Assessment of aortic hemodynamics in patients with thoracoabdominal aortic aneurysm using four-dimensional magnetic resonance imaging: a cross-sectional study.

Background: Thoracoabdominal aortic aneurysms (TAAAs) are rare but complicated aortic pathologies that can result in high morbidity and mortality. The whole-aorta hemodynamic characteristics of TAAA survivors remains unknown. This study sought to obtain a comprehensive view of flow hemodynamics of the whole aorta in patients with TAAA using four-dimensional flow (4D flow) magnetic resonance imaging (MRI). Methods: This study included patients who had experienced TAAA or abdominal aortic aneurysm (AAA) and age- and sex-matched volunteers who had attended China Hospital from December 2021 to December 2022 in West. Patients with unstable ruptured aneurysm or other cardiovascular diseases were excluded. 4D-flow MRI that covered the whole aorta was acquired. Both planar parameters [(regurgitation fraction (RF), peak systolic velocity (Vmax), overall wall shear stress (WSS)] and segmental parameters [pulse wave velocity (PWV) and viscous energy loss (VEL)] were generated during postprocessing. The Student's t-test or Mann-Whitney test was used to compare flow dynamics among the three groups. Results: A total of 11 patients with TAAA (mean age 53.2±11.9 years; 10 males), 19 patients with AAA (mean age 58.0±11.7 years; 16 males), and 21 controls (mean age 55.4±15.0 years; 19 males) were analyzed. The patients with TAAA demonstrated a significantly higher RF and lower Vmax in the aortic arch compared to healthy controls. The whole length of the aorta in patients with TAAA was characterized by lower WSS, predominantly in the planes of pulmonary artery bifurcation and the middle infrarenal planes (all P values <0.001). As for segmental hemodynamics, compared to controls, patients with TAAA had a significantly higher PWV in the thoracic aorta (TAAA: median 11.41 m/s, IQR 9.56-14.32 m/s; control: median 7.21 m/s, IQR 5.57-7.79 m/s; P<0.001) as did those with AAA (AAA: median 8.75 m/s, IQR 7.35-10.75 m/s; control: median 7.21 m/s, IQR 5.57-7.79 m/s; P=0.024). Moreover, a greater VEL was observed in the whole aorta and abdominal aorta in patients with TAAA. Conclusions: Patients with TAAA exhibited a stiffer aortic wall with a lower WSS and a greater VEL for the whole aorta, which was accompanied by a higher RF and lower peak velocity in the dilated portion of the aorta.

Advanced multifunctional hydrogels for diabetic foot ulcer healing: Active substances and biological functions.

AIM: Hydrogels with excellent biocompatibility and biodegradability can be used as the desirable dressings for the therapy of diabetic foot ulcer (DFU). This review aimed to summarize the biological functions of hydrogels, combining with the pathogenesis of DFU. METHODS: The studies in the last 10 years were searched and summarized from the online database PubMed using a combination of keywords such as hydrogel and diabetes. The biological functions of hydrogels and their healing mechanism on DFU were elaborated. RESULTS: In this review, hydrogels were classified by their active substances such as drugs, cytokines, photosensitizers, and biomimetic peptide. Based on this, the biological functions of hydrogels were summarized by associating the pathogenesis of DFU, including oxidative stress, chronic inflammation, cell phenotype change, vasculopathy, and infection. This review also pointed out some of the shortcomings of hydrogels in present researches. CONCLUSIONS: Hydrogels were classified into carrier hydrogels and self-functioning hydrogels in this review. Besides, the functions and components of existing hydrogels were clarified to provide assistance for future researches and clinical applications.

From 2D to 3D: Automatic measurement of the Cobb angle in adolescent idiopathic scoliosis with the weight-bearing 3D imaging.

