Domain transformation learning for MR image reconstruction from dual domain input.

Medical images are acquired through diverse imaging systems, with each system employing specific image reconstruction techniques to transform sensor data into images. In MRI, sensor data (i.e., k-space data) is encoded in the frequency domain, and fully sampled k-space data is transformed into an image using the inverse Fourier Transform. However, in efforts to reduce acquisition time, k-space is often subsampled, necessitating a sophisticated image reconstruction method beyond a simple transform. The proposed approach addresses this challenge by training a model to learn domain transform, generating the final image directly from undersampled k-space input. Significantly, to improve the stability of reconstruction from randomly subsampled k-space data, folded images are incorporated as supplementary inputs in the dual-input ETER-net. Moreover, modifications are made to the formation of inputs for the bi-RNN stages to accommodate non-fixed k-space trajectories. Experimental validation, encompassing both regular and irregular sampling trajectories, validates the method's effectiveness. The results demonstrated superior performance, measured by PSNR, SSIM, and VIF, across acceleration factors of 4 and 8. In summary, the dual-input ETER-net emerges as an effective both regular and irregular sampling trajectories, and accommodating diverse acceleration factors.

Competition-level code generation with AlphaCode.

Programming is a powerful and ubiquitous problem-solving tool. Systems that can assist programmers or even generate programs themselves could make programming more productive and accessible. Recent transformer-based neural network models show impressive code generation abilities yet still perform poorly on more complex tasks requiring problem-solving skills, such as competitive programming problems. Here, we introduce AlphaCode, a system for code generation that achieved an average ranking in the top 54.3% in simulated evaluations on recent programming competitions on the Codeforces platform. AlphaCode solves problems by generating millions of diverse programs using specially trained transformer-based networks and then filtering and clustering those programs to a maximum of just 10 submissions. This result marks the first time an artificial intelligence system has performed competitively in programming competitions.

Baseline Correction of the Human 1H MRS(I) Spectrum Using T2* Selective Differential Operators in the Frequency Domain.

The baseline distortion caused by water and fat signals is a crucial issue in the 1H MRS(I) study of the human brain. This paper suggests an effective and reliable preprocessing technique to calibrate the baseline distortion caused by the water and fat signals exhibited in the MRS spectral signal. For the preprocessing, we designed a T2* (or linewidth within the spectral signal) selective filter for the MRS(I) data based on differential filtering within the frequency domain. The number and types for the differential filtering were determined by comparing the T2* selectivity profile of each differential operator with the T2* profile of the metabolites to be suppressed within the MRS(I) data. In the performance evaluation of the proposed differential filtering, the simulation data for MRS spectral signals were used. Furthermore, the spectral signal of the human 1H MRSI data obtained by 2D free induction decay chemical shift imaging with a typical water suppression technique was also used in the performance evaluation. The absolute values of the average of the filtered dataset were quantitatively analyzed using the LCModel software. With the suggested T2* selective (not frequency selective) filtering technique, in the simulated MRS data, we removed the metabolites from the simulated MRS(I) spectral signal baseline distorted by the water and fat signal observed in the most frequency band. Moreover, in the obtained MRSI data, the quantitative analysis results for the metabolites of interest showed notable improvement in the uncertainty estimation accuracy, the CRLB (Cramer-Rao Lower Bound) levels.

A New Combination of Radio-Frequency Coil Configurations Using High-Permittivity Materials and Inductively Coupled Structures for Ultrahigh-Field Magnetic Resonance Imaging.

In ultrahigh-field (UHF) magnetic resonance imaging (MRI) system, the RF power required to excite the nuclei of the target object increases. As the strength of the main magnetic field (B0 field) increases, the improvement of the RF transmit field (B1+ field) efficiency and receive field (B1- field) sensitivity of radio-frequency (RF) coils is essential to reduce their specific absorption rate and power deposition in UHF MRI. To address these problems, we previously proposed a method to simultaneously improve the B1+ field efficiency and B1- field sensitivity of 16-leg bandpass birdcage RF coils (BP-BC RF coils) by combining a multichannel wireless RF element (MCWE) and segmented cylindrical high-permittivity material (scHPM) comprising 16 elements in 7.0 T MRI. In this work, we further improved the performance of transmit/receive RF coils. A new combination of RF coil with wireless element and HPM was proposed by comparing the BP-BC RF coil with the MCWE and the scHPM proposed in the previous study and the multichannel RF coils with a birdcage RF coil-type wireless element (BCWE) and the scHPM proposed in this study. The proposed 16-ch RF coils with the BCWE and scHPM provided excellent B1+ field efficiency and B1- field sensitivity improvement.

