Knockdown of ChREBP ameliorates retinal microvascular endothelial cell injury and angiogenic responses in diabetic retinopathy.

PURPOSE: To examine whether and how carbohydrate response element-binding protein (ChREBP) plays a role in diabetic retinopathy. METHODS: Western blotting was used to detect ChREBP expression and location following high glucose stimulation of Human Retinal Microvascular Endothelial Cells (HRMECs). Flow cytometry, TUNEL staining, and western blotting were used to evaluate apoptosis following ChREBP siRNA silencing. Cell scratch, transwell migration, and tube formation assays were used to determine cell migration and angiogenesis. Diabetic models for wild-type (WT) and ChREBP knockout (ChKO) mice were developed. Retinas of WT and ChKO animals were cultivated in vitro with vascular endothelial growth factor + high glucose to assess neovascular development. RESULTS: ChREBP gene knockdown inhibited thioredoxin-interacting protein and NOD-like receptor family pyrin domain containing protein 3 expression in HRMECs, which was caused by high glucose stimulation, reduced apoptosis, hindered migration, and tube formation, and repressed AKT/mTOR signaling pathway activation. Compared with WT mice, ChKO mice showed suppressed high glucose-induced alterations in retinal structure, alleviated retinal vascular leakage, and reduced retinal neovascularization. CONCLUSIONS: ChREBP deficiency decreased high glucose-induced apoptosis, migration, and tube formation in HRMECs as well as structural and angiogenic responses in the mouse retina; thus, it is a potential therapeutic target for diabetic retinopathy.

Toward evaluation of multiresolution cortical thickness estimation with FreeSurfer, MaCRUISE, and BrainSuite.

Advances in Magnetic Resonance Imaging hardware and methodologies allow for promoting the cortical morphometry with submillimeter spatial resolution. In this paper, we generated 3D self-enhanced high-resolution (HR) MRI imaging, by adapting 1 deep learning architecture, and 3 standard pipelines, FreeSurfer, MaCRUISE, and BrainSuite, have been collectively employed to evaluate the cortical thickness. We systematically investigated the differences in cortical thickness estimation for MRI sequences at multiresolution homologously originated from the native image. It has been revealed that there systematically exhibited the preferences in determining both inner and outer cortical surfaces at higher resolution, yielding most deeper cortical surface placements toward GM/WM or GM/CSF boundaries, which directs a consistent reduction tendency of mean cortical thickness estimation; on the contrary, the lower resolution data will most probably provide a more coarse and rough evaluation in cortical surface reconstruction, resulting in a relatively thicker estimation. Although the differences of cortical thickness estimation at the diverse spatial resolution varied with one another, almost all led to roughly one-sixth to one-fifth significant reduction across the entire brain at the HR, independent to the pipelines we applied, which emphasizes on generally coherent improved accuracy in a data-independent manner and endeavors to cost-efficiency with quantitative opportunities.

New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS.

Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.

Effect of 0.02% and 0.01% atropine on astigmatism: a two-year clinical trial.

