Cone beam micro-CT system for small animal imaging and performance evaluation

Antitumorigenic and antiangiogenic efficacy of apatinib in liver cancer evaluated by multimodality molecular imaging

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related mortality worldwide. Sorafenib is the standard first-line treatment for advanced HCC, but its efficacy is limited. Apatinib is a small-molecule tyrosine kinase inhibitor that has shown promising antitumor effects in gastric and non-small cell lung cancers in clinical trials, but there have been only a few studies reporting its anti-HCC effects in vitro and in HCC xenograft models. Hence, our present study systemically investigated and compared the antitumorigenic and antiangiogenic efficacy of apatinib and sorafenib in HCC in vitro and in vivo using multimodality molecular imaging, including bioluminescence imaging (BLI), bioluminescence tomography (BLT), fluorescence molecular imaging (FMI), and computed tomography angiography (CTA). Moreover, the safety and side effects of the two drugs were systemically evaluated. We found that apatinib showed a comparable therapeutic efficacy to sorafenib for the inhibition of HCC. The drug safety evaluation revealed that both of these drugs caused hypertension and mild liver and kidney damage. Sorafenib caused diarrhea, rash, and weight loss in mice, but these effects were not observed in mice treated with apatinib. In conclusion, apatinib has similar antitumorigenic and antiangiogenic efficacy as sorafenib in HCC with less toxicity. These findings may provide preclinical evidence supporting the potential application of apatinib for the treatment of HCC patients.

Researchers have combined different sophisticated imaging techniques to assess the safety and efficacy of liver cancer therapy in animal models. Many hepatocellular carcinoma (HCC) patients respond to sorafenib, but this drug is expensive and may cause severe side-effects. Qian Liang at China’s Institute of Automation, Beijing, and colleagues have employed cutting-edge imaging technologies to study an alternative drug, apatinib, which has shown promise for stomach and lung cancer and has an excellent safety profile. Using bioluminescence imaging, the researchers could directly visualize apatanib-mediated inhibition of tumor growth in live mice much earlier than would be possible with other methods. The researchers subsequently used additional imaging techniques to demonstrate that apatanib inhibits tumor blood vessel growth. These findings reveal a promising alternative treatment for HCC, as well as a powerful strategy for drug testing in animals.

Comparison of GPU reconstruction based on different symmetries for dual-head PET

Purpose

Dual‐head positron emission tomography (PET) scanners have increasingly attracted the attention of many researchers. However, with the compact geometry, the depth‐of‐interaction blurring will reduce the image resolution considerably. Monte Carlo (MC)‐based system response matrix (SRM) is able to describe the physical process of PET imaging accurately and improve reconstruction quality significantly. The MC‐based SRM is large and precomputed, which leads to a longer image reconstruction time with indexing and retrieving precomputed system matrix elements. In this study, we proposed a GPU acceleration algorithm to accelerate the iterative reconstruction.

Methods

It has been demonstrated that the line‐of‐response (LOR)‐based symmetry and the Graphics Processing Unit (GPU) technology can accelerate the reconstruction tremendously. LOR‐based symmetry is suitable for the forward projection calculation, but not for the backprojection. In this study, we proposed a GPU acceleration algorithm that combined the LOR‐based symmetry and voxel‐based symmetry together, in which the LOR‐based symmetry is responsible for the forward projection, and the voxel‐based symmetry is used for the backprojection.

Results

Simulation and real experiments verify the efficiency of the algorithm. Compared with the CPU‐based calculation, the acceleration ratios of the forward projection and the backprojection operation are 130 and 110, respectively. The total acceleration ratio is 113×. In order to compare the acceleration effect of the different symmetries, we realized the reconstruction with the voxel‐based symmetry and the LOR‐based symmetry strategies. Compared with the LOR‐based GPU reconstruction, the acceleration ratio is 3.5×. Compared with the voxel‐based GPU reconstruction, the acceleration ratio is 12×.

Conclusion

We have proposed a new acceleration algorithm for the dual‐head PET system, in which both the forward and backprojection operations are accelerated by GPU.