BACKGROUND CONTEXT: Adolescent idiopathic scoliosis (AIS) necessitates accurate spinal curvature assessment for effective clinical management. Traditional two-dimensional (2D) Cobb angle measurements have been the standard, but the emergence of three-dimensional (3D) automatic measurement techniques, such as those using weight-bearing 3D imaging (WR3D), presents an opportunity to enhance the accuracy and comprehensiveness of AIS evaluation. PURPOSE: This study aimed to compare traditional 2D Cobb angle measurements with 3D automatic measurements utilizing the WR3D imaging technique in patients with AIS. STUDY DESIGN/SETTING: A cohort of 53 AIS patients was recruited, encompassing 88 spinal curves, for comparative analysis. PATIENT SAMPLE: The patient sample consisted of 53 individuals diagnosed with AIS. OUTCOME MEASURES: Cobb angles were calculated using the conventional 2D method and three different 3D methods: the Analytical Method (AM), the Plane Intersecting Method (PIM), and the Plane Projection Method (PPM). METHODS: The 2D cobb angle was manually measured by 3 experienced clinicians with 2D frontal whole-spine radiographs. For 3D cobb angle measurements, the spine and femoral heads were segmented from the WR3D images using a 3D-UNet deep-learning model, and the automatic calculations of the angles were performed with the 3D slicer software. RESULTS: AM and PIM estimates were found to be significantly larger than 2D measurements. Conversely, PPM results showed no statistical difference compared to the 2D method. These findings were consistent in a subgroup analysis based on 2D Cobb angles. CONCLUSION: Each 3D measurement method provides a unique assessment of spinal curvature, with PPM offering values closely resembling 2D measurements, while AM and PIM yield larger estimations. The utilization of WR3D technology alongside deep learning segmentation ensures accuracy and efficiency in comparative analyses. However, additional studies, particularly involving patients with severe curves, are required to validate and expand on these results. This study emphasizes the importance of selecting an appropriate measurement method considering the imaging modality and clinical context when assessing AIS, and it also underlines the need for continuous refinement of these techniques for optimal use in clinical decision-making and patient management.

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.

This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in computed tomography (CT) for hepatic lesion detection. A total of 40 patients with 98 clinically confirmed hepatic lesions were retrospectively included. The mean volume CT dose index was 13.66 ± 1.73 mGy in routine-dose portal venous CT examinations, where the images were originally obtained with hybrid iterative reconstruction (HIR). Low-dose simulations were performed in projection domain for 40%-, 20%-, and 10%-dose levels, followed by reconstruction using both HIR and AIIR. Two radiologists were asked to detect hepatic lesion on each set of low-dose image in separate sessions. Qualitative metrics including lesion conspicuity, diagnostic confidence, and overall image quality were evaluated using a 5-point scale. The contrast-to-noise ratio (CNR) for lesion was also calculated for quantitative assessment. The lesion CNR on AIIR at reduced doses were significantly higher than that on routine-dose HIR (all p < 0.05). Lower qualitative image quality was observed as the radiation dose reduced, while there were no significant differences between 40%-dose AIIR and routine-dose HIR images. The lesion detection rate was 100%, 98% (96/98), and 73.5% (72/98) on 40%-, 20%-, and 10%-dose AIIR, respectively, whereas it was 98% (96/98), 73.5% (72/98), and 40% (39/98) on the corresponding low-dose HIR, respectively. AIIR outperformed HIR in simulated low-dose CT examinations of the liver. The use of AIIR allows up to 60% dose reduction for lesion detection while maintaining comparable image quality to routine-dose HIR.

A comprehensive multi-omics analysis identifies a robust scoring system for cancer-associated fibroblasts and intervention targets in colorectal cancer.