BACKGROUND: To evaluate the effects of 0.02% and 0.01% atropine eye drops on ocular and corneal astigmatism over 2 years. METHODS: A prospective clinic-controlled trail. The cohort study assessed 400 myopic children and divided them into three groups: 138 and 142 children were randomized to use either 0.02% or 0.01% atropine eye drops, respectively. They wore single-vision (SV) spectacles, with one drop of atropine applied to both eyes once nightly. Control children (n = 120) only wore SV spectacles. Spherical equivalent refractive errors (SER) and corneal curvature were measured every 4 months. The SER and corneal curvature were assessed by cycloplegic autorefraction and IOLMaster. Ocular and corneal astigmatism were calculated by Thibos vector analysis and then split into its power vector components, J0 (with-the-rule astigmatism) and J45 (oblique). RESULTS: After 2 years, the ocular astigmatism increased by -0.38 ± 0.29 D, -0.47 ± 0.38 D, -0.41 ± 0.35 D in the 0.02%, 0.01% atropine groups and control group, respectively (p = 0.15). The corresponding corneal astigmatism increased by -0.20 ± 0.34 D, -0.28 ± 0.35 D and -0.26 ± 0.26 D (p = 0.18). The ocular astigmatism J0 increased by 0.19 ± 0.28 D, 0.22 ± 0.36 D, 0.18 ± 0.31 D in the 0.02% atropine, 0.01% atropine and control groups, respectively (p = 0.65). The corresponding corneal astigmatism J0 increased by -0.05 ± 0.34 D, -0.11 ± 0.37 D and -0.13 ± 0.30 D (p = 0.23). There was a small but significant increase in ocular astigmatism (including J0) (all P < 0.05), but there were no changes in the ocular astigmatism J45 and corneal astigmatism (including J0 and J45) in the three groups over time (all p > 0.05). However, there were no significant differences in the changes in ocular astigmatism (including J0) among the three groups. CONCLUSIONS: Treatment with 0.02% and 0.01% atropine had no clinically significant effect on ocular and corneal astigmatism over 2 years. TRIAL REGISTRATION: The First Affiliated Hospital of Zhengzhou University, ChiCTR-IPD-16008844 . Registered 14/07/2016.

SLIMM: Slice localization integrated MRI monitoring.

Functional MRI (fMRI) is extremely challenging to perform in subjects who move because subject motion disrupts blood oxygenation level dependent (BOLD) signal measurement. It has become common to use retrospective framewise motion detection and censoring in fMRI studies to eliminate artifacts arising from motion. Data censoring results in significant loss of data and statistical power unless the data acquisition is extended to acquire more data not corrupted by motion. Acquiring more data than is necessary leads to longer than necessary scan duration, which is more expensive and may lead to additional subject non-compliance. Therefore, it is well established that real-time prospective motion monitoring is crucial to ensure data quality and reduce imaging costs. In addition, real-time monitoring of motion allows for feedback to the operator and the subject during the acquisition, to enable intervention to reduce the subject motion. The most widely used form of motion monitoring for fMRI is based on volume-to-volume registration (VVR), which quantifies motion as the misalignment between subsequent volumes. However, motion is not constrained to occur only at the boundaries of volume acquisition, but instead may occur at any time. Consequently, each slice of an fMRI acquisition may be displaced by motion, and assessment of whole volume to volume motion may be insensitive to both intra-volume and inter-volume motion that is revealed by displacement of the slices. We developed the first slice-by-slice self-navigated motion monitoring system for fMRI by developing a real-time slice-to-volume registration (SVR) algorithm. Our real-time SVR algorithm, which is the core of the system, uses a local image patch-based matching criterion along with a Levenberg-Marquardt optimizer, all accelerated via symmetric multi-processing, with interleaved and simultaneous multi-slice acquisition schemes. Extensive experimental results on real motion data demonstrated that our fast motion monitoring system, named Slice Localization Integrated MRI Monitoring (SLIMM), provides more accurate motion measurements than a VVR based approach. Therefore, SLIMM offers improved online motion monitoring which is particularly important in fMRI for challenging patient populations. Real-time motion monitoring is crucial for online data quality control and assurance, for enabling feedback to the subject and the operator to act to mitigate motion, and in adaptive acquisition strategies that aim to ensure enough data of sufficient quality is acquired without acquiring excess data.

Handling noise in single image defocus map estimation by using directional filters.

State-of-the-art defocus map estimation methods are sensitive to image noise. Even a small amount of noise can degrade defocus map estimation dramatically. However, directly applying image denoising methods often changes edge profiles, thus leading to inaccurate defocus estimation. In this Letter, we propose a new method for estimating a defocus map from a noisy image. We observe that after using a directional low-pass filter to an input image, noise is greatly reduced while the edges orthogonal to the directional filter are well preserved. Based on this observation, we apply a series of directional filters at different orientations, and then estimate the blur amount of the edges, which are orthogonal to the direction of the filter in each filtered image. In order to obtain a full defocus map, we propagate the blur amount estimated at edges to the entire image by an edge-aware interpolation method. Experimental results on synthetic and real data demonstrate that our method can estimate defocus maps better than the state-of-the-art approaches.

