Fetal Head and Pubic Symphysis Segmentation in Intrapartum Ultrasound Image Using a Dual-Path Boundary-Guided Residual Network.

Accurate segmentation of the fetal head and pubic symphysis in intrapartum ultrasound images and measurement of fetal angle of progression (AoP) are critical to both outcome prediction and complication prevention in delivery. However, due to poor quality of perinatal ultrasound imaging with blurred target boundaries and the relatively small target of the public symphysis, fully automated and accurate segmentation remains challenging. In this paper, we propse a dual-path boundary-guided residual network (DBRN), which is a novel approach to tackle these challenges. The model contains a multi-scale weighted module (MWM) to gather global context information, and enhance the feature response within the target region by weighting the feature map. The model also incorporates an enhanced boundary module (EBM) to obtain more precise boundary information. Furthermore, the model introduces a boundary-guided dual-attention residual module (BDRM) for residual learning. BDRM leverages boundary information as prior knowledge and employs spatial attention to simultaneously focus on background and foreground information, in order to capture concealed details and improve segmentation accuracy. Extensive comparative experiments have been conducted on three datasets. The proposed method achieves average Dice score of 0.908 ±0.05 and average Hausdorff distance of 3.396 ±0.66 mm. Compared with state-of-the-art competitors, the proposed DBRN achieves better results. In addition, the average difference between the automatic measurement of AoPs based on this model and the manual measurement results is 6.157 °, which has good consistency and has broad application prospects in clinical practice.

Highly-accelerated CEST MRI using frequency-offset-dependent k-space sampling and deep-learning reconstruction.

PURPOSE: To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction. METHODS: For k-space down-sampling, a customized pattern was proposed for CEST, with the randomized probability following a frequency-offset-dependent (FOD) function in the direction of saturation offset. For reconstruction, the convolution network (CNN) was enhanced with a Partially Separable (PS) function to optimize the spatial domain and frequency domain separately. Retrospective experiments on a self-acquired human brain dataset (13 healthy adults and 15 brain tumor patients) were conducted using k-space resampling. The prospective performance was also assessed on six healthy subjects. RESULTS: In retrospective experiments, the combination of FOD sampling and PS network (FOD + PSN) showed the best quantitative metrics for reconstruction, outperforming three other combinations of conventional sampling with varying density and a regular CNN (nMSE and SSIM, p < 0.001 for healthy subjects). Across all acceleration factors from 4 to 14, the FOD + PSN approach consistently outperformed the comparative methods in four contrast maps including MTRasym, MTRrex, as well as the Lorentzian Difference maps of amide and nuclear Overhauser effect (NOE). In the subspace replacement experiment, the error distribution demonstrated the denoising benefits achieved in the spatial subspace. Finally, our prospective results obtained from healthy adults and brain tumor patients (14×) exhibited the initial feasibility of our method, albeit with less accurate reconstruction than retrospective ones. CONCLUSION: The combination of FOD sampling and PSN reconstruction enabled highly accelerated CEST MRI acquisition, which may facilitate CEST metabolic MRI for brain tumor patients.

Accurate and robust segmentation of cerebral vasculature on four-dimensional arterial spin labeling magnetic resonance angiography using machine-learning approach.

Segmentation of cerebral vasculature on MR vascular images is of great significance for clinical application and research. However, the existing cerebrovascular segmentation approaches are limited due to insufficient image contrast and complicated algorithms. This study aims to explore the potential of the emerging four-dimensional arterial spin labeling magnetic resonance angiography (4D ASL-MRA) technique for fast and accurate cerebrovascular segmentation with a simple machine-learning approach. Nine temporal features were extracted from the intensity-time signal of each voxel, and eight spatial features from the neighboring voxels. Then, the unsupervised outlier detection algorithm, i.e. Isolation Forest, is used for segmentation of the vascular voxels based on the extracted features. The total length of the centerlines of the intracranial arterial vasculature, the dice similarity coefficient (DSC), and the average Hausdorff Distance (AVGHD) on the cross-sections of small- to large-sized vessels were calculated to evaluate the performance of the segmentation approach on 4D ASL-MRA of 18 subjects. Experiments show that the temporal information on 4D ASL-MRA can largely improve the segmentation performance. In addition, the proposed segmentation approach outperforms the traditional methods that were performed on the 3D image (i.e. the temporal average intensity projection of 4D ASL-MRA) and the previously proposed frame-wise approach. In conclusion, this study demonstrates that accurate and robust segmentation of cerebral vasculature is achievable on 4D ASL-MRA by using a simple machine-learning approach with appropriate features.

