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Background: Vessel diameter is the principal imaging parameter assessed clinically for aortic disease, but adverse events can occur at normal diameters. Aortic stiffness has been studied as an additional imaging-based risk factor, and has been shown to be

Currently, there is no ideal noninvasive method to quantify the progressive loss of pancreatic β-cell mass (BCM) that occurs in type 1 diabetes. Magnetic resonance imaging has detected gross differences in BCM between healthy and diabetic mice using the contrast agent manganese, which labels functional β-cells and increases the water proton relaxation rate (R1), but its ability to measure gradations in BCM during disease progression is unknown. Our objective was to test the hypothesis that measurements of the manganese-enhanced pancreatic R1 could detect decreasing BCM in a mouse model of type 1 diabetes. We used cyclophosphamide-accelerated BDC2.5 T-cell receptor transgenic nonobese diabetic mice, which experience development of type 1 diabetes during a 7-day time period after cyclophosphamide injection, whereas transgene-negative mice do not. We measured the manganese-enhanced pancreatic R1 before cyclophosphamide injection (day 0) and on days 3, 4, 5, and 7 afterward. Pancreatic R1 remained constant in transgene-negative mice and decreased stepwise day-to-day in transgene-positive mice, mirroring their loss of BCM, confirmed by pancreatic insulin measurements and histology. Changes in R1 in transgene-positive mice occurred before elevations in blood glucose, a clinical indicator of diabetes, suggesting potential for early noninvasive detection of changes in functional BCM. [ABSTRACT FROM AUTHOR]

Preeclampsia is a serious complication during pregnancy that includes potentially life-threatening risks to the mother and fetus. It may be challenging to distinguish this from other causes of rapidly escalating hypertension, especially in women with end-stage renal disease, because current diagnostic criteria for preeclampsia cannot be easily applied. We report a woman undergoing hemodialysis who was considered to be preeclamptic when her blood pressure suddenly increased during her 29th week of gestation. At that time, she underwent emergent cesarean section. The presence of a normal-sized placenta with no histological evidence of preeclampsia and retrospective analyses of maternal antiangiogenic biomarkers (soluble fms-like tyrosine kinase-1 and soluble endoglin) that were within normal levels for pregnancy suggest an alternative diagnosis. There is growing evidence that circulating levels of these proteins cause the preeclamptic phenotypes and also are sensitive and specific predictors and markers of this disease, suggesting that measurements of soluble fms-like tyrosine kinase-1 and soluble endoglin be considered in such difficult diagnostic dilemmas as the cause of hypertension in pregnant dialysis patients. Additional studies in this particular group of patients are required. [ABSTRACT FROM AUTHOR]

BACKGROUND: Quantitative noninvasive imaging of myocardial mechanics in mice enables studies of the roles of individual genes in cardiac function. We sought to develop comprehensive three-dimensional methods for imaging myocardial mechanics in mice. METHODS: A 3D cine DENSE pulse sequence was implemented on a 7T small-bore scanner. The sequence used three-point phase cycling for artifact suppression and a stack-of-spirals k-space trajectory for efficient data acquisition. A semi-automatic 2D method was adapted for 3D image segmentation, and automated 3D methods to calculate strain, twist, and torsion were employed. A scan protocol that covered the majority of the left ventricle in a scan time of less than 25 minutes was developed, and seven healthy C57Bl/6 mice were studied. RESULTS: Using these methods, multiphase normal and shear strains were measured, as were myocardial twist and torsion. Peak end-systolic values for the normal strains at the mid-ventricular level were 0.29 +/- 0.17, -0.13 +/- 0.03, and -0.18 +/- 0.14 for Err, Ecc, and Ell, respectively. Peak end-systolic values for the shear strains were 0.00 +/- 0.08, 0.04 +/- 0.12, and 0.03 +/- 0.07 for Erc, Erl, and Ecl, respectively. The peak end-systolic normalized torsion was 5.6 +/- 0.9 degrees. CONCLUSIONS: Using a 3D cine DENSE sequence tailored for cardiac imaging in mice at 7T, a comprehensive assessment of 3D myocardial mechanics can be achieved with a scan time of less than 25 minutes and an image analysis time of approximately 1 hour. [ABSTRACT FROM AUTHOR]