Naturally occurring lactic Acid bacteria isolated from tomato pomace silage.

Silage making has become a significant method of forage conservation worldwide. To determine how tomato pomace (TP) may be used effectively as animal feed, it was ensilaged for 90 days and microbiology counts, fermentation characteristics and chemical composition of tomato pomace silage (TPS) were evaluated at the 30th, 60th, and 90th days, respectively. In addition, 103 lactic acid bacteria were isolated from TPS. Based on the phenotypic and chemotaxonomic characteristics, 16S rDNA sequence and carbohydrate fermentation tests, the isolates were identified as 17 species namely: Lactobacillus coryniformis subsp. torquens (0.97%), Lactobacillus pontis (0.97%), Lactobacillus hilgardii (0.97%), Lactobacillus pantheris (0.97%), Lactobacillus amylovorus (1.9%), Lactobacillus panis (1.9%), Lactobacillus vaginalis (1.9%), Lactobacillus rapi (1.9%), Lactobacillus buchneri (2.9%), Lactobacillus parafarraginis (2.9%), Lactobacillus helveticus (3.9%), Lactobacillus camelliae (3.9%), Lactobacillus fermentum (5.8%), Lactobacillus manihotivorans (6.8%), Lactobacillus plantarum (10.7%), Lactobacillus harbinensis (16.5%) and Lactobacillus paracasei subsp. paracasei (35.0%). This study has shown that TP can be well preserved for 90 days by ensilaging and that TPS is not only rich in essential nutrients, but that physiological and biochemical properties of the isolates could provide a platform for future design of lactic acid bacteria (LAB) inoculants aimed at improving the fermentation quality of silage.

Genome-Wide Association Studies Using 3VmrMLM Model Provide New Insights into Branched-Chain Amino Acid Contents in Rice Grains.

Rice (Oryza sativa L.) is a globally important food source providing carbohydrates, amino acids, and dietary fiber for humans and livestock. The branched-chain amino acid (BCAA) level is a complex trait related to the nutrient quality of rice. However, the genetic mechanism underlying the BCAA (valine, leucine, and isoleucine) accumulation in rice grains remains largely unclear. In this study, the grain BCAA contents and 239,055 SNPs of a diverse panel containing 422 rice accessions were adopted to perform a genome-wide association study (GWAS) using a recently proposed 3VmrMLM model. A total of 357 BCAA-content-associated main-effect quantitative trait nucleotides (QTNs) were identified from 15 datasets (12 BCAA content datasets and 3 BLUP datasets of BCAA). Furthermore, the allelic variation of two novel candidate genes, LOC_Os01g52530 and LOC_Os06g15420, responsible for the isoleucine (Ile) content alteration were identified. To reveal the genetic basis of the potential interactions between the gene and environmental factor, 53 QTN-by-environment interactions (QEIs) were detected using the 3VmrMLM model. The LOC_Os03g24460, LOC_Os01g55590, and LOC_Os12g31820 were considered as the candidate genes potentially contributing to the valine (Val), leucine (Leu), and isoleucine (Ile) accumulations, respectively. Additionally, 10 QTN-by-QTN interactions (QQIs) were detected using the 3VmrMLM model, which were putative gene-by-gene interactions related to the Leu and Ile contents. Taken together, these findings suggest that the implementation of the 3VmrMLM model in a GWAS may provide new insights into the deeper understanding of BCAA accumulation in rice grains. The identified QTNs/QEIs/QQIs serve as potential targets for the genetic improvement of rice with high BCAA levels.

Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax.