Free-breathing abdominal chemical exchange saturation transfer imaging using water presaturation and respiratory gating at 3.0 T.

Free-breathing abdominal chemical exchange saturation transfer (CEST) has great potential for clinical application, but its technical implementation remains challenging. This study aimed to propose and evaluate a free-breathing abdominal CEST sequence. The proposed sequence employed respiratory gating (ResGat) to synchronize the data acquisition with respiratory motion and performed a water presaturation module before the CEST saturation to abolish the influence of respiration-induced repetition time variation. In vivo experiments were performed to compare different respiratory motion-control strategies and B0 offset correction methods, and to evaluate the effectiveness and necessity of the quasi-steady-state (QUASS) approach for correcting the influence of the water presaturation module on CEST signal. ResGat with a target expiratory phase of 0.5 resulted in a higher structural similarity index and a lower coefficient of variation on consecutively acquired CEST S0 images than breath-holding (BH) and respiratory triggering (all p < 0.05). B0 maps derived from the abdominal CEST dataset itself were more stable for B0 correction, compared with the separately acquired B0 maps by a dual-echo time scan and B0 maps derived from the water saturation shift referencing approach. Compared with BH, ResGat yielded more homogeneous magnetization transfer ratio asymmetry maps at 3.5 ppm (standard deviation: 3.96% vs. 3.19%, p = 0.036) and a lower mean squared difference between scan and rescan (27.52‱ vs. 16.82‱, p = 0.004). The QUASS approach could correct the water presaturation-induced CEST signal change, but its necessity for in vivo scanning needs further verification. The proposed free-breathing abdominal CEST sequence using ResGat had an acquisition efficiency of approximately four times that using BH. In conclusion, the proposed free-breathing abdominal CEST sequence using ResGat and water presaturation has a higher acquisition efficiency and image quality than abdominal CEST using BH.

Associations of Intracranial Artery Length and Branch Number on Time-of-Flight MRA With Cognitive Impairment in Hypertensive Older Males.

BACKGROUND: Hypertension-induced impairment of the cerebral artery network contributes to cognitive impairment. Characterizing the structure and function of cerebral arteries may facilitate the understanding of hypertension-related pathological mechanisms and lead to the development of new indicators for cognitive impairment. PURPOSE: To investigate the associations between morphological features of the intracranial arteries distal to the circle of Willis on time-of-flight MRA (TOF-MRA) and cognitive performance in a hypertensive cohort. STUDY TYPE: Prospective observational study. POPULATION: 189 hypertensive older males (mean age 64.9 ± 7.2 years). FIELD STRENGTH/SEQUENCE: TOF-MRA sequence with a 3D spoiled gradient echo readout and arterial spin labeling perfusion imaging sequence with a 3D stack-of-spirals fast spin echo readout at 3T. ASSESSMENT: The intracranial arteries were segmented from TOF-MRA and the total length of distal arteries (TLoDA) and number of arterial branches (NoB) were calculated. The mean gray matter cerebral blood flow (GM-CBF) was extracted from arterial spin labeling perfusion imaging. The cognitive level was assessed with short-term and long-term delay-recall auditory verbal learning test (AVLT) scores, and with montreal cognitive assessment. STATISTICAL TESTS: Univariable and multivariable linear regression were used to analyze the associations between TLoDA, NoB, GM-CBF and the cognitive assessment scores, with P < 0.05 indicating significance. RESULTS: TLoDA (r = 0.314) and NoB (r = 0.346) were significantly correlated with GM-CBF. Multivariable linear regression analyses showed that TLoDA and NoB, but not GM-CBF (P = 0.272 and 0.141), were significantly associated with short-term and long-term delay-recall AVLT scores. These associations remained significant after adjusting for GM-CBF. DATA CONCLUSION: The TLoDA and NoB of distal intracranial arteries on TOF-MRA are significantly associated with cognitive impairment in hypertensive subjects. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities.

