Exhaustive matching of 3D/2D coronary artery structure based on imperfect segmentations.

PURPOSE: The 3D/2D coronary artery registration technique has been developed for the guidance of the percutaneous coronary intervention. It introduces the absent 3D structural information by fusing the pre-operative computed tomography angiography (CTA) volume with the intra-operative X-ray coronary angiography (XCA) image. To conduct the registration, an accurate matching of the coronary artery structures extracted from the two imaging modalities is an essential step. METHODS: In this study, we propose an exhaustive matching algorithm to solve this problem. First, by recognizing the fake bifurcations in the XCA image caused by projection and concatenating the fractured centerline fragments, the original XCA topological structure is restored. Then, the vessel segments in the two imaging modalities are removed orderly, which generates all the potential structures to simulate the imperfect segmentation results. Finally, the CTA and XCA structures are compared pairwise, and the matching result is obtained by searching for the structure pair with the minimum similarity score. RESULTS: The experiments were conducted based on a clinical dataset collected from 46 patients and comprising of 240 CTA/XCA data pairs. And the results show that the proposed method is very effective, which achieves an accuracy of 0.960 for recognizing the fake bifurcations in the XCA image and an accuracy of 0.896 for matching the CTA/XCA vascular structures. CONCLUSION: The proposed exhaustive structure matching algorithm is simple and straightforward without any impractical assumption or time-consuming computations. With this method, the influence of the imperfect segmentations is eliminated and the accurate matching could be achieved efficiently. This lays a good foundation for the subsequent 3D/2D coronary artery registration task.

Long Noncoding RNA and mRNA Expression Profiles in Rats with LPS-induced Myocardial Dysfunction.

Background: Sepsis is an uncontrolled systemic inflammatory response. Long noncoding RNAs (lncRNAs) are involved in the pathogenesis of sepsis. However, little is known about the roles of lncRNAs in sepsis-induced myocardial dysfunction. Objective: We aimed to determine the regulatory mechanism of lncRNAs in sepsis-induced myocardial dysfunction. Methods: In this study, we analysed the lncRNA and mRNA expression profiles using microarray analysis. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, protein-protein interaction network, and gene set enrichment analysis were used to evaluate the data. We also constructed coding and noncoding coexpression and competing endogenous RNA networks to investigate the mechanisms. Results: In vivo lipopolysaccharide -induced sepsis rat model was established. A total of 387 lncRNAs and 1,952 mRNAs were identified as significantly changed in the left ventricle. Kyoto Encyclopedia of Genes and Genomes analysis of mRNAs showed that the upregulated genes were mainly enriched in the "complement and coagulation cascade pathway" and "immune-related biological processes" terms. Eight significantly changed lncRNAs detected by RT-qPCR may be responsible for these processes. A competing endogenous RNA network was generated, and the results indicated that eight lncRNAs were related to the "calcium ion binding" process. Conclusion: These results demonstrate that crosstalk between lncRNAs and mRNAs may play important roles in the development of sepsis-induced myocardial dysfunction.

LncRNA-mRNA expression profile and functional network of vascular dysfunction in septic rats.

BACKGROUND: We used microarrays to analyse the changes in long non-coding RNAs (lncRNAs) and mRNAs in aorta tissue in model rats with lipopolysaccharide-induced sepsis and determined the lncRNA-mRNA and lncRNA-miRNA-mRNA functional networks. METHODS: Wistar rats were intraperitoneally injected with lipopolysaccharide, and the lncRNA and mRNA expression profiles in the aorta were evaluated using microarrays. The functions of the differentially expressed mRNAs were analysed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We then constructed coding/non-coding co-expression and competing endogenous RNA networks to study the mechanisms related to sepsis in rats. RESULTS: We identified 503 differentially expressed lncRNAs and 2479 differentially expressed mRNAs in the model rats with lipopolysaccharide-induced sepsis. Mitochondrial fission process 1 (MTFP1) was the most significantly down-regulated mRNA. Bioinformatics analysis showed that the significantly down-regulated mRNAs in the sepsis models were in pathways related to mitochondrial structure, function, and energy metabolism. Coding/non-coding co-expression and competing endogenous RNA analyses were conducted using 12 validated lncRNAs in combination with all mRNAs. The coding/non-coding co-expression analysis showed that the 12 validated lncRNAs were mainly regulatory factors for abnormal energy metabolism, including mitochondrial structure damage and aberrant mitochondrial dynamics. The competing endogenous RNA analysis revealed that the potential functions of these 12 lncRNAs might be related to the inflammatory response. CONCLUSION: We determined the differentially expressed lncRNAs and mRNAs in the aorta of septic rats using microarrays. Further studies on these lncRNAs will help elucidate the mechanism of sepsis at the genetic level and may identify potential therapeutic targets.