An End-to-End Recurrent Neural Network for Radial MR Image Reconstruction.

Recent advances in deep learning have contributed greatly to the field of parallel MR imaging, where a reduced amount of k-space data are acquired to accelerate imaging time. In our previous work, we have proposed a deep learning method to reconstruct MR images directly from k-space data acquired with Cartesian trajectories. However, MRI utilizes various non-Cartesian trajectories, such as radial trajectories, with various numbers of multi-channel RF coils according to the purpose of an MRI scan. Thus, it is important for a reconstruction network to efficiently unfold aliasing artifacts due to undersampling and to combine multi-channel k-space data into single-channel data. In this work, a neural network named 'ETER-net' is utilized to reconstruct an MR image directly from k-space data acquired with Cartesian and non-Cartesian trajectories and multi-channel RF coils. In the proposed image reconstruction network, the domain transform network converts k-space data into a rough image, which is then refined in the following network to reconstruct a final image. We also analyze loss functions including adversarial and perceptual losses to improve the network performance. For experiments, we acquired k-space data at a 3T MRI scanner with Cartesian and radial trajectories to show the learning mechanism of the direct mapping relationship between the k-space and the corresponding image by the proposed network and to demonstrate the practical applications. According to our experiments, the proposed method showed satisfactory performance in reconstructing images from undersampled single- or multi-channel k-space data with reduced image artifacts. In conclusion, the proposed method is a deep-learning-based MR reconstruction network, which can be used as a unified solution for parallel MRI, where k-space data are acquired with various scanning trajectories.

Simulation Study of Radio Frequency Safety and the Optimal Size of a Single-Channel Surface Radio Frequency Coil for Mice at 9.4 T Magnetic Resonance Imaging.

The optimized size of a single-channel surface radio frequency (RF) coil for mouse body images in a 9.4 T magnetic resonance imaging (MRI) system was determined via electromagnetic-field analysis of the signal depth according to the size of a single-channel coil. The single-channel surface RF coils used in electromagnetic field simulations were configured to operate in transmission/reception mode at a frequency of 9.4 T-400 MHz. Computational analysis using the finite-difference time-domain method was used to assess the single-channel surface RF coil by comparing single-channel surface RF coils of varying sizes in terms of |B1|-, |B1+|-, |B1-|- and |E|-field distribution. RF safety for the prevention of burn injuries to small animals was assessed using an analysis of the specific absorption rate. A single-channel surface RF coil with a 20 mm diameter provided optimal B1-field distribution and RF safety, thus confirming that single-channel surface RF coils with ≥25 mm diameter could not provide typical B1-field distribution. A single-channel surface RF coil with a 20 mm diameter for mouse body imaging at 9.4 T MRI was recommended to preserve the characteristics of single-channel surface RF coils, and ensured that RF signals were applied correctly to the target point within RF safety guidelines.

Bilateral superficial cervical plexus block for parathyroidectomy during pregnancy: A case report.

BACKGROUND: Primary hyperparathyroidism (PHPT) is the most common cause of pregnancy-related hypercalcemia. PHPT can cause maternal and fetal complications in pregnant women. General anesthesia for non-obstetric surgery in pregnant women is associated with maternal hazards and concerns regarding long-term neonatal neurocognitive effects. Surgical removal of the lesion in mid-pregnancy is currently the primary treatment option for pregnant patients with PHPT. However, the blood calcium concentration at which surgery should be considered remains under discussion due to the risk of miscarriage. CASE SUMMARY: A 31-year-old nulliparous woman at 11 wk of gestation was admitted to our hospital for parathyroidectomy. The patient had a history of intrauterine fetal death with unknown etiology at 16 wk of gestation 1 year prior. Her blood test results showed that the serum calcium level was elevated to 12.9 mg/dL, and the parathyroid hormone level was elevated to 157 pg/mL. In a neck ultrasound, it revealed a 0.8 cm × 1.5 cm sized oval, hypoechoic mass in the upper posterior of the left thyroid gland, which was compatible with parathyroid adenoma. Superficial cervical plexus block (SCPB) for parathyroidectomy was performed. After surgery, the obstetrician checked the status of the fetus, and there were no abnormal signs. Since then her calcium level returned to normal values after one week of surgery and a healthy male neonate of 2910 g was delivered vaginally at 38 wk of gestation. CONCLUSION: Our case suggests that SCPB can be an anesthetic option for parathyroidectomy during the first trimester of pregnancy.