Regularized reconstruction based on joint L1 and total variation for sparse-view cone-beam X-ray luminescence computed tomography

As an emerging hybrid imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed based on the development of X-ray excitable nanoparticles. Owing to the high degree of absorption and scattering of light through tissues, the CB-XLCT inverse problem is inherently ill-conditioned. Appropriate priors or regularizations are needed to facilitate reconstruction and to restrict the search space to a specific solution set. Typically, the goal of CB-XLCT reconstruction is to get the distributions of nanophosphors in the imaging object. Considering that the distributions of nanophosphors inside bodies preferentially accumulate in specific areas of interest, the reconstruction of XLCT images is usually sparse with some locally smoothed high-intensity regions. Therefore, a combination of the L₁ and total variation regularization is designed to improve the imaging quality of CB-XLCT in this study. The L₁ regularization is used for enforcing the sparsity of the reconstructed images and the total variation regularization is used for maintaining the local smoothness of the reconstructed image. The implementation of this method can be divided into two parts. First, the reconstruction image was reconstructed based on the fast iterative shrinkage-thresholding (FISTA) algorithm, then the reconstruction image was minimized by the gradient descent method. Numerical simulations and phantom experiments indicate that compared with the traditional ART, ADAPTIK and FISTA methods, the proposed method demonstrates its advantage in improving spatial resolution and reducing imaging time.

Self-assembled micro-computed tomography for dental education

This study used available or purchased equipment and an image reconstruction system developed by the college of dentistry to establish a basic self-assembled micro-computed tomography (micro-CT) system. Such a system would be suitable for teaching dental radiology to dental students. Specifically, it could help students to understand the principles governing dental cone-beam computed tomography (CBCT) and provide graduate students with a system for scanning small samples (e.g., individual teeth) during the early stages of research. The self-assembled micro-CT system was constructed using a portable dental X-ray tube, an intraoral digital X-ray detector, a high-precision rotation stage, related bracket accessories, and a notebook computer. Reconstructed images and three-dimensional models of the maxillary right third molar were produced using the self-assembled micro-CT system and an advanced commercially available micro-CT system (Skyscan 2211). Subsequently, the reconstructed images and 3D models produced using the two systems were compared by two senior dentists to determine whether considerable visual differences could be observed. Finally, the signal-to-noise ratio (SNR) was used for quantitative analysis and to compare the systems. Although the self-assembled micro-CT system produced image boundaries that were not as sharp as those of Skyscan 2211, the images were nonetheless remarkably similar. In addition, the two micro-CT systems produced 3D models that were almost identical in appearance and root canal shape. Quantitative analysis revealed that Skyscan 2211 had produced a SNR that was superior to that of the self-assembled micro-CT system, with the difference ranging from 36.77% to 136.22%; enamel, which has a higher density, exhibited lower SNR differences, whereas dentin, which has a lower density, exhibited higher SNR differences. The self-assembled micro-CT system with a resolution of 36 μm was created using a portable dental X-ray tube and an intraoral digital X-ray detector. Although the scanning time was relatively long (~30 min to scan images of a tooth), the images were adequate in the preliminary stage of experiments. More importantly, students were afforded the opportunity to observe the process of assembling and disassembling each component of a micro-CT scanner and thereby achieve a more comprehensive understanding of the principles governing micro-CT and dental CBCT.

Reconstruction method for fluorescence molecular tomography based on L1-norm primal accelerated proximal gradient

Fluorescence molecular tomography (FMT) has been widely used in preclinical tumor imaging, which enables three-dimensional imaging of the distribution of fluorescent probes in small animal bodies via image reconstruction method. However, the reconstruction results are usually unsatisfactory in the term of robustness and efficiency because of the ill-posed and ill-conditioned of FMT problem. In this study, an FMT reconstruction method based on primal accelerated proximal gradient (PAPG) descent and L1-norm regularized projection (L1RP) is proposed. The proposed method utilizes the current and previous iterations to obtain a search point at each iteration. To achieve fast convergence, the PAPG method is applied to efficiently solve the search point, and then L1RP is performed to obtain the robust and accurate reconstruction. To verify the performance of the proposed method, simulation experiments are conducted. The comparative results revealed that it held advantages of robustness, accuracy, and efficiency in FMT reconstructions. Furthermore, a phantom experiment and an in vivo mouse experiment were also performed, which proved the potential and feasibility of the proposed method for practical applications.

Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage

With the advances of x-ray excitable nanophosphors, x-ray luminescence computed tomography (XLCT) has become a promising hybrid imaging modality. In particular, a cone-beam XLCT (CB-XLCT) system has demonstrated its potential in in vivo imaging with the advantage of fast imaging speed over other XLCT systems. Currently, the imaging models of most XLCT systems assume that nanophosphors emit light based on the intensity distribution of x-ray within the object, not completely reflecting the nature of the x-ray excitation process. To improve the imaging quality of CB-XLCT, an imaging model that adopts an excitation model of nanophosphors based on x-ray absorption dosage is proposed in this study. To solve the ill-posed inverse problem, a reconstruction algorithm that combines the adaptive Tikhonov regularization method with the imaging model is implemented for CB-XLCT reconstruction. Numerical simulations and phantom experiments indicate that compared with the traditional forward model based on x-ray intensity, the proposed dose-based model could improve the image quality of CB-XLCT significantly in terms of target shape, localization accuracy, and image contrast. In addition, the proposed model behaves better in distinguishing closer targets, demonstrating its advantage in improving spatial resolution.

Cone Beam X-ray Luminescence Computed Tomography Based on Bayesian Method

X-ray luminescence computed tomography (XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. Combining the principles of X-ray excitation of luminescence-based probes and optical signal detection, XLCT naturally fuses functional and anatomical images and provides complementary information for a wide range of applications in biomedical research. In order to improve the data acquisition efficiency of previously developed narrow-beam XLCT, a cone beam XLCT (CB-XLCT) mode is adopted here to take advantage of the useful geometric features of cone beam excitation. Practically, a major hurdle in using cone beam X-ray for XLCT is that the inverse problem here is seriously ill-conditioned, hindering us to achieve good image quality. In this paper, we propose a novel Bayesian method to tackle the bottleneck in CB-XLCT reconstruction. The method utilizes a local regularization strategy based on Gaussian Markov random field to mitigate the ill-conditioness of CB-XLCT. An alternating optimization scheme is then used to automatically calculate all the unknown hyperparameters while an iterative coordinate descent algorithm is adopted to reconstruct the image with a voxel-based closed-form solution. Results of numerical simulations and mouse experiments show that the self-adaptive Bayesian method significantly improves the CB-XLCT image quality as compared with conventional methods.

Fast and Robust Reconstruction for Fluorescence Molecular Tomography via L1-2 Regularization

Sparse reconstruction inspired by compressed sensing has attracted considerable attention in fluorescence molecular tomography (FMT). However, the columns of system matrix used for FMT reconstruction tend to be highly coherent, which means L₁ minimization may not produce the sparsest solution. In this paper, we propose a novel reconstruction method by minimization of the difference of L₁ and L₂ norms. To solve the nonconvex L_1-2 minimization problem, an iterative method based on the difference of convex algorithm (DCA) is presented. In each DCA iteration, the update of solution involves an L₁ minimization subproblem, which is solved by the alternating direction method of multipliers with an adaptive penalty. We investigated the performance of the proposed method with both simulated data and in vivo experimental data. The results demonstrate that the DCA for L_1-2 minimization outperforms the representative algorithms for L₁, L₂, L_1/2, and L₀ when the system matrix is highly coherent.

L p Regularization for Bioluminescence Tomography Based on the Split Bregman Method

PURPOSE

Bioluminescence tomography (BLT) is a promising in vivo optical imaging technique in preclinical research at cellular and molecular levels. The problem of BLT reconstruction is quite ill-posed and ill-conditioned. In order to achieve high accuracy and efficiency for its inverse reconstruction, we proposed a novel approach based on L _p regularization with the Split Bregman method.

PROCEDURES

The diffusion equation was used as the forward model. Then, we defined the objective function of L _p regularization and developed a Split Bregman iteration algorithm to optimize this function. After that, we conducted numerical simulations and in vivo experiments to evaluate the accuracy and efficiency of the proposed method.