BACKGROUND: Cancer-associated fibroblasts (CAF) play a critical role in promoting tumor growth, metastasis, and immune evasion. While numerous studies have investigated CAF, there remains a paucity of research on their clinical application in colorectal cancer (CRC). METHODS: In this study, we collected differentially expressed genes between CAF and normal fibroblasts (NF) from previous CRC studies, and utilized machine learning analysis to differentiate two distinct subtypes of CAF in CRC. To enable practical application, a CAF-related genes (CAFGs) scoring system was developed based on multivariate Cox regression. We then conducted functional enrichment analysis, Kaplan-Meier plot, consensus molecular subtypes (CMS) classification, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to investigate the relationship between the CAFGs scoring system and various biological mechanisms, prognostic value, tumor microenvironment, and response to immune checkpoint blockade (ICB) therapy. Moreover, single-cell transcriptomics and proteomics analyses have been employed to validate the significance of scoring system-related molecules in the identity and function of CAF. RESULTS: We unveiled significant distinctions in tumor immune status and prognosis not only between the CAF clusters, but also across high and low CAFGs groups. Specifically, patients in CAF cluster 2 or with high CAFGs scores exhibited higher CAF markers and were enriched for CAF-related biological pathways such as epithelial-mesenchymal transition (EMT) and angiogenesis. In addition, CAFGs score was identified as a risk index and correlated with poor overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and recurrence-free survival (RFS). High CAFGs scores were observed in patients with advanced stages, CMS4, as well as lymphatic invasion. Furthermore, elevated CAFG scores in patients signified a suppressive tumor microenvironment characterized by the upregulation of programmed death-ligand 1 (PD-L1), T-cell dysfunction, exclusion, and TIDE score. And high CAFGs scores can differentiate patients with lower response rates and poor prognosis under ICB therapy. Notably, single-cell transcriptomics and proteomics analyses identified several molecules related to CAF identity and function, such as FSTL1, IGFBP7, and FBN1. CONCLUSION: We constructed a robust CAFGs score system with clinical significance using multiple CRC cohorts. In addition, we identified several molecules related to CAF identity and function that could be potential intervention targets for CRC patients.

Safety of non-ionic contrast media in CT examinations for out-patients: retrospective multicenter analysis of 473,482 patients.

OBJECTIVES: This study aimed to explore the incidence of and potential risk factors for adverse drug reactions (ADRs) after non-ionic iodinated contrast media (NICM) administration for CT exams in out-patient settings in China. MATERIALS AND METHODS: A total of 473,482 out-patients who underwent intravenous NICM between January 1st, 2017, and Dec 31st, 2021, were retrospectively enrolled from three institutions. The occurrence of ADRs and clinical information were recorded. Chi-square test, Poisson regression, and logistic regression analyses were used to evaluate potential ADR risk factors and correlation with demographics, season, and NICM type. RESULTS: Among the 473,482 patients (mean age 55.22 ± 14.85; 253,499 male) who received intravenous NICM, the overall ADR incidence was 0.110% (522 of 473,482), with 0.099% acute-related drug reactions (469 of 473,482) and 0.0004% serious ADRs (two of 473,482). Iopromide was associated with a higher risk of acute ADRs. Late ADRs were more frequently observed with iodixanol 320. Multi-level logistic regression of patients with acute ADRs and a control group (matched 1:1 for age, gender, NICM, prescriber department, and institution) showed that summer (adjusted OR = 1.579; p = 0.035) and autumn (adjusted OR = 1.925; p < 0.001) were risk factors of acute ADRs. However, underlying disease and scanned body area were not related to a higher ADR incidence. CONCLUSION: The use of NICM for out-patients is in general safe with a low ADR incidence. The type of contrast medium (iopromide) and the seasons (summer and autumn) were associated with a higher risk of acute ADRs. Late ADRs were more often observed with iodixanol. CLINICAL RELEVANCE STATEMENT: In comparison to in-patients, out-patients may be exposed to higher risk due to a lack of extensive risk screening, less nursing care, and higher throughput pressure. Safety data about NICM from a large population may complement guidelines and avoid ambiguity. KEY POINTS: • The incidence and risk factors for adverse events after using non-ionic iodinated contrast media are complex in out-patients. • Non-ionic iodinated contrast media are safe for out-patients and the overall incidence of adverse drug reactions was 0.110%. • There is a higher risk of acute adverse drug reactions in summer and autumn.

