Abdominal ectopic fat deposition and excess visceral fat depots in obesity may be related to cardiovascular disease (CVD) as both are involved in the metabolic syndrome (MetS). The awareness of the link between abdominal adiposity and subclinical cardiac remodeling would help improve treatment and outcome. Besides, liver fibrosis has also shown a potential relationship with cardiac dysfunction. Thus, we aimed to investigate the associations of magnetic resonance (MR)-based abdominal adiposity and hepatic shear stiffness with subclinical left ventricular (LV) remodeling while taking account of MetS-related confounders in adults free of overt CVD.This was an exploratory, prospective study of 88 adults  who underwent 3 T cardiac and body MR exams. Measures of abdominal MR included hepatic and pancreatic proton density fat fraction (H-PDFF and P-PDFF), hepatic shear stiffness by MR elastography, and subcutaneous and visceral adipose tissue (SAT and VAT). Cardiac measures included epicardial adipose tissue (EAT) and parameters of LV geometry and function. Associations were assessed using Pearson correlation and multivariable linear regression analyses, in which age, sex, and MetS-related confounders were adjusted for.p < 0.05), and P-PDFF, SAT and VAT were independently and positively associated with LV end-diastolic volume and stroke volume  in the over-all cohort. In the obesity subgroup, higher P-PDFF and VAT were independently associated with lower circumferential and longitudinal PS, respectively . No independent correlation between hepatic shear stiffness and EAT or LV remodeling was found .The LV ejection fractions of all participants were within the normal range. Higher H-PDFF, P-PDFF, SAT and VAT were independently associated with lower LV global myocardial strain parameters  (β = − 0.001 to − 0.41, Ectopic fat depositions in the liver and pancreas, and excess abdominal adipose tissue pose a risk of subclinical LV remodeling beyond MetS-related CVD risk factors in adults without overt CVD. VAT may play a more considerable role as a risk factor for subclinical LV dysfunction than does SAT in individuals with obesity. The underlying mechanisms of these associations and their longitudinal clinical implications need further investigation.The online version contains supplementary material available at 10.1186/s12933-023-01828-1. Body mass index (BMI) is commonly used to identify obesity with different cutoff values across various racial or ethnic groups. For example, the BMI cutoff for obesity among adults is 30 kg/mulations , 2. The In obesity, the overload of calories gives rise to fat accumulation in the visceral depots  and ectopic fat deposition , which is highly involved in the development of metabolic disorders , 5. It hThe underlying mechanisms of the relationship between abdominal adiposity and CVD are complicated and less well understood. One of the putative mechanisms is that ectopic fat deposition and excess visceral adipose tissue (VAT) release fat-derived toxic metabolites and activate inflammatory pathways triggering a cluster of pathophysiological changes that promote the development of CVD . The devCardiac magnetic resonance (MR) has been a vital modality for the highly accurate and reproducible assessment of cardiac geometry and function, especially for the evaluation of subclinical dysfunction using myocardial strain parameters . AbdominIn addition, liver fibrosis in chronic liver disease has shown a potential relationship with cardiac dysfunction . A few sTo this end, the purpose of this exploratory study was to investigate the associations of MR-based abdominal adiposity and hepatic shear stiffness with subclinical LV remodeling while taking account of MetS-related confounders in adults free of overt CVD.2 for subjects with obesity, BMI < 23 kg/m2 for healthy controls  ≥ 27.5 kg/mThis study was approved by our Institutional Review Board. Informed written consent was obtained from each subject.Demographic, anthropometric, and laboratory data of all subjects were collected, including age, sex, weight, height, BMI, waist circumference, hip circumference, heart rate, systolic and diastolic blood pressure (BP), hypertension, fasting and 2 h serum glucose concentration, prediabetes, and serum lipid profiles . Heart rate was assessed using a 12-lead electrocardiogram (ECG). BP was measured twice in the sitting position with feet on the floor and back supported after 15 min of rest to help better reduce the white coat effect, and the mean BP values were calculated. Hypertension was defined by systolic BP ≥ 130 mmHg and/or diastolic BP ≥ 80 mmHg . Serum gNon-contrast cardiac and abdominal MR examinations were performed at 3 T  on the same day. To minimize potential physiological confounding factors, participants were instructed to fast for a minimum of 4 h before abdominal scanning. Subjects were scanned in the supine position with an 18-channel phased-array body coil for cardiac imaging