Search

We present multiwavelength data of SN 2020acct, a double-peaked stripped-envelope supernova (SN) in NGC 2981 at ∼150 Mpc. The two peaks are temporally distinct, with maxima separated by 58 rest-frame days and a factor of 20 reduction in flux between. The first is luminous ( M _r = −18.00 ± 0.02 mag) and blue ( g − r = 0.27 ± 0.03 mag) and displays spectroscopic signatures of interaction with hydrogen-free circumstellar material. The second peak is fainter ( M _r = −17.29 ± 0.03 mag) and has some spectroscopic similarities to an evolved stripped-envelope SN, with strong forbidden [Ca ii ] and [O ii ] features. No other known double-peaked SN exhibits a light curve similar to that of SN 2020acct. We find the likelihood of two individual SNe occurring in the same star-forming region within that time to be highly improbable, while an implausibly fine-tuned configuration would be required to produce two SNe from a single binary system. We find that the peculiar properties of SN 2020acct match models of pulsational pair instability (PPI), in which the initial peak is produced by collisions of shells of ejected material, shortly followed by core collapse. Pulsations from a star with a 72 M _⊙ helium core provide an excellent match to the double-peaked light curve. The local galactic environment has a metallicity of 0.4 Z _⊙ , a level where massive single stars are not expected to retain enough mass to encounter the PPI. However, late binary mergers or a low-metallicity pocket may allow the required core mass. We measure the rate of SN 2020acct–like events to be

We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω _M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q _0 < 0 in ΛCDM) with over 5 σ confidence. We find $({{\rm{\Omega }}}_{{\rm{M}}},w)=({0.264}_{-0.096}^{+0.074},-{0.80}_{-0.16}^{+0.14})$ in flat w CDM. For flat w _0 w _a CDM, we find $({{\rm{\Omega }}}_{{\rm{M}}},{w}_{0},{w}_{a})=({0.495}_{-0.043}^{+0.033},-{0.36}_{-0.30}^{+0.36},-{8.8}_{-4.5}^{+3.7})$ , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω _M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

We present a comprehensive analysis of the photometric and spectroscopic evolution of SN 2021foa, unique among the class of transitional supernovae for repeatedly changing its spectroscopic appearance from hydrogen-to-helium-to-hydrogen dominated (IIn-to-Ibn-to-IIn) within 50 days past peak brightness. The spectra exhibit multiple narrow (≈300–600 km s ^−1 ) absorption lines of hydrogen, helium, calcium, and iron together with broad helium emission lines with a full width at half-maximum (FWHM) of ∼6000 km s ^−1 . For a steady, wind mass-loss regime, light-curve modeling results in an ejecta mass of ∼8 M _⊙ and circumstellar material (CSM) mass below 1 M _⊙ , and an ejecta velocity consistent with the FWHM of the broad helium lines. We obtain a mass-loss rate of ≈2 M _⊙ yr ^−1 . This mass-loss rate is 3 orders of magnitude larger than derived for normal Type II supernovae. We estimate that the bulk of the CSM of SN 2021foa must have been expelled within half a year, about 12 yr ago. Our analysis suggests that SN 2021foa had a helium-rich ejecta that swept up a dense shell of hydrogen-rich CSM shortly after explosion. At about 60 days past peak brightness, the photosphere recedes through the dense ejecta-CSM region, occulting much of the redshifted emission of the hydrogen and helium lines, which results in an observed blueshift (∼−3000 km s ^−1 ). Strong mass-loss activity prior to explosion, such as those seen in SN 2009ip-like objects and SN 2021foa as precursor emission, are the likely origin of a complex, multiple-shell CSM close to the progenitor star.