Introduction: Flax (Linum usitatissimum L.) is an economically important crop due to its oil and fiber. However, it is prone to various diseases, including pasmo caused by the fungus Septoria linicola. Methods: In this study, we conducted field evaluations of 445 flax accessions over a five-year period (2012-2016) to assess their resistance to pasmo A total of 246,035 single nucleotide polymorphisms (SNPs) were used for genetic analysis. Four statistical models, including the single-locus model GEMMA and the multi-locus models FarmCPU, mrMLM, and 3VmrMLM, were assessed to identify quantitative trait nucleotides (QTNs) associated with pasmo resistance. Results: We identified 372 significant QTNs or 132 tag QTNs associated with pasmo resistance from five pasmo resistance datasets (PAS2012-PAS2016 and the 5-year average, namely PASmean) and three genotypic datasets (the all SNPs/ALL, the gene-based SNPs/GB and the RGA-based SNPs/RGAB). The tag QTNs had R2 values of 0.66-16.98% from the ALL SNP dataset, 0.68-20.54%from the GB SNP dataset, and 0.52-22.42% from the RGAB SNP dataset. Of these tag QTNs, 93 were novel. Additionally, 37 resistance gene analogs (RGAs)co-localizing with 39 tag QTNs were considered as potential candidates for controlling pasmo resistance in flax and 50 QTN-by-environment interactions(QEIs) were identified to account for genes by environmental interactions. Nine RGAs were predicted as candidate genes for ten QEIs. Discussion: Our results suggest that pasmo resistance in flax is polygenic and potentially influenced by environmental factors. The identified QTNs provide potential targets for improving pasmo resistance in flax breeding programs. This study sheds light on the genetic basis of pasmo resistance and highlights the importance of considering both genetic and environmental factors in breeding programs for flax.

Cu(II)-catalyzed asymmetric hydrosilylation of diaryl- and aryl heteroaryl ketones: application in the enantioselective synthesis of orphenadrine and neobenodine.

With certain amounts of sodium tert-butoxide and tert-butanol as additives, catalytic amounts of an inexpensive and easy-to-handle copper source Cu(OAc)(2)⋅H(2)O, a commercially available and air-stable non-racemic dipyridylphosphine ligand, as well as the stoichiometric desirable hydride donor polymethylhydrosiloxane (PMHS), formed a versatile in situ catalyst system for the enantioselective reduction of a broad spectrum of prochiral diaryl and aryl heteroarylketones in air, in high yields and with good to excellent enantioselectivities (up to 96 %). In particular, the practical viability of this process was evinced by its successful applications in the asymmetric synthesis of optically enriched potent antihistaminic drugs orphenadrine and neobenodine.

Scan-Specific Generative Neural Network for MRI Super-Resolution Reconstruction.

The interpretation and analysis of Magnetic resonance imaging (MRI) benefit from high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is time-consuming and costly, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) is one of the most widely used methods in MRI since it allows for the trade-off between high spatial resolution, high SNR, and reduced scan times. Deep learning has emerged for improved SRR as compared to conventional methods. However, current deep learning-based SRR methods require large-scale training datasets of high-resolution images, which are practically difficult to obtain at a suitable SNR. We sought to develop a methodology that allows for dataset-free deep learning-based SRR, through which to construct images with higher spatial resolution and of higher SNR than can be practically obtained by direct Fourier encoding. We developed a dataset-free learning method that leverages a generative neural network trained for each specific scan or set of scans, which in turn, allows for SRR tailored to the individual patient. With the SRR from three short duration scans, we achieved high quality brain MRI at an isotropic spatial resolution of 0.125 cubic mm with six minutes of imaging time for T2 contrast and an average increase of 7.2 dB (34.2%) in SNR to these short duration scans. Motion compensation was achieved by aligning the three short duration scans together. We assessed our technique on simulated MRI data and clinical data acquired from 15 subjects. Extensive experimental results demonstrate that our approach achieved superior results to state-of-the-art methods, while in parallel, performed at reduced cost as scans delivered with direct high-resolution acquisition.

Genome-wide association studies of five free amino acid levels in rice.