and with an 8-channel torso phased-array receive coil for abdominal imaging. A dielectric pad was placed between the surface coil and the abdominal wall to reduce shading from B1 heterogeneity. MRE examinations were performed using a 60-Hz paddle vibration frequency, as previously described .With a standard ECG-triggering device, data were acquired during the end-expiratory breath-hold period. A segmented breath-hold balanced steady-state free precession (bSSFP) sequence was used to obtain 8–14 continuous cine images from the heart base to the apex in the short-axis view, and LV two- and four-chamber cine images in the long-axis view. Twenty-five phases were reconstructed in a cardiac cycle. The temporal resolution was 39.34 ms. Other acquisition parameters are summarized in Table EAT volume, LV geometry, and global systolic function were measured on the short-axis cine images; LV global myocardial strain was assessed on the long-axis two- and four-chamber and short-axis cine images. Parameters of LV geometry and global systolic function included LV mass (LVM) at end-diastole, mean LV regional values for 16 myocardial segment thicknesses (excluding the apex) (LVMT), LV ejection fraction (LVEF), LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), and stroke volume (SV). LV global myocardial strain parameters included radial, circumferential, and longitudinal peak strain , peak systolic strain rate , peak diastolic strain rate . If applied to C-PS, C-PSSR, L-PS, L-PSSR, and R-PDSR, the values are negative. A lower absolute value for myocardial strain parameters means worse myocardial contractility. Analysis details are described in the Additional file Two experienced cardiovascular radiologists (with more than 3 years of experience) who were blinded to the clinical and abdominal MR data performed the cardiac image analyses using CVI42 v5.11.3 . The intra- and interobserver variability of the LV global myocardial strain parameters were assessed  were acquired using iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) sequence in one 20-s breath-hold. Abdominal SAT and VAT area were measured on axial fat images generated by axial liver acquisition with volume acceleration flex (LAVA-Flex) sequence. Hepatic shear stiffness was generated by breath-hold 2D 60 Hz MRE using spin-echo echo-planar imaging (SE-EPI). Acquisition parameters are listed in Table Two experienced abdominal radiologists (with more than 4 years of experience) who were blinded to the clinical and cardiac MR data performed abdominal image analyses. H-PDFF, P-PDFF and hepatic shear stiffness analyses were performed using Horos imaging software , and SAT and VAT areas were analyzed using sliceOmatic v5.0 . The intra- and interobserver variability of abdominal MR measures were assessed  was calculated to assess the intra- and interobserver variability.In univariate analyses, Pearson correlation coefficients (r) were calculated to explore the associations of H-PDFF, P-PDFF, SAT, VAT and hepatic shear stiffness with cardiac measures in the over-all cohort, in the obesity subgroup, and in the control subgroup, respectively. Relationships that showed significant differences in univariate analyses were then further examined using multivariable linear regression analyses. In each regression, the outcome was one cardiac MR measure, and the predictors consisted of one abdominal MR measure as well as the covariates of (a) age, sex, and with/without MetS (Model 1), or (b) age, sex, hypertension, TG, HDL-C, and prediabetes (Model 2). MetS, hypertension and prediabetes were not adjusted in healthy controls, as no subject had any of them. A 2-tailed p value < 0.05 was considered statistically significant. All analyses were conducted with SPSS Version 26.0 . As this was an exploratory study, correction for multiple comparisons was not applied.2), 46 subjects  were with obesity, and 42 subjects  were healthy controls. Subjects with obesity and healthy controls did not differ in age (p = 0.09) or sex (p = 0.95) , HDL-C in subjects with obesity was significantly lower than that in healthy controls (p < 0.001) , and lower R-PS, |C-PS|, |L-PS|, |L-PSSR|, C-PDSR, and L-PDSR    Figs. ; Table 2p ≤ 0.02), and was inversely correlated with R-PS, |C-PS|, |L-PS|, |L-PSSR|, |R-PDSR|, C-PDSR, and L-PDSR  in univariate analyses. The associations of H-PDFF with EAT, R-PS, |L-PS| persisted in both models  . Age, sex and MetS did not affect these associations . However, the associations were not significant in Model 2 . In healthy controls, |C-PS|, |R-PDSR|, and L-PDSR decreased significantly with increasing H-PDFF in univariate analyses . The associations between H-PDFF and |R-PDSR|, L-PDSR remained significant in both models  ; R-PS, |C-PS|, |L-PS|, C-PDSR, and L-PDSR decreased significantly with increasing P-PDFF  in univariate analyses. The associations between P-PDFF and EAT, LVEDV, SV, |C-PS|, and |L-PS| remained significant in both models  , which was