RESULTS

The results of the simulations indicated that compared with the conjugate gradient and iterative shrinkage methods, the proposed method is more accurate and faster for multisource reconstructions. Furthermore, in vivo imaging suggested that it could clearly distinguish the viable and apoptotic tumor regions.

CONCLUSIONS

The Split Bregman iteration method is able to minimize the L _p regularization problem and achieve fast and accurate reconstruction in BLT.

Novel l 2,1-norm optimization method for fluorescence molecular tomography reconstruction

Fluorescence molecular tomography (FMT) is a promising tomographic method in preclinical research, which enables noninvasive real-time three-dimensional (3-D) visualization for in vivo studies. The ill-posedness of the FMT reconstruction problem is one of the many challenges in the studies of FMT. In this paper, we propose a l 2,1-norm optimization method using a priori information, mainly the structured sparsity of the fluorescent regions for FMT reconstruction. Compared to standard sparsity methods, the structured sparsity methods are often superior in reconstruction accuracy since the structured sparsity utilizes correlations or structures of the reconstructed image. To solve the problem effectively, the Nesterov's method was used to accelerate the computation. To evaluate the performance of the proposed l 2,1-norm method, numerical phantom experiments and in vivo mouse experiments are conducted. The results show that the proposed method not only achieves accurate and desirable fluorescent source reconstruction, but also demonstrates enhanced robustness to noise.

Investigation of spatial resolution characteristics of an in vivo micro computed tomography system

The spatial resolution characteristics of an in vivo micro computed tomography (CT) system was investigated in the in-plane (x-y), cross plane (z) and projection imaging modes. The micro CT system utilized in this study employs a flat panel detector with a 127 μm pixel pitch, a micro focus x-ray tube with a focal spot size ranging from 5-30 μm, and accommodates three geometric magnifications (M) of 1.72, 2.54 and 5.10. The in-plane modulation transfer function (MTF) curves were measured as a function of the number of projections, geometric magnification (M), detector binning and reconstruction magnification (M_Recon). The in plane cutoff frequency (10% MTF) ranged from 2.31 lp/mm (M=1.72, 2×2 binning) to 12.56 lp/mm (M=5.10, 1×1 binning) and a bar pattern phantom validated those measurements. A slight degradation in the spatial resolution was observed when comparing the image reconstruction with 511 and 918 projections, whose effect was visible at the lower frequencies. Small value of M_Recon has little or no impact on the in-plane spatial resolution owning to a stable system. Large value of M_Recon has implications on the spatial resolution and it was evident when comparing the bar pattern images reconstructed with M_Recon=1.25 and 2.5. The cross plane MTF curves showed that the spatial resolution increased as the slice thickness decreased. The cutoff frequencies in the projection imaging mode yielded slightly higher values as compared to the in-plane and cross plane modes at all the geometric magnifications (M). At M=5.10, the cutoff resolution of the projection and cross plane on an ultra-high contrast resolution bar chip phantom were 14.9 lp/mm and 13-13.5 lp/mm. Due to the finite focal spot size of the x-ray tube, the detector blur and the reconstruction kernel functions, the system's spatial resolution does not reach the limiting spatial resolution as defined by the Nyquist's detector criteria with an ideal point source. The geometric magnification employed in the micro CTs provide a tradeoff between field of view and spatial resolution for a wide range of applications.

Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function

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.

Reconstruction Method for Optical Tomography Based on the Linearized Bregman Iteration with Sparse Regularization

Optical molecular imaging is a promising technique and has been widely used in physiology, and pathology at cellular and molecular levels, which includes different modalities such as bioluminescence tomography, fluorescence molecular tomography and Cerenkov luminescence tomography. The inverse problem is ill-posed for the above modalities, which cause a nonunique solution. In this paper, we propose an effective reconstruction method based on the linearized Bregman iterative algorithm with sparse regularization (LBSR) for reconstruction. Considering the sparsity characteristics of the reconstructed sources, the sparsity can be regarded as a kind of a priori information and sparse regularization is incorporated, which can accurately locate the position of the source. The linearized Bregman iteration method is exploited to minimize the sparse regularization problem so as to further achieve fast and accurate reconstruction results. Experimental results in a numerical simulation and in vivo mouse demonstrate the effectiveness and potential of the proposed method.