Design, development and evaluation of an ergonomically designed dual-use mechanism for robot-assisted cardiovascular intervention.

PURPOSE: Robot-assisted cardiovascular intervention has been recently developed, which enables interventionists to avoid x-ray radiation and improve their comfort. However, there are still some challenges in the robotic design, such as the inability of the interventionist to freely perform natural clinical techniques and the limited motion travel of the interventional tool. To overcome these challenges, this paper proposes an ergonomically designed dual-use mechanism for cardiovascular intervention (DMCI). METHODS: DMCI can work as an ergonomic interface or a compact slave robot with unlimited motion travel. Our kinematic analysis of DMCI includes motion decoupling and coupling. Motion decoupling decomposes the translation and rotation from the interventionist's natural clinical actions at the master side. Motion coupling can calculate the input pulses of motors according to the desired rotation and translation, thus composing the motion of the intervention tool at the slave side. RESULTS: Our kinematic analysis of DMCI has been experimentally verified, where the overall mean rotational errors are all less than 1° and translational errors are all less than 1 mm. We also evaluated the performance of the DMCI-based master-slave system, where the overall rotational and translational errors are 0.821 ± 0.753° and 0.608 ± 0.512 mm. Moreover, operators were found to be generally more efficient when using the DMCI-based interface compared to the conventional joystick. CONCLUSION: We have validated our kinematic analysis of DMCI. The master-slave teleoperation experiment demonstrated that operators can freely perform natural clinical techniques through the DMCI-based interface, and the slave robot can replicate the operators' manipulation at the master side well.

An automatic framework for estimating the pose of the catheter distal section using a coarse-to-fine network.

BACKGROUND AND OBJECTIVE: During percutaneous coronary intervention procedures, generally only 2D X-ray images are provided. The consequent lack of depth perception makes it difficult for interventionists to visually estimate the pose of medical tools inside the vasculature, especially for novices. Although some automatic methods have been developed to aid interventionists, it is still a challenging task to obtain stable and accurate pose estimation. In this paper, we describe a learning-based framework for estimating the pose of the catheter distal section (CDS). The main innovation of this framework is the proposal of a coarse-to-fine fusion network (CFF-Net) which can achieve the shape and orientation estimation for the CDS. METHODS: By adopting a two-step fusion, CFF-Net progressively solves the shape and orientation ambiguities. The first step is the early fusion where the 2D projection image fuses with the shape prior before input, which makes the estimated result own a specific catheter distal shape. The second step is the late fusion where CFF-Net fuse feature maps and the orientation data from Electromagnetic (EM) sensors to confirm the overall orientation of the CDS. Finally, the estimated pose in the EM space will be obtained after we combine the estimated shape and orientation from CFF-Net with the position information from the EM sensor. RESULTS: The effectiveness of CFF-Net has been verified in a simulated environment where RMSE of CFF-Net is 0.706 ± 0.121 mm. This approach was further transferred from simulation to reality using the real-world data, where RMSE of CFF-Net is 1.121 ± 0.124 mm and RMSE of the whole proposed framework is 1.577 ± 0.144 mm. CONCLUSION: In simulated and real-world experiments, our proposed approach has been proven to achieve high accuracy while ensuring real-time processing for estimating the pose of the CDS.