Deep Learning Image Reconstruction for Transcatheter Aortic Valve Implantation Planning: Image Quality, Diagnostic Performance, Contrast volume and Radiation Dose Assessment.

RATIONALE AND OBJECTIVES: To assess image quality, contrast volume and radiation dose reduction potential and diagnostic performance with the use of high-strength deep learning image reconstruction (DLIR-H) in transcatheter aortic valve implantation (TAVI) planning CT. METHODS: We prospectively enrolled 128 patients referred to TAVI-planning CT. Patients were randomly divided into two groups: DLIR-H group (n = 64) and conventional group (n = 64). The DLIR-H group was scanned with tube voltage of 80kVp and body weighted-dependent contrast injection rate of 28mgI/kg/s, images reconstructed using DLIR-H; the conventional group was scanned with 100kVp and contrast injection rate of 40mgI/kg/s, and images reconstructed using adaptive statistical iterative reconstruction-V at 50% (ASIR-V 50%). Radiation dose, contrast volume, contrast injection rate, and image quality were compared between the two groups. The diagnostic performance of TAVI planning CT for coronary stenosis in 115 patients were calculated using invasive coronary angiography as golden standard. RESULTS: DLIR-H group significantly reduced radiation dose (4.94 ± 0.39mSv vs. 7.93 ± 1.20mSv, p < 0.001), contrast dose (45.28 ± 5.38 mL vs. 63.26 ± 9.88 mL, p < 0.001), and contrast injection rate (3.1 ± 0.31 mL/s vs. 4.9 ± 0.2 mL/s, p < 0.001) compared to the conventional group. Images in DLIR-H group had significantly higher SNR and CNR (all p < 0.001). For the diagnostic performance on a per-patient basis, TAVI planning CT in the DLIR-H group provided 100% sensitivity, 92.1% specificity, 100% negative predictive value (NPV), and 84.2% positive predictive value for the detection of > 50% stenosis. In the conventional group, the corresponding results were 94.7%, 95.3%, 97.6%, and 90.0%, respectively. CONCLUSION: DLIR-H in TAVI-planning CT provides improved image quality with reduced radiation and contrast doses, and enables satisfactory diagnostic performance for coronary arteries stenosis.

Healthcare facilities management: A novel data-driven model for predictive maintenance of computed tomography equipment.

BACKGROUND: The breakdown of healthcare facilities is a huge challenge for hospitals. Medical images obtained by Computed Tomography (CT) provide information about the patients' physical conditions and play a critical role in diagnosis of disease. To deliver high-quality medical images on time, it is essential to minimize the occurrence frequencies of anomalies and failures of the equipment. METHODS: We extracted the real-time CT equipment status time series data such as oil temperature, of three equipment, between May 19, 2020, and May 19, 2021. Tube arcing is treated as the classification label. We propose a dictionary-based data-driven model SAX-HCBOP, where the two methods, Histogram-based Information Gain Binning (HIGB) and Coefficient improved Bag of Pattern (CoBOP), are implemented to transform the data into the bag-of-words paradigm. We compare our model to the existing predictive maintenance models based on statistical and time series classification algorithms. RESULTS: The results show that the Accuracy, Recall, Precision and F1-score of the proposed model achieve 0.904, 0.747, 0.417, 0.535, respectively. The oil temperature is identified as the most important feature. The proposed model is superior to other models in predicting CT equipment anomalies. In addition, experiments on the public dataset also demonstrate the effectiveness of the proposed model. CONCLUSIONS: The two proposed methods can improve the performance of the dictionary-based time series classification methods in predictive maintenance. In addition, based on the proposed real-time anomaly prediction system, the model assists hospitals in making accurate healthcare facilities maintenance decisions.

Generation of human induced pluripotent stem cell lines from five patients with Myofibrillar myopathy carrying different heterozygous mutations in the DES gene.