Background: Alterations in circulating soluble fms-like tyrosine kinase 1 (sFlt1), an antiangiogenic protein, and placental growth factor (PlGF), a proangiogenic protein, appear to be involved in the pathogenesis of preeclampsia. Since soluble endoglin, another antiangiogenic protein, acts together with sFlt1 to induce a severe preeclampsia-like syndrome in pregnant rats, we examined whether it is associated with preeclampsia in women. Methods: We performed a nested case-control study of healthy nulliparous women within the Calcium for Preeclampsia Prevention trial. The study included all 72 women who had preterm preeclampsia (<37 weeks), as well as 480 randomly selected women--120 women with preeclampsia at term (at > or =37 weeks), 120 women with gestational hypertension, 120 normotensive women who delivered infants who were small for gestational age, and 120 normotensive controls who delivered infants who were not small for gestational age. Results: Circulating soluble endoglin levels increased markedly beginning 2 to 3 months before the onset of preeclampsia. After the onset of clinical disease, the mean serum level in women with preterm preeclampsia was 46.4 ng per milliliter, as compared with 9.8 ng per milliliter in controls (P<0.001). The mean serum level in women with preeclampsia at term was 31.0 ng per milliliter, as compared with 13.3 ng per milliliter in controls (P<0.001). Beginning at 17 weeks through 20 weeks of gestation, soluble endoglin levels were significantly higher in women in whom preterm preeclampsia later developed than in controls (10.2 ng per milliliter vs. 5.8 ng per milliliter, P<0.001), and at 25 through 28 weeks of gestation, the levels were significantly higher in women in whom term preeclampsia developed than in controls (8.5 ng per milliliter vs. 5.9 ng per milliliter, P<0.001). An increased level of soluble endoglin was usually accompanied by an increased ratio of sFlt1:PlGF. The risk of preeclampsia was greatest among women in the highest quartile of the control distributions for both biomarkers but not for either biomarker alone. Conclusions: Rising circulating levels of soluble endoglin and ratios of sFlt1:PlGF herald the onset of preeclampsia. [ABSTRACT FROM AUTHOR]

Background: The cause of preeclampsia remains unclear. Limited data suggest that excess circulating soluble fms-like tyrosine kinase 1 (sFlt-1), which binds placental growth factor (PlGF) and vascular endothelial growth factor (VEGF), may have a pathogenic role. Methods: We performed a nested case-control study within the Calcium for Preeclampsia Prevention trial, which involved healthy nulliparous women. Each woman with preeclampsia was matched to one normotensive control. A total of 120 pairs of women were randomly chosen. Serum concentrations of angiogenic factors (total sFlt-1, free PlGF, and free VEGF) were measured throughout pregnancy; there were a total of 655 serum specimens. The data were analyzed cross-sectionally within intervals of gestational age and according to the time before the onset of preeclampsia. Results: During the last two months of pregnancy in the normotensive controls, the level of sFlt-1 increased and the level of PlGF decreased. These changes occurred earlier and were more pronounced in the women in whom preeclampsia later developed. The sFlt-1 level increased beginning approximately five weeks before the onset of preeclampsia. At the onset of clinical disease, the mean serum level in the women with preeclampsia was 4382 pg per milliliter, as compared with 1643 pg per milliliter in controls with fetuses of similar gestational age (P<0.001). The PlGF levels were significantly lower in the women who later had preeclampsia than in the controls beginning at 13 to 16 weeks of gestation (mean, 90 pg per milliliter vs. 142 pg per milliliter, P=0.01), with the greatest difference occurring during the weeks before the onset of preeclampsia, coincident with the increase in the sFlt-1 level. Alterations in the levels of sFlt-1 and free PlGF were greater in women with an earlier onset of preeclampsia and in women in whom preeclampsia was associated with a small-for-gestational-age infant. Conclusions: Increased levels of sFlt-1 and reduced levels of PlGF predict the subsequent development of preeclampsia. [ABSTRACT FROM AUTHOR]