Effect of berberine on global modulation of lncRNAs and mRNAs expression profiles in patients with stable coronary heart disease.

BACKGROUND: Berberine (BBR) is an isoquinoline alkaloid found in the Berberis species. It was found to have protected effects in cardiovascular diseases. Here, we investigated the effect the regulatory function of long noncoding RNAs (lncRNAs) during the treatment of stable coronary heart disease (CHD) using BBR. We performed microarray analyses to identify differentially expressed (DE) lncRNAs and mRNAs between whole blood samples from 5 patients with stable CHD taking BBR and 5 no BBR volunteers. DE lncRNAs and mRNAs were validated by quantitative real-time PCR. RESULTS: A total of 1703 DE lncRNAs and 912 DE mRNAs were identified. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated DE mRNAs might be associated with mammalian target of rapamycin and mitogen-activated protein kinase pathway. These pathways may be involved in the healing process after CHD. To study the relationship between mRNAs encoding transcription factors (DNA damage inducible transcript 3, sal-like protein 4 and estrogen receptor alpha gene) and CHD related de mRNAs, we performed protein and protein interaction analysis on their corresponding proteins. AKT and apoptosis pathway were significant enriched in protein and protein interaction network. BBR may affect downstream apoptosis pathways through DNA damage inducible transcript 3, sal-like protein 4 and estrogen receptor alpha gene. Growth arrest-specific transcript 5 might regulate CHD-related mRNAs through competing endogenous RNA mechanism and may be the downstream target gene regulated by BBR. Verified by the quantitative real-time PCR, we identified 8 DE lncRNAs that may relate to CHD. We performed coding and non-coding co-expression and competing endogenous RNA mechanism analysis of these 8 DE lncRNAs and CHD-related DE mRNA, and predicted their subcellular localization and N6-methyladenosine modification sites. CONCLUSION: Our research found that BBR may affect mammalian target of rapamycin, mitogen-activated protein kinase, apoptosis pathway and growth arrest-specific transcript 5 in the process of CHD. These pathways may be involved in the healing process after CHD. Our research might provide novel insights for functional research of BBR.

CAR-Net: A Deep Learning-Based Deformation Model for 3D/2D Coronary Artery Registration.

Percutaneous coronary intervention is widely applied for the treatment of coronary artery disease under the guidance of X-ray coronary angiography (XCA) image. However, the projective nature of XCA causes the loss of 3D structural information, which hinders the intervention. This issue can be addressed by the deformable 3D/2D coronary artery registration technique, which fuses the pre-operative computed tomography angiography volume with the intra-operative XCA image. In this study, we propose a deep learning-based neural network for this task. The registration is conducted in a segment-by-segment manner. For each vessel segment pair, the centerlines that preserve topological information are decomposed into an origin tensor and a spherical coordinate shape tensor as network input through independent branches. Features of different modalities are fused and processed for predicting angular deflections, which is a special type of deformation field implying motion and length preservation constraints for vessel segments. The proposed method achieves an average error of 1.13 mm on the clinical dataset, which shows the potential to be applied in clinical practice.

Recursive Centerline- and Direction-Aware Joint Learning Network with Ensemble Strategy for Vessel Segmentation in X-ray Angiography Images.

BACKGROUND AND OBJECTIVE: Automatic vessel segmentation from X-ray angiography images is an important research topic for the diagnosis and treatment of cardiovascular disease. The main challenge is how to extract continuous and completed vessel structures from XRA images with poor quality and high complexity. Most existing methods predominantly focus on pixel-wise segmentation and overlook the geometric features, resulting in breaking and absence in segmentation results. To improve the completeness and accuracy of vessel segmentation, we propose a recursive joint learning network embedded with geometric features. METHODS: The network joins the centerline- and direction-aware auxiliary tasks with the primary task of segmentation, which guides the network to explore the geometric features of vessel connectivity. Moreover, the recursive learning strategy is designed by passing the previous segmentation result into the same network iteratively to improve segmentation. To further enhance connectivity, we present a complementary-task ensemble strategy by fusing the outputs of the three tasks for the final segmentation result with majority voting. RESULTS: To validate the effectiveness of our method, we conduct qualitative and quantitative experiments on the XRA images of the coronary artery and aorta including aortic arch, thoracic aorta, and abdominal aorta. Our method achieves F1 scores of 85.61±3.48% for the coronary artery, 89.02±2.89% for the aortic arch, 88.22±3.33% for the thoracic aorta, and 83.12±4.61% for the abdominal aorta. CONCLUSIONS: Compared with six state-of-the-art methods, our method shows the most complete and accurate vessel segmentation results.