Background: Whether white matter hyperintensities (WMHs) involve U-fibers is of great value in understanding the different etiologies of cerebral white matter (WM) lesions. However, clinical practice currently relies only on the naked eye to determine whether WMHs are in the vicinity of U-fibers, and there is a lack of good neuroimaging tools to quantify WMHs and U-fibers. Methods: Here, we developed a multimodal neuroimaging toolbox named U-fiber analysis (UFA) that can automatically extract WMHs and quantitatively characterize the volume and number of WMHs in different brain regions. In addition, we proposed an anatomically constrained U-fiber tracking scheme and quantitatively characterized the microstructure diffusion properties, fiber length, and number of U-fibers in different brain regions to help clinicians to quantitatively determine whether WMHs in the proximal cortex disrupt the microstructure of U-fibers. To validate the utility of the UFA toolbox, we analyzed the neuroimaging data from 246 patients with cerebral small vessel disease (cSVD) enrolled at Zhongshan Hospital between March 2018 and November 2019 in a cross-sectional study. Results: According to the manual judgment of the clinician, the patients with cSVD were divided into a WMHs involved U-fiber group (U-fiber-involved group, 51 cases) and WMHs not involved U-fiber group (U-fiber-spared group, 163 cases). There were no significant differences between the U-fiber-spared group and the U-fiber-involved group in terms of age (P=0.143), gender (P=0.462), education (P=0.151), Mini-Mental State Examination (MMSE) scores (P=0.151), and Montreal Cognitive Assessment (MoCA) scores (P=0.411). However, patients in the U-fiber-involved group had higher Fazekas scores (P<0.001) and significantly higher whole brain WMHs (P=0.046) and deep WMH volumes (P<0.001) compared to patients in the U-fiber-spared group. Moreover, the U-fiber-involved group had higher WMH volumes in the bilateral frontal [P(left) <0.001, P(right) <0.001] and parietal lobes [P(left) <0.001, P(right) <0.001]. On the other hand, patients in the U-fiber-involved group had higher mean diffusivity (MD) and axial diffusivity (AD) in the bilateral parietal [P(left, MD) =0.048, P(right, MD) =0.045, P(left, AD) =0.015, P(right, AD) =0.015] and right frontal-parietal regions [P(MD) =0.048, P(AD) =0.027], and had significantly reduced mean fiber length and number in the right parietal [P(length) =0.013, P(number) =0.028] and right frontal-parietal regions [P(length) =0.048] compared to patients in the U-fiber-spared group. Conclusions: Our results suggest that WMHs in the proximal cortex may disrupt the microstructure of U-fibers. Our tool may provide new insights into the understanding of WM lesions of different etiologies in the brain.

Single breath-hold three-dimensional whole-heart T2 mapping with low-rank plus sparse reconstruction.

The purpose of the current study was to develop and evaluate a three-dimensional single Breath-hOLd cardiac T2 mapping sequence (3D BOLT) with low-rank plus sparse (L + S) reconstruction for rapid whole-heart T2 measurement. 3D BOLT collects three highly accelerated electrocardiogram-triggered volumes with whole-heart coverage, all within a single 12-heartbeat breath-hold. Saturation pulses are performed every heartbeat to prepare longitudinal magnetization before T2 preparation (T2 -prep) or readout, and the echo time of T2 -prep is varied per volume for variable T2 weighting. Accelerated volumes are reconstructed jointly by an L + S algorithm. 3D BOLT was optimized and validated against gradient spin echo (GraSE) and a previously published approach (three-dimensional free-breathing cardiac T2 mapping [3DFBT2]) in both phantoms and human subjects (11 healthy subjects and 10 patients). The repeatability of 3D BOLT was validated on healthy subjects. Retrospective experiments indicated that 3D BOLT with 4.2-fold acceleration achieved T2 measurements comparable with those obtained with fully sampled data. T2 measured in phantoms using 3D BOLT demonstrated good accuracy and precision compared with the reference (R2 > 0.99). All in vivo imaging was successful and the average left ventricle T2 s measured by GraSE, 3DFBT2, and 3D BOLT were comparable and consistent for all healthy subjects (47.0 ± 2.3 vs. 47.7 ± 2.7 vs. 48.4 ± 1.8 ms) and patients (50.8 ± 3.0 vs. 48.6 ± 3.9 vs. 49.1 ± 3.7 ms), respectively. Myocardial T2 measured by 3D BOLT had excellent agreement with 3DFBT2 and there was no significant difference in mean, standard deviation, and coefficient of variation. 3D BOLT showed excellent repeatability (intraclass correlation coefficient: 0.938). The proposed 3D BOLT achieved whole-heart T2 mapping in a single breath-hold with good accuracy, precision, and repeatability on T2 measurements.