Cardiac resynchronization therapy (CRT) can lead to marked symptom reduction and improved survival in selected patients with heart failure with reduced ejection fraction (HFrEF); however, many candidates for CRT based on clinical guidelines do not have a favorable response. A better way to identify patients expected to benefit from CRT that applies machine learning to accessible and cost-effective diagnostic tools such as the 12-lead electrocardiogram (ECG) could have a major impact on clinical care in HFrEF by helping providers personalize treatment strategies and avoid delays in initiation of other potentially beneficial treatments. This study addresses this need by demonstrating that a novel approach to ECG waveform analysis using functional principal component decomposition (FPCD) performs better than measures that require manual ECG analysis with the human eye and also at least as well as a previously validated but more expensive approach based on cardiac magnetic resonance (CMR). Analyses are based on five-fold cross validation of areas under the curve (AUCs) for CRT response and survival time after the CRT implant using Cox proportional hazards regression with stratification of groups using a Gaussian mixture model approach. Furthermore, FPCD and CMR predictors are shown to be independent, which demonstrates that the FPCD electrical findings and the CMR mechanical findings together provide a synergistic model for response and survival after CRT. In summary, this study provides a highly effective approach to prognostication after CRT in HFrEF using an accessible and inexpensive diagnostic test with a major expected impact on personalization of therapies., Competing Interests: Declaration of competing interest Dr. Bilchick has research grant support from Medtronic and Siemens Healthineers. Dr. Mangrum has research grant support from Boston Scientific, CardioFocus, and St. Jude Medical. Dr. Epstein has research grant support from Siemens Healthineers. Dr. Patel has a research grant from GE Healthcare and research support from Circle CVI and Neosoft., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence (AI) technology have shown great potential to address many CMR limitations. While the developments are remarkable, translation of AI-based methods into real-world CMR clinical practice remains at a nascent stage and much work lies ahead to realize the full potential of AI for CMR., Methods: Herein we review recent cutting-edge and representative examples demonstrating how AI can advance CMR in areas such as exam planning, accelerated image reconstruction, post-processing, quality control, classification and diagnosis., Results: These advances can be applied to speed up and simplify essentially every application including cine, strain, late gadolinium enhancement, parametric mapping, 3D whole heart, flow, perfusion and others. AI is a unique technology based on training models using data. Beyond reviewing the literature, this paper discusses important AI-specific issues in the context of CMR, including (1) properties and characteristics of datasets for training and validation, (2) previously published guidelines for reporting CMR AI research, (3) considerations around clinical deployment, (4) responsibilities of clinicians and the need for multi-disciplinary teams in the development and deployment of AI in CMR, (5) industry considerations, and (6) regulatory perspectives., Conclusions: Understanding and consideration of all these factors will contribute to the effective and ethical deployment of AI to improve clinical CMR., Competing Interests: Declaration of competing interests Qiang Zhang reports a relationship with British Heart Foundation that includes funding grants. Qiang Zhang has patent #Enhancement of Medical Images (WO/2021/044153) pending to Oxford University Innovation. Qiang Zhang has patent #Validation of quantitative magnetic resonance imaging protocols (WO2020234570A1) pending to Oxford University Innovation. Mariya Doneva is an employee of Philips GmbH Innovative Technologies, Hamburg, Germany. Mariya Doneva is an editorial board member of Magnetic Resonance Medicine and IEEE Transactions on Computational Imaging. Jens Wetzl is an employee and shareholder of Siemens Healthineers AG. DPO’R has consulted for Bayer and BMS on AI, holds a research grant from Bayer, and holds relevant patents. Claudia Prieto is an Associate Editor for Magnetic Resonance in Medicine and was not involved in the editorial review or the decision to publish this article. Frederick H. Epstein has research support from Siemens. Frederick H. Epstein is an editorial board member of JCMR and was not involved in the editorial review or the decision to publish this article. Frederick H. Epstein holds relevants patents. Sona Ghadimi holds relevant patents. Yu Wang holds relevant patents. The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Heart failure with preserved ejection fraction (HFpEF) is a complex disease process influenced by metabolic disorders, systemic inflammation, myocardial fibrosis, and microvascular dysfunction. The goal of our study is to identify potential relationships between plasma biomarkers and cardiac magnetic resonance (CMR) imaging markers in patients with HFpEF., Methods: Nineteen subjects with HFpEF and 15 age-matched healthy controls were enrolled and underwent multiparametric CMR and plasma biomarker analysis using the Olink® Cardiometabolic Panel (Olink Proteomics, Uppsala, Sweden). Partial least squares discriminant analysis (PLS-DA) was used to characterize CMR and biomarker variables that differentiate the subject groups into two principal components. Orthogonal projection to latent structures by partial least squares (OPLS) analysis was used to identify biomarker patterns that correlate with myocardial perfusion reserve (MPR) and extracellular volume (ECV) mapping., Results: A PLS-DA could differentiate between HFpEF and normal controls with two significant components explaining 79% (Q2 = 0.47) of the differences. For OPLS, there were 7 biomarkers that significantly correlated with ECV (R2 = 0.85, Q = 0.53) and 6 biomarkers that significantly correlated with MPR (R2 = 0.92, Q2 = 0.32). Only 1 biomarker significantly correlated with both ECV and MPR., Discussion: Patients with HFpEF have unique imaging and biomarker patterns that suggest mechanisms associated with metabolic disease, inflammation, fibrosis and microvascular dysfunction., Competing Interests: LG is an employee of Ribo Life Science. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Siggins, Pan, Löffler, Yang, Shaw, Balfour, Epstein, Gan, Kramer, Keeley and Salerno.)