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Traumatic brain injury (TBI) is a common diagnosis requiring acute hospitalization. Long-term, TBI is a significant source of health and socioeconomic impact in the United States and globally. The goal of clinicians who manage TBI is to prevent secondary brain injury. In this population, post-traumatic cerebral infarction (PTCI) acutely after TBI is an important but under-recognized complication that is associated with negative functional outcomes. In this comprehensive review, we describe the incidence and pathophysiology of PTCI. We then discuss the diagnostic and treatment approaches for the most common etiologies of isolated PTCI, including brain herniation syndromes, cervical artery dissection, venous thrombosis, and post-traumatic vasospasm. In addition to these mechanisms, hypercoagulability and microcirculatory failure can also exacerbate ischemia. We aim to highlight the importance of this condition and future clinical research needs with the goal of improving patient outcomes after TBI.

Abstract Plantar fascia (PF) is the commonest causes of foot pain in the adult population. Several surgical treatments are available to treat PF. This study was aimed to investigate the clinical efficacy of three different treatments for plantar fasciitis. It was conducted among 60 patients, divided equally into three treatment groups named Needle Knife Therapy, Endoscopic Plantar Fasciotomy, and Conventional Painkillers. Descriptive and analytical analysis were done by using SPSS 25 software. VAS and AOFAS scores were analyzed. The maximum (n = 31) participants were in 41–60 year age range group with normal BMI. These differences of mean VAS and AOFAS pain scores between different treatment groups were statistically significant (One-way ANOVA, p

PurposeTo extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment.MethodsMT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated.ResultsMT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects.ConclusionThe refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted.

BACKGROUND: Quantitative plaque assessment based on 3D magnetic resonance (MR) vessel wall imaging (VWI) has been shown to provide valuable numerical markers of the burden and risk of intracranial atherosclerotic disease (ICAD). However, plaque quantification is currently time-consuming and observer-dependent due to the demand for heavy manual effort. A VWI-dedicated automated processing pipeline (VWI-APP) is desirable. PURPOSE: To develop and evaluate a VWI-APP for end-to-end quantitative analysis of intracranial atherosclerotic plaque. METHODS: We retrospectively enrolled 91 subjects with ICAD (80 for pipeline development, 10 for an end-to-end pipeline evaluation, and 1 for demonstrating longitudinal plaque assessment) who had undergone VWI and MR angiography. In an end-to-end evaluation, diameter stenosis (DS), normalized wall index (NWI), remodeling ratio (RR), plaque wall contrast ratio (CR), and total plaque volume (TPV) were quantified at each culprit lesion using the developed VWI-APP and a computer-aided manual approach by a neuroradiologist, respectively. The time consumed in each quantification approach was recorded. Two-sided paired t-tests and intraclass correlation coefficient (ICC) were used to determine the difference and agreement in each plaque metric between VWI-APP and manual quantification approaches. RESULTS: There was no significant difference between VWI-APP and manual quantification in each plaque metric. The ICC was 0.890, 0.813, 0.827, 0.891, and 0.991 for DS, NWI, RR, CR, and TPV, respectively, suggesting good to excellent accuracy of the pipeline method in plaque quantification. Quantitative analysis of each culprit lesion on average took 675.7 s using the manual approach but shortened to 238.3 s with the aid of VWI-APP. CONCLUSIONS: VWI-APP is an accurate and efficient approach to intracranial atherosclerotic plaque quantification. Further clinical assessment of this automated tool is warranted to establish its utility in the risk assessment of ICAD lesions.

PURPOSE: To develop an automated vessel wall segmentation method on T1-weighted intracranial vessel wall magnetic resonance images, with a focus on modeling the inclusion relation between the inner and outer boundaries of the vessel wall. METHODS: We propose a novel method that estimates the inner and outer vessel wall boundaries simultaneously, using a network with a single output channel resembling the level-set function height. The network is driven by a unique tiered loss that accounts for data fidelity of the lumen and vessel wall classes and a length regularization to encourage boundary smoothness. RESULTS: Implemented with a 2.5D UNet with a ResNet backbone, the proposed method achieved Dice similarity coefficients (DSC) in 2D of 0.925 ± 0.048, 0.786 ± 0.084, Hausdorff distance (HD) of 0.286 ± 0.436, 0.345 ± 0.419 mm, and mean surface distance (MSD) of 0.083 ± 0.037 and 0.103 ± 0.032 mm for the lumen and vessel wall, respectively, on a test set; compared favorably to a baseline UNet model that achieved DSC 0.924 ± 0.047, 0.794 ± 0.082, HD 0.298 ± 0.477, 0.394 ± 0.431 mm, and MSD 0.087 ± 0.056, 0.119 ± 0.059 mm. Our vessel wall segmentation method achieved substantial improvement in morphological integrity and accuracy compared to benchmark methods. CONCLUSIONS: The proposed method provides a systematic approach to model the inclusion morphology and incorporate it into an optimization infrastructure. It can be applied to any application where inclusion exists among a (sub)set of classes to be segmented. Improved feasibility in result morphology promises better support for clinical quantification and decision.

