Ching-Han Hsu

A large deformation diffeomorphic metric mapping solution for diffusion spectrum imaging datasets

Spatial transformation for diffusion spectrum imaging (DSI) is an important step for group analyses of DSI datasets. In this study, we developed a transformation method for DSI datasets under the framework of large deformation diffeomorphic metric mapping (LDDMM), which is termed LDDMM-DSI. The proposed method made use of the fact that a DSI dataset is 6D, and generalized the original 2D/3D LDDMM algorithm to the 6D case with some modifications made for the DSI datasets. In this manner, the conventional reorientation problem that arises from transforming diffusion-weighted datasets was avoided by making the DSI datasets capable of being freely deformed in the q-space. The algorithm treated the data-matching task as a variational problem under the LDDMM framework and sought optimal velocity fields from which the generated transformations were diffeomorphic and the transformation curve was a geodesic. The mathematical materials and numerical implementation are detailed in the paper, and experiments were performed to analyze the proposed method on real brain DSI datasets. The results showed that the method was capable of registering different DSI datasets in both global structural shapes and local diffusion profiles. In conclusion, the proposed method can facilitate group analyses of DSI datasets and the generation of a DSI template.

A study of lesion contrast recovery for iterative PET image reconstructions versus filtered backprojection using an anthropomorphic thoracic phantom

Iterative methods for the reconstruction of positron emission tomography images can produce results superior to filtered backprojection (FBP) due to their ability to explicitly model the Poisson statistics of photon pair coincidence detection. Many conventional implementations of these methods use simple forward and backward projection schemes based on computing the area of intersection of detection tubes with each voxel. Other important physical system factors, such as depth-dependent geometric sensitivity and spatially variant detector pair resolution are often ignored. One goal of this work is to examine the effect of a more accurate system model on iterative algorithm performance. A second factor that limits the performance of an iterative algorithm is the chosen objective function and the manner in which it is optimized. In this paper, performance of the following image reconstruction methods is evaluated: FBP, ordered subsets expectation maximization (OSEM) algorithm, and maximum a posteriori (MAP) estimation using Gibbs prior with convex potential functions. Using the contrast recovery coefficient (CRC) as a performance measure, this paper presents a lesion detection experiment based on an anthropomorphic thoracic phantom and demonstrates how the choices of reconstruction algorithm and projection matrix affect reconstruction accuracy. Plots of CRC versus background variance were generated by varying cut-off frequency in FBP, post-smoothing Gaussian kernel in OSEM, and smoothing hyper-parameter in MAP. The results of these studies show that all of the iterative methods evaluated produce superior CRCs than FBP at matched background variation. In addition, there is also considerable variation in performance within the class of statistical iterative methods depending on the choice of projection matrix and reconstruction algorithm.

Cyber surveillance for flood disasters.

Regional heavy rainfall is usually caused by the influence of extreme weather conditions. Instant heavy rainfall often results in the flooding of rivers and the neighboring low-lying areas, which is responsible for a large number of casualties and considerable property loss. The existing precipitation forecast systems mostly focus on the analysis and forecast of large-scale areas but do not provide precise instant automatic monitoring and alert feedback for individual river areas and sections. Therefore, in this paper, we propose an easy method to automatically monitor the flood object of a specific area, based on the currently widely used remote cyber surveillance systems and image processing methods, in order to obtain instant flooding and waterlogging event feedback. The intrusion detection mode of these surveillance systems is used in this study, wherein a flood is considered a possible invasion object. Through the detection and verification of flood objects, automatic flood risk-level monitoring of specific individual river segments, as well as the automatic urban inundation detection, has become possible. The proposed method can better meet the practical needs of disaster prevention than the method of large-area forecasting. It also has several other advantages, such as flexibility in location selection, no requirement of a standard water-level ruler, and a relatively large field of view, when compared with the traditional water-level measurements using video screens. The results can offer prompt reference for appropriate disaster warning actions in small areas, making them more accurate and effective.

Visual Sensing for Urban Flood Monitoring

With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.