A Novel Restraining Device for Small Animal Imaging Exams: Validation in Rabbits

Objective. To develop, validate, and patent a Restraining Device for Small Animal Imaging Exams (RDSAIE) that allows exams to be comfortably conducted without risks to animals and professionals. Methods. A RDSAIE with a mobile cover and shelf was built with transparent acrylic material. A total of six anesthetized rabbits were used to perform the following imaging exams of the skull: Cone Beam Computed Tomography, Magnetic Resonance Imaging, and Scintigraphy. Results. The device showed great functionality and full visibility of the animal behavior, which remained fully stabilized and immobilized in either the horizontal or vertical position without the need for a person to remain in the test room to assist them. The procedures were performed without difficulty, and images of good resolution and without artifacts were obtained. Conclusion. The RDSAIE is comfortable, safe, efficient, and ergonomic. It allows the easy placement of animals in different body positions, including the vertical, the maintenance of postural stability, and full visibility. It may be constructed for animals heavier than 4 kg and it is adaptable for translational studies in anima nobile.

A Novel Region Reconstruction Method for Fluorescence Molecular Tomography

Fluorescence molecular tomography (FMT) could exploit the distribution of fluorescent biomarkers that target tumors accurately and effectively, which enables noninvasive real-time 3-D visualization as well as quantitative analysis of small tumors in small animal studies in vivo. Due to the difficulties of reconstruction, continuous efforts are being made to find more practical and efficient approaches to accurately obtain the characteristics of fluorescent regions inside biological tissues. In this paper, we propose a region reconstruction method for FMT, which is defined as an L1-norm regularization piecewise constant level set approach. The proposed approach adopts a priori information including the sparsity of the fluorescent sources and the fluorescent contrast between the target and background. When the contrast of different fluorescent sources is low to a certain degree, our approach can simultaneously solve the detection and characterization problems for the reconstruction of FMT. To evaluate the performance of the region reconstruction method, numerical phantom experiments and in vivo bead-implanted mouse experiments were performed. The results suggested that the proposed region reconstruction method was able to reconstruct the features of the fluorescent regions accurately and effectively, and the proposed method was able to be feasibly adopted in in vivo application.

Reconstruction of fluorescence molecular tomography via a nonmonotone spectral projected gradient pursuit method

Fluorescence molecular tomography (FMT) is a promising imaging technique in preclinical research, enabling three-dimensional location of the specific tumor position for small animal imaging. However, FMT presents a challenging inverse problem that is quite ill-posed and ill-conditioned. Thus, the reconstruction of FMT faces various challenges in its robustness and efficiency. We present an FMT reconstruction method based on nonmonotone spectral projected gradient pursuit (NSPGP) with /₁-norm optimization. At each iteration, a spectral gradient-projection method approximately minimizes a least-squares problem with an explicit one-norm constraint. A nonmonotone line search strategy is utilized to get the appropriate updating direction, which guarantees global convergence. Additionally, the Barzilai-Borwein step length is applied to build the optimal step length, further improving the convergence speed of the proposed method. Several numerical simulation studies, including multisource cases as well as comparative analyses, have been performed to evaluate the performance of the proposed method. The results indicate that the proposed NSPGP method is able to ensure the accuracy, robustness, and efficiency of FMT reconstruction. Furthermore, an in vivo experiment based on a heterogeneous mouse model was conducted, and the results demonstrated that the proposed method held the potential for practical applications of FMT.

Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method

Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

Comprehensive evaluation of the anti-angiogenic and anti-neoplastic effects of Endostar on liver cancer through optical molecular imaging