Comparative analysis of the efficacy of early and late surgical intervention for acute spinal cord injury: A systematic review and meta-analysis based on 16 studies.

BACKGROUND: Spinal cord injuries (SCI) are a devastating condition and can lead to severe functional and psychosocial problems. However, the influence of the timing of the surgical intervention for acute SCI remains debated, with substantial variability in clinical practice. Thus, this study aims to compare the efficacy of early and late surgical intervention for acute SCI. METHODS: A systematic search of PubMed, Embase, Cochrane Library and Web of Science up to January 10, 2021 was conducted for relevant studies that compared early and late acute SCI. Neurological outcomes were assessed by American Spinal Injury Association (ASIA). Early surgery was defined as the surgical intervention within 24 h after spinal injury. The primary outcome was the change of ASIA score from baseline to follow-up time after spinal injury. Second primary outcomes were clinical outcomes including neurological improvement rate, mortality, length of stay (LOS), charges ($), complications and ASIA Impairment Scale (AIS). All statistical analyses were performed using standard statistical procedures provided in Review Manager 5.2. RESULTS: A total of 16 studies including 3977 SCI patients were identified finally. Our pooled results indicated that, compared with late surgery, patients who underwent early surgery experienced more ASIA score improvement, with pooled MDs of 2.32 points (95% CI 1.07-3.57; P = 0.0003) in total motor scores, 5.13 points (95% CI 3.94-6.32; P < 0.0001) in light touch scores, and 4.49 points (95% CI 2.22-6.76; P = 0.0001) in pin prick scores respectively. In addition, patients receiving early surgery experienced more total motor score after surgery (MD 3.30; 95% CI 0.82-5.79; P = 0.009). Patients who had early surgery also had higher neurological improvement rate (OR 1.66; 95% CI 1.19-2.31; P = 0.003), shorter LOS (MD -4.77; 95% CI -7.42 to -2.12), less charges ($) (MD -0.33; 95% CI -0.43 to -0.22), lower incidence of complications (OR 0.62; 95% CI 0.48-0.81), and higher AIS improvement rate (OR 1.71; 95% CI 1.20-2.44) respectively. CONCLUSIONS: Compared with late surgery, acute SCI patients who underwent early surgery experienced greater recovery after spinal injury, with better neurological improvement, shorter LOS, less charges and lower incidence of complications.

Genome-wide identification of altered RNA m6A profiles in vascular tissue of septic rats.

Sepsis is the leading cause of death in hospital intensive care units. In light of recent studies showing that variations in N6-methyladenosine (m6A) levels in different RNA transcripts influence inflammatory responses, we evaluated the m6A profiles of rat aortic mRNAs and lncRNAs after lipopolysaccharide (LPS)-induced sepsis. LC-MS-based mRNA modification analysis showed that global m6A levels were significantly decreased in aortic tissue of rats injected intraperitoneally with LPS. This finding was consistent with downregulated expression of METTL3 and WTAP, two members of the m6A writer complex, in LPS-exposed aortas. Microarray analysis of m6A methylation indicated that 40 transcripts (31 mRNAs and 9 lncRNAs) were hypermethylated, while 223 transcripts (156 mRNAs and 67 lncRNAs) were hypomethylated, in aortic tissue from LPS-treated rats. On GO and KEGG analyses, 'complement and coagulation cascades', 'transient receptor potential channels', and 'organic anion transmembrane transporter activity' were the major biological processes modulated by the differentially m6A methylated mRNAs. In turn, competing endogenous RNA network analysis suggested that decreased m6A levels in lncRNA-XR_343955 may affect the inflammatory response through the cell adhesion molecule pathway. Our data suggest that therapeutic modulation of the cellular m6A machinery may be useful to preserve vascular integrity and function during sepsis.