A Comparative Study of Birdcage RF Coil Configurations for Ultra-High Field Magnetic Resonance Imaging.

Improvements in transmission and reception sensitivities of radiofrequency (RF) coils used in ultra-high field (UHF) magnetic resonance imaging (MRI) are needed to reduce specific absorption rates (SAR) and RF power deposition, albeit without applying high-power RF. Here, we propose a method to simultaneously improve transmission efficiency and reception sensitivity of a band-pass birdcage RF coil (BP-BC RF coil) by combining a multi-channel wireless RF element (MCWE) with a high permittivity material (HPM) in a 7.0 T MRI. Electromagnetic field (EM-field) simulations, performed using two types of phantoms, viz., a cylindrical phantom filled with oil and a human head model, were used to compare the effects of MCWE and HPM on BP-BC RF coils. EM-fields were calculated using the finite difference time-domain (FDTD) method and analyzed using Matlab software. Next, to improve RF transmission efficiency, we compared two HPM structures, namely, a hollow cylinder shape HPM (hcHPM) and segmented cylinder shape HPM (scHPM). The scHPM and MCWE model comprised 16 elements (16-rad BP-BC RF coil) and this coil configuration demonstrated superior RF transmission efficiency and reception sensitivity along with an acceptable SAR. We expect wider clinical application of this combination in 7.0 T MRIs, which were recently approved by the United States Food and Drug Administration.

A Preliminary Study for Reference RF Coil at 11.7 T MRI: Based on Electromagnetic Field Simulation of Hybrid-BC RF Coil According to Diameter and Length at 3.0, 7.0 and 11.7 T.

Magnetic resonance imaging (MRI) systems must undergo quantitative evaluation through daily and periodic performance assessments. In general, the reference or standard radiofrequency (RF) coils for these performance assessments of 1.5 to 7.0 T MRI systems have been low-pass-type birdcage (LP-BC) RF coils. However, LP-BC RF coils are inappropriate for use as reference RF coils because of their relatively lower magnetic field (B1-field) sensitivity than other types of BC RF coils, especially in ultrahigh-field (UHF) MRI systems above 3.0 T. Herein, we propose a hybrid-type BC (Hybrid-BC) RF coil as a reference RF coil with improved B1-field sensitivity in UHF MRI system and applied it to an 11.7 T MRI system. An electromagnetic field (EM-field) analysis on the Hybrid-BC RF coil was performed to provide the proper dimensions for its use as a reference RF coil. Commercial finite difference time-domain program was used in EM-field simulation, and home-made analysis programs were used in analysis. The optimal specifications of the proposed Hybrid-BC RF coils for them to qualify as reference RF coils are proposed based on their B1+-field sensitivity under unnormalized conditions, as well as by considering their B1+-field uniformity and RF safety under normalized conditions.

A 2D-GRAPPA Algorithm with a Boomerang Kernel for 3D MRI Data Accelerated along Two Phase-Encoding Directions.

For the reconstruction of 3D MRI data that are accelerated along the two phase-encoding directions, the 2D-generalized autocalibrating partially parallel acquisitions (GRAPPA) algorithm can be used to estimate the missing data in the k-space. We propose a new boomerang-shaped kernel based on theoretic and systemic analyses of the shape and dimensions of the kernel. The reconstruction efficiency of the 2D-GRAPPA algorithm with the proposed boomerang-shaped kernel (i.e., boomerang kernel (BK)-2D-GRAPPA) was compared with other 2D-GRAPPA algorithms that utilize different types of kernels (i.e., EX-2D-GRAPPA and SK-2D-GRAPPA) based on computer simulation, phantom and in vivo experiments. The proposed method was validated for different sets of ACS lines with acceleration factors from four to eight and various sizes of the kernels. A quantitative analysis was also performed by comparing the normalized root mean squared error (nRMSE) in the images and the undersampled edges. Computer simulation, in vivo and phantom experiments, and the quantitative analysis, showed that the proposed method could reduce aliasing artifacts without reducing the SNRs of the reconstructed images.