Rice (Oryza sativa L.) is one of the important staple foods for human consumption and livestock use. As a complex quality trait, free amino acid (FAA) content in rice is of nutritional importance. To dissect the genetic mechanism of FAA level, five amino acids' (Val, Leu, Ile, Arg, and Trp) content and 4,325,832 high-quality SNPs of 448 rice accessions were used to conduct genome-wide association studies (GWAS) with nine different methods. Of these methods, one single-locus method (GEMMA), seven multi-locus methods (mrMLM, pLARmEB, FASTmrEMMA, pKWmEB, FASTmrMLM, ISIS EM-BLASSO, and FarmCPU), and the recent released 3VmrMLM were adopted for methodological comparison of quantitative trait nucleotide (QTN) detection and identification of stable quantitative trait nucleotide loci (QTLs). As a result, 987 QTNs were identified by eight multi-locus GWAS methods; FASTmrEMMA detected the most QTNs (245), followed by 3VmrMLM (160), and GEMMA detected the least QTNs (0). Among 88 stable QTLs identified by the above methods, 3VmrMLM has some advantages, such as the most common QTNs, the highest LOD score, and the highest proportion of all detected stable QTLs. Around these stable QTLs, candidate genes were found in the GO classification to be involved in the primary metabolic process, biosynthetic process, and catalytic activity, and shown in KEGG analysis to have participated in metabolic pathways, biosynthesis of amino acids, and tryptophan metabolism. Natural variations of candidate genes resulting in the content alteration of five FAAs were identified in this association panel. In addition, 95 QTN-by-environment interactions (QEIs) of five FAA levels were detected by 3VmrMLM only. GO classification showed that the candidate genes got involved in the primary metabolic process, transport, and catalytic activity. Candidate genes of QEIs played important roles in valine, leucine, and isoleucine degradation (QEI_09_03978551 and candidate gene LOC_Os09g07830 in the Leu dataset), tryptophan metabolism (QEI_01_00617184 and candidate gene LOC_Os01g02020 in the Trp dataset), and glutathione metabolism (QEI_12_09153839 and candidate gene LOC_Os12g16200 in the Arg dataset) pathways through KEGG analysis. As an alternative of the multi-locus GWAS method, these findings suggested that the application of 3VmrMLM may provide new insights into better understanding FAA accumulation and facilitate the molecular breeding of rice with high FAA level.

Super-resolution reconstruction of T2-weighted thick-slice neonatal brain MRI scans.

BACKGROUND AND PURPOSE: Super-resolutionreconstruction (SRR) can be used to reconstruct 3-dimensional (3D) high-resolution (HR) volume from several 2-dimensional (2D) low-resolution (LR) stacks of MRI slices. The purpose is to compare lengthy 2D T2-weighted HR image acquisition of neonatal subjects with 3D SRR from several LR stacks in terms of image quality for clinical and morphometric assessments. METHODS: LR brain images were acquired from neonatal subjects to reconstruct isotropic 3D HR volumes by using SRR algorithm. Quality assessments were done by an experienced pediatric radiologist using scoring criteria adapted to newborn anatomical landmarks. The Wilcoxon signed-rank test was used to compare scoring results between HR and SRR images. For quantitative assessments, morphology-based segmentation was performed on both HR and SRR images and Dice coefficients between the results were computed. Additionally, simple linear regression was performed to compare the tissue volumes. RESULTS: No statistical difference was found between HR and SRR structural scores using Wilcoxon signed-rank test (p = .63, Z = .48). Regarding segmentation results, R2 values for the volumes of gray matter, white matter, cerebrospinal fluid, basal ganglia, cerebellum, and total brain volume including brain stem ranged between .95 and .99. Dice coefficients between the segmented regions from HR and SRR ranged between .83 ± .04 and .96 ± .01. CONCLUSION: Qualitative and quantitative assessments showed that 3D SRR of several LR images produces images that are of comparable quality to standard 2D HR image acquisition for healthy neonatal imaging without loss of anatomical details with similar edge definition allowing the detection of fine anatomical structures and permitting comparable morphometric measurement.

Copper(II)-catalyzed hydrosilylation of ketones using chiral dipyridylphosphane ligands: highly enantioselective synthesis of valuable alcohols.