Lipopolysaccharide Alters the m6A Epitranscriptomic Tagging of RNAs in Cardiac Tissue.

N6-methyladenosine (m6A) modification plays important roles in the pathology of a variety of diseases. However, the roles of m6A modification in sepsis-induced myocardial dysfunction are not well defined. Rats were divided into control and lipopolysaccharide (LPS)-induced sepsis group. Global m6A levels of left ventricle tissue were measured by LC-MS/MS, and transcriptome-wide m6A modifications were profiled using epitranscriptomic microarrays (mRNAs and lncRNAs). Bioinformatics analysis was conducted to understand the functional implications of m6A modifications during sepsis. Methylated lncRNAs and mRNAs were measured by m6A single-base site qPCR. The global m6A levels in left ventricle tissue were significantly decreased in the LPS group. While 27 transcripts (23 mRNAs and four lncRNAs) were hypermethylated, 46 transcripts (39 mRNAs and 7 lncRNAs) were hypomethylated in the LPS group. The mRNA expression of writers and readers was significantly decreased in the LPS group. The m6A modification of Clec1b, Stk38l and Tnfrsf26 was associated with platelet activation and apoptotic pathways. Moreover, the decrease in m6A modification of lncRNA XR_346,771 may be related to cation import in cardiac tissue. Our data provide novel information regarding changes to m6A modifications in cardiac tissue during sepsis, and m6A modifications might be promising therapeutic targets.

Incremental improvement of diagnostic performance of coronary CT angiography for the assessment of coronary stenosis in the presence of calcium using a dual-layer spectral detector CT: validation by invasive coronary angiography.

To investigate value of spectral reconstructions for the quantification of coronary stenosis in the presence of calcified or partially calcified plaques using a dual-layer spectral detector CT (SDCT). Seventy-two consecutive patients were retrospectively enrolled. Conventional 120 kVp images, eight virtual monoenergetic images (VMI) (70 to 140 keV), the effective atomic number (Z effective) and iodine no water images were reconstructed. Invasive coronary angiography was used as the reference standard. Parallel and serial testing were used to assess the incremental diagnostic value of Z effective and iodine no water images to the best VMI series. 122 coronary lesions of 72 patients (49 men and 23 women; 63.7 ± 10.2 years) were enrolled in analysis. Reconstruction at 100 keV yielded optimal diagnostic performance, the sensitivity, specificity, PPV, NPV and diagnostic accuracy to identify stenosis ≥ 50% or ≥ 70% were 84%, 70%, 80%, 76%, 79% and 78%, 98%, 93%, 91%, 92%, respectively. A serial combination (100 keV VMI followed by Z effective images) resulted in an improved specificity (from 70 to 80%) with a moderate loss of sensitivity (81% from 84%) in identifying ≥ 50% stenosis (P = 0.021). For patients with high Agatston score, this combination could further reduce false positive cases and improve diagnostic accuracy. 100 keV VMI provide optimal diagnostic performance for the detection of coronary stenosis in the presence of calcified or partially calcified plaques using a dual-layer SDCT, with further improvements obtained with the combined use of Z effective images.

Target localization during respiration motion based on LSTM: A pilot study on robotic puncture system.