Dilated convolution network with edge fusion block and directional feature maps for cardiac MRI segmentation.

Cardiac magnetic resonance imaging (MRI) segmentation task refers to the accurate segmentation of ventricle and myocardium, which is a prerequisite for evaluating the soundness of cardiac function. With the development of deep learning in medical imaging, more and more heart segmentation methods based on deep learning have been proposed. Due to the fuzzy boundary and uneven intensity distribution of cardiac MRI, some existing methods do not make full use of multi-scale characteristic information and have the problem of ambiguity between classes. In this paper, we propose a dilated convolution network with edge fusion block and directional feature maps for cardiac MRI segmentation. The network uses feature fusion module to preserve boundary information, and adopts the direction field module to obtain the feature maps to improve the original segmentation features. Firstly, multi-scale feature information is obtained and fused through dilated convolutional layers of different scales while downsampling. Secondly, in the decoding stage, the edge fusion block integrates the edge features into the side output of the encoder and concatenates them with the upsampled features. Finally, the concatenated features utilize the direction field to improve the original segmentation features and generate the final result. Our propose method conducts comprehensive comparative experiments on the automated cardiac diagnosis challenge (ACDC) and myocardial pathological segmentation (MyoPS) datasets. The results show that the proposed cardiac MRI segmentation method has better performance compared to other existing methods.

Simultaneous T1, T2, and T2* Mapping of Carotid Plaque: The SIMPLE* Technique.

Background Quantitative T1, T2, and T2* measurements of carotid atherosclerotic plaque are important in evaluating plaque vulnerability and monitoring its progression. Purpose To develop a sequence to simultaneously quantify T1, T2, and T2* of carotid plaque. Materials and Methods The simultaneous T1, T2, and T2* mapping of carotid plaque (SIMPLE*) sequence is composed of three modules with different T2 preparation pulses, inversion-recovery pulses, and acquisition schemas. Single-echo data were used for T1 and T2 quantification, while the multiecho (ME) data were used for T2* quantification. The quantitative accuracy of SIMPLE* was tested in a phantom study by comparing its measurements with those of reference standard sequences. In vivo feasibility of the technique was prospectively evaluated between November 2020 and February 2022 in healthy volunteers and participants with carotid atherosclerotic plaque. The Pearson or Spearman correlation test, Student t test, and Wilcoxon rank-sum test were used. Results T1, T2, and T2* estimated with SIMPLE* strongly correlated with inversion-recovery spin-echo (SE) (correlation coefficient [r] = 0.99), ME-SE (r = 0.99), and ME gradient-echo (r = 0.99) sequences in the phantom study. In five healthy volunteers (mean age, 25 years ± 3 [SD]; three women), measurements were similar between SIMPLE* and modified Look-Locker inversion recovery, or MOLLI (1151 msec ± 71 vs 1098 msec ± 64; P = .14), ME turbo SE (31 msec ± 1 vs 31 msec ± 1; P = .32), and ME turbo field echo (24 msec ± 2 vs 25 msec ± 2; P = .19). In 18 participants with carotid plaque (mean age, 65 years ± 9; 16 men), quantitative T1, T2, and T2* of plaque components were consistent with their signal characteristics on multicontrast images. Conclusion A quantitative technique for simultaneous T1, T2, and T2* mapping of carotid plaque with 100-mm3 coverage and 0.8-mm3 resolution was developed using the proposed SIMPLE* sequence and demonstrated high accuracy and in vivo feasibility. © RSNA, 2023 Supplemental material is available for this article.