Myofibrillar myopathy (MFM) is a rare genetic disorder characterized by muscular dystrophy that is often associated with cardiac disease. This disease is caused by mutations in several genes, among them DES (encoding desmin) is the most frequently affected. Peripheral blood mononuclear cells from 5 different MFM patients with different DES mutations were reprogrammed into induced pluripotent stem cells (IPSC) using non-integrative vectors. For each patient, one IPSC clone was selected and demonstrated pluripotency hallmarks without genomic abnormalities. SNP profiles were identical to the cells of origin and all the clones have the capacity to differentiate into all three germ layers.

Imaging-based deep learning in kidney diseases: recent progress and future prospects.

Kidney diseases result from various causes, which can generally be divided into neoplastic and non-neoplastic diseases. Deep learning based on medical imaging is an established methodology for further data mining and an evolving field of expertise, which provides the possibility for precise management of kidney diseases. Recently, imaging-based deep learning has been widely applied to many clinical scenarios of kidney diseases including organ segmentation, lesion detection, differential diagnosis, surgical planning, and prognosis prediction, which can provide support for disease diagnosis and management. In this review, we will introduce the basic methodology of imaging-based deep learning and its recent clinical applications in neoplastic and non-neoplastic kidney diseases. Additionally, we further discuss its current challenges and future prospects and conclude that achieving data balance, addressing heterogeneity, and managing data size remain challenges for imaging-based deep learning. Meanwhile, the interpretability of algorithms, ethical risks, and barriers of bias assessment are also issues that require consideration in future development. We hope to provide urologists, nephrologists, and radiologists with clear ideas about imaging-based deep learning and reveal its great potential in clinical practice.Critical relevance statement The wide clinical applications of imaging-based deep learning in kidney diseases can help doctors to diagnose, treat, and manage patients with neoplastic or non-neoplastic renal diseases.Key points• Imaging-based deep learning is widely applied to neoplastic and non-neoplastic renal diseases.• Imaging-based deep learning improves the accuracy of the delineation, diagnosis, and evaluation of kidney diseases.• The small dataset, various lesion sizes, and so on are still challenges for deep learning.

Multimodality magnetic resonance evaluating the effect of enhanced physical exercise on the growth rate, flow haemodynamics, aneurysm wall and ventricular-aortic coupling of patients with small abdominal aortic aneurysms (AAA MOVE trial): a study protocol for an open-label randomised controlled trial.

INTRODUCTION: The best lifestyle for small abdominal aortic aneurysms (sAAA) is essential for its conservative management. Physical exercise can improve the cardiopulmonary function of the patients, but it remains unclear which specific type of exercise is most beneficial for individuals with sAAA. The current study was designed to investigate the effect of physician-guided enhanced physical exercise programme on the aorto-cardiac haemodynamic environment, aneurysm sac wall, cardiac function and growth rate of sAAA by multimodality MRI. METHODS AND ANALYSIS: AAA MOVE study is a prospective, parallel, equivalence, randomised controlled trial. Eligible individuals will be recruited if they are diagnosed with sAAA (focal dilation of abdominal aorta with maximum diameter <5 cm), without contraindication for MRI scanning, or severe heart failure, or uncontrolled arrhythmia. Participants will be randomly allocated to intervention group (physician-guided enhanced physical exercise programme: mainly aerobic training) and control group (standard clinical care) separately in a 1:1 ratio. The primary outcome is 12-month growth rate of sAAA. The first set of secondary outcomes involve multimodality MRI parameters covering flow haemodynamics, aortic wall inflammation and cardiac function. The other secondary outcome (safety end point) is a composite of exercise-related injury, aneurysm rupture and aneurysm intervention. Follow-up will be conducted at 6 and 12 months after intervention. ETHICS AND DISSEMINATION: This study was approved by the Ethics Committee on Biomedical Research of West China Hospital (approval number: 2023-783) on 16 June 2023. Main findings from the trial will be disseminated through presentations at conferences, peer-reviewed publications and directly pushed to smartphone of participants. TRIAL REGISTRATION NUMBER: ChiCTR2300073334.

Critical contribution of mitochondria in the development of cardiomyopathy linked to desmin mutation.

