Modeling and Development of Iterative Reconstruction Algorithms in Emerging X-ray Imaging Technologies

Many new promising X-ray-based biomedical imaging technologies have emerged over the last two decades. Five different novel X-ray based imaging technologies are discussed in this dissertation: differential phase-contrast tomography (DPCT), grating-based phase-contrast tomography (GB-PCT), spectral-CT (K-edge imaging), cone-beam computed tomography (CBCT), and in-line X-ray phase contrast (XPC) tomosynthesis. For each imaging modality, one or more specific problems prevent them being effectively or efficiently employed in clinical applications have been discussed. Firstly, to mitigate the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods in DPCT, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction. Secondly, to improve image quality in grating-based phase-contrast tomography, we incorporate 2nd order statistical properties of the object property sinograms, including correlations between them, into the formulation of an advanced multi-channel (MC) image reconstruction algorithm, which reconstructs three object properties simultaneously. We developed an advanced algorithm based on the proximal point algorithm and the augmented Lagrangian method to rapidly solve the MC reconstruction problem. Thirdly, to mitigate image artifacts that arise from reduced-view and/or noisy decomposed sinogram data in K-edge imaging, we exploited the inherent sparseness of typical K-edge objects and incorporated the statistical properties of the decomposed sinograms to formulate two penalized weighted least square problems with a total variation (TV) penalty and a weighted sum of a TV penalty and an l1-norm penalty with a wavelet sparsifying transform. We employed a fast iterative shrinkage/thresholding algorithm (FISTA) and splitting-based FISTA algorithm to solve these two PWLS problems. Fourthly, to enable advanced iterative algorithms to obtain better diagnostic images and accurate patient positioning information in image-guided radiation therapy for CBCT in a few minutes, two accelerated variants of the FISTA for PLS-based image reconstruction are proposed. The algorithm acceleration is obtained by replacing the original gradient-descent step by a sub-problem that is solved by use of the ordered subset concept (OS-SART). In addition, we also present efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units (GPUs). Finally, we employed our developed accelerated version of FISTA for dealing with the incomplete (and often noisy) data inherent to in-line XPC tomosynthesis which combines the concepts of tomosynthesis and in-line XPC imaging to utilize the advantages of both for biological imaging applications. We also investigate the depth resolution properties of XPC tomosynthesis and demonstrate that the z-resolution properties of XPC tomosynthesis is superior to that of conventional absorption-based tomosynthesis. To investigate all these proposed novel strategies and new algorithms in these different imaging modalities, we conducted computer simulation studies and real experimental data studies. The proposed reconstruction methods will facilitate the clinical or preclinical translation of these emerging imaging methods

Serological analysis of allergic components of house dust mite provides more insight in epidemiological characteristics and clinical symptom development in North China

BackgroundHouse dust mite (HDM) is the most common airborne source causing complex allergy symptoms. There are geographic differences in the allergen molecule sensitization profiles. Serological testing with allergen components may provide more clues for diagnosis and clinical management.ObjectiveThis study aims to investigate the sensitization profile of eight HDM allergen components in a large number of patients enrolled in the clinic and to analyze the relation of gender, age, and clinical symptoms in North China.MethodsThe 548 serum samples of HDM-allergic patients (ImmunoCAP® d1 or d2 IgE ≥0.35) were collected in Beijing City and divided in four different age groups and three allergic symptoms. The specific IgE of HDM allergenic components, Der p 1/Der f 1, Der p 2/Der f 2, Der p 7, Der p 10, Der p 21, and Der p 23, was measured using the micro-arrayed allergen test kit developed by Hangzhou Zheda Dixun Biological Gene Engineering Co., Ltd. The new system was validated by comparing to single-component Der p 1, Der p 2, and Der p 23 tests by ImmunoCAP in 39 sera. The epidemiological study of these IgE profiles and the relation to age and clinical phenotypes were analyzed.ResultsA greater proportion of male patients was in the younger age groups, while more female patients were in the adult groups. Both the sIgE levels and the positive rates (approximately 60%) against Der p 1/Der f 1 and Der p 2/Der f 2 were higher than for the Der p 7, Der p 10, and Der p 21 components (below 25%). The Der f 1 and Der p 2 positive rates were higher in 2–12-year-old children. The Der p 2 and Der f 2 IgE levels and positive rates were higher in the allergic rhinitis group. The positive rates of Der p 10 increased significantly with age. Der p 21 is relevant in allergic dermatitis symptom, while Der p 23 contributes to asthma development.ConclusionHDM groups 1 and 2 were the major sensitizing allergens, with group 2 being the most important component relevant to respiratory symptoms in North China. The Der p 10 sensitization tends to increase with age. Der p 21 and Der p 23 might be associated with the development of allergic skin disease and asthma, respectively. Multiple allergen sensitizations increased the risk of allergic asthma