Alterations in cerebral distal vascular features and effect on cognition in a high cardiovascular risk population: A prospective longitudinal study.

BACKGROUND: Alterations in cerebral vasculature are instrumental in affecting cognition. Current studies mainly focus on proximal large arteries and small vessels, while disregarding morphology and blood flow of the arteries between them (medium-to-large arteries). METHODS: In this prospective study, two types of non-contrast enhanced magnetic resonance angiography (NCE-MRA) techniques, simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) and 3D Time-of-flight (TOF), were used to measure vascular morphologic features in medium-to-large intracranial arteries. Grey matter (GM) tissue level perfusion was assessed with arterial spin labeling (ASL) MRI. Twenty-seven subjects at high cardiovascular risk underwent baseline and 12-month follow-up MRI to compare the relationship between morphological features measured by NCE MRA, GM CBF by ASL MRI, and cognitive function measured by the Montreal Cognitive Assessment (MoCA). RESULTS: Changes in both global medium-to-large arteries and posterior cerebral (PCA) distal artery length and branch numbers, measured on SNAP MRA, were significantly associated with alterations in MoCA scores (P < 0.01), after adjusting for clinical confounding factors, total brain volume, and total white matter lesion (WML) volume. There were no associations between MoCA scores and vascular features on TOF MRA or ASL GM CBF. CONCLUSIONS: Alterations in vascular features of distal medium-to-large arteries may be more sensitive for detecting potential changes in cognition than cerebral blood flow alterations at the parenchymal level captured by perfusion ASL. Hemodynamic information from distal medium-to-large arteries provides an additional tool to advance understanding of the vascular contributions to cognitive function.

Omega-3 polyunsaturated fatty acids inhibit cardiomyocyte apoptosis and attenuate sepsis-induced cardiomyopathy.

OBJECTIVES: Sepsis can cause myocardial injury, which is one of the leading causes of death in critically ill patients. Fish oil rich in omega-3 polyunsaturated fatty acids (PUFAs) in ultralong chains has immunomodulatory effects and can inhibit the production of various critically ill proinflammatory cytokines. Therefore, this study focused on whether ω-3 PUFAs have a protective effect on sepsis-induced cardiomyopathy (SIC). METHODS: Male 6-8 weeks old C57BL/6 mice were pretreated with 3% special fish oil supplement rat food for seven consecutive days prior to surgery. Cecal ligation and puncture (CLP) was perfromed to induce polymicrobial sepsis.The cardiac function was assessed by echocardiography, apoptosis of cardiomyocyte were detected by TUNEL assay and Western blotting, and the level of TNF-α, IL-6, and IL-1ß in plasma was determined 24h after CLP. RESULTS: Pretreatment with omega-3 PUFAs attenuated cardiomyocyte apoptosis, decreased the production of proinflammatory cytokines, attenuated the SIC, and improved the survival rate of septic mice induced by CLP. CONCLUSIONS: ω-3 PUFAs alleviate SIC through attenuating cardiomyocyte apoptosis, which provides a new direction for the prevention and treatment of SIC.

Frequency importance analysis for chemical exchange saturation transfer magnetic resonance imaging using permuted random forest.

Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) is a promising molecular imaging tool that allows sensitive detection of endogenous metabolic changes. However, because the CEST spectrum does not display a clear peak like MR spectroscopy, its signal interpretation is challenging, especially under 3-T field strength or with a large saturation B1 . Herein, as an alternative to conventional Z-spectral fitting approaches, a permuted random forest (PRF) method is developed to determine featured saturation frequencies for lesion identification, so-called CEST frequency importance analysis. Briefly, voxels in the CEST dataset were labeled as lesion and control according to multicontrast MR images. Then, by considering each voxel's saturation signal series as a sample, a permutation importance algorithm was employed to rank the contribution of saturation frequency offsets in the differentiation of lesion and normal tissue. Simulations demonstrated that PRF could correctly determine the frequency offsets (3.5 or -3.5 ppm) for classifying two groups of Z-spectra, under a range of B0 , B1 conditions and sample sizes. For ischemic rat brains, PRF only displayed high feature importance around amide frequency at 2 h postischemia, reflecting that the pH changes occurred at an early stage. By contrast, the data acquired at 24 h postischemia exhibited high feature importance at multiple frequencies (amide, water, and lipids), which suggested the complex tissue changes that occur during the later stages. Finally, PRF was assessed using 3-T CEST data from four brain tumor patients. By defining the tumor region on amide proton transfer-weighted images, PRF analysis identified different CEST frequency importance for two types of tumors (glioblastoma and metastatic tumor) (p < 0.05, with each image slice as a subject). In conclusion, the PRF method was able to rank and interpret the contribution of all acquired saturation offsets to lesion identification; this may facilitate CEST analysis in clinical applications, and open up new doors for comprehensive CEST analysis tools other than model-based approaches.

Associations between cerebral blood flow and progression of white matter hyperintensity in community-dwelling adults: a longitudinal cohort study.

Background: White matter hyperintensity (WMH) is prevalent in elderly populations. Ischemia is characterized by a decline in cerebral blood flow (CBF) and may play a key role in the pathogenesis of WMH. However, the association between CBF reduction and WMH progression remains controversial. This study aimed to investigate the association between CBF and the progression of WMH at a 2-year follow-up of community-based, asymptomatic adults in a longitudinal cohort study across the lifespan. Methods: Asymptomatic adults who participated in a community-based study were recruited and underwent brain structural and perfusion magnetic resonance imaging (MRI) at baseline and at a 2-year follow-up visit. The CBF was measured on pseudo-continuous arterial spin-labeling (pCASL) MRI. The WMH was evaluated on T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images. Tissue segmentation was conducted on T1-weighted (T1W) images to derive binary masks of gray matter and normal-appearing white matter. Linear mixed effect models were conducted to analyze the cross-sectional and longitudinal associations between CBF and WMH. Results: A total of 229 adults (mean age 57.3±12.6 years; 94 males) were enrolled at baseline, among whom 84 participants (mean age 54.1±11.9 years; 41 males) completed a follow-up visit with a mean time interval of 2.77±0.44 years. At baseline, there was a decreasing trend in gray matter (GM) CBF with an increase of WMH burden (P=0.063), but this association was attenuated after adjusting for age (P=0.362). In the longitudinal analysis, baseline WMH volume was significantly associated with the reduction of perfusion in GM [coefficient =-1.96, 95% confidence interval (CI): -3.25 to -0.67; P=0.004] and normal appearing white matter (coefficient =-0.99, 95% CI: -1.66 to -0.31; P=0.005) during follow-up. On the contrary, neither baseline CBF in GM (P=0.888) nor normal appearing white matter (P=0.850) was associated with WMH progression. In addition, CBF changes within WMH were significantly associated with both baseline (coefficient =-0.014, 95% CI: -0.025 to -0.003; P=0.017) and progression (coefficient =-1.01, 95% CI: -1.81 to -0.20; P=0.015) of WMH volume. Conclusions: A WMH burden was not found to be directly associated with cortex perfusion at baseline due to the effects of age on both CBF and WMH. However, baseline WMH volume could predict the reduction of perfusion.

Improving accuracy of myocardial T1 estimation in MyoMapNet.