BACKGROUND: Beyond the observed alterations in cellular structure and mitochondria, the mechanisms linking rare genetic mutations to the development of heart failure in patients affected by desmin mutations remain unclear due in part, to the lack of relevant human cardiomyocyte models. METHODS: To shed light on the role of mitochondria in these mechanisms, we investigated cardiomyocytes derived from human induced pluripotent stem cells carrying the heterozygous DESE439K mutation that were either isolated from a patient or generated by gene editing. To increase physiological relevance, cardiomyocytes were either cultured on an anisotropic micropatterned surface to obtain elongated and aligned cardiomyocytes, or as a cardiac spheroid to create a micro-tissue. Moreover, when applicable, results from cardiomyocytes were confirmed with heart biopsies of suddenly died patient of the same family harboring DESE439K mutation, and post-mortem heart samples from five control healthy donors. RESULTS: The heterozygous DESE439K mutation leads to dramatic changes in the overall cytoarchitecture of cardiomyocytes, including cell size and morphology. Most importantly, mutant cardiomyocytes display altered mitochondrial architecture, mitochondrial respiratory capacity and metabolic activity reminiscent of defects observed in patient's heart tissue. Finally, to challenge the pathological mechanism, we transferred normal mitochondria inside the mutant cardiomyocytes and demonstrated that this treatment was able to restore mitochondrial and contractile functions of cardiomyocytes. CONCLUSIONS: This work highlights the deleterious effects of DESE439K mutation, demonstrates the crucial role of mitochondrial abnormalities in the pathophysiology of desmin-related cardiomyopathy, and opens up new potential therapeutic perspectives for this disease.

Clinical Applications and Recent Updates of Simultaneous Multi-slice Technique in Accelerated MRI.

Simultaneous multi-slice (SMS) is a magnetic resonance imaging (MRI) acceleration technique that utilizes multi-band radio-frequency pulses to simultaneously excite and encode multiple slices. Currently, SMS has been widely studied and applied in the MRI examination to reduce acquisition time, which can significantly improve the examination efficiency and patient throughput. Moreover, SMS technique can improve spatial resolution, which is of great value in disease diagnosis, treatment response monitoring, and prognosis prediction. This review will briefly introduce the technical principles of SMS, and summarize its current clinical applications. More importantly, we will discuss the recent technical progress and future research direction of SMS, hoping to highlight the clinical value and scientific potential of this technique.

Choroid plexus volume enlargement in first-episode antipsychotic-naïve schizophrenia.

Investigation of the choroid plexus in schizophrenia has seen growing interest due to its role in the interaction between neuroinflammation and brain dysfunction. Most previous studies included treated and long-term ill patients, while antipsychotics and illness course might both affect the choroid plexus. Here, we recruited first-episode antipsychotic-naïve schizophrenia patients, performed high-resolution structural brain scan and manually extracted choroid plexus volume. Choroid plexus volume was compared between patients and healthy controls after controlling for age, sex and intracranial volume. Age and sex effects were examined on choroid plexus volume in patient and healthy control groups respectively. In patients, we also examined the correlation of choroid plexus volume with volume measures of cortical and subcortical gray matter, white matter, lateral ventricular as well as symptom severity and cognitive function. Schizophrenia patients showed significantly enlarged choroid plexus volume compared with healthy controls. Choroid plexus volume was positively correlated with age in only patient group and we found significantly larger choroid plexus volumes in males than females in both patient and healthy control groups, while the sex effects did not differ between groups. Choroid plexus volume was only found correlated with lateral ventricular volume among the brain volume measures. No significant correlation between choroid plexus volume and clinical ratings or cognitive performance was observed. Without potential confounding effects of pharmacotherapy or illness course, our findings indicated the enlargement of choroid plexus in schizophrenia might be an enduring trait for schizophrenia.

Early left ventricular microvascular dysfunction in diabetic pigs: a longitudinal quantitative myocardial perfusion CMR study.