not affected by age, sex, hypertension, TG, HDL-C, prediabetes, or MetS (p = 0.01) .In subjects with obesity, P-PDFF was inversely correlated with C-PS in univariate analysis  Fig. . In healp ≤ 0.04), and negative correlations between SAT and R-PS, |L-PS|, |L-PSSR| and L-PDSR  in univariate analyses. The associations between SAT and EAT, LVEDV, SV, |L-PS|, |L-PSSR| and L-PDSR persisted in both models  . In healthy controls, there was a negative correlation between SAT and LVMT in univariate analysis , while it did not remain significant in either model .In subjects with obesity, there was no significant association between SAT and any LV measure in univariate analyses , and was negatively correlated with |C-PS|, |L-PS|, C-PDSR, and L-PDSR  in univariate analyses. VAT was associated with EAT, SV, |L-PS| in both models   Fig. .p = 0.02), and there were negative correlations between VAT and |L-PS|, C-PDSR, and L-PDSR  in univariate analyses. Only |L-PS| decreased with increasing VAT in both models  , which was of no significance in either model .In subjects with obesity, there was a positive correlation between VAT and LVMT  Fig. . In healp = 0.02). There were positive correlations between hepatic shear stiffness and LVM, LVMT, and SV in subjects with obesity in univariate analyses ; however, they did not remain significant in multivariable analyses (p ≥ 0.05). In healthy controls, there was no significant association between hepatic shear stiffness and any cardiac measure in univariate analyses .In univariate analyses, there was a negative correlation between hepatic shear stiffness and |L-PS| in the over-all cohort  subjects with obesity exhibited alterations in LV geometry compared to healthy controls, and P-PDFF, SAT and VAT were positively associated with LVEDV and SV independent of MetS in the over-all cohort; (2) subjects with obesity had subclinical LV dysfunction manifested by decreased myocardial strain, and H-PDFF, P-PDFF, SAT and VAT were inversely associated with LV global myocardial strain parameters independent of MetS in the over-all cohort; (3) In the obesity subgroup, increasing P-PDFF and VAT were independently associated with decreasing C-PS and L-PS; and (4) hepatic shear stiffness showed no independent association with EAT or subclinical LV remodeling.In our study, subjects with obesity, who had higher visceral fat depots (EAT and VAT) and ectopic fat deposition (H-PDFF and P-PDFF), had higher LVEDV, LVESV, and SV than healthy controls, which was similarly observed by prior studies using echocardiography or cardiovascular MR –22. It mAlthough the LVEF of all subjects was within the normal range and no significant difference existed between the obesity and control subgroups, subjects with obesity had impaired LV systolic and diastolic function compared to healthy controls, manifested by lower R-PS, |C-PS|, |L-PS|, |L-PSSR|, C-PDSR, and L-PDSR. It indicated that subclinical LV dysfunction had occurred in individuals with obesity before LVEF was reduced. Moreover, global myocardial peak strain decreased with increasing H-PDFF (with R-PS and L-PS) and P-PDFF (with C-PS and L-PS) independent of MetS in the over-all cohort, indicating that higher ectopic fat in the liver and pancreas was associated with worse subclinical LV function. Similarly, Levelt et al.  found thIn our study, higher VAT was independently associated with worse subclinical LV function manifested by lower |L-PS| in both the over-all cohort and obesity subgroup. Nevertheless, the inverse association between SAT and LV myocardial deformation observed in the over-all cohort was not shown in the obesity subgroup after adjusting for covariates. These findings suggest that VAT may play a more critical role in the connection with LV subclinical dysfunction than SAT in individuals with obesity. A prior study reported similar observations in subjects from the general population without a history of CVD, finding an independent association for VAT to measures of LV remodeling but not for SAT . The undThe present study did not find a significant association between hepatic shear stiffness and EAT; although there were significant associations of hepatic shear stiffness with LV geometry and function in univariate analyses, they were attenuated when taking account of age, sex, and MetS. Our findings are not in accordance with prior studies , 13. BroFirst, this is a single-center, cross-sectional study. Given that the design precludes inferring the causality of the observational interferences, it is unclear whether there would be a reversion of myocardial function with the reduction of visceral and ectopic fat depositions. Besides, it is a cross-sectional and exploratory study, and correction for multiple comparisons and the interdependencies of some cardiac MR measures, such as LVEF and LVEDV, were not taken into account. The given p-values are used for exploratory purposes, and the results with a p value < 0.05 mainly provide