Angiogenic evaluation of ginsenoside Rg1 from Panax ginseng in fluorescent transgenic mice

BACKGROUND Evaluation of angiogenesis-inducing compounds is essential in tissue engineering to develop biological substitutes for the repair or regeneration of tissue function. In this report, we evaluated the angiogenic ability of ginsenoside Rg 1 from Panax ginseng, in Matrigel implanted on fluorescent transgenic mice. METHODS The in vitro proliferation ability of each test agent was estimated by MTS assay. The Matrigel loaded with basic fibroblast growth factor (bFGF) or Rg 1 and Matrigel alone were implanted on fluorescent transgenic mice and were retrieved at 1, 4, 6 and 8 weeks after implantation to measure various conventional markers for angiogenesis including neo-vascular density and hemoglobin content. Additionally, the functional neo-vasculature in the implanted Matrigel was visualized using confocal laser scanning microscopy (CLSM). RESULTS The in vitro results indicated that the stimulating effect of Rg 1 on HUVECs proliferation remained unchanged after dissolved for 30 days in culture medium at 37 degrees C when compared with the effect of bFGF. One week after implantation in transgenic mice, bFGF or Rg 1 mixed in Matrigel plug significantly enhanced angiogenesis; however, at 6 weeks a significant decrease in angiogenic effect was observed in Matrigel with bFGF, but not in Matrigel with Rg 1. The neo-vessels structure was visualized in three dimensions (3D) by CLSM and the results were in agreement with other conventional measurements for angiogenesis. CONCLUSION These findings confirm that Rg 1 could be used in tissue tissue-engineering applications and that the fluorescent transgenic mice can be a useful experimental model for studying angiogenesis.

Correction for Susceptibility-Induced Distortion in Echo-Planar Imaging Using Field Maps and Model-Based Point Spread Function

Susceptibility-induced distortion is one of the major artifacts in echo-planar imaging (EPI), and many solutions have been proposed for the problem, including the Fourier method and the point spread function (PSF) method. In this paper, a framework unifying both methods is presented. Under this framework, a model-based PSF method is proposed in which the PSF of the source object is modeled along with a single field map measured by TE-offset reference scans. EPI images of a phantom and a healthy human subject were acquired, and the results of distortion correction by the Fourier method, linear interpolation method, and the model-based PSF method were compared. The results showed that the model-based PSF method could correct for geometric distortion and signal intensity distortion satisfactorily, avoiding the rippling artifact shown in the Fourier method. In conclusion, the proposed framework gave us an overall picture of how different correction methods work. The model-based PSF method, which required fewer reference scans and less computational load, was more clinically feasible than other methods.

Respiration-Averaged CT for Attenuation Correction of PET Images – Impact on PET Texture Features in Non-Small Cell Lung Cancer Patients

Purpose We compared attenuation correction of PET images with helical CT (PET/HCT) and respiration-averaged CT (PET/ACT) in patients with non-small-cell lung cancer (NSCLC) with the goal of investigating the impact of respiration-averaged CT on 18F FDG PET texture parameters. Materials and Methods A total of 56 patients were enrolled. Tumors were segmented on pretreatment PET images using the adaptive threshold. Twelve different texture parameters were computed: standard uptake value (SUV) entropy, uniformity, entropy, dissimilarity, homogeneity, coarseness, busyness, contrast, complexity, grey-level nonuniformity, zone-size nonuniformity, and high grey-level large zone emphasis. Comparisons of PET/HCT and PET/ACT were performed using Wilcoxon signed-rank tests, intraclass correlation coefficients, and Bland-Altman analysis. Receiver operating characteristic (ROC) curves as well as univariate and multivariate Cox regression analyses were used to identify the parameters significantly associated with disease-specific survival (DSS). A fixed threshold at 45% of the maximum SUV (T45) was used for validation. Results SUV maximum and total lesion glycolysis (TLG) were significantly higher in PET/ACT. However, texture parameters obtained with PET/ACT and PET/HCT showed a high degree of agreement. The lowest levels of variation between the two modalities were observed for SUV entropy (9.7%) and entropy (9.8%). SUV entropy, entropy, and coarseness from both PET/ACT and PET/HCT were significantly associated with DSS. Validation analyses using T45 confirmed the usefulness of SUV entropy and entropy in both PET/HCT and PET/ACT for the prediction of DSS, but only coarseness from PET/ACT achieved the statistical significance threshold. Conclusions Our results indicate that 1) texture parameters from PET/ACT are clinically useful in the prediction of survival in NSCLC patients and 2) SUV entropy and entropy are robust to attenuation correction methods.