Objective.To develop and test the feasibility of a novel Single ProjectIon DrivEn Real-time Multi-contrast (SPIDERM) MR imaging technique that can generate real-time 3D images on-the-fly with flexible contrast weightings and a low latency.Approach.In SPIDERM, a 'prep' scan is first performed, with sparse k-space sampling periodically interleaved with the central k-space line (navigator data), to learn a subject-specific model, incorporating a spatial subspace and a linear transformation between navigator data and subspace coordinates. A 'live' scan is then performed by repeatedly acquiring the central k-space line only to dynamically determine subspace coordinates. With the 'prep'-learned subspace and 'live' coordinates, real-time 3D images are generated on-the-fly with computationally efficient matrix multiplication. When implemented based on a multi-contrast pulse sequence, SPIDERM further allows for data-driven image contrast regeneration to convert real-time contrast-varying images into contrast-frozen images at user's discretion while maintaining motion states. Both digital phantom andin-vivoexperiments were performed to evaluate the technical feasibility of SPIDERM.Main results.The elapsed time from the input of the central k-space line to the generation of real-time contrast-frozen 3D images was approximately 45 ms, permitting a latency of 55 ms or less. Motion displacement measured from SPIDERM and reference images showed excellent correlation (R2≥0.983). Geometric variation from the ground truth in the digital phantom was acceptable as demonstrated by pancreas contour analysis (Dice ≥ 0.84, mean surface distance ≤ 0.95 mm). Quantitative image quality metrics showed good consistency between reference images and contrast-varying SPIDREM images inin-vivostudies (meanNMRSE=0.141,PSNR=30.12,SSIM=0.88).Significance.SPIDERM is capable of generating real-time multi-contrast 3D images with a low latency. An imaging framework based on SPIDERM has the potential to serve as a standalone package for MR-guided radiation therapy by offering adaptive simulation through a 'prep' scan and real-time image guidance through a 'live' scan.

Analysis of vessel morphology is important in assessing intracranial atherosclerosis disease (ICAD). Recently, magnetic resonance (MR) vessel wall imaging (VWI) has been introduced to image ICAD and characterize morphology for atherosclerotic lesions. In order to automatically perform quantitative analysis on VWI data, MR angiography (MRA) acquired in the same imaging session is typically used to localize the vessel segments of interest. However, MRA may be unavailable caused by the lack or failure of the sequence in a VWI protocol. This study aims to investigate the feasibility to infer the vessel location directly from VWI. We propose to synergize an atlas-based method to preserve general vessel structure topology with a deep learning network in the motion field domain to correct the residual geometric error. Performance is quantified by examining the agreement between the extracted vessel structures from the pair-acquired and alignment-corrected angiogram, and the estimated output using a cross-validation scheme. Our proposed pipeline yields clinically feasible performance in localizing intracranial vessels, demonstrating the promise of performing vessel morphology analysis using VWI alone.

PurposeTo develop an MR multitasking-based multidimensional assessment of cardiovascular system (MT-MACS) with electrocardiography-free and navigator-free data acquisition for a comprehensive evaluation of thoracic aortic diseases.MethodsThe MT-MACS technique adopts a low-rank tensor image model with a cardiac time dimension for phase-resolved cine imaging and a T2 -prepared inversion-recovery dimension for multicontrast assessment. Twelve healthy subjects and 2 patients with thoracic aortic diseases were recruited for the study at 3 T, and both qualitative (image quality score) and quantitative (contrast-to-noise ratio between lumen and wall, lumen and wall area, and aortic strain index) analyses were performed in all healthy subjects. The overall image quality was scored based on a 4-point scale: 3, excellent; 2, good; 1, fair; and 0, poor. Statistical analysis was used to test the measurement agreement between MT-MACS and its corresponding 2D references.ResultsThe MT-MACS images reconstructed from acquisitions as short as 6 minutes demonstrated good or excellent image quality for bright-blood (2.58 ± 0.46), dark-blood (2.58 ± 0.50), and gray-blood (2.17 ± 0.53) contrast weightings, respectively. The contrast-to-noise ratios for the three weightings were 49.2 ± 12.8, 20.0 ± 5.8 and 2.8 ± 1.8, respectively. There were good agreements in the lumen and wall area (intraclass correlation coefficient = 0.993, P < .001 for lumen; intraclass correlation coefficient = 0.969, P < .001 for wall area) and strain (intraclass correlation coefficient = 0.947, P < .001) between MT-MACS and conventional 2D sequences.ConclusionThe MT-MACS technique provides high-quality, multidimensional images for a comprehensive assessment of the thoracic aorta. Technical feasibility was demonstrated in healthy subjects and patients with thoracic aortic diseases. Further clinical validation is warranted.

