Litter aeration and spread of Salmonella in broilers

Litter quality in the poultry sector is one of the main parameters of health, productivity, and animal welfare. Therefore, innovative management methods have been developed to improve the quality of litter. One of them is litter aeration (LA) by tumbling. However, there is little information related to the effect of this technique on the spreading of pathogens of public health importance such as Salmonella. In this context, the objective of this study was to determine the epidemiology of Salmonella in poultry farms, when serial LA were implemented during the rearing cycle of broilers. For this purpose, an experimental broiler farm with 3 identical rooms was used in the study. Two rooms were assigned to the LA treatment, and the other one served as the control room. Environmental samples were taken in poultry houses after LA in 4 consecutive weeks at the end of the cycle. All samples collected were analyzed according to the standards of the International Organization for Standardization (ISO 6579:2002, Annex D). The results of this study showed that in the control and treated rooms, the percentage of positive samples for Salmonella decreased in the first 3 LA sessions (LA 1, LA 2, and LA 3). However, in the last LA session of rearing (LA 4), the percentage of positive samples increased from 8.2 to 33.2% in the control room instead the treated rooms where the positive samples decreased (P = 0.017). Thus, the aeration of the litter as litter management technique in poultry broiler production does not increase the shedding or the spread of Salmonella throughout broiler houses. In addition, it could be an effective technique to reduce the infective pressure of this bacterium in several areas of the farm or in certain moments of the rearing period with more risk of multiplication and spreading of Salmonella

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology

[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was designed to directly target the volumes to estimate, not requiring any labeled segmentation on the images. The network was based on a 3D U-net with extra layers defined in a scan-ning module that learned features like the circularity of the objects and the volumes to estimate in a weakly-supervised manner. The only targets defined were the left ventricle volumes and the circularity of the object detected through the estimation of the pi value derived from its shape. We had access to 397 cases corresponding to 397 different subjects. We randomly selected 98 cases to use as test set. Results: The results show a good match between the real and estimated volumes in the test set, with a mean relative error of 8% and a mean absolute error of 9.12 ml with a Pearson correlation coefficient of 0.95. The derived segmentations obtained by the network achieved Dice coefficients with a mean value of 0.79. Conclusions: The proposed method is capable of obtaining the left ventricle volume biomarker in the end-diastole and offer an explanation of how it obtains the result in the form of a segmentation mask without the need of segmentation labels to train the algorithm, making it a potentially more trustworthy method for clinicians and a way to train neural networks more easily when segmentation labels are not readily available.The authors acknowledge financial support from the Consel-leria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana (grants AEST/2019/037 and AEST/2020/029) , from the Agencia Valenciana de la Innovacion, Generalitat Valenciana (ref. INNCAD00/19/085) , and from the Centro para el Desarrollo Tecnologico Industrial (Programa Eurostars2, actuacion Interempresas Internacional) , Spanish Ministerio de Ciencia, Innovacion y Universidades (ref. CIIP-20192020) .Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Pérez-Pelegrí, L.; Maceira, AM.; Bodi, V.; Moratal, D. (2021). Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology. Computer Methods and Programs in Biomedicine. 208:1-8. https://doi.org/10.1016/j.cmpb.2021.106275S1820

PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles

[EN] Characterization of the heart anatomy and function is mostly done with magnetic resonance image cine series. To achieve a correct characterization, the volume of the right and left ventricle need to be segmented, which is a timeconsuming task. We propose a new convolutional neural network architecture that combines U-net with PSP modules (PSPU-net) for the segmentation of left and right ventricle cavities and left ventricle myocardium in the diastolic frame of short-axis cine MRI images and compare its results against a classic 3D U-net architecture. We used a dataset containing 399 cases in total. The results showed higher quality results in both segmentation and final volume estimation for a test set of 99 cases in the case of the PSPU-net, with global dice metrics of 0.910 and median absolute relative errors in volume estimations of 0.026 and 0.039 for the left ventricle cavity and myocardium and 0.051 for the right ventricles cavity.DM acknowledges financial support from the Conselleria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana (grants AEST/2019/037 and AEST/2020/029), from the Agencia Valenciana de la Innovacion, Generalitat Valenciana (ref. INNCAD00/19/085), and from the Centro para el Desarrollo Tecnologico Industrial (Programa Eurostars-2, actuacion Interempresas Internacional), Spanish Ministerio de Ciencia, Innovacion y Universidades (ref. CIIP20192020). We are grateful to Andres Larroza for his valuable technical assistance in the project.Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Ruiz-España, S.; Del-Canto, I.; Bodi, V.; Moratal, D. (2020). PSPU-Net for Automatic Short Axis Cine MRI Segmentation of Left and Right Ventricles. IEEE Computer Society. 1048-1053. https://doi.org/10.1109/BIBE50027.2020.00177S1048105

A Novel Clinical and Stress Cardiac Magnetic Resonance (C-CMR-10) Score to Predict Long-Term All-Cause Mortality in Patients with Known or Suspected Chronic Coronary Syndrome