We present the full Hubble diagram of photometrically classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7000 host galaxies. Based on the light-curve quality, we select 1635 photometrically identified SNe Ia with spectroscopic redshift 0.10 < z < 1.13, which is the largest sample of supernovae from any single survey and increases the number of known z > 0.5 supernovae by a factor of 5. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are ${\sigma }_{{{\rm{\Omega }}}_{M},\mathrm{stat}+\mathrm{sys}}^{{\rm{\Lambda }}\mathrm{CDM}}=$ 0.017 in a flat ΛCDM model, and $({\sigma }_{{{\rm{\Omega }}}_{M}},{\sigma }_{w}{)}_{\mathrm{stat}+\mathrm{sys}}^{w\mathrm{CDM}}$ = (0.082, 0.152) in a flat w CDM model. Combining the DES SN data with the highly complementary cosmic microwave background measurements by Planck Collaboration reduces by a factor of 4 uncertainties on cosmological parameters. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

We present Lightcurve Anomaly Identification and Similarity Search ( LAISS ), an automated pipeline to detect anomalous astrophysical transients in real-time data streams. We deploy our anomaly detection model on the nightly Zwicky Transient Facility (ZTF) Alert Stream via the ANTARES broker, identifying a manageable ∼1–5 candidates per night for expert vetting and coordinating follow-up observations. Our method leverages statistical light-curve and contextual host galaxy features within a random forest classifier, tagging transients of rare classes ( spectroscopic anomalies), of uncommon host galaxy environments ( contextual anomalies), and of peculiar or interaction-powered phenomena ( behavioral anomalies). Moreover, we demonstrate the power of a low-latency (∼ms) approximate similarity search method to find transient analogs with similar light-curve evolution and host galaxy environments. We use analogs for data-driven discovery, characterization, (re)classification, and imputation in retrospective and real-time searches. To date, we have identified ∼50 previously known and previously missed rare transients from real-time and retrospective searches, including but not limited to superluminous supernovae (SLSNe), tidal disruption events, SNe IIn, SNe IIb, SNe I-CSM, SNe Ia-91bg-like, SNe Ib, SNe Ic, SNe Ic-BL, and M31 novae. Lastly, we report the discovery of 325 total transients, all observed between 2018 and 2021 and absent from public catalogs (∼1% of all ZTF Astronomical Transient reports to the Transient Name Server through 2021). These methods enable a systematic approach to finding the “needle in the haystack” in large-volume data streams. Because of its integration with the ANTARES broker, LAISS is built to detect exciting transients in Rubin data.

We present UV–optical–near-infrared observations and modeling of supernova (SN) 2024ggi, a type II supernova (SN II) located in NGC 3621 at 7.2 Mpc. Early-time (“flash”) spectroscopy of SN 2024ggi within +0.8 days of discovery shows emission lines of H i , He i , C iii , and N iii with a narrow core and broad, symmetric wings (i.e., “IIn-like”) arising from the photoionized, optically thick, unshocked circumstellar material (CSM) that surrounded the progenitor star at shock breakout (SBO). By the next spectral epoch at +1.5 days, SN 2024ggi showed a rise in ionization as emission lines of He ii , C iv , N iv/v , and O v became visible. This phenomenon is temporally consistent with a blueward shift in the UV–optical colors, both likely the result of SBO in an extended, dense CSM. The IIn-like features in SN 2024ggi persist on a timescale of t _IIn = 3.8 ± 1.6 days, at which time a reduction in CSM density allows the detection of Doppler-broadened features from the fastest SN material. SN 2024ggi has peak UV–optical absolute magnitudes of M _w2 = −18.7 mag and M _g = −18.1 mag, respectively, that are consistent with the known population of CSM-interacting SNe II. Comparison of SN 2024ggi with a grid of radiation hydrodynamics and non–local thermodynamic equilibrium radiative-transfer simulations suggests a progenitor mass-loss rate of $\dot{M}={10}^{-2}\,{M}_{\odot }$ yr ^−1 ( v _w = 50 km s ^−1 ), confined to a distance of r < 5 × 10 ^14 cm. Assuming a wind velocity of v _w = 50 km s ^−1 , the progenitor star underwent an enhanced mass-loss episode in the last ∼3 yr before explosion.