PurposeSegmentation of multiple organs-at-risk (OARs) is essential for magnetic resonance (MR)-only radiation therapy treatment planning and MR-guided adaptive radiotherapy of abdominal cancers. Current practice requires manual delineation that is labor-intensive, time-consuming, and prone to intra- and interobserver variations. We developed a deep learning (DL) technique for fully automated segmentation of multiple OARs on clinical abdominal MR images with high accuracy, reliability, and efficiency.MethodsWe developed Automated deep Learning-based abdominal multiorgan segmentation (ALAMO) technique based on two-dimensional U-net and a densely connected network structure with tailored design in data augmentation and training procedures such as deep connection, auxiliary supervision, and multiview. The model takes in multislice MR images and generates the output of segmentation results. 3.0-Tesla T1 VIBE (Volumetric Interpolated Breath-hold Examination) images of 102 subjects were used in our study and split into 66 for training, 16 for validation, and 20 for testing. Ten OARs were studied, including the liver, spleen, pancreas, left/right kidneys, stomach, duodenum, small intestine, spinal cord, and vertebral bodies. An experienced radiologist manually labeled each OAR, followed by reediting, if necessary, by a senior radiologist, to create the ground-truth. The performance was measured using volume overlapping and surface distance.ResultsThe ALAMO technique generated segmentation labels in good agreement with the manual results. Specifically, among the ten OARs, nine achieved high dice similarity coefficients (DSCs) in the range of 0.87-0.96, except for the duodenum with a DSC of 0.80. The inference completed within 1 min for a three-dimensional volume of 320 × 288 × 180. Overall, the ALAMO model matched the state-of-the-art techniques in performance.ConclusionThe proposed ALAMO technique allows for fully automated abdominal MR segmentation with high accuracy and practical memory and computation time demands.

Steam condensation in the presence of air is an important thermal-hydraulic phenomenon in containment under loss of coolant accidents (LOCAs) or main steam line break accidents (MSLBs). Previous studies have focused on the effects of thermal parameters such as air mass fraction, gas pressure and sub-cooling on heat transfer characteristics, but less on the influence and action principle of geometric parameters such as tube length, tube diameter and inclination angle. Fully understanding the influence of geometric parameters on condensation heat transfer of steam containing air is of great significance for efficient heat transfer, so as to improve the safety and economy of related applications. The effects of tube diameter (4-60 mm), tube length (0.1-7 m) and inclination angle (0°-90°) on condensation heat transfer characteristics of air containing steam were studied based on the diffusion boundary layer condensation mechanism model by using three-dimensional CFD numerical simulation method. The results show that the tube diameter, tube length and inclination angle have significant effects on condensation heat transfer characteristics of air containing steam. However, when tube diameter exceeds 30 mm, tube length exceeds 1 m and inclination angle exceeds 60°, the average condensation heat transfer coefficient is no longer sensitive to the change of geometric parameters. The average condensation heat transfer coefficient decreases with the increase of tube diameter, and the descent speed decreases rapidly. When the tube diameter is 4 mm, the average condensation heat transfer coefficient is twice that of 60 mm. It first decreases and then increases with the increase of tube length, and reaches the minimum value at about 3 m. And it increases with the increase of inclination angle. The high concentration air layer near the wall is the main thermal resistance in the condensation process of steam-air, and its thickness makes a good negative correlation with condensation heat transfer coefficient. The high concentration air layer will first accumulate and thicken along the tube wall, and then produce a certain negative pressure due to the high density and high flow rate of mixed gas near the wall, so as to form a transverse velocity, so that the air layer will be thinned slowly after 1 m from the top of the pipe. Thus, the local condensation heat transfer coefficient decreases rapidly at first and then increases slowly along the direction of tube length. In addition, the tube circumferential local condensation heat transfer coefficient is uneven obviously under the inclined arrangement, the heat transfer on the upper surface is significantly enhanced due to the thinning of air layer by natural convection scouring and falling off, and gradually weakened to both sides, while the lower surface forms a stagnation zone due to the obstruction of the tube wall, which causes the accumulation and thickening of the air layer, resulting in a certain heat transfer inhibition. Compared with the vertical tube, about 75% of the circumferential area has different degrees of heat transfer enhancement, and only the dorsal flow surface has a certain heat transfer inhibition.