a possible positive signal for future research. Further longitudinal and multi-center studies with more sophisticated statistical methods are needed to corroborate our findings in the future. Second, our sample size, especially for the subjects with liver fibrosis, is relatively small; and no subject had diabetes. While on the other hand, our study inadvertently eliminated the potential effect of diabetes on the association between abdominal adiposity and cardiac geometry and function. A larger study population with sufficient subjects in diverse fibrosis stages and hyperglycemic states is required to assess the associations in various subgroups. Third, we utilized LV two- and four-chamber cine images in the long-axis view for the measurement of global strain parameters, consistent with some prior studies , 29. FurIn adults free of overt CVD, higher H-PDFF, P-PDFF, SAT, and VAT were associated with worse subclinical LV function, and LVEDV and SV increased with P-PDFF, SAT, and VAT independent of MetS. In individuals with obesity, VAT rather than SAT was associated with subclinical LV dysfunction. Hepatic shear stiffness showed no independent association with EAT or LV geometry or LV function. Our results suggest that ectopic fat depositions in the liver and pancreas and excess abdominal adipose tissue pose a risk of subclinical LV dysfunction beyond MetS-related CVD risk factors, and VAT may play a more considerable role as a risk factor for subclinical LV dysfunction than SAT in obesity. The mechanisms underpinning these associations and their longitudinal clinical implications need to be further investigated.Additional file 1: Table S1. Intra- and interobserver variability of cardiac and abdominal MR measures.


Systemic right ventricular failure after physiologic repair for dextro‐transposition of the great arteries can be managed with durable mechanical circulatory support; however, the right ventricular morphology, such as intervening papillary muscles, presents challenges to inflow cannula positioning. Papillary muscle repositioning is an innovative technique to circumvent obstructive anatomy. Cardiac catheterization demonstrated low cardiac output 1.4 L/min) and elevated pulmonary capillary wedge pressure (24 mmHg). While admitted, his clinical condition deteriorated to Interagency Registry for Mechanically Assisted Circulatory Support level 2 with progressive decline of hemodynamics despite inotropic support. Cardiac magnetic resonance imaging revealed severe global systolic function and calculated an end‐diastolic volume index of 164 ml/m.4 L/min 22.1After redo sternotomy, the aorta was cannulated centrally, and bicaval venous cannulation was achieved via the femoral vein and left innominate vein. The anatomy was confirmed to be that of D‐TGA with an anterior, rightward aorta originating from the RV. We selected a site on the diaphragmatic surface of the RV near the acute marginal border for inflow insertion, and transesophageal echocardiography (TEE) guidance revealed a heavily trabeculated RV Figure . To ensu3We describe the unique presentation of HM3 implantation within a systemic RV for D‐TGA after Mustard palliation. While the atrial switch is now uncommonly performed as the principal operation, there are long‐term survivors who inevitably develop systemic RV failure mostly due to an inability of the morphologic RV to sustain systemic pressures.HM3 implantation in the LV apex requires the inflow cannula to be inserted parallel to the interventricular septum and directed toward the atrioventricular valve. This can typically be performed without cardioplegic arrest and with reliance on TEE guidance. In our D‐TGA scenario, there are several anatomic considerations that make apical implantation technically challenging. The morphologic RV is more tubular as opposed to the cone‐shaped LV, and the less‐developed RV apex, especially one that is hypertrophic or dilated, may not necessarily correspond to the apex of the heart. As such, insertion points can vary from the anterior to the diaphragmatic RV. The RV is also relatively more trabeculated, and the abundance of muscle bundles and papillary muscles can interfere with device placement and subsequent inflow drainage.For these reasons, we advocate for cardioplegic arrest to decompress the heart and position the device under direct vision. Excision of trabeculations and the moderator band have been reported,The patient recovered well and was discharged on postoperative Day 43. Positioning of the device on chest roentgenogram can be compared to that of “normal” left ventricular (LV) positioning (Figure The authors declare no conflict of interest.We waive the option to obtain consent as the following writing involves no more than minimal risk to the patient. This waiver will not affect the rights and welfare of the described subject. If appropriate, the patient will be provided with additional pertinent information gained from the readership.