We present ultraviolet/optical/near-infrared observations and modeling of Type II supernovae (SNe II) whose early time ( δ t < 2 days) spectra show transient, narrow emission lines from shock ionization of confined ( r < 10 ^15 cm) circumstellar material (CSM). The observed electron-scattering broadened line profiles (i.e., IIn-like) of H i , He i/ii , C iv , and N iii/iv/v from the CSM persist on a characteristic timescale ( t _IIn ) that marks a transition to a lower-density CSM and the emergence of Doppler-broadened features from the fast-moving SN ejecta. Our sample, the largest to date, consists of 39 SNe with early time IIn-like features in addition to 35 “comparison” SNe with no evidence of early time IIn-like features, all with ultraviolet observations. The total sample includes 50 unpublished objects with a total of 474 previously unpublished spectra and 50 multiband light curves, collected primarily through the Young Supernova Experiment and Global Supernova Project collaborations. For all sample objects, we find a significant correlation between peak ultraviolet brightness and both t _IIn and the rise time, as well as evidence for enhanced peak luminosities in SNe II with IIn-like features. We quantify mass-loss rates and CSM density for the sample through the matching of peak multiband absolute magnitudes, rise times, t _IIn , and optical SN spectra with a grid of radiation hydrodynamics and non-local thermodynamic equilibrium radiative-transfer simulations. For our grid of models, all with the same underlying explosion, there is a trend between the duration of the electron-scattering broadened line profiles and inferred mass-loss rate: ${t}_{\mathrm{IIn}}\approx 3.8[\dot{M}/$ (0.01 M _⊙ yr ^−1 )] days.

We present photometric and spectroscopic data for SN 2022joj, a nearby peculiar Type Ia supernova (SN Ia) with a fast decline rate (Δ m _15,B = 1.4 mag). SN 2022joj shows exceedingly red colors, with a value of approximately B − V ≈ 1.1 mag during its initial stages, beginning from 11 days before maximum brightness. As it evolves, the flux shifts toward the blue end of the spectrum, approaching B − V ≈ 0 mag around maximum light. Furthermore, at maximum light and beyond, the photometry is consistent with that of typical SNe Ia. This unusual behavior extends to its spectral characteristics, which initially displayed a red spectrum and later evolved to exhibit greater consistency with typical SNe Ia. Spectroscopically, we find strong agreement between SN 2022joj and double detonation models with white dwarf masses of around 1 M _⊙ and a thin He shell between 0.01 and 0.05 M _⊙ . Moreover, the early red colors are explained by line-blanketing absorption from iron peak elements created by the double detonation scenario in similar mass ranges. The nebular spectra in SN 2022joj deviate from expectations for double detonation, as we observe strong [Fe iii ] emission instead of [Ca ii ] lines as anticipated, though this is not as robust a prediction as early red colors and spectra. The fact that as He shells get thinner these SNe start to look more like normal SNe Ia raises the possibility that this is the triggering mechanism for the majority of SNe Ia, though evidence would be missed if the SNe are not observed early enough.

We present UV and/or optical observations and models of SN 2023ixf, a type II supernova (SN) located in Messier 101 at 6.9 Mpc. Early time ( flash ) spectroscopy of SN 2023ixf, obtained primarily at Lick Observatory, reveals emission lines of H i , He i/ii , C iv , and N iii/iv/v with a narrow core and broad, symmetric wings arising from the photoionization of dense, close-in circumstellar material (CSM) located around the progenitor star prior to shock breakout. These electron-scattering broadened line profiles persist for ∼8 days with respect to first light, at which time Doppler broadened the features from the fastest SN ejecta form, suggesting a reduction in CSM density at r ≳ 10 ^15 cm. The early time light curve of SN 2023ixf shows peak absolute magnitudes (e.g., M _u = −18.6 mag, M _g = −18.4 mag) that are ≳2 mag brighter than typical type II SNe, this photometric boost also being consistent with the shock power supplied from CSM interaction. Comparison of SN 2023ixf to a grid of light-curve and multiepoch spectral models from the non-LTE radiative transfer code CMFGEN and the radiation-hydrodynamics code HERACLES suggests dense, solar-metallicity CSM confined to r = (0.5–1) × 10 ^15 cm, and a progenitor mass-loss rate of $\dot{M}={10}^{-2}\,{M}_{\odot }$ yr ^−1 . For the assumed progenitor wind velocity of v _w = 50 km s ^−1 , this corresponds to enhanced mass loss (i.e., superwind phase) during the last ∼3–6 yr before explosion.