[EN] Vasodilator stress cardiac magnetic resonance (stressCMR) has shown robust diagnostic and prognostic value in patients with known or suspected chronic coronary syndrome (CCS). However, it is unknown whether integration of stressCMR with clinical variables in a simple clinical-imaging score can straightforwardly predict all-cause mortality in this population. We included 6187 patients in a large registry that underwent stressCMR for known or suspected CCS. Several clinical and stressCMR variables were collected, such as left ventricular ejection fraction (LVEF) and ischemic burden (number of segments with stress-induced perfusion defects (PD)). During a median follow-up of 5.56 years, we registered 682 (11%) all-cause deaths. The only independent predictors of all-cause mortality in multivariable analysis were age, male sex, diabetes mellitus (DM), LVEF and ischemic burden. Based on the weight of the chi-square increase at each step of the multivariable analysis, we created a simple clinical-stressCMR (C-CMR-10) score that included these variables (age >= 65 years = 3 points, LVEF 5 segments = 1 point). This 0 to 10 points C-CMR-10 score showed good performance to predict all-cause annualized mortality rate ranging from 0.29%/year (score = 0) to >4.6%/year (score >= 7). The goodness of the model and of the C-CMR-10 score was separately confirmed in 2 internal cohorts (n> 3000 each). We conclude that a novel and simple clinical-stressCMR score, which includes clinical and stressCMR variables, can provide robust prediction of the risk of long-term all-cause mortality in a population of patients with known or suspected CCS.This work was supported by the Instituto de Salud Carlos III and co-funded by Fondo Europeo de Desarrollo Regional (FEDER) (grant numbers PI17/01836 and CIBERCV16/11/00486).Marcos-Garces, V.; Gavara-Doñate, J.; Monmeneu-Menadas, JV.; Lopez-Lereu, MP.; Pérez, N.; Rios-Navarro, C.; De Dios, E.... (2020). A Novel Clinical and Stress Cardiac Magnetic Resonance (C-CMR-10) Score to Predict Long-Term All-Cause Mortality in Patients with Known or Suspected Chronic Coronary Syndrome. Journal of Clinical Medicine. 9(6):1-13. https://doi.org/10.3390/jcm9061957S11396Hendel, R. C., Friedrich, M. G., Schulz-Menger, J., Zemmrich, C., Bengel, F., Berman, D. S., … Nagel, E. (2016). CMR First-Pass Perfusion for Suspected Inducible Myocardial Ischemia. JACC: Cardiovascular Imaging, 9(11), 1338-1348. doi:10.1016/j.jcmg.2016.09.010Chang, S.-A., & Kim, R. J. (2016). The Use of Cardiac Magnetic Resonance in Patients with Suspected Coronary Artery Disease: A Clinical Practice Perspective. Journal of Cardiovascular Ultrasound, 24(2), 96. doi:10.4250/jcu.2016.24.2.96Kiaos, A., Tziatzios, I., Hadjimiltiades, S., Karvounis, C., & Karamitsos, T. D. (2018). Diagnostic performance of stress perfusion cardiac magnetic resonance for the detection of coronary artery disease. International Journal of Cardiology, 252, 229-233. doi:10.1016/j.ijcard.2017.11.066Li, M., Zhou, T., Yang, L., Peng, Z., Ding, J., & Sun, G. (2014). Diagnostic Accuracy of Myocardial Magnetic Resonance Perfusion to Diagnose Ischemic Stenosis With Fractional Flow Reserve as Reference. JACC: Cardiovascular Imaging, 7(11), 1098-1105. doi:10.1016/j.jcmg.2014.07.011Siontis, G. C., Mavridis, D., Greenwood, J. P., Coles, B., Nikolakopoulou, A., Jüni, P., … Windecker, S. (2018). Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials. BMJ, k504. doi:10.1136/bmj.k504Nagel, E., Greenwood, J. P., McCann, G. P., Bettencourt, N., Shah, A. M., Hussain, S. T., … Berry, C. (2019). Magnetic Resonance Perfusion or Fractional Flow Reserve in Coronary Disease. New England Journal of Medicine, 380(25), 2418-2428. doi:10.1056/nejmoa1716734Siontis, G. C., Branca, M., Serruys, P., Silber, S., Räber, L., Pilgrim, T., … Hunziker, L. (2019). Impact of left ventricular function on clinical outcomes among patients with coronary artery disease. European Journal of Preventive Cardiology, 26(12), 1273-1284. doi:10.1177/2047487319841939Buckert, D., Kelle, S., Buss, S., Korosoglou, G., Gebker, R., Birkemeyer, R., … Bernhardt, P. (2016). Left ventricular ejection fraction and presence of myocardial necrosis assessed by cardiac magnetic resonance imaging correctly risk stratify patients with stable coronary artery disease: a multi-center all-comers trial. Clinical Research in Cardiology, 106(3), 219-229. doi:10.1007/s00392-016-1042-5Catalano, O., Moro, G., Perotti, M., Frascaroli, M., Ceresa, M., Antonaci, S., … Priori, S. G. (2012). Late gadolinium enhancement by cardiovascular magnetic resonance is complementary to left ventricle ejection fraction in predicting prognosis of patients with stable coronary artery disease. Journal of Cardiovascular Magnetic Resonance, 14(1). doi:10.1186/1532-429x-14-29Lipinski, M. J., McVey, C. M., Berger, J. S., Kramer, C. M., & Salerno, M. (2013). Prognostic Value of Stress Cardiac Magnetic Resonance Imaging in Patients With Known or Suspected Coronary Artery Disease. Journal of the American College of Cardiology, 62(9), 826-838. doi:10.1016/j.jacc.2013.03.080Gargiulo, P., Dellegrottaglie, S., Bruzzese, D., Savarese, G., Scala, O., Ruggiero, D., … Filardi, P. P. (2013). The Prognostic Value of Normal Stress Cardiac Magnetic Resonance in Patients With Known or Suspected Coronary Artery Disease. Circulation: Cardiovascular Imaging, 6(4), 574-582. doi:10.1161/circimaging.113.000035Kwong, R. Y., Ge, Y., Steel, K., Bingham, S., Abdullah, S., Fujikura, K., … Simonetti, O. P. (2019). Cardiac Magnetic Resonance Stress Perfusion Imaging for Evaluation of Patients With Chest Pain. Journal of the American College of Cardiology, 74(14), 1741-1755. doi:10.1016/j.jacc.2019.07.074Marcos-Garces, V., Gavara, J., Monmeneu, J. V., Lopez-Lereu, M. P., Bosch, M. J., Merlos, P., … Bodi, V. (2020). Vasodilator Stress CMR and All-Cause Mortality in Stable Ischemic Heart Disease. JACC: Cardiovascular Imaging, 13(8), 1674-1686. doi:10.1016/j.jcmg.2020.02.027Heitner, J. F., Kim, R. J., Kim, H. W., Klem, I., Shah, D. J., Debs, D., … Judd, R. M. (2019). Prognostic Value of Vasodilator Stress Cardiac Magnetic Resonance Imaging. JAMA Cardiology, 4(3), 256. doi:10.1001/jamacardio.2019.0035Bodi, V., Sanchis, J., Lopez-Lereu, M. P., Nunez, J., Mainar, L., Monmeneu, J. V., … Llacer, A. (2007). Prognostic Value of Dipyridamole Stress Cardiovascular Magnetic Resonance Imaging in Patients With Known or Suspected Coronary Artery Disease. Journal of the American College of Cardiology, 50(12), 1174-1179. doi:10.1016/j.jacc.2007.06.016Bodi, V., Husser, O., Sanchis, J., Núñez, J., Monmeneu, J. V., López-Lereu, M. P., … Llacer, Á. (2012). Prognostic Implications of Dipyridamole Cardiac MR Imaging: A Prospective Multicenter Registry. Radiology, 262(1), 91-100. doi:10.1148/radiol.11110134Ponikowski, P., Voors, A. A., Anker, S. D., Bueno, H., Cleland, J. G. F., Coats, A. J. S., … van der Meer, P. (2016). 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. European Heart Journal, 37(27), 2129-2200. doi:10.1093/eurheartj/ehw128Marschner, I. C., Colquhoun, D., Simes, R. J., Glasziou, P., Harris, P., Singh, B. B., … Tonkin, A. (2001). Long-term risk stratification for survivors of acute coronary syndromes. Journal of the American College of Cardiology, 38(1), 56-63. doi:10.1016/s0735-1097(01)01360-2Knuuti, J., Wijns, W., Saraste, A., Capodanno, D., Barbato, E., Funck-Brentano, C., … Cuisset, T. (2019). 