Molecular imaging enables non-invasive monitoring of tumor growth, progression, and drug treatment response, and it has become an important tool to promote biological studies in recent years. In this study, we comprehensively evaluated the in vivo anti-angiogenic and anti-neoplastic effects of Endostar on liver cancer based on the optical molecular imaging systems including micro-computer tomography (Micro-CT), bioluminescence molecular imaging (BLI) and fluorescence molecular tomography (FMT). Firefly luciferase (fLuc) and green fluorescent protein (GFP) dual labeled human hepatocellular carcinoma cells (HCC-LM3-fLuc-GFP cells) were used to establish the subcutaneous and orthotopic liver tumor model. After the tumor cells were implanted 14∼18 days, Endostar (5 mg/kg/day) was administered through an intravenous tail vein injection for continuous 14 days. The computer tomography angiography (CTA) and BLI were carried out for the subcutaneous tumor model. FMT was executed for the orthotopic tumor model. The CTA data showed that tumor vessel formation and the peritumoral vasculature of subcutaneous tumor in the Endostar treatment group was significantly inhibited compared to the control group. The BLI data exhibited the obvious tumor inhibition day 8 post-treatment. The FMT detected the tumor suppression effects of Endostar as early as day 4 post-treatment and measured the tumor location. The above data confirmed the effects of Endostar on anti-angiogenesis and tumor suppression on liver cancer. Our system combined CTA, BLI, and FMT to offer more comprehensive information about the effects of Endostar on the suppression of vessel and tumor formation. Optical molecular imaging system enabled the non-invasive and reliable assessment of anti-tumor drug efficacy on liver cancer.

Adaptive regularized method based on homotopy for sparse fluorescence tomography

Determining an appropriate regularization parameter is often challenging work because it has a narrow range and varies with problems, which is likely to lead to large reconstruction errors. In this contribution, an adaptive regularized method based on homotopy is presented for sparse fluorescence tomography reconstruction. Due to the adaptive regularization strategy, the proposed method is always able to reconstruct sources accurately independent of the estimation of the regularization parameter. Moreover, the proposed method is about two orders of magnitude faster than the two contrasting methods. Numerical and in vivo mouse experiments have been employed to validate the robustness and efficiency of the proposed method.

L1-regularized Cerenkov luminescence tomography with a SP3 method and CT fusion

Imaging modality of radionuclides has been enriched by an optical approach, Cerenkov luminescence tomography (CLT). Referred to the traditional radionuclide imaging, such as positron emission tomography (PET) or single photon emission computed tomography (SPECT), any incremental improvement of CLT imaging is consistent with the application to information needs. In this contribution, the paper presents an l(1)-regularized imaging method for CLT problem. After utilizing the Vavilov-Cerenkov effect via third-order simplified spherical harmonics (SP(3)) approximation, we establish the large-scale linear equations in the CLT framework. The derived linear problem is seriously ill-posed, and transformed into an l(1)-regularized least squares program. The inverse solution to these equations is the three-dimensional radioisotope recovery data by an interior-point method. In the physical phantom and the in vivo mouse experiment, results demonstrate that the proposed technique produces better imaging quality and improves the reconstruction efficacy, compared with those from diffusion approximation with the Tikhonov regularization.

Quantifying the gantry sag on linear accelerators and introducing an MLC-based compensation strategy

PURPOSE

Gantry sag is one of the well-known sources of mechanical imperfections that compromise the spatial accuracy of radiation dose delivery. The objectives of this study were to quantify the gantry sag on multiple linear accelerators (linacs), to investigate a multileaf collimator (MLC)-based strategy to compensate for gantry sag, and to verify the gantry sag and its compensation with film measurements.

METHODS

The authors used the Winston-Lutz method to measure gantry sag on three Varian linacs. A ball bearing phantom was imaged with megavolt radiation fields at 10° gantry angle intervals. The images recorded with an electronic portal imaging device were analyzed to derive the radiation isocenter and the gantry sag, that is, the superior-inferior wobble of the radiation field center, as a function of the gantry angle. The authors then attempted to compensate for the gantry sag by applying a gantry angle-specific correction to the MLC leaf positions. The gantry sag and its compensation were independently verified using film measurements.

RESULTS

Gantry sag was reproducible over a six-month measurement period. The maximum gantry sag was found to vary from 0.7 to 1.0 mm, depending on the linac and the collimator angle. The radiation field center moved inferiorly (i.e., away from the gantry) when the gantry was rotated from 0° to 180°. After the MLC leaf position compensation was applied at 90° collimator angle, the maximum gantry sag was reduced to <0.2 mm. The film measurements at gantry angles of 0° and 180° verified the inferior shift of the radiation fields and the effectiveness of MLC compensation.