Purpose: Radiotherapy treatment planning (RTP) using MR has been used increasingly for the abdominal site. Multiple contrast weightings and motion‐resolved imaging are desired for accurate delineation of the target and various organs‐at‐risk and patient‐tailored planning. Current MR protocols achieve these through multiple scans with distinct contrast and variable respiratory motion management strategies and acquisition parameters, leading to a complex and inaccurate planning process. This study presents a standalone MR Multitasking (MT)–based technique to produce volumetric, motion‐resolved, multicontrast images for abdominal radiotherapy treatment planning. Methods: The MT technique resolves motion and provides a wide range of contrast weightings by repeating a magnetization‐prepared (saturation recovery and T2 preparations) spoiled gradient‐echo readout series and adopting the MT image reconstruction framework. The performance of the technique was assessed through digital phantom simulations and in vivo studies of both healthy volunteers and patients with liver tumors. Results: In the digital phantom study, the MT technique presented structural details and motion in excellent agreement with the digital ground truth. The in vivo studies showed that the motion range was highly correlated (R2 = 0.82) between MT and 2D cine imaging. MT allowed for a flexible contrast‐weighting selection for better visualization. Initial clinical testing with interobserver analysis demonstrated acceptable target delineation quality (Dice coefficient = 0.85 ± 0.05, Hausdorff distance = 3.3 ± 0.72 mm). Conclusion: The developed MT‐based, abdomen‐dedicated technique is capable of providing motion‐resolved, multicontrast volumetric images in a single scan, which may facilitate abdominal radiotherapy treatment planning. [ABSTRACT FROM AUTHOR]

Animals may experience early negative (mechanical pain: being retrieved using an incisor by parents or attacked) or positive stimulation (being licked and groomed) that may affect emotional and social behaviors in adulthood. Whether positive tactile stimulation can reverse adverse consequences on emotional and social behaviors in adulthood resulting from chronic mechanical pain and underlying mechanisms remain unclear. This study used a tail‐pinching model during development to simulate mechanical pain experienced by pups in high‐social mandarin voles (Microtus mandarinus). Subsequently, brush‐like positive tactile stimuli were applied to the backs of the mandarin voles. Various behavioral tests were used to measure levels of anxiety, depression, and sociability. The results showed that early tail‐pinching delayed the eye opening of pups, increased levels of anxiety, reduced levels of sociality in male mandarin voles, and impaired social cognition in females during adulthood. Brushing on the back reversed some of these effects. While mandarin voles that were exposed to tail‐pinching during development were exposed to sub‐threshold variable stress as adults, they were more likely to show a stress‐induced increase of anxiety‐like behavior, reduction of sociability, and impairment of social cognition, displaying heightened susceptibility to stress, particularly in males. However, back‐brushing reversed some of these effects, implying that these adults display enhanced stress resilience. In addition, tail‐pinching reduced levels of serum oxytocin and increased corticosterone levels in serum, but back‐brushing reversed these effects. Overall, it was found that positive tactile stimulation reversed increases in anxiety and impairments of social behavior induced by negative stimulation in male mandarin voles via alteration of oxytocin and corticosterone levels. [ABSTRACT FROM AUTHOR]

DNAJB6, a major member of the DNAJ/HSP40 family, plays an important role in tumor development. We explored the effect of DNAJB6 expression on the prognosis of patients and its biological role in lung adenocarcinoma (LUAD). mRNA and clinical data were obtained from The Cancer Genome Atlas (TCGA). Enriched pathways were determined by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A nomogram incorporating DNAJB6 and three clinical features was constructed to predict the survival rate. DNAJB6 expression and function in LUAD were explored using immunohistochemistry, Western blotting, proliferation, cell cycle analysis, RNA sequencing, and xenograft tumor assays. DNAJB6 mRNA levels were elevated in the LUAD-TCGA dataset. DNAJB6 protein levels were higher in LUAD tumor tissues than in normal tissues. A high DNAJB6 level was an independent risk factor for poor prognosis in patients with LUAD. The proportion of tumor-infiltrating immune cells significantly differed between high and low DNAJB6 expression. DNAJB6 was associated with cell cycle pathways; therefore, its knockdown induced G2/M cell cycle arrest and inhibited LUAD cell proliferation. This is the first report of the DNAJB6 requirement for LUAD cell proliferation and its potentially crucial role in LUAD prognosis. [ABSTRACT FROM AUTHOR]