We present extensive optical photometry of the afterglow of GRB 221009A. Our data cover 0.9–59.9 days from the time of Swift and Fermi gamma-ray burst (GRB) detections. Photometry in rizy -band filters was collected primarily with Pan-STARRS and supplemented by multiple 1–4 m imaging facilities. We analyzed the Swift X-ray data of the afterglow and found a single decline rate power law f ( t ) ∝ t ^−1.556±0.002 best describes the light curve. In addition to the high foreground Milky Way dust extinction along this line of sight, the data favor additional extinction to consistently model the optical to X-ray flux with optically thin synchrotron emission. We fit the X-ray-derived power law to the optical light curve and find good agreement with the measured data up to 5−6 days. Thereafter we find a flux excess in the riy bands that peaks in the observer frame at ∼20 days. This excess shares similar light-curve profiles to the Type Ic broad-lined supernovae SN 2016jca and SN 2017iuk once corrected for the GRB redshift of z = 0.151 and arbitrarily scaled. This may be representative of an SN emerging from the declining afterglow. We measure rest-frame absolute peak AB magnitudes of M _g = −19.8 ± 0.6 and M _r = − 19.4 ± 0.3 and M _z = −20.1 ± 0.3. If this is an SN component, then Bayesian modeling of the excess flux would imply explosion parameters of ${M}_{\mathrm{ej}}={7.1}_{-1.7}^{+2.4}$ M _⊙ , ${M}_{\mathrm{Ni}}={1.0}_{-0.4}^{+0.6}$ M _⊙ , and ${v}_{\mathrm{ej}}={{\rm{33,900}}}_{-5700}^{+5900}$ km s ^−1 , for the ejecta mass, nickel mass, and ejecta velocity respectively, inferring an explosion energy of E _kin ≃ 2.6–9.0 × 10 ^52 erg.

The unknown cause of the correlation between Type Ia supernova (SN Ia) Hubble residuals and their host-galaxy masses (the “mass step”) may bias cosmological parameter measurements. To better understand the mass step, we develop a SALT3 light-curve model for SN cosmology that uses the host-galaxy masses of 296 low-redshift SNe Ia to derive a spectral energy distribution–host-galaxy mass relationship. The resulting model has larger Ca ii H and K, Ca ii near-infrared triplet, and Si ii equivalent widths for SNe in low-mass host galaxies at 2.2–2.7 σ significance; this indicates higher explosion energies per unit mass in low-mass-hosted SNe. The model has phase-dependent changes in SN Ia colors as a function of host mass, indicating intrinsic differences in mean broadband light curves. Although the model provides a better fit to the SN data overall, it does not substantially reduce data–model residuals for a typical light curve in our sample nor does it significantly reduce Hubble residual dispersion. This is because we find that previous SALT models parameterized most host-galaxy dependencies with their first principal component, although they failed to model some significant spectral variations. Our new model is luminosity and cosmology independent, and applying it to data reduces the mass step by 0.021 ± 0.002 mag (uncertainty accounts for correlated data sets); these results indicate that ∼35% of the mass step can be attributed to luminosity-independent effects. This SALT model version could be trained using alternative host-galaxy properties and at different redshifts, and therefore will be a tool for understanding redshift-dependent correlations between SNe Ia and their host properties as well as their impact on cosmological parameter measurements.

Type Ia supernovae (SNe Ia) are standardizable candles that must be modeled empirically to yield cosmological constraints. To understand the robustness of this modeling to variations in the model-training procedure, we build an end-to-end pipeline to test the recently developed SALT3 model. We explore the consequences of removing pre-2000s low- z or poorly calibrated U -band data, adjusting the amount and fidelity of SN Ia spectra, and using a model-independent framework to simulate the training data. We find that the SALT3 model surfaces are improved by having additional spectra and U -band data, and can be shifted by ∼5% if host-galaxy contamination is not sufficiently removed from SN spectra. We find that resulting measurements of w are consistent to within 2.5% for all of the training variants explored in this work, with the largest shifts coming from variants that add color-dependent calibration offsets or host-galaxy contamination to the training spectra and those that remove pre-2000s low- z data. These results demonstrate that the SALT3 model-training procedure is largely robust to reasonable variations in the training data, but that additional attention must be paid to the treatment of spectroscopic data in the training process. We also find that the training procedure is sensitive to the color distributions of the input data—the resulting w measurement can be biased by ∼2% if the color distribution is not sufficiently wide. Future low- z data, particularly u -band observations and high signal-to-noise ratio SN Ia spectra, will help to significantly improve SN Ia modeling in the coming years.