Effect of Deep versus Moderate Neuromuscular Blockade on Quantitatively Assessed Postoperative Atelectasis Using Computed Tomography in Thoracic Surgery; a Randomized Double-Blind Controlled Trial.

BACKGROUND: postoperative atelectasis is a significant clinical problem during thoracic surgery with one-lung ventilation. Intraoperative deep neuromuscular blockade can improve surgical conditions, but an increased risk of residual paralysis may aggravate postoperative atelectasis. Every patient was verified to have full reversal before extubation. We compared the effect of deep versus moderate neuromuscular blockade on postoperative atelectasis quantitatively using chest computed tomography. METHODS: patients undergoing thoracic surgery were randomly allocated to two groups: moderate neuromuscular blockade during surgery (group M) and deep neuromuscular blockade during surgery (group D). The primary outcome was the proportion and the volume of postoperative atelectasis measured by chest computed tomography on postoperative day 2. The mean values of the repeatedly measured intraoperative dynamic lung compliance during surgery were also compared. RESULT: the proportion of postoperative atelectasis did not differ between the groups (1.32 [0.47-3.20]% in group M and 1.41 [0.24-3.07]% in group D, p = 0.690). The actual atelectasis volume was 38.2 (12.8-61.4) mL in group M and 31.9 (7.84-75.0) mL in group D (p = 0.954). Some factors described in the lung protective ventilation were not taken into account and might explain the atelectasis in both groups. The mean lung compliance during one-lung ventilation was higher in group D (26.6% in group D vs. 24.1% in group M, p = 0.026). CONCLUSIONS: intraoperative deep neuromuscular blockade did not affect postoperative atelectasis when compared with moderate neuromuscular blockade if full reversal was verified.

New analysis method for functional brain imaging: White noise removed T2* variation mapping using multi-echo EPI.

BACKGROUND: Generally, the analysis of functional magnetic resonance imaging (fMRI) using echo-planar imaging (EPI) data is based on independent component analysis (ICA) and the general linear model (GLM). The application of these two approaches is highly independent, like GLM is for task-related activation mapping, and ICA is for resting-state imaging. Herein, we propose white noise-removed T2*-variation mapping as a new analysis method for fMRI that integrates the two conventional mapping approaches. NEW METHOD: We derived the standard deviation to the mean-square ratio of the true T2* signal from the multi-echo EPI (ME-EPI) dataset. For the true T2*-variation-based value, we removed the S0 (initial signal intensity) and white noise component from the variation in the EPI signal using signal-coherence analysis of the echo time (TE) dataset and slope analysis of the TE-variated coefficient of variation of the ME-EPI dataset. RESULTS: The activation mapping for a visual task and resting-state imaging by the proposed method showed the reliable activation map in the visual cortex area and area for the typical default mode network, with white noise and the S0 component removed. COMPARISON WITH EXISTING METHODS: Conventional analyses for fMRI cannot be applied to both activation mapping and resting-state imaging, with white noise removed, while the proposed method can be applied. CONCLUSIONS: We demonstrated white noise-removed true T2*-variation-based mapping as a new functional brain analysis approach. We expect the method allows studying in which that the association between task timing and brain activity is somewhat uncertain, such as studies of emotion and awareness.

Adenosine A2A receptor agonist polydeoxyribonucleotide ameliorates short-term memory impairment by suppressing cerebral ischemia-induced inflammation via MAPK pathway.

Cerebral ischemia causes tissue death owing to occlusion of the cerebral blood vessels, and cerebral ischemia activates mitogen-activated protein kinase (MAPK) and induces secretion of pro-inflammatory cytokines. Adenosine A2A receptor agonist, polydeoxyribonucleotide (PDRN), suppresses the secretion of pro-inflammatory cytokines and exhibits anti-inflammatory effect. In the current study, the therapeutic effect of PDRN on cerebral ischemia was evaluated using gerbils. For the induction of cerebral ischemia, the common carotid arteries were exposed, and then aneurysm clips were used to occlude the common carotid arteries bilaterally for 7 minutes. In the PDRN-treated groups, the gerbils were injected intraperitoneally with 0.3 mL of saline containing 8 mg/kg PDRN, per a day for 7 days following cerebral ischemia induction. In order to confirm the participation of the adenosine A2A receptor in the effects mediated by PDRN, 8 mg/kg 7-dimethyl-1-propargylxanthine (DMPX), adenosine A2A receptor antagonist, was treated with PDRN. In the current study, induction of ischemia enhanced the levels of pro-inflammatory cytokines and increased phosphorylation of MAPK signaling factors in the hippocampus and basolateral amygdala. However, treatment with PDRN ameliorated short-term memory impairment by suppressing the production of pro-inflammatory cytokines and inactivation of MAPK signaling factors in cerebral ischemia. Furthermore, PDRN treatment enhanced the concentration of cyclic adenosine-3,5'-monophosphate (cAMP) as well as phosphorylation of cAMP response element-binding protein (p-CREB). Co-treatment of DMPX and PDRN attenuated the therapeutic effect of PDRN on cerebral ischemia. Based on these findings, PDRN may be developed as the primary treatment in cerebral ischemia.