In the presence of PhSiH(3) as the reductant, the combination of enantiomeric dipyridylphosphane ligands and Cu(OAc)(2)·H(2)O, which is an easy-to-handle and inexpensive copper salt, led to a remarkably practical and versatile chiral catalyst system. The stereoselective formation of a selection of synthetically interesting ß-, γ- or δ-halo alcohols bearing high degrees of enantiopurity (up to 99.9% enantiomeric excess (ee)) was realized with a substrate-to-ligand molar ratio (S/L) of up to 10,000. The present protocol also allowed the hydrosilylation of a diverse spectrum of alkyl aryl ketones with excellent enantioselectivities (up to 98% ee) and exceedingly high turn-over rates (up to 50,000 S/L molar ratio in 50 min reaction time) in air, under very mild conditions, which offers great opportunities for the preparation of various physiologically active targets. The synthetic utility of the chiral products obtained was highlighted by the efficient conversion of optically enriched ß-halo alcohols into the corresponding styrene oxide, ß-amino alcohol, and ß-azido alcohol, respectively.

MRI Super-Resolution Through Generative Degradation Learning.

Spatial resolution plays a critically important role in MRI for the precise delineation of the imaged tissues. Unfortunately, acquisitions with high spatial resolution require increased imaging time, which increases the potential of subject motion, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) has recently emerged as a technique that allows for a trade-off between high spatial resolution, high SNR, and short scan duration. Deconvolution-based SRR has recently received significant interest due to the convenience of using the image space. The most critical factor to succeed in deconvolution is the accuracy of the estimated blur kernels that characterize how the image was degraded in the acquisition process. Current methods use handcrafted filters, such as Gaussian filters, to approximate the blur kernels, and have achieved promising SRR results. As the image degradation is complex and varies with different sequences and scanners, handcrafted filters, unfortunately, do not necessarily ensure the success of the deconvolution. We sought to develop a technique that enables accurately estimating blur kernels from the image data itself. We designed a deep architecture that utilizes an adversarial scheme with a generative neural network against its degradation counterparts. This design allows for the SRR tailored to an individual subject, as the training requires the scan-specific data only, i.e., it does not require auxiliary datasets of high-quality images, which are practically challenging to obtain. With this technique, we achieved high-quality brain MRI at an isotropic resolution of 0.125 cubic mm with six minutes of imaging time. Extensive experiments on both simulated low-resolution data and clinical data acquired from ten pediatric patients demonstrated that our approach achieved superior SRR results as compared to state-of-the-art deconvolution-based methods, while in parallel, at substantially reduced imaging time in comparison to direct high-resolution acquisitions.

Gradient-Guided Isotropic MRI Reconstruction from Anisotropic Acquisitions.

The trade-off between image resolution, signal-to-noise ratio (SNR), and scan time in any magnetic resonance imaging (MRI) protocol is inevitable and unavoidable. Super-resolution reconstruction (SRR) has been shown effective in mitigating these factors, and thus, has become an important approach in addressing the current limitations of MRI. In this work, we developed a novel, image-based MRI SRR approach based on anisotropic acquisition schemes, which utilizes a new gradient guidance regularization method that guides the high-resolution (HR) reconstruction via a spatial gradient estimate. Further, we designed an analytical solution to propagate the spatial gradient fields from the low-resolution (LR) images to the HR image space and exploited these gradient fields over multiple scales with a dynamic update scheme for more accurate edge localization in the reconstruction. We also established a forward model of image formation and inverted it along with the proposed gradient guidance. The proposed SRR method allows subject motion between volumes and is able to incorporate various acquisition schemes where the LR images are acquired with arbitrary orientations and displacements, such as orthogonal and through-plane origin-shifted scans. We assessed our proposed approach on simulated data as well as on the data acquired on a Siemens 3T MRI scanner containing 45 MRI scans from 14 subjects. Our experimental results demonstrate that our approach achieved superior reconstructions compared to state-of-the-art methods, both in terms of local spatial smoothness and edge preservation, while, in parallel, at reduced, or at the same cost as scans delivered with direct HR acquisition.