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. European Heart Journal, 41(3), 407-477. doi:10.1093/eurheartj/ehz425Klem, I., Shah, D. J., White, R. D., Pennell, D. J., van Rossum, A. C., Regenfus, M., … Kim, R. J. (2011). Prognostic Value of Routine Cardiac Magnetic Resonance Assessment of Left Ventricular Ejection Fraction and Myocardial Damage. Circulation: Cardiovascular Imaging, 4(6), 610-619. doi:10.1161/circimaging.111.964965Grothues, F., Smith, G. C., Moon, J. C. ., Bellenger, N. G., Collins, P., Klein, H. U., & Pennell, D. J. (2002). Comparison of interstudy reproducibility of cardiovascular magnetic resonance with two-dimensional echocardiography in normal subjects and in patients with heart failure or left ventricular hypertrophy. The American Journal of Cardiology, 90(1), 29-34. doi:10.1016/s0002-9149(02)02381-0Timmis, A., Raharja, A., Archbold, R. A., & Mathur, A. (2018). Validity of inducible ischaemia as a surrogate for adverse outcomes in stable coronary artery disease. Heart, 104(21), 1733-1738. doi:10.1136/heartjnl-2018-313230Pontone, G., Andreini, D., Bertella, E., Loguercio, M., Guglielmo, M., Baggiano, A., … Masci, P. G. (2015). Prognostic value of dipyridamole stress cardiac magnetic resonance in patients with known or suspected coronary artery disease: a mid-term follow-up study. European Radiology, 26(7), 2155-2165. doi:10.1007/s00330-015-4064-xHeydari, B., Juan, Y.-H., Liu, H., Abbasi, S., Shah, R., Blankstein, R., … Kwong, R. Y. (2016). Stress Perfusion Cardiac Magnetic Resonance Imaging Effectively Risk Stratifies Diabetic Patients With Suspected Myocardial Ischemia. Circulation: Cardiovascular Imaging, 9(4). doi:10.1161/circimaging.115.004136Vincenti, G., Masci, P. G., Monney, P., Rutz, T., Hugelshofer, S., Gaxherri, M., … Schwitter, J. (2017). Stress Perfusion CMR in Patients With Known and Suspected CAD. JACC: Cardiovascular Imaging, 10(5), 526-537. doi:10.1016/j.jcmg.2017.02.006Buckert, D., Cieslik, M., Tibi, R., Radermacher, M., Rottbauer, W., & Bernhardt, P. (2017). Cardiac magnetic resonance imaging derived quantification of myocardial ischemia and scar improves risk stratification and patient management in stable coronary artery disease. Cardiology Journal, 24(3), 293-304. doi:10.5603/cj.a2017.0036Zemrak, F., & Petersen, S. E. (2011). Late Gadolinium Enhancement CMR Predicts Adverse Cardiovascular Outcomes and Mortality in Patients With Coronary Artery Disease: Systematic Review and Meta-Analysis. Progress in Cardiovascular Diseases, 54(3), 215-229. doi:10.1016/j.pcad.2011.07.003El Aidi, H., Adams, A., Moons, K. G. M., Den Ruijter, H. M., Mali, W. P. T. M., Doevendans, P. A., … Leiner, T. (2014). Cardiac Magnetic Resonance Imaging Findings and the Risk of Cardiovascular Events in Patients With Recent Myocardial Infarction or Suspected or Known Coronary Artery Disease. Journal of the American College of Cardiology, 63(11), 1031-1045. doi:10.1016/j.jacc.2013.11.048Fox, K. A. A., Metra, M., Morais, J., & Atar, D. (2019). The myth of ‘stable’ coronary artery disease. Nature Reviews Cardiology, 17(1), 9-21. doi:10.1038/s41569-019-0233-ySchiele, F., Ecarnot, F., & Chopard, R. (2017). Coronary artery disease: Risk stratification and patient selection for more aggressive secondary prevention. European Journal of Preventive Cardiology, 24(3_suppl), 88-100. doi:10.1177/2047487317706586Fordyce, C. B., Douglas, P. S., Roberts, R. S., Hoffmann, U., Al-Khalidi, H. R., … Patel, M. R. (2017). Identification of Patients With Stable Chest Pain Deriving Minimal Value From Noninvasive Testing. JAMA Cardiology, 2(4), 400. doi:10.1001/jamacardio.2016.5501Papireddy, M. R., Lavie, C. J., Deoker, A., Mamudu, H., & Paul, T. K. (2018). New Algorithm for the Prediction of Cardiovascular Risk in Symptomatic Adults with Stable Chest Pain. Current Cardiology Reports, 20(5). doi:10.1007/s11886-018-0973-