We described the usefulness of using magnetic resonance imaging (MRI) T2* of the pancreas, liver, and heart were executed on all patients in the same setting. Objective values of iron overload in these organs were obtained using the MRI post-processing software from online software.We conducted a cross-sectional study on 39 patients with thalassemia major in one of the tertiary university hospitals for a 1-year period. Demographic data were collected from the patient's history. MRI T2P < 0.001). No significant correlation was found between the relaxation time of the pancreas with the liver and the heart with the liver.A total of 32 (82.1%) patients had pancreatic iron overload including 2 patients (5.1%) with severe iron overload and 15 patients (38.5%) with moderate and mild iron overload, respectively. Nine patients (23.1%) had myocardial iron overload, which included 3 patients (7.7%) who had severe cardiac haemosiderosis. Notably, 37 patients (94.9%) had liver iron overload, which included 15 patients (38.5%) who had severe liver haemosiderosis. There was a moderate positive correlation between the relaxation time of the pancreas and heart haemosiderosis (r = 0.504, Pancreatic haemosiderosis precedes cardiac haemosiderosis, which establishes a basis for initiating earlier iron chelation therapy to patients with thalassemia major. Thalassemia major is a type of haemolytic anemia. There are many different types of thalassemia, and the most common type is beta thalassemia major, which is characterized by biosynthesis defect of beta-globin chains , 2. The Advances in B-thalassemia major management have improved survival. Relatedly, it is paramount to have methods of non-invasive iron overload estimation in different organs of patients with thalassemia. In the past, serum ferritin had been utilized as a marker for iron store evaluation, but conditions such as inflammation, infection, liver disease, or hepatitis can raise ferritin levels and, thus, it is a non-specific marker for iron storage and illness in general –4. Altho* magnetic resonance imaging (MRI) technique is a valid, accurate, and non-invasive method for the evaluation of tissue iron storage. This method has revolutionized thalassemia patient management, mainly in modifying iron chelation regimens  all patients were those with thalassemia major who received regular blood transfusions at 2-to-4-week intervals for at least 18 months prior to research participation, (2) received iron chelation therapy, (3) had regular serum ferritin with the most recent is within 1 week before or after the MRI pancreas, and (4) verbal and written consent obtained prior to the study from the patients and the parents for the pediatric patients.The exclusion criteria especially for the pediatric population included (1) patients who were younger than 5 years old (since they would not receive enough transfusion), (2) patients who required general anesthesia or sedation for the MRI scan, (3) patients who were uncooperative, (4) patients who had absolute or relative contraindications for MRI , and (5) those who were claustrophobic. Criteria 4 and 5 are also applicable to the adult population.* scan appointment. The MRI was performed in a 1.5 Tesla Siemens Avanto MRI scanner  using a standard body coil. The MRI scans were synchronized to the cardiac cycle using a standard ECG gating. The T2* gradient echo pulse sequence was obtained in 3 specific regions . MRI cardiac T2*, liver, and pancreas were performed with the breath-hold technique. The T2* technique for the heart, liver, and pancreas was as follows: heart (bright blood) – slice thickness: 10 mm; field of view (FOV): 400 mm; flip angle: 20; matrix: 256 × 128; TE: 2.0 to 3.0 minimum; increment from 1.5 to 2.0 ms; up to 16 ms; number of TEs: 10; bandwidth: 810 Hz/pixel; flow compensation: on; fat saturation: off; heart (dark blood)–other parameters were similar except for the flow compensation (off) with extra double inversion pulse and TI to extend to diastole; liver–slice thickness: 10 mm; FOV: 400 mm; matrix: 96-128 × 64-96; flip angle: 20; and time to echo (TE): ideally 0.8–1.3 ms (minimum), increments (echo spacing) of 0.8 to 1.0 ms; up to 12 ms; number of TEs: 10; bandwidth: 810 Hz/pixel; flow compensation: on; fat saturation: off; TR: 100–150 ms. In contrast, the T2* pancreas technique adopted similar to the T2* liver technique except for the reduced slice thickness of 6 mm. We imaged the pancreas in axial cuts at the pancreatic neck and body where we could identify the consistent anatomy, i.e., confluence of splenic vein and superior mesenteric vein . We discovered that selecting the region of interest (ROI) at the pancreatic neck or proximal pancreatic body would produce the most consistent result because this part of the pancreatic parenchyma is less likely to be atrophied. In addition, there is less motion artifact from the adjacent small bowel loops or adjacent vessels pulsating artifacts and there is more pancreatic parenchyma for the purpose of drawing ROI.Patients who fulfilled the inclusion criteria were recruited