Association of polymorphisms in survivin gene with the risk of hepatocellular carcinoma in Chinese han population: a case control study

<p>Abstract</p> <p>Background</p> <p>Survivin, one of the strongest apoptosis inhibitors, plays a critical role in the development and progression of hepatocellular carcinoma (HCC). By comparison, relatively little is known about the effect of <it>survivin </it>gene polymorphisms on HCC susceptibility. Our study aimed to investigate the association of <it>survivin </it>gene polymorphisms with the risk of HCC in Chinese han population.</p> <p>Methods</p> <p>A case-control study was conducted in Chinese han population consisting of 178 HCC cases and 196 cancer-free controls. Information on demographic data and related risk factors was collected for all subjects. Polymorphisms of the <it>survivin </it>gene, including three loci of rs8073069, rs9904341 and rs1042489, were selected and genotyped by a polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP) technique. Association analysis of genotypes/alleles and haplotypes from these loci with the risk of HCC was conducted under different genetic models.</p> <p>Results</p> <p>Using univariate analysis of rs8073069, rs9904341 and rs1042489 under different genetic models, no statistically significant difference was found in genotype or allele distribution of HCC cases relative to the controls (<it>P </it>> 0.05). Linkage disequilibrium (LD) analysis showed that these loci were in LD. Multivariate logistic regression indicated that with no G-C-T haplotype as reference, the haplotype of G-C-T from these loci was associated with a lower risk for HCC under the recessive model (<it>OR = </it>0.46, 95% confidence interval (<it>CI</it>): 0.24~0.90, <it>P </it>= 0.023). Both HBsAg+ and the medical history of viral hepatitis type B were risk factors for HCC. However, no statistically significant haplotype-environment interaction existed.</p> <p>Conclusions</p> <p>No association between rs8073069, rs9904341 or rs1042489 in <it>survivin </it>gene and the risk of HCC is found in Chinese han population, but rs8073069G-rs9904341C- rs1042489T is perhaps a protective haplotype for HCC.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

DataSheet_1_Deep-learning-based generation of synthetic 6-minute MRI from 2-minute MRI for use in head and neck cancer radiotherapy.pdf

BackgroundQuick magnetic resonance imaging (MRI) scans with low contrast-to-noise ratio are typically acquired for daily MRI-guided radiotherapy setup. However, for patients with head and neck (HN) cancer, these images are often insufficient for discriminating target volumes and organs at risk (OARs). In this study, we investigated a deep learning (DL) approach to generate high-quality synthetic images from low-quality images.MethodsWe used 108 unique HN image sets of paired 2-minute T2-weighted scans (2mMRI) and 6-minute T2-weighted scans (6mMRI). 90 image sets (~20,000 slices) were used to train a 2-dimensional generative adversarial DL model that utilized 2mMRI as input and 6mMRI as output. Eighteen image sets were used to test model performance. Similarity metrics, including the mean squared error (MSE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) were calculated between normalized synthetic 6mMRI and ground-truth 6mMRI for all test cases. In addition, a previously trained OAR DL auto-segmentation model was used to segment the right parotid gland, left parotid gland, and mandible on all test case images. Dice similarity coefficients (DSC) were calculated between 2mMRI and either ground-truth 6mMRI or synthetic 6mMRI for each OAR; two one-sided t-tests were applied between the ground-truth and synthetic 6mMRI to determine equivalence. Finally, a visual Turing test using paired ground-truth and synthetic 6mMRI was performed using three clinician observers; the percentage of images that were correctly identified was compared to random chance using proportion equivalence tests.ResultsThe median similarity metrics across the whole images were 0.19, 0.93, and 33.14 for MSE, SSIM, and PSNR, respectively. The median of DSCs comparing ground-truth vs. synthetic 6mMRI auto-segmented OARs were 0.86 vs. 0.85, 0.84 vs. 0.84, and 0.82 vs. 0.85 for the right parotid gland, left parotid gland, and mandible, respectively (equivalence pConclusionsUsing 2mMRI inputs, we demonstrate that DL-generated synthetic 6mMRI outputs have high similarity to ground-truth 6mMRI, but further improvements can be made. Our study facilitates the clinical incorporation of synthetic MRI in MRI-guided radiotherapy.</p

Paired Design of dCas9 as a Systematic Platform for the Detection of Featured Nucleic Acid Sequences in Pathogenic Strains

We developed an <i>in vitro</i> DNA detection system using a pair of dCas9 proteins linked to split halves of luciferase. Luminescence was induced upon colocalization of the reporter pair to a ∼44 bp target sequence defined by sgRNAs. We used the system to detect <i>Mycobacterium tuberculosis</i> DNA with high specificity and sensitivity. The reprogrammability of dCas9 was further leveraged in an array design that accesses sequence information across the entire genome