Development and Initial Results of a Brain PET Insert for Simultaneous 7-Tesla PET/MRI Using an FPGA-Only Signal Digitization Method.

In study, we developed a positron emission tomography (PET) insert for simultaneous brain imaging within 7-Tesla (7T) magnetic resonance (MR) imaging scanners. The PET insert has 18 sectors, and each sector is assembled with two-layer depth-of-interaction (DOI)-capable high-resolution block detectors. The PET scanner features a 16.7-cm-long axial field-of-view (FOV) to provide entire human brain images without bed movement. The PET scanner early digitizes a large number of block detector signals at a front-end data acquisition (DAQ) board using a novel field-programmable gate array (FPGA)-only signal digitization method. All the digitized PET data from the front-end DAQ boards are transferred using gigabit transceivers via non-magnetic high-definition multimedia interface (HDMI) cables. A back-end DAQ system provides a common clock and synchronization signal for FPGAs over the HDMI cables. An active cooling system using copper heat pipes is applied for thermal regulation. All the 2.17-mm-pitch crystals with two-layer DOI information were clearly identified in the block detectors, exhibiting a system-level energy resolution of 12.6%. The PET scanner yielded clear hot-rod and Hoffman brain phantom images and demonstrated 3D PET imaging capability without bed movement. We also performed a pilot simultaneous PET/MR imaging study of a brain phantom. The PET scanner achieved a spatial resolution of 2.5 mm at the center FOV (NU 4) and a sensitivity of 18.9 kcps/MBq (NU 2) and 6.19% (NU 4) in accordance with the National Electrical Manufacturers Association (NEMA) standards.

Allogeneic Umbilical Cord Blood-Derived Mesenchymal Stem Cell Implantation Versus Microfracture for Large, Full-Thickness Cartilage Defects in Older Patients: A Multicenter Randomized Clinical Trial and Extended 5-Year Clinical Follow-up.

BACKGROUND: There is currently no optimal method for cartilage restoration in large, full-thickness cartilage defects in older patients. PURPOSE: To determine whether implantation of a composite of allogeneic umbilical cord blood-derived mesenchymal stem cells and 4% hyaluronate (UCB-MSC-HA) will result in reliable cartilage restoration in patients with large, full-thickness cartilage defects and whether any clinical improvements can be maintained up to 5 years postoperatively. STUDY DESIGN: Randomized controlled trial; Level of evidence, 1. METHODS: A randomized controlled phase 3 clinical trial was conducted for 48 weeks, and the participants then underwent extended 5-year observational follow-up. Enrolled were patients with large, full-thickness cartilage defects (International Cartilage Repair Society [ICRS] grade 4) in a single compartment of the knee joint, as confirmed by arthroscopy. The defect was treated either with UCB-MSC-HA implantation through mini-arthrotomy or with microfracture. The primary outcome was proportion of participants who improved by ≥1 grade on the ICRS Macroscopic Cartilage Repair Assessment (blinded evaluation) at 48-week arthroscopy. Secondary outcomes included histologic assessment; changes in pain visual analog scale (VAS) score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and International Knee Documentation Committee (IKDC) score from baseline; and adverse events. RESULTS: Among 114 randomized participants (mean age, 55.9 years; 67% female; body mass index, 26.2 kg/m2), 89 completed the phase 3 clinical trial and 73 were enrolled in the 5-year follow-up study. The mean defect size was 4.9 cm2 in the UCB-MSC-HA group and 4.0 cm2 in the microfracture group (P = .051). At 48 weeks, improvement by ≥1 ICRS grade was seen in 97.7% of the UCB-MSC-HA group versus 71.7% of the microfracture group (P = .001); the overall histologic assessment score was also superior in the UCB-MSC-HA group (P = .036). Improvement in VAS pain, WOMAC, and IKDC scores were not significantly different between the groups at 48 weeks, however the clinical results were significantly better in the UCB-MSC-HA group at 3- to 5-year follow-up (P < .05). There were no differences between the groups in adverse events. CONCLUSION: In older patients with symptomatic, large, full-thickness cartilage defects with or without osteoarthritis, UCB-MSC-HA implantation resulted in improved cartilage grade at second-look arthroscopy and provided more improvement in pain and function up to 5 years compared with microfracture. REGISTRATION: NCT01041001, NCT01626677 (ClinicalTrials.gov identifier).