Human Breast Tumor Cells Express Multimodal Imaging Reporter Genes

ObjectiveHuman ZR75-1 cells were among the first few characterized estrogen-dependent mammary gland carcinoma cell lines and had been utilized in various studies for the pro- or antitumor effect of xenoestrogens and antiestrogens. The objective of this study was to establish a breast tumor model in ZR75-1 cells bearing multimodal reporter genes to allow noninvasive imaging of tumor growth using fluorescence and nuclear imaging platforms.Methods and ResultsEnhanced green fluorescent protein (eGFP) cDNA was fused at the C-terminus with herpes simplex virus type 1 thymidine kinase (HSV1-tk) to form the fusion reporter gene (eGFP-tk).In vitro proliferation, migration, and invasion assays revealed that eGFP-tk-transfected ZR75-1 cells exhibited decreased proliferation rate, migratory activity, and invasion ability compared to the wild-type cells. The functional HSV1-tk enzymatic activity in stably transfected cells were confirmed by in vitro ganciclovir (GCV) sensitivity and [123I]2-fluoro-2-deoxy-1-β-d-arabinofuranosyl-5-iodouracil (FIAU) accumulation assays. In vivo fluorescence and nuclear imaging were performed on nude mice bearing multiple subcutaneous xenografts established from ZR75-1-eGFP-tk and wild-type cells. Optical imaging was able to detect the green fluorescence of eGFP-tk tumor. The eGFP-tk reporter gene-specific imaging was achieved by single photon emission computed tomography (SPECT) using [123I]FIAU as a radiotracer and demonstrated decreased FIAU uptake in eGFP-tk tumor by GCV treatment. Probably due to a flare reaction after GCV treatment, micro-positron emission tomography (micro-PET) imaging using 2-deoxy-2-[18F]fluoro-d-glucose (FDG) could not demonstrate decreases in FDG uptake. However, in vitro metabolic assay also revealed that eGFP-tk cells transiently increased [3H]-deoxyglucose uptake in response to GCV treatment.ConclusionsThis study confirmed the usefulness of eGFP-tk in many applications by providing, in vitro and in vivo, the sensitive and reporter gene-specific imaging. ZR75-1-eGFP-tk cells that are ready to incorporate in various imaging platforms constitute a useful model in breast cancer research.

RU486-inducible recombination in the salivary glands of lactoferrin promoter-driven green fluorescent Cre transgenic mice.

When compared with the many tamoxifen‐activated Cre mouse lines available for gene manipulation studies, relatively few RU486‐inducible Cre mice are in use, due to leakiness issues. Here, we report the generation of an RU486‐inducible triple fusion gene (GCrePR1e), consisting of green fluorescent protein, Cre, and the progesterone receptor ligand‐binding domain (F642‐L901). We sought to improve the GCrePR1e by selecting a truncated human lactoferrin (Lf) promoter to drive its expression, based on the promoters low basal activity and innate sensitivity to RU486. The resulting vector displayed decreased leakiness and increased Cre induction by RU486 through transcriptional and posttranslational regulation in in vitro transfection assays. Inducible GCrePR1e expression was found in most organs of Lf‐GCrePR1e transgenic mice and highly activated in the salivary gland, spleen, and lymph nodes. In the bigenic mouse generated by crossing the Lf‐GCrePR1e mouse and the Cre reporter mouse (R26R‐LacZ), we found that RU486‐induced LacZ expression only in the mucous acini and striated ducts of the salivary gland and had very low background recombination in the untreated mice. Our results demonstrated that the Lf‐CrePR1e vector was suitable for in vitro recombination in culture models, and Lf‐CrePR1e transgenic mice could mediate spatially restricted and RU486‐induced gene manipulation in the salivary gland. genesis 48:585–595, 2010.

Scatter correction for 3D PET using beam stoppers combined with dual-energy window acquisition: a feasibility study.

Fully three-dimensional (3D) positron emission tomography (PET) can achieve high sensitivity of coincidence events, but the absence of inter-slice septa inevitably leads to increased scattered events. The scattered events can represent as much as 50% of the total detected events. In this research, we proposed a scatter correction method for 3D PET based on beam stoppers and dual-energy window acquisition. The beam stoppers were placed surrounding the object to attenuate primary beams. The scatter fractions were directly estimated at those blocked lines of response and then the entire scatter fraction distribution was recovered using the dual-energy window ratio as reference. The performance was evaluated by using Monte Carlo simulations of various digital phantoms. For the Utah phantom study, the proposed method accurately estimated the scatter fraction distribution, and improved image contrast and quantification based on four different quality indices as performance measures. For the non-homogeneous Zubal phantom, the simulated results also demonstrated that the proposed method achieved a better restoration of image contrast than the dual-energy window method. We conclude that the proposed scatter correction method could effectively suppress various kinds of scattered events, including multiple scatter and scatter from outside the field of view.