RBCK1‐related disease: A rare multisystem disorder with polyglucosan storage, auto‐inflammation, recurrent infections, skeletal, and cardiac myopathy—Four additional patients and a review of the current literature

In this article, we report four new patients, from three kindreds, with pathogenic variants in RBCK1 and a multisystem disorder characterised by widespread polyglucosan storage. We describe the clinical presentation of progressive skeletal and cardiac myopathy, combined immunodeficiencies and auto‐inflammation, illustrate in detail the histopathological findings in multiple tissue types, and report muscle MRI findings

Incidence, Outcomes, and Predictors of Ventricular Thrombus after Reperfused ST-Segment-Elevation Myocardial Infarction by Using Sequential Cardiac MR Imaging

[EN] Purpose: To characterize the incidence, outcomes, and predictors of left ventricular (LV) thrombus by using sequential cardiac magnetic resonance (MR) imaging after ST-segment-elevation myocardial infarction (STEMI). Materials and Methods: Written informed consent was obtained from all patients, and the study protocol was approved by the committee on human research. In a cohort of 772 patients with STEMI, 392 (mean age, 58 years; range, 24-89 years) were retrospectively selected who were studied with cardiac MR imaging at 1 week and 6 months. Cardiac MR imaging guided the initiation and withdrawal of anticoagulants. Patients with LV thrombus at 6 months were restudied at 1 year. For predicting the occurrence of LV thrombus, a multiple regression model was applied. Results: LV thrombus was detected in 27 of 392 patients (7%): 18 (5%) at 1 week and nine (2%) at 6 months. LV thrombus resolved in 22 of 25 patients (88%) restudied within the first year. During a mean follow-up of 181 weeks 6 168, patients with LV thrombus displayed a very low rate of stroke (0%), peripheral embolism (0%), and severe hemorrhage (n = 1, 3.7%). LV ejection fraction (LVEF) less than 50% (P < .001) and anterior infarction (P = .008) independently helped predict LV thrombus. The incidence of LV thrombus was as follows: (a) nonanterior infarction, LVEF 50% or greater (one of 135, 1%); (b) nonanterior infarction, LVEF less than 50% (one of 50, 2%); (c) anterior infarction, LVEF 50% or greater (two of 92, 2%); and (d) anterior infarction, LVEF less than 50% (23 of 115, 20%) (P < .001 for the trend). Conclusion: Cardiac MR imaging contributes information for the diagnosis and therapy of LV thrombus after STEMI. Patients with simultaneous anterior infarction and LVEF less than 50% are at highest risk. (C) RSNA, 2017Study supported by Instituto de Salud Carlos III and FEDER (CB16/11/00486, PI14/00271, PIE15/00013) and Generalitat Valenciana (PROMETEO/2013/007).Cambronero-Cortinas, E.; Bonanad, C.; Monmeneu, J.; López-Lereu, M.; Gavara-Doñate, J.; De Dios, E.; Rios, C.... (2017). Incidence, Outcomes, and Predictors of Ventricular Thrombus after Reperfused ST-Segment-Elevation Myocardial Infarction by Using Sequential Cardiac MR Imaging. Radiology. 284(2):372-380. https://doi.org/10.1148/radiol.2017161898S372380284

Dilated Cardiomyopathy with Increased SR Ca2+ Loading Preceded by a Hypercontractile State and Diastolic Failure in the α1CTG Mouse

Mice over-expressing the α1−subunit (pore) of the L-type Ca2+ channel (α1CTG) by 4months (mo) of age exhibit an enlarged heart, hypertrophied myocytes, increased Ca2+ current and Ca2+ transient amplitude, but a normal SR Ca2+ load. With advancing age (8–11 mo), some mice demonstrate advanced hypertrophy but are not in congestive heart failure (NFTG), while others evolve to frank dilated congestive heart failure (FTG). We demonstrate that older NFTG myocytes exhibit a hypercontractile state over a wide range of stimulation frequencies, but maintain a normal SR Ca2+ load compared to age matched non-transgenic (NTG) myocytes. However, at high stimulation rates (2–4 Hz) signs of diastolic contractile failure appear in NFTG cells. The evolution of frank congestive failure in FTG is accompanied by a further increase in heart mass and myocyte size, and phospholamban and ryanodine receptor protein levels and phosphorylation become reduced. In FTG, the SR Ca2+ load increases and Ca2+ release following excitation, increases further. An enhanced NCX function in FTG, as reflected by an accelerated relaxation of the caffeine-induced Ca2+ transient, is insufficient to maintain a normal diastolic Ca2+ during high rates of stimulation. Although a high SR Ca2+ release following excitation is maintained, the hypercontractile state is not maintained at high rates of stimulation, and signs of both systolic and diastolic contractile failure appear. Thus, the dilated cardiomyopathy that evolves in this mouse model exhibits signs of both systolic and diastolic failure, but not a deficient SR Ca2+ loading or release, as occurs in some other cardiomyopathic models

Predictive Value of Cardiac Magnetic Resonance Feature Tracking after Acute Myocardial Infarction: A Comparison with Dobutamine Stress Echocardiography