Voxel-wise partial volume correction method for accurate estimation of tissue sodium concentration in 23 Na-MRI at 7 T.

Sodium is crucial for the maintenance of cell physiology, and its regulation of the sodium-potassium pump has implications for various neurological conditions. The distribution of sodium concentrations in tissue can be quantitatively evaluated by means of sodium MRI (23 Na-MRI). Despite its usefulness in diagnosing particular disease conditions, tissue sodium concentration (TSC) estimated from 23 Na-MRI can be strongly biased by partial volume effects (PVEs) that are induced by broad point spread functions (PSFs) as well as tissue fraction effects. In this work, we aimed to propose a robust voxel-wise partial volume correction (PVC) method for 23 Na-MRI. The method is based on a linear regression (LR) approach to correct for tissue fraction effects, but it utilizes a 3D kernel combined with a modified least trimmed square (3D-mLTS) method in order to minimize regression-induced inherent smoothing effects. We acquired 23 Na-MRI data with conventional Cartesian sampling at 7 T, and spill-over effects due to the PSF were considered prior to correcting for tissue fraction effects using 3D-mLTS. In the simulation, we found that the TSCs of gray matter (GM) and white matter (WM) were underestimated by 20% and 11% respectively without correcting tissue fraction effects, but the differences between ground truth and PVE-corrected data after the PVC using the 3D-mLTS method were only approximately 0.6% and 0.4% for GM and WM, respectively. The capability of the 3D-mLTS method was further demonstrated with in vivo 23 Na-MRI data, showing significantly lower regression errors (ie root mean squared error) as compared with conventional LR methods (p < 0.001). The results of simulation and in vivo experiments revealed that 3D-mLTS is superior for determining under- or overestimated TSCs while preserving anatomical details. This suggests that the 3D-mLTS method is well suited for the accurate determination of TSC, especially in small focal lesions associated with pathological conditions.

A k-space-to-image reconstruction network for MRI using recurrent neural network.

PURPOSE: Reconstructing the images from undersampled k-space data are an ill-posed inverse problem. As a solution to this problem, we propose a method to reconstruct magnetic resonance (MR) images directly from k-space data using a recurrent neural network. METHODS: A novel neural network architecture named "ETER-net" is developed as a unified solution to reconstruct MR images from undersampled k-space data, where two bi-RNNs and convolutional neural network (CNN) are utilized to perform domain transformation and de-aliasing. To demonstrate the practicality of the proposed method, we conducted model optimization, cross-validation, and network pruning using in-house data from a 3T MRI scanner and public dataset called "FastMRI." RESULTS: The experimental results showed that the proposed method could be utilized for accurate image reconstruction from undersampled k-space data. The size of the proposed model was optimized and cross-validation was performed to show the robustness of the proposed method. For in-house dataset (R = 4), the proposed method provided nMSE = 1.09% and SSIM = 0.938. For "FastMRI" dataset, the proposed method provided nMSE = 1.05 % and SSIM = 0.931 for R = 4, and nMSE = 3.12 % and SSIM = 0.884 for R = 8. The performance of the pruned model trained the loss function including with L2 regularization was consistent for a pruning ratio of up to 70%. CONCLUSIONS: The proposed method is an end-to-end MR image reconstruction method based on recurrent neural networks. It performs direct mapping of the input k-space data and the reconstructed images, operating as a unified solution that is applicable to various scanning trajectories.

Polydeoxyribonucleotide Ameliorates Inflammation and Apoptosis in Achilles Tendon-Injury Rats.