Fast and High-Resolution Neonatal Brain MRI Through Super-Resolution Reconstruction From Acquisitions With Variable Slice Selection Direction.

The brain of neonates is small in comparison to adults. Imaging at typical resolutions such as one cubic mm incurs more partial voluming artifacts in a neonate than in an adult. The interpretation and analysis of MRI of the neonatal brain benefit from a reduction in partial volume averaging that can be achieved with high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is slow, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio. The purpose of this study is thus that using super-resolution reconstruction in conjunction with fast imaging protocols to construct neonatal brain MRI images at a suitable signal-to-noise ratio and with higher spatial resolution than can be practically obtained by direct Fourier encoding. We achieved high quality brain MRI at a spatial resolution of isotropic 0.4 mm with 6 min of imaging time, using super-resolution reconstruction from three short duration scans with variable directions of slice selection. Motion compensation was achieved by aligning the three short duration scans together. We applied this technique to 20 newborns and assessed the quality of the images we reconstructed. Experiments show that our approach to super-resolution reconstruction achieved considerable improvement in spatial resolution and signal-to-noise ratio, while, in parallel, substantially reduced scan times, as compared to direct high-resolution acquisitions. The experimental results demonstrate that our approach allowed for fast and high-quality neonatal brain MRI for both scientific research and clinical studies.

Learning a Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction.

In MRI practice, it is inevitable to appropriately balance between image resolution, signal-to-noise ratio (SNR), and scan time. It has been shown that super-resolution reconstruction (SRR) is effective to achieve such a balance, and has obtained better results than direct high-resolution (HR) acquisition, for certain contrasts and sequences. The focus of this work was on constructing images with spatial resolution higher than can be practically obtained by direct Fourier encoding. A novel learning approach was developed, which was able to provide an estimate of the spatial gradient prior from the low-resolution (LR) inputs for the HR reconstruction. By incorporating the anisotropic acquisition schemes, the learning model was trained over the LR images themselves only. The learned gradients were integrated as prior knowledge into a gradient-guided SRR model. A closed-form solution to the SRR model was developed to obtain the HR reconstruction. Our approach was assessed on the simulated data as well as the data acquired on a Siemens 3T MRI scanner containing 45 MRI scans from 15 subjects. The experimental results demonstrated that our approach led to superior SRR over state-of-the-art methods, and obtained better images at lower or the same cost in scan time than direct HR acquisition.

Toward Precise Osteotomies: A Coarse-to-Fine 3D Cut Plane Planning Method for Image-Guided Pelvis Tumor Resection Surgery.

Surgical resection is the main clinical method for the treatment of bone tumors. A critical procedure for bone tumor resection is to plan a set of cut planes that enable resecting the bone tumor with a safe margin while preserving the maximum amount of healthy bone. Currently, the surgeons rely on manual methods to plan the cut planes, which highly depend on the surgeons' experiences and have been demonstrated to be error-prone, and in turn, increase the recurrence rate or resect much healthy bone. This study targets on improving the precision of cut plane planning for the image guided pelvis tumor resection surgeries. A semi-automatic approach to cut plane planning was proposed via a coarse-to-fine strategy. It can efficiently identify a dangerous region in the 3D space, which contains the bone tumor and its surrounding normal tissue with a safe margin. By projecting the dangerous region into an appropriate 2D space, a segmented boundary-constrained linear regression method was leveraged to plan a set of 3D cut planes that ensure the minimum area of the resected specimen in the 2D space while having the dangerous region cleared. Further, a coarse-to-fine 3D cut plane planning method was developed by incorporating a 3D cut plane refinement scheme with our 2D planning method. Extensive experiments, on the surgical data from nine previous pelvis tumor resection surgeries, demonstrated that our proposed approach substantially improved the localization precision of cut planes ( ) and decreased the amount of resected specimen ( ), as compared to the manual method.