[EN] In acute ST-segment elevation myocardial infarction (STEMI) late gadolinium enhancement (LGE) may underestimate segmental functional recovery. We evaluated the predictive value of cardiac magnetic resonance (CMR) feature-tracking (FT) for functional recovery and whether it incremented the value of LGE compared to low-dose dobutamine stress echocardiography (LDDSE) and speckle-tracking echocardiography (STE). Eighty patients underwent LDDSE and CMR within 5-7 days after STEMI and segmental functional recovery was defined as improvement in wall-motion at 6-months CMR. Optimal conventional and FT parameters were analyzed and then also applied to an external validation cohort of 222 STEMI patients. Circumferential strain (CS) was the strongest CMR-FT predictor and addition to LGE increased the overall accuracy to 74% and was especially relevant in segments with 50-74% LGE (AUC 0.60 vs. 0.75, p = 0.001). LDDSE increased the overall accuracy to 71%, and in the 50-74% LGE subgroup improved the AUC from 0.60 to 0.69 (p = 0.039). LGE + CS showed similar value as LGE + LDDSE. In the validation cohort, CS was also the strongest CMR-FT predictor of recovery and addition of CS to LGE improved overall accuracy to 73% although this difference was not significant (AUC 0.69, p = 0.44). Conclusion: CS is the strongest CMR-FT predictor of segmental functional recovery after STEMI. Its incremental value to LGE is comparable to that of LDDSE whilst avoiding an inotropic stress agent. CS is especially relevant in segments with 50-74% LGE where accuracy is lower and further testing is frequently required to clarify the potential for recovery.This research was supported by the Instituto de Salud Carlos III and co-funded by Fondo Europeo de Desarrollo Regional (FEDER) (grant numbers PI17/01836 and CIBERCV16/11/00486). JG and DM acknowledge financial support from the "Agencia Valenciana de la Innovacion, Generalitat Valenciana" (grant) and from the "Conselleria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana" (grant number AEST/2019/037).Valente, FX.; Gavara-Doñate, J.; Gutiérrez, L.; Rios-Navarro, C.; Rello, P.; Maymi, M.; Fernandez-Galera, R.... (2021). Predictive Value of Cardiac Magnetic Resonance Feature Tracking after Acute Myocardial Infarction: A Comparison with Dobutamine Stress Echocardiography. Journal of Clinical Medicine. 10(22):1-12. https://doi.org/10.3390/jcm10225261S112102

Cardiac magnetic resonance imaging analysis in STEMI: quantitative or still visual?

Cardiovascular Aspects of Radiolog

Magnetic resonance microscopy and correlative histopathology of the infarcted heart

Altres ajuts:The present study was supported by the EU Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI HDHL INTIMIC-085), Generalitat Valenciana (GV/2018/116), INCLIVA and Universitat de Valencia (program VLC-BIOCLINIC 20-nanomIRM-2016A).Delayed enhancement cardiovascular magnetic resonance (MR) is the gold-standard for non-invasive assessment after myocardial infarction (MI). MR microscopy (MRM) provides a level of detail comparable to the macro objective of light microscopy. We used MRM and correlative histopathology to identify infarct and remote tissue in contrast agent-free multi-sequence MRM in swine MI hearts. One control group (n = 3 swine) and two experimental MI groups were formed: 90 min of ischemia followed by 1 week (acute MI = 6 swine) or 1 month (chronic MI = 5 swine) reperfusion. Representative samples of each heart were analysed by contrast agent-free multi-sequence (T1-weighting, T2-weighting, T2*-weighting, T2-mapping, and T2*-mapping). MRM was performed in a 14-Tesla vertical axis imager (Bruker-AVANCE 600 system). Images from MRM and the corresponding histopathological stained samples revealed differences in signal intensities between infarct and remote areas in both MI groups (p-value < 0.001). The multivariable models allowed us to precisely classify regions of interest (acute MI: specificity 92% and sensitivity 80%; chronic MI: specificity 100% and sensitivity 98%). Probabilistic maps based on MRM images clearly delineated the infarcted regions. As a proof of concept, these results illustrate the potential of MRM with correlative histopathology as a platform for exploring novel contrast agent-free MR biomarkers after MI