PURPOSE: Adenosine A2A receptor agonist polydeoxyribonucleotide (PDRN) possesses an anti-inflammatory effect and suppress apoptotic cell death in several disorders. In this current study, the effect of PDRN on inflammation and apoptosis in rats with Achilles tendon injury was investigated. METHODS: von Frey filament test and plantar test were conducted for the determination of pain threshold. Analysis of histological alterations was conducted by hematoxylin and eosin staining. Immunohistochemistry for cleaved caspase-3-positive cells and cleaved caspase-9-positive cells was done. Enzyme-linked immunoassay was used to detect the concentrations of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and cyclic adenosine-3',5'-monophosphate (cAMP). Western blot was conducted to detect the protein levels of cAMP response element-binding protein (CREB), protein kinase A (PKA), Bcl-2-associated X (Bax), and B-cell lymphoma 2 (Bcl-2). RESULTS: PDRN treatment relieved mechanical allodynia and alleviated thermal hyperalgesia after Achilles tendon injury. TNF-α and IL-6 concentrations were decreased by PDRN application. PDRN injection significantly enhanced cAMP concentration and phosphorylated CREB versus CREB ratio, showing cAMP-PKA-CREB pathway was activated by PDRN application. PDRN treatment inhibited percentages of cleaved caspase-3-positive cells and caspase-9-posiive cells and the suppressed Bax versus Bcl-2 ratio in Achilles tendon injury rats. CONCLUSION: PDRN is probably believed to have a good effect on pain and inflammation in the urogenital organs. PDRN may be used as a new treatment for Achilles tendon injury.

Lung sonography can improve the specificity of determination of left-sided double-lumen tracheal tube position in both novices and experts: a randomised prospective study.

OBJECTIVE: Lung sonography can be helpful to determine the position of a left-sided double-lumen tube (DLT). However, clinical experience is required for correct assessment. We investigated whether lung sonography can improve the diagnostic efficacy of determining the DLT position in novices and experts. METHODS: In this randomised prospective clinical study, 88 patients were allocated to two groups using auscultation or lung sonography for initial assessment of the DLT position. In each group, two repeated assessments were performed; the first was performed by a novice, and the second was performed by an expert. The final DLT position was confirmed by fibre-optic bronchoscopy. The primary outcome was the diagnostic efficacy (including overall accuracy, sensitivity, and specificity) in confirming the DLT position. RESULTS: In both the novices and experts, the specificity of determining the DLT position was significantly higher with lung sonography than auscultation (60.0% vs. 21.7% and 66.7% vs. 37.5%, respectively). Additionally, the predictability of an incorrect position was similar between the novices and experts using lung sonography (area under the curve of 0.665 and 0.690, respectively). CONCLUSIONS: Lung sonography can improve the diagnostic efficacy of detecting an incorrect DLT position in both novices and experts.

Dexmedetomidine Improves Locomotor Function and Alleviates Thermal Hyperalgesia Following Sciatic Nerve Crush Injury in Rats.

PURPOSE: The effects of dexmedetomidine on locomotor function and thermal hyperalgesia in sciatic nerve crush injury (SNCI) were investigated using rats. METHODS: After exposing the right sciatic nerve, the sciatic nerve was crushed for 1 minute by a surgical clip. One day after nerve injury, dexmedetomidine (5, 25, and 50 µg/kg) was directly applied to the injured sciatic nerve once a day for 14 days. Walking track analysis was used to assess locomotor function and plantar test was conducted to assess thermal pain sensitivity. Immunohistochemistry was performed to determine the expression of c-Fos in the ventrolateral periaqueductal gray (vlPAG) and paraventricular nucleus (PVN). Western blot was used to evaluate the expression level of nerve growth factor (NGF) and myelin basic protein (MBP) in the sciatic nerve. RESULTS: SNCI resulted in deterioration of locomotor function and increased thermal pain sensitivity. The level of c-Fos expression in the PVN and vlPAG was increased and the level of NGF and MBP expression in the sciatic nerve was enhanced by SNCI. Dexmedetomidine treatment improved locomotor function and upregulated expression of NGF and MBP in the sciatic nerve of SNCI. Dexmedetomidine treatment alleviated thermal hyperalgesia and downregulated expression of c-Fos in the vlPAG and PVN after SNCI. CONCLUSION: Dexmedetomidine may be used as a potential new treatment drug for recovery of locomotion and control of pain in peripheral nerve injury.