An Autograft for Anterior Cruciate Ligament Reconstruction Results in Better Biomechanical Performance and Tendon-Bone Incorporation Than Does a Hybrid Graft in a Rat Model.

BACKGROUND: The biomechanical and tendon-bone incorporation properties of allograft-augmented hybrid grafts for anterior cruciate ligament (ACL) reconstruction compared with traditional autografts are unknown. HYPOTHESIS: Using an autograft for ACL reconstruction yields better results on biomechanical testing, radiographic analysis, and histological evaluation versus using a hybrid graft. STUDY DESIGN: Controlled laboratory study. METHODS: A total of 66 adult male Sprague Dawley rats underwent unilateral ACL reconstruction with an autograft (AT group; n = 33) or a hybrid graft (HB group; n = 33). The grafts used in both groups were harvested from the peroneus longus tendon and were fixed by suturing to the surrounding periosteum. Samples were harvested for biomechanical testing, micro-computed tomography (CT), and histological evaluation at 4, 8, and 12 weeks postoperatively. Bone tunnels on the femoral and tibial sides were divided into 3 subregions: intra-articular (IA), midtunnel (MT), and extra-articular (EA). A cylinder-like volume of interest in the bone tunnel and a tubular-like volume of interest around the bone tunnel were used to evaluate new bone formation and bone remodeling, respectively, via micro-CT. RESULTS: In the AT group, there were significantly higher failure loads and stiffness at 8 weeks (failure load: 3.04 ± 0.40 vs 2.09 ± 0.54 N, respectively; P = .006) (stiffness: 3.43 ± 0.56 vs 1.75 ± 0.52 N/mm, respectively; P < .001) and 12 weeks (failure load: 9.10 ± 1.13 vs 7.14 ± 0.94 N, respectively; P = .008) (stiffness: 4.45 ± 0.75 vs 3.36 ± 0.29 N/mm, respectively; P = .008) than in the HB group. With regard to new bone formation in the bone tunnel, in the AT group, the bone volume/total volume (BV/TV) was significantly higher than in the HB group on the tibial side at 8 weeks (IA: 22.21 ± 4.98 vs 5.16 ± 3.98, respectively; P < .001) (EA: 19.66 ± 7.19 vs 10.85 ± 2.16, respectively; P = .030) and 12 weeks (IA: 30.50 ± 5.04 vs 17.11 ± 7.31, respectively; P = .010) (MT: 21.15 ± 2.58 vs 15.55 ± 4.48, respectively; P = .041) (EA: 20.75 ± 3.87 vs 10.64 ± 3.94, respectively; P = .003). With regard to bone remodeling around the tunnel, the BV/TV was also significantly higher on the tibial side at 8 weeks (MT: 33.17 ± 8.05 vs 15.21 ± 7.60, respectively; P = .007) (EA: 25.19 ± 6.38 vs 13.94 ± 7.10, respectively; P = .030) and 12 weeks (IA: 69.46 ± 4.45 vs 47.80 ± 6.16, respectively; P < .001) (MT: 33.15 ± 3.88 vs 13.76 ± 4.07, respectively; P < .001) in the AT group than in the HB group. Sharpey-like fibers had formed at 8 weeks in the AT group. A large number of fibroblasts withdrew at 12 weeks. In the AT group, the width of the interface was significantly narrower at 4 weeks (85.86 ± 17.49 vs 182.97 ± 14.35 µm, respectively; P < .001), 8 weeks (58.86 ± 10.99 vs 90.15 ± 11.53 µm, respectively; P = .002), and 12 weeks (42.70 ± 7.96 vs 67.29 ± 6.55 µm, respectively; P = .001) than in the HB group. CONCLUSION: Using an autograft for ACL reconstruction may result in improved biomechanical properties and tendon-bone incorporation compared with a hybrid graft. CLINICAL RELEVANCE: Augmenting small autografts with allograft tissue may result in decreased biomechanical performance and worse tendon-bone incorporation, increasing the risk of graft failure.