We present pre- and postexplosion observations of the Type II-P supernova (SN II-P) 2019mhm located in NGC 6753. Based on optical spectroscopy and photometry, we show that SN 2019mhm exhibits broad lines of hydrogen with a velocity of −8500 ± 200 km s ^−1 and a 111 ± 2 day extended plateau in its luminosity, typical of the Type II-P subclass. We also fit its late-time bolometric light curve and infer that it initially produced a ^56 Ni mass of 1.3 × 10 ^−2 ± 5.5 × 10 ^−4 M _⊙ . Using imaging from the Wide Field Planetary Camera 2 on the Hubble Space Telescope obtained 19 yr before explosion, we aligned to a postexplosion Wide Field Camera 3 image and demonstrate that there is no detected counterpart to the SN to a limit of >24.53 mag in F814W, corresponding to an absolute magnitude limit of M _F814W < −7.7 mag. Comparing to massive-star evolutionary tracks, we determine that the progenitor star had a maximum zero-age main-sequence mass

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE’s magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (∼71%) SNe Ia, 339 (∼23%) SNe II, and 96 (∼6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.

Abstract Background Myocardial infarction (MI) leads to complex changes in left ventricular (LV) haemodynamics that are linked to clinical outcomes. We hypothesize that LV blood flow kinetic energy (KE) is altered in MI and is associated with LV function and infarct characteristics. This study aimed to investigate the intra-cavity LV blood flow KE in controls and MI patients, using cardiovascular magnetic resonance (CMR) four-dimensional (4D) flow assessment. Methods Forty-eight patients with MI (acute-22; chronic-26) and 20 age/gender-matched healthy controls underwent CMR which included cines and whole-heart 4D flow. Patients also received late gadolinium enhancement imaging for infarct assessment. LV blood flow KE parameters were indexed to LV end-diastolic volume and include: averaged LV, minimal, systolic, diastolic, peak E-wave and peak A-wave KEiEDV. In addition, we investigated the in-plane proportion of LV KE (%) and the time difference (TD) to peak E-wave KE propagation from base to mid-ventricle was computed. Association of LV blood flow KE parameters to LV function and infarct size were investigated in all groups. Results LV KEiEDV was higher in controls than in MI patients (8.5 ± 3 μJ/ml versus 6.5 ± 3 μJ/ml, P = 0.02). Additionally, systolic, minimal and diastolic peak E-wave KEiEDV were lower in MI (P

Abstract Background Non-invasive assessment of myocardial ischaemia is a cornerstone of the diagnosis of coronary artery disease. Measurement of myocardial blood flow (MBF) using positron emission tomography (PET) is the current reference standard for non-invasive quantification of myocardial ischaemia. Dynamic myocardial perfusion cardiovascular magnetic resonance (CMR) offers an alternative to PET and a recently developed method with automated inline perfusion mapping has shown good correlation of MBF values between CMR and PET. This study assessed the repeatability of myocardial perfusion mapping by CMR in healthy subjects. Methods Forty-two healthy subjects were recruited and underwent adenosine stress and rest perfusion CMR on two visits. Scans were repeated with a minimum interval of 7 days. Intrastudy rest and stress MBF repeatability were assessed with a 15-min interval between acquisitions. Interstudy rest and stress MBF and myocardial perfusion reserve (MPR) were measured for global myocardium and regionally for coronary territories and slices. Results There was no significant difference in intrastudy repeated global rest MBF (0.65 ± 0.13 ml/g/min vs 0.62 ± 0.12 ml/g/min, p = 0.24, repeatability coefficient (RC) =24%) or stress (2.89 ± 0.56 ml/g/min vs 2.83 ± 0.64 ml/g/min, p = 0.41, RC = 29%) MBF. No significant difference was seen in interstudy repeatability for global rest MBF (0.64 ± 0.13 ml/g/min vs 0.64 ± 0.15 ml/g/min, p = 0.80, RC = 32%), stress MBF (2.71 ± 0.61 ml/g/min vs 2.55 ± 0.57 ml/g/min, p = 0.12, RC = 33%) or MPR (4.24 ± 0.69 vs 3.73 ± 0.76, p = 0.25, RC = 36%). Regional repeatability was good for stress (RC = 30–37%) and rest MBF (RC = 32–36%) but poorer for MPR (RC = 35–43%). Within subject coefficient of variation was 8% for rest and 11% for stress within the same study, and 11% for rest and 12% for stress between studies. Conclusions Fully automated, inline, myocardial perfusion mapping by CMR shows good repeatability that is similar to the published PET literature. Both rest and stress MBF show better repeatability than MPR, particularly in regional analysis.