CONCLUSIONS

The results indicate that gantry sag on a linac can be quantitatively measured using a simple phantom and an electronic portal imaging device. Reduction of gantry sag is feasible by applying a gantry angle-specific correction to MLC leaf positions at 90° collimator angle.

Dynamic cone beam CT angiography of carotid and cerebral arteries using canine model

PURPOSE

This research is designed to develop and evaluate a flat-panel detector-based dynamic cone beam CT system for dynamic angiography imaging, which is able to provide both dynamic functional information and dynamic anatomic information from one multirevolution cone beam CT scan.

METHODS

A dynamic cone beam CT scan acquired projections over four revolutions within a time window of 40 s after contrast agent injection through a femoral vein to cover the entire wash-in and wash-out phases. A dynamic cone beam CT reconstruction algorithm was utilized and a novel recovery method was developed to correct the time-enhancement curve of contrast flow. From the same data set, both projection-based subtraction and reconstruction-based subtraction approaches were utilized and compared to remove the background tissues and visualize the 3D vascular structure to provide the dynamic anatomic information.

RESULTS

Through computer simulations, the new recovery algorithm for dynamic time-enhancement curves was optimized and showed excellent accuracy to recover the actual contrast flow. Canine model experiments also indicated that the recovered time-enhancement curves from dynamic cone beam CT imaging agreed well with that of an IV-digital subtraction angiography (DSA) study. The dynamic vascular structures reconstructed using both projection-based subtraction and reconstruction-based subtraction were almost identical as the differences between them were comparable to the background noise level. At the enhancement peak, all the major carotid and cerebral arteries and the Circle of Willis could be clearly observed.

CONCLUSIONS

The proposed dynamic cone beam CT approach can accurately recover the actual contrast flow, and dynamic anatomic imaging can be obtained with high isotropic 3D resolution. This approach is promising for diagnosis and treatment planning of vascular diseases and strokes.

Comparison of permissible source region and multispectral data using efficient bioluminescence tomography method

As a novel molecular imaging technology, bioluminescence tomography (BLT) has become an important tool for biomedical research in recent years, which can perform a quantitative reconstruction of an internal light source distribution with the scattered and transmitted bioluminescent signals measured on the external surface of a small animal. However, BLT is severely ill-posed because of complex photon propagation in the biological tissue and limited boundary measured data with noise. Therefore, sufficient a priori knowledge should be fused for the uniqueness and stability of BLT solution. Permissible source region strategy and spectrally resolved measurements are two kinds of a priori knowledge commonly used in BLT reconstruction. This paper compares their performance with simulation and in vivo heterogeneous mouse experiments. In order to improve the efficiency of large-scale source restoration, this paper introduces an efficient iterative shrinkage thresholding method that not only has faster convergence rate but also has better reconstruction accuracy than the modified Newton-type optimization approach. Finally, a discussion of these two kinds of a priori knowledge is given based on the comparison results.

Cerenkov luminescence tomography for in vivo radiopharmaceutical imaging

Cerenkov luminescence imaging (CLI) is a cost-effective molecular imaging tool for biomedical applications of radiotracers. The introduction of Cerenkov luminescence tomography (CLT) relative to planar CLI can be compared to the development of X-ray CT based on radiography. With CLT, quantitative and localized analysis of a radiopharmaceutical distribution becomes feasible. In this contribution, a feasibility study of in vivo radiopharmaceutical imaging in heterogeneous medium is presented. Coupled with a multimodal in vivo imaging system, this CLT reconstruction method allows precise anatomical registration of the positron probe in heterogeneous tissues and facilitates the more widespread application of radiotracers. Source distribution inside the small animal is obtained from CLT reconstruction. The experimental results demonstrated that CLT can be employed as an available in vivo tomographic imaging of charged particle emitters in a heterogeneous medium.

