of the platform is based on Visual Studio 2010 with C++, which is used in multi-modality systems of our group. Compared with the traditional divided methods, our proposed platform is more robust in FMT reconstruction and can conveniently integrate with other imaging modalities. Furthermore, more accurate results can be obtained by using our platform which has been shown in this study.
As an important molecular imaging modality, fluorescence molecular imaging (FMI) has the advantages of high sensitivity, low cost and ease of use. By labeling the regions of interest with fluorophore, FMI can noninvasively obtain the distribution of fluorophore in-vivo. However, due to the fact that the spectrum of fluorescence is in the section of the visible light range, there are mass of autofluorescence on the surface of the bio-tissues, which is a major disturbing factor in FMI. Meanwhile, the high-level of dark current for charge-coupled device (CCD) camera and other influencing factor can also produce a lot of background noise. In this paper, a novel method for image denoising of FMI based on fuzzy C-Means clustering (FCM) is proposed, because the fluorescent signal is the major component of the fluorescence images, and the intensity of autofluorescence and other background signals is relatively lower than the fluorescence signal. First, the fluorescence image is smoothed by sliding-neighborhood operations to initially eliminate the noise. Then, the wavelet transform (WLT) is performed on the fluorescence images to obtain the major component of the fluorescent signals. After that, the FCM method is adopt to separate the major component and background of the fluorescence images. Finally, the proposed method was validated using the original data obtained by invivo implanted fluorophore experiment, and the results show that our proposed method can effectively obtain the fluorescence signal while eliminate the background noise, which could increase the quality of fluorescence images.
In vivo fluorescence molecular imaging (FMI) has played an increasingly important role in biomedical research of preclinical
area. Fluorescence molecular tomography (FMT) further upgrades the two-dimensional FMI optical information
to three-dimensional fluorescent source distribution, which can greatly facilitate applications in related studies. However,
FMT presents a challenging inverse problem which is quite ill-posed and ill-conditioned. Continuous efforts to develop
more practical and efficient methods for FMT reconstruction are still needed. In this paper, a method based on spectral
projected gradient pursuit (SPGP) has been proposed for FMT reconstruction. The proposed method was based on the
directional pursuit framework. A mathematical strategy named the nonmonotone line search was associated with the
SPGP method, which guaranteed the global convergence. In addition, the Barzilai-Borwein step length was utilized to
build the new step length of the SPGP method, which was able to speed up the convergence of this gradient method. To
evaluate the performance of the proposed method, several heterogeneous simulation experiments including multisource
cases as well as comparative analyses have been conducted. The results demonstrated that, the proposed method was
able to achieve satisfactory source localizations with a bias less than 1 mm; the computational efficiency of the method
was one order of magnitude faster than the contrast method; and the fluorescence reconstructed by the proposed method
had a higher contrast to the background than the contrast method. All the results demonstrated the potential for practical
FMT applications with the proposed method.
KEYWORDS: Surgery, Lymphatic system, Breast cancer, Luminescence, Molecular imaging, Near infrared, Navigation systems, In vivo imaging, Cameras, Beam splitters
Introduction: Precision and personalization treatments are expected to be effective methods for early stage cancer studies. Breast cancer is a major threat to women’s health and sentinel lymph node biopsy (SLNB) is an effective method to realize precision and personalized treatment for axillary lymph node (ALN) negative patients. In this study, we developed a surgical navigation system (SNS) based on optical molecular imaging technology for the precise detection of the sentinel lymph node (SLN) in breast cancer patients. This approach helps surgeons in precise positioning during surgery.
Methods: The SNS was mainly based on the technology of optical molecular imaging. A novel optical path has been designed in our hardware system and a feature-matching algorithm has been devised to achieve rapid fluorescence and color image registration fusion. Ten in vivo studies of SLN detection in rabbits using indocyanine green (ICG) and blue dye were executed for system evaluation and 8 breast cancer patients accepted the combination method for therapy.
Results: The detection rate of the combination method was 100% and an average of 2.6 SLNs was found in all patients. Our results showed that the method of using SNS to detect SLN has the potential to promote its application.
Conclusion: The advantage of this system is the real-time tracing of lymph flow in a one-step procedure. The results demonstrated the feasibility of the system for providing accurate location and reliable treatment for surgeons. Our approach delivers valuable information and facilitates more detailed exploration for image-guided surgery research.
For clinical surgery, it is still a challenge to objectively determine tumor margins during surgery. With the development of medical imaging technology, fluorescence molecular imaging (FMI) method can provide real-time intraoperative tumor margin information. Furthermore, surgical navigation system based on FMI technology plays an important role for the aid of surgeons’ precise tumor margin decision. However, detection depth is the most limitation exists in the FMI technique and the method convenient for either macro superficial detection or micro deep tissue detection is needed. In this study, we combined advantages of both open surgery and endoscopic imaging systems with FMI technology. Indocyanine green (ICG) experiments were performed to confirm the feasibility of fluorescence detection in our system. Then, the ICG signal was photographed in the detection area with our system. When the system connected with endoscope lens, the minimum quantity of ICG detected by our system was 0.195 ug. For aspect of C mount lens, the sensitivity of ICG detection with our system was 0.195ug. Our experiments results proved that it was feasible to detect fluorescence images with this combination method. Our system shows great potential in the clinical applications of precise dissection of various tumors
Currently, it has been an international focus on intraoperative precise positioning and accurate resection of tumor and metastases. The methods such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role in preoperative accurate diagnosis. However, most of them are inapplicable for intraoperative surgery. We have proposed a surgical navigation system based on optical molecular imaging technology for intraoperative detection of tumors and metastasis. This system collects images from two CCD cameras for real-time fluorescent and color imaging. For image processing, the template matching algorithm is used for multispectral image fusion. For the application of tumor detection, the mouse breast cancer cell line 4T1-luc, which shows highly metastasis, was used for tumor model establishment and a model of matrix metalloproteinase (MMP) expressing breast cancer. The tumor–bearing nude mice were given tail vein injection of MMP 750FAST (PerkinElmer, Inc. USA) probe and imaged with both bioluminescence and fluorescence to assess in vivo binding of the probe to the tumor and metastases sites. Hematoxylin and eosin (H&E) staining was performed to confirm the presence of tumor and metastasis. As a result, one tumor can be observed visually in vivo. However liver metastasis has been detected under surgical navigation system and all were confirmed by histology. This approach helps surgeons to find orthotopic tumors and metastasis during intraoperative resection and visualize tumor borders for precise positioning. Further investigation is needed for future application in clinics.
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