BACKGROUND: Microvascular pathology is one of the main characteristics of diabetic cardiomyopathy; however, the early longitudinal course of diabetic microvascular dysfunction remains uncertain. This study aimed to investigate the early dynamic changes in left ventricular (LV) microvascular function in diabetic pig model using the cardiac magnetic resonance (CMR)-derived quantitative perfusion technique. METHODS: Twelve pigs with streptozotocin-induced diabetes mellitus (DM) were included in this study, and longitudinal CMR scanning was performed before and 2, 6, 10, and 16 months after diabetic modeling. CMR-derived semiquantitative parameters (upslope, maximal signal intensity, perfusion index, and myocardial perfusion reserve index [MPRI]) and fully quantitative perfusion parameters (myocardial blood flow [MBF] and myocardial perfusion reserve [MPR]) were analyzed to evaluate longitudinal changes in LV myocardial microvascular function. Pearson correlation was used to analyze the relationship between LV structure and function and myocardial perfusion function. RESULTS: With the progression of DM duration, the upslope at rest showed a gradually increasing trend (P = 0.029); however, the upslope at stress and MBF did not change significantly (P > 0.05). Regarding perfusion reserve function, both MPRI and MPR showed a decreasing trend with the progression of disease duration (MPRI, P = 0.001; MPR, P = 0.042), with high consistency (r = 0.551, P < 0.001). Furthermore, LV MPR is moderately associated with LV longitudinal strain (r = - 0.353, P = 0.022), LV remodeling index (r = - 0.312, P = 0.033), fasting blood glucose (r = - 0.313, P = 0.043), and HbA1c (r = - 0.309, P = 0.046). Microscopically, pathological results showed that collagen volume fraction increased gradually, whereas no significant decrease in microvascular density was observed with the progression of DM duration. CONCLUSIONS: Myocardial microvascular reserve function decreased gradually in the early stage of DM, which is related to both structural (but not reduced microvascular density) and functional abnormalities of microvessels, and is associated with increased blood glucose, reduced LV deformation, and myocardial remodeling.

Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing.

OBJECTIVES: To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus. METHODS: Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus. Apparent signal-to-noise ratios (aSNRs), apparent contrast-to-noise ratios (aCNRs), and qualitative scores on a 4-point scale were evaluated and compared by ANOVA and the Friedman test. Interobserver agreement was evaluated by calculating the intraclass correlation coefficients. RESULTS: DLCS4x achieved higher aSNR and aCNR than SENSE4x, CS4x, and DLCS8x (all p < 0.05). For the root segment of the brachial plexus, no statistically significant differences in the qualitative scores were found among the four sequences. For the trunk segment, DLCS4x had higher scores than SENSE4x (p = 0.04) in the contrast-enhanced group and had higher scores than SENSE4x and DLCS8x in the unenhanced group (all p < 0.05). For the divisions, cords, and branches, DLCS4x had higher scores than SENSE4x, CS4x, and DLCS8x (all p ≤ 0.01). No overt difference was found among SENSE4x, CS4x, and DLCS8x in any segment of the brachial plexus (all p > 0.05). CONCLUSIONS: In three-dimensional MRI for the brachial plexus, DLCS4x can improve image quality compared with SENSE4x and CS4x, and DLCS8x can maintain the image quality compared to SENSE4x and CS4x. CLINICAL RELEVANCE STATEMENT: Deep learning-constrained compressed sensing can improve the image quality or accelerate acquisition of 3D MRI of the brachial plexus, which should be benefit in evaluating the brachial plexus and its branches in clinical practice. KEY POINTS: •Deep learning-constrained compressed sensing showed higher aSNR, aCNR, and qualitative scores for the brachial plexus than SENSE and CS at the same acceleration factor with similar scanning time. •Deep learning-constrained compressed sensing at acceleration factor of 8 had comparable aSNR, aCNR, and qualitative scores to SENSE4x and CS4x with approximately half the examination time. •Deep learning-constrained compressed sensing may be helpful in clinical practice for improving image quality and acquisition time in three-dimensional MRI of the brachial plexus.

hsa_circ_0002980 prevents proliferation, migration, invasion, and epithelial-mesenchymal transition of liver cancer cells through microRNA-1303/cell adhesion molecule 2 axis.