PURPOSE: To improve the accuracy and robustness of T1 estimation by MyoMapNet, a deep learning-based approach using 4 inversion-recovery T1 -weighted images for cardiac T1 mapping. METHODS: MyoMapNet is a fully connected neural network for T1 estimation of an accelerated cardiac T1 mapping sequence, which collects 4 T1 -weighted images by a single Look-Locker inversion-recovery experiment (LL4). MyoMapNet was originally trained using in vivo data from the modified Look-Locker inversion recovery sequence, which resulted in significant bias and sensitivity to various confounders. This study sought to train MyoMapNet using signals generated from numerical simulations and phantom MR data under multiple simulated confounders. The trained model was then evaluated by phantom data scanned using new phantom vials that differed from those used for training. The performance of the new model was compared with modified Look-Locker inversion recovery sequence and saturation-recovery single-shot acquisition for measuring native and postcontrast T1 in 25 subjects. RESULTS: In the phantom study, T1 values measured by LL4 with MyoMapNet were highly correlated with reference values from the spin-echo sequence. Furthermore, the estimated T1 had excellent robustness to changes in flip angle and off-resonance. Native and postcontrast myocardium T1 at 3 Tesla measured by saturation-recovery single-shot acquisition, modified Look-Locker inversion recovery sequence, and MyoMapNet were 1483 ± 46.6 ms and 791 ± 45.8 ms, 1169 ± 49.0 ms and 612 ± 36.0 ms, and 1443 ± 57.5 ms and 700 ± 57.5 ms, respectively. The corresponding extracellular volumes were 22.90% ± 3.20%, 28.88% ± 3.48%, and 30.65% ± 3.60%, respectively. CONCLUSION: Training MyoMapNet with numerical simulations and phantom data will improve the estimation of myocardial T1 values and increase its robustness to confounders while also reducing the overall T1 mapping estimation time to only 4 heartbeats.

Frequency and mortality of sepsis and septic shock in China: a systematic review and meta-analysis.

BACKGROUND: Sepsis, a life-threatening organ dysfunction induced by infection, is a major public health problem. This study aimed to evaluate the frequency and mortality of sepsis, severe sepsis, and septic shock in China. METHODS: We Searched MEDLINE, Embase, PubMed, and Cochrane Library from 1 January 1992 to 1 June 2020 for studies that reported on the frequency and mortality of sepsis, severe sepsis, and septic shock conducted in China. Random effects models were performed to estimate the pooled frequency and mortality of sepsis, severe sepsis, and septic shock. RESULTS: Our search yielded 846 results, of which 29 studies were included in this review. The pooled frequency of sepsis was estimated at 33.6% (95% CI 25.9% to 41.3%, I2 = 99.2%; p < 0.001), and the pooled mortality of sepsis, severe sepsis and septic shock were 29.0% (95% CI 25.3%-32.8%, I2 = 92.1%; p = 0), 31.1% (95% CI 25.3% to 36.9%, I2 = 85.8%; p < 0.001) and 37.3% (95% CI 28.6%-46.0%, I2 = 93.5%; p < 0.001). There was significant heterogeneity between studies. With a small number of included studies and the changing definition of sepsis, trends in sepsis frequency and mortality were not sufficient for analysis. Epidemiological data on sepsis in the emergency department (ED) are severely lacking, and more research is urgently needed in this area is urgently needed. CONCLUSIONS: Our findings indicated that the frequency and mortality of sepsis and septic shock in China were much higher than North America and Europe countries. Based on our results, an extremely high incidence and mortality of sepsis and septic shock in China's mainland requires more healthcare budget support. Epidemiological data on sepsis and septic shock in ED are severely lacking, and more research is urgently needed in this area. Trial registration This systematic review was conducted according to the statement of the preferred reporting items for systematic review (PROSPERO CRD42021243325) and the meta-analysis protocols (PRISMA-P).

Blood flow and perfusion lateralization in border zone infarct using 4D flow and arterial spin labeling.

PURPOSE: Hemodynamics may play an important role in border zone infarct (BZI), but macroscopic and microscopic hemodynamics of BZI still remain unclear. This study aims to investigate arterial flow and tissue perfusion differences between BZI and non-BZI in patients with unilateral middle cerebral artery (MCA) territory infarcts. METHODS: Subacute ischemic stroke patients with unilateral infarcts at MCA territory were included. Imaging protocols included 4D flow, ASL (arterial spin labeling), and routine clinical brain MRI scan. A total of 56 patients (56.1 ± 11.9 years, 39 male) were included and divided as BZI (n = 26) and non-BZI (n = 30). BZI was further subdivided as cortical BZI (CBZI, n = 9), internal BZI (IBZI, n = 11), and mixed BZI (n = 6). Average blood flow (Flowavg), regional average cerebral blood flow (CBFavg) were compared between infarct and contralateral sides to test hemodynamic lateralization. Flow-index and CBF-index (infarct sides/contralateral sides) were compared between groups and subgroups. RESULTS: Flowavg and CBFavg showed significant lateralization in both BZI and non-BZI as well as CBZI and IBZI. Flow-index (0.51 ± 0.37 vs. 0.87 ± 0.36, p < 0.01) and CBF-index (0.70 ± 0.21 vs. 0.90 ± 0.19, p < 0.01) were significantly different between BZI and non-BZI but were not significantly different between CBZI and IBZI. CONCLUSION: In summary, hemodynamic lateralization can occur in subacute stroke patients with BZI and non-BZI and the one that occurs in BZI tends to be more severe in view of arterial flow and tissue perfusion.