BACKGROUND: In the needle biopsy, the respiratory motion causes the displacement of thoracic-abdominal soft tissues, which brings great difficulty to accurate localization. Based on internal target motion and external marker motion, the existing methods need to establish a correlation model or a prediction model to compensate the respiratory movement, which can hardly achieve required accuracy in clinic use due to the complexity of the internal tissue motion. METHODS: In order to improve the tracking accuracy and reduce the number of models, we propose a framework for target localization based on long short-term memory (LSTM) method. Combined with the correlation model and the prediction model by using LSTM, we adopted the principal component of time-series features of external surrogate signals to predict the trajectory of the internal tumour target. Additionally, based on the electromagnetic tracking system and Universal Robots 3 robotic arm, we applied the proposed approach to a prototype of robotic puncture system for real-time tumour tracking. RESULTS: To verify the proposed method, experiments on both public datasets and customized motion phantom for respiratory simulation were performed. In the public dataset study, an average mean absolute error, and an average root-mean-square error of predictive results of 0.44 and 0.58 mm were achieved, respectively. In the motion phantom study, an average root mean square of puncturing error resulted in 0.65 mm. CONCLUSION: The experimental results demonstrate the proposed method improves the accuracy of target localization during respiratory movement and appeals the potentials applying to clinical application.

Efficacy of adaptive servo-ventilation and continuous positive airway pressure treatment in chronic heart failure with sleep-disordered breathing: a systematic review and meta-analysis.

Noninvasive positive-pressure ventilation (NPPV) is recognized as an effective adjuvant therapy for sleep-disordered breathing (SDB) in heart failure patients with reduced ejection fraction (HFrEF + SDB). In recent years, some studies have found that adaptive servo-ventilation (ASV) has a negative impact on survival, especially among patients with central sleep apnea (CSA), the use of which is controversial. This study aims to explore the effects of NPPV on cardiac function and survival in patients with sleep-disordered breathing and chronic congestive heart failure. This meta-analysis was based on literature searches of publications published before August 31, 2019, in the PubMed, EMBASE, Cochrane Library, and Web of Science databases. A total of 88 independent studies were summarized and compared, comprising a sampling of 19,259 subjects. Compared with the nontreatment group, treatment with ASV had no effect on all-cause mortality in patients with HFrEF + CSA (hazard ratio (HR) = 1.13 [0.84, 1.51]). Short-term treatment with ASV, e.g., 3-6 months, was significantly beneficial regarding event-free survival in patients with HFrEF + CSA (HR = 0.13 [0.04, 0.45]). Periodic short-term (e.g., 3-6 months) positive-pressure ventilation can significantly improve cardiac function, which is beneficial for the survival of patients with HFrEF + CSA. Attention should be paid to the length and period of treatment, as prolonged treatment may have negative effects.

Analyses of circRNA and mRNA profiles in the submandibular gland in hypertension.

The aim of this study was to elucidate the roles played by circular RNAs (circRNAs) in the mechanism underlying submandibular gland (SMG) dysfunction in hypertension. We employed RNA-seq to analyze the circRNA and mRNA expression profiles of SMGs. Seventy-five differentially expressed (DE) circRNAs and 691 DE mRNAs were determined to be significantly altered in spontaneously hypertensive rats. Altered mRNAs were primarily related to the immune system and immune response. Eight circRNAs were selected for further analysis. Cell adhesion molecules were determined to be the most strongly enriched pathway through analysis of DE mRNAs, the coding noncoding gene co-expression (CNC) network and the competitive endogenous RNA (ceRNA) network. The salivary secretion pathway was observed to be notably enriched through analysis of the ceRNA network. These results suggest that the crosstalk among circRNAs may play a crucial role in the development of SMG dysfunction in hypertension.

Deformable Registration of Coronary Arteries with Topological Constraints for Image-Guided Vascular Interventions.

2D/3D registration of preoperative computed tomography angiography with intra-operative X-ray angiography improves image guidance in percutaneous coronary intervention. However, previous registration methods are inaccurate and time-consuming due to simple deformation and iterative optimization, respectively. In this paper, we propose a novel method for non-rigid registration of coronary arteries based on a point set registration network, which predicts the complex deformation field directly without iterative optimization. In order to maintain the structure of coronary arteries, we advance the classical point set registration network with a loss function containing global and local topological constraints. The method was evaluated on ten clinical data, and it achieved a median chamfer distance of 73.60 pixels with a run time of less than 1s on CPU. Experimental results demonstrate that the proposed method is highly accurate and efficient.