BACKGROUND: Liver cancer (LC) is a rare malignancy. Circular RNA (circRNA) dysregulation is associated with LC metastasis. hsa_circ_0002980 was found to be unexpectedly downregulated in LC tissues; however, its specific function remains unclear. METHODS: hsa_circ_0002980 expression was confirmed using RT-qPCR. The effects of circ_0002980 on the proliferation, metastasis, and EMT-related proteins of LC cells were assessed using clone formation, flow cytometry, Transwell assays, and Western blotting. The relationship between circ_0002980 and miR-1303 or miR-1303 and CADM2 was analyzed using a dual-luciferase reporter assay. Thereafter, the influence of these three genes on LC cell progression was determined through rescue experiments. RESULTS: hsa_circ_0002980 expression was lower in LC. circ_0002980 overexpression inhibited the proliferation, migration, invasion, and EMT of LC cells. In addition, circ_0002980 specifically binds to miR-1303, and the accelerated effect of miR-1303 overexpression on LC progression was partially reversed by circ_0002980. Moreover, miR-1303 can also target CADM2, and CADM2-mediated prevention can also be attenuated by miR-1303 overexpression. CONCLUSIONS: In LC cells, circ_0002980 upregulation prevents cell proliferation, metastasis, and EMT by affecting the miR-1303/CADM2 axis. Therefore, this axis may be a novel therapeutic target in LC.

Deep Learning-Based Motion Correction in Projection Domain for Coronary Computed Tomography Angiography: A Clinical Evaluation.

OBJECTIVE: This study aimed to evaluate the clinical performance of a deep learning-based motion correction algorithm (MCA) in projection domain for coronary computed tomography angiography (CCTA). METHODS: A total of 192 patients who underwent CCTA examinations were included and divided into 2 groups based on the average heart rate (HR): group 1, 82 patients with HR of <75 beats per minute; group 2, 110 patients with HR of ≥75 beats per minute. The CCTA images were reconstructed with and without MCA. The subjective image quality was graded in terms of vessel visualization, sharpness, diagnostic confidence, and overall image quality using a 5-point scale, where cases with all scores of ≥3 were deemed interpretable. Objective image quality was measured through signal-to-noise ratio and contrast-to-noise ratio in regions relative to the vessels. The image quality scores for 2 reconstructions and effective dose between 2 groups were compared. RESULTS: The mean effective dose was similar between 2 groups. Neither group showed significant difference on objective image quality for 2 reconstructions. Images reconstructed with and without MCA were both found interpretable for group 1, whereas the subjective image quality was significantly improved by the MCA for all 4 metrics in group 2, with the interpretability increased from 80.91% to 99.09%. Compared with group 1, group 2 showed similar interpretability and diagnostic confidence, despite inferior overall image quality. CONCLUSIONS: In CCTA examinations, the deep learning-based MCA is capable of improving the image quality and diagnostic confidence for patients with increased HR to a similar level as for those with low HR.

Generation of induced pluripotent stem cell line (TMOi001-A-11) carrying a homozygous deletion in the synemin gene using CRISPR/Cas9.

A number of genetic variants in the SYNM gene encoding for the intermediate filament synemin have been reported in patients with cardiomyopathies, skeletal myopathies, cancer and certain neurodegenerative disorders. To better understand its role, we generated a human induced pluripotent stem cell line with a homozygous deletion in the SYNM gene by CRISPR/Cas9 genome editing. The synemin-knockout human induced pluripotent stem cells exhibit typical morphology of pluripotent cells, expression of pluripotency markers, normal karyotype and differentiation capacity in the three germ layers. This line will allow us to investigate the role of synemin in cardiomyopathy upon differentiation into beating cardiomyocytes.