Associations of intracranial artery length and branch number on non-contrast enhanced MRA with cognitive impairment in individuals with carotid atherosclerosis.

Developing novel risk markers for vascular contributions to cognitive impairment and dementia is important. This study aimed to extract total length, branch number and average tortuosity of intracranial distal arteries (A2, M2, P2 and more distal) from non-contrast enhanced magnetic resonance angiography (NCE-MRA) images, and explore their associations with global cognition. In 29 subjects (aged 40-90 years) with carotid atherosclerotic disease, the 3 intracranial vascular features on two NCE-MRA techniques (i.e. time of flight, TOF and simultaneous non-contrast angiography and intraplaque hemorrhage, SNAP) were extracted using a custom-developed software named iCafe. Arterial spin labeling (ASL) and phase contrast (PC) cerebral blood flow (CBF) were measured as references. Linear regression was performed to study their associations with global cognition, measured with the Montreal Cognitive Assessment (MoCA). Intracranial artery length and number of branches on NCE-MRA, ASL CBF and PC CBF were found to be positively associated with MoCA scores (P < 0.01). The associations remained significant for artery length and number of branches on NCE-MRA after adjusting for clinical covariates and white matter hyperintensity volume. Further adjustment of confounding factors of ASL CBF or PC CBF did not abolish the significant association for artery length and number of branches on TOF. Our findings suggest that intracranial vascular features, including artery length and number of branches, on NCE-MRA may be useful markers of cerebrovascular health and provide added information over conventional brain blood flow measurements in individuals with cognitive impairment.

Saturated multi-delay renal arterial spin labeling technique for simultaneous perfusion and T1 quantification in kidneys.

PURPOSE: To propose a free-breathing simultaneous multi-delay arterial spin labeling (ASL) and T1 mapping technique with a stepwise kinetic model for renal assessment in a single 4-min scan at 3 T. METHODS: The proposed saturated multi-delay renal arterial spin labeling (SAMURAI) sequence used flow-sensitive alternating inversion recovery (FAIR) preparation, followed by acquisition of 9 images with Look-Locker spoiled gradient recalled echo (SPGR). Pre-saturation at the imaging slice was used to achieve saturation-based T1 mapping. A 4-step 2-compartment kinetic model was proposed to characterize water transition through artery- and tissue-compartment. The impact of the Look-Locker sampling scheme on the ASL signal was corrected in this model. T1 estimation with dictionary searching method and perfusion quantification based on the proposed kinetic model fitting were conducted after groupwise registration of the acquired images. The feasibility and repeatability of SAMURAI were validated in healthy subjects (n = 11) and patients with different renal diseases (n = 4). RESULTS: The proposed SAMURAI technique can provide accurate T1 map with strong correlation (R2  = 0.98) with inversion recovery spin echo (IR-SE) on phantom. SAMURAI provided equally reliable whole kidney and cortical ASL and T1 quantification results compared with multi-TI FAIR (intraclass correlation coefficient [ICC], 0.880-0.958) and IR-SPGR (ICC, 0.875-0.912), respectively. Low renal blood flow and increased T1 were detected by SAMURAI in the affected kidneys of the patients. SAMURAI had excellent scan-rescan repeatability (ICC, 0.905-0.992) and significantly reduced scan time (4 min 6 s vs. 45 min for 9 TIs) compared to multi-TI FAIR. CONCLUSION: The proposed SAMURAI technique is feasible and repeatable for simultaneously quantifying T1 and perfusion of kidneys with high time-efficiency.