Abstract Background Assessment of left main stem (LMS) stenosis has prognostic and therapeutic implications. Data on assessment of LMS disease by cardiovascular magnetic resonance (CMR) and single photon emission computed tomography (SPECT) are limited. CE-MARC is the largest prospective comparison of CMR and SPECT against quantitative invasive coronary angiography (QCA) for detection of coronary artery disease (CAD), and provided the framework for this evaluation. The aims of this study were to compare diagnostic accuracy of visual and quantitative perfusion CMR to SPECT in patients with LMS stable CAD. Methods Fifty-four patients from the CE-MARC study were included: 27 (4%) with significant LMS or LMS-equivalent disease on QCA, and 27 age/sex-matched patients with no flow-limiting CAD. All patients underwent multi-parametric CMR, SPECT and QCA. Performance of visual and quantitative perfusion CMR by Fermi-constrained deconvolution to detect LMS disease was compared with SPECT. Results Of 27 patients in the LMS group, 22 (81%) had abnormal CMR and 16 (59%) had abnormal SPECT. All patients with abnormal CMR had abnormal perfusion by visual analysis. CMR demonstrated significantly higher area under the curve (AUC) for detection of disease (0.95; 0.85–0.99) over SPECT (0.63; 0.49–0.76) (p = 0.0001). Global mean stress myocardial blood flow (MBF) by CMR in LMS patients was significantly lower than controls (1.77 ± 0.72 ml/g/min vs. 3.28 ± 1.20 ml/g/min, p

Background Spironolactone may have prognostic benefit in selected patients with heart failure with preserved ejection fraction. This study assessed the myocardial tissue effects of spironolactone in heart failure with preserved ejection fraction. Methods and Results A 1:1 randomized controlled study of 6 months of spironolactone versus control in heart failure with preserved ejection fraction. The primary outcome was change in myocardial extracellular volume fraction by cardiovascular magnetic resonance as a surrogate of diffuse fibrosis. Of 55 randomized patients, 40 (20 women; age, 75.2±5.9 years) completed follow‐up (19 treatment, 21 control). A significant change in extracellular volume over the study period was not seen (treatment, 28.7±3.7% versus 27.7±3.4% [P=0.14]; controls, 27.6±3.4% versus 28.3±4.4% [P=0.14]); however, the rate of extracellular volume expansion was decreased by spironolactone (−1.0±2.4% versus 0.8±2.2%). Indexed left ventricular mass decreased with treatment (104.4±26.6 versus 94.0±20.6 g/m2; P=0.001) but not in controls (101.4±29.4 versus 104.0±32.8 g/m2; P=0.111). Extracellular mass decreased by 13.8% (15.1±4.8 versus 13.0±3.4 g/m2; P=0.003), and cellular mass decreased by 8.3% (37.6±10.0 versus 34.3±7.9 g/m2; P=0.001) with spironolactone, but was static in controls. Conclusions Spironolactone did not lead to significant change in extracellular volume. However, spironolactone did decrease rate of extracellular expansion, with a decrease in the mass of both cellular and extracellular myocardial compartments. These data point to the mechanism of action of spironolactone in heart failure with preserved ejection fraction, including a direct tissue effect with a reduction in rate of myocardial fibrosis.