LncRNA and mRNA expression profiles and functional networks of hyposalivation of the submandibular gland in hypertension.

Hyposalivation is a complication of hypertension. However, little is known about the role of long non-coding RNAs (lncRNAs) in salivary glands in hypertension. This study aimed to compare the lncRNA and mRNA expression profiles between spontaneous hypertension rats (SHRs) and Wistar-Kyoto (WKY) rats through microarray analysis and apple bioinformatics methods to analyse their potential roles in hyposalivation. The differentially expressed (DE) lncRNAs and mRNAs were confirmed by quantitative real-time PCR (qRT-PCR). Compared with WKY rats, 225 DE lncRNAs and 473 DE mRNAs were identified in the SMG of SHRs. The pathway analyses of DE mRNAs showed that inflammatory mediator regulation of transient receptor potential channels was involved in hyposalivation in SHRs. Ten DE lncRNAs were chosen for further research. A coding-non-coding gene co-expression (CNC) network and competing endogenous RNA (ceRNA) network analysis revealed that the potential functions of these 10 DE lncRNAs were closely connected with the processes of the immune response. This study showed abundant DE lncRNAs and mRNAs in hypertensive SMGs. Furthermore, our results indicated strong associations between the immune response and hyposalivation and showed the potential of immune-related genes as novel and therapeutic targets for hyposalivation.

Generation of a local lung respiratory motion model using a weighted sparse algorithm and motion prior-based registration.

Respiration-introduced tumor location uncertainty is a challenge in lung percutaneous interventions, especially for the respiratory motion estimation of the tumor and surrounding vessel structures. In this work, a local motion modeling method is proposed based on whole-chest computed tomography (CT) and CT-fluoroscopy (CTF) scans. A weighted sparse statistical modeling (WSSM) method that can accurately capture location errors for each landmark point is proposed for lung motion prediction. By varying the sparse weight coefficients of the WSSM method, newly input motion information is approximately represented by a sparse linear combination of the respiratory motion repository and employed to serve as prior knowledge for the following registration process. We have also proposed an adaptive motion prior-based registration method to improve the motion prediction accuracy of the motion model in the region of interest (ROI). This registration method adopts a B-spline scheme to interactively weight the relative influence of the prior knowledge, model surface and image intensity information by locally controlling the deformation in the CTF image region. The proposed method has been evaluated on 15 image pairs between the end-expiratory (EE) and end-inspiratory (EI) phases and 31 four-dimensional CT (4DCT) datasets. The results reveal that the proposed WSSM method achieved a better motion prediction performance than other existing lung statistical motion modeling methods, and the motion prior-based registration method can generate more accurate local motion information in the ROI.

Identification of circRNA and mRNA expression profiles and functional networks of vascular tissue in lipopolysaccharide-induced sepsis.

Sepsis is the most common cause of death in intensive care units. This study investigated the circular RNA (circRNA) and mRNA expression profiles and functional networks of the aortic tissue in sepsis. We established a lipopolysaccharide (LPS)-induced rat sepsis model. High-throughput sequencing was performed on the aorta tissue to identify differentially expressed (DE) circRNAs and mRNAs, which were validated by real-time quantitative polymerase chain reaction (RT-qPCR). Bioinformatic analysis was carried out and coding and non-coding co-expression (CNC) and competing endogenous RNA (ceRNA) regulatory networks were constructed to investigate the mechanisms. In total, 373 up-regulated and 428 down-regulated circRNAs and 2063 up-regulated and 2903 down-regulated mRNAs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of mRNAs showed that the down-regulated genes were mainly enriched in the process of energy generation. CNC and ceRNA regulatory networks were constructed with seven DE circRNAs. The results of functional enrichment analysis of CNC target genes revealed the important role of circRNAs in inflammatory response. The ceRNA network also highlighted the significant enrichment in calcium signalling pathway. Significant alterations in circRNAs and mRNAs were observed in the aortic tissue of septic rats. In addition, CNC and ceRNA networks were established.