High-resolution computed tomography of single breast cancer microcalcifications in vivo

Microcalcification is a hallmark of breast cancer and a key diagnostic feature for mammography. We recently described the first robust animal model of breast cancer microcalcification. In this study, we hypothesized that high-resolution computed tomography (CT) could potentially detect the genesis of a single microcalcification in vivo and quantify its growth over time. Using a commercial CT scanner, we systematically optimized acquisition and reconstruction parameters. Two ray-tracing image reconstruction algorithms were tested: a voxel-driven "fast" cone beam algorithm (FCBA) and a detector-driven "exact" cone beam algorithm (ECBA). By optimizing acquisition and reconstruction parameters, we were able to achieve a resolution of 104 μm full width at half-maximum (FWHM). At an optimal detector sampling frequency, the ECBA provided a 28 μm (21%) FWHM improvement in resolution over the FCBA. In vitro, we were able to image a single 300 μm × 100 μm hydroxyapatite crystal. In a syngeneic rat model of breast cancer, we were able to detect the genesis of a single microcalcification in vivo and follow its growth longitudinally over weeks. Taken together, this study provides an in vivo "gold standard" for the development of calcification-specific contrast agents and a model system for studying the mechanism of breast cancer microcalcification.

Tomographic bioluminescence imaging reconstruction via a dynamically sparse regularized global method in mouse models

Generally, the performance of tomographic bioluminescence imaging is dependent on several factors, such as regularization parameters and initial guess of source distribution. In this paper, a global-inexact-Newton based reconstruction method, which is regularized by a dynamic sparse term, is presented for tomographic reconstruction. The proposed method can enhance higher imaging reliability and efficiency. In vivo mouse experimental reconstructions were performed to validate the proposed method. Reconstruction comparisons of the proposed method with other methods demonstrate the applicability on an entire region. Moreover, the reliable performance on a wide range of regularization parameters and initial unknown values were also investigated. Based on the in vivo experiment and a mouse atlas, the tolerance for optical property mismatch was evaluated with optical overestimation and underestimation. Additionally, the reconstruction efficiency was also investigated with different sizes of mouse grids. We showed that this method was reliable for tomographic bioluminescence imaging in practical mouse experimental applications.

A quality assurance procedure to evaluate cone-beam CT image center congruence with the radiation isocenter of a linear accelerator

A quality assurance (QA) procedure was developed to evaluate the congruence between the cone‐beam computed tomography (CBCT) image center and the radiation isocenter on a Varian Trilogy linac. In contrast to the published QA procedures, this method did not require a ball bearing (BB) phantom to be placed exactly at the radiation isocenter through precalibrated room lasers or light field crosshairs. The only requirement was that the BB phantom be in a stationary position near the radiation isocenter during the image acquisition process. The radiation isocenter was determined with respect to the center of the BB using a Winston‐Lutz test. The CBCT image center was found to have excellent short‐term positional reproducibility (i.e., less than 0.1 mm of wobble in each of the x (lateral), y (vertical), and z (longitudinal) directions) in 10 consecutive acquisitions. Measured over a seven‐month period, the CBCT image center deviated from the radiation isocenter by 0.40±0.12mm(x),0.43±0.04mm(y), and 0.34±0.14mm(z). The z displacement of the 3D CBCT image center was highly correlated (ρ=0.997) with that of the 2D kV portal image center. The correlation coefficients in the x and y directions were poor (ρ=0.66 and ‐0.35, respectively). Systematic discrepancies were found between the CBCT image center and the 2D MV, kV portal image centers. For the linear accelerator studied, we detected a 0.8 mm discrepancy between the CBCT image center and the MV EPID image center in the anterior‐posterior direction. This discrepancy was demonstrated in a clinical case study where the patient was positioned with CBCT followed by MV portal verification. The results from the new QA procedure are useful for guiding high‐precision patient positioning in stereotactic body radiation therapy.

PACS number: 87.55.Qr

An efficient global inexact Newton method regularized by a dynamic sparse term for in vivo tomographic bioluminescence imaging

Tomographic bioluminescence imaging suffers from poor imaging robustness, since it is severely affected by selection of regularization parameter (RP) and initialization for source distribution. In this paper, a global-inexact-Newton based reconstruction methodology, which is regularized by a dynamic sparse term, is demonstrated for in vivo tomographic imaging. The novel method can enhance higher imaging reliability and efficiency. Mouse experimental reconstructions were performed to validate the proposed method. These results demonstrate that the source distribution can be accurately located over a wide range of values of RP and iteration initializations. Moreover, the reconstruction efficiency was also studied.