from the hospital paediatric day care center and then arranged for an MRI T2* examination  took ~15 to 20 min per patient wherein having an extra pancreas scan would take an additional 1 to 2 min relative to the usual routine scan.The whole MRI T2* calculation at the interventricular septum (excluding cardiac vein), liver , and pancreas (excluding splenic artery and vein). This software calculates T2* in an ROI-based algorithm. The mean signal intensity of the ROI was measured for each image and, subsequently, was plotted against the TE. A mono-exponential trendline was incorporated with an equation in the form: y = Ke–TE/T2*, where y represents the image signal intensity, K represents a constant, and TE represents the echo time.Post-processing of these images was performed with an online open-source tool that has been validated against CVI 42 version 5.1 . By using the online open-source automated truncated software, we drew ROIs to allow T2* was calculated by using a mono-exponential equation to the time course of each pixel, and the map image was produced based on the pixel's T2* value. The T2* RGB map of the liver and heart was created for all patients. The T2* map became the guide to choose the ROI homogenously. The mean T2* pixel values in the ROI were obtained for the liver and heart. The results were tabulated using the statistical analysis of data expressed as mean ± standard deviation, median, frequency, and percentage. The normal T2* value of the heart, liver, and pancreas was based on previous literature . This study included 39 patients that consists of 19 men and 20 women. The mean age was 23.7 years with an age range between 9 and 37 years. The demographic characteristic of patients is shown in * are summarized in * , and a weak correlation was seen between serum ferritin and cardiac relaxation time  and a moderate negative correlation between ferritin and pancreas relaxation time . When comparing between the relaxation time of liver, pancreas, and heart T2*, there was a moderate positive correlation between the relaxation time of pancreas and heart   patients had pancreatic iron overload, including 2 patients (5.1%) who had severe iron overload, 15 patients (38.5%) who had moderate iron overload, and 15 patients (38.5%) who had mild iron overload . Notably < 0.01) . However < 0.01) .* value for the liver was 3.84 ms for the online automated truncated open-source software and 5.45 ms for the color RGB map tool. The mean T2* value for the heart was 27.67 ms for the online tool and 32.04 ms for the color RGB map tool. In the liver, the mean difference was 1.608 ms (95% CI 0.963 to 2.252 ms) with a correlation coefficient of 0.595 (moderate correlation), while in the heart, the mean difference was 4.367 ms (95% CI 1.559 to 7.174 ms) with a correlation coefficient of 0.782 (strong correlation) (The mean T2elation) .* value, resulting in a mild or moderate haemosiderosis categorization for the patient. Correlation coefficients for T2* values measured between the automated truncated online software and the color RGB map software were 0.951 , 0.433 , and 0.243   .* values derived from the two software for both liver and heart iron content, which results in a significant difference in iron content categorization, especially for the liver iron, as the T2* value range among different categories was small.These results indicated that there was a marked difference in the mean T2* MRI has become the technique of choice for the non-invasive quantification of both hepatic and myocardial iron overload. It shows a good sensitivity when compared with the liver iron content of liver biopsies, while cardiac T2* correlates inversely with cardiac iron concentration ] showed pancreatic haemosiderosis, while only 9 (23.1%) patients showed cardiac haemosiderosis categorized between moderate to severe cardiac haemosiderosis. Interestingly, they had similar categories for their pancreatic haemosiderosis, for example, those who had severe pancreatic haemosiderosis also had severe cardiac haemosiderosis to a moderate degree. The similar degree of iron overload severity in both the heart and pancreas prove that the pancreas, like the heart, exclusively loads non-transferrin-bound iron (NTBI). The kinetics of pancreatic iron loading and unloading are intermediate between the heart and the liver, making the pancreas T2ver iron . This stver iron , 17.* preceded cardiac T2* iron loading. This scenario provides an earlier iron therapeutic window for clinicians to intensify the iron chelating medication to prevent diabetes and, in the longer prospective, prevent cardiac failure. This study concurs with Noetzli et al. . This is explained by the fact that both pancreas and cardiac iron overload share the same iron loading pathway. This finding is similar to other study findings  have different parenchymal sizes and anatomical positions between participants. Furthermore, in participants who have pancreatic atrophy, the pancreatic neck and proximal body still have considerable parenchyma for ROI to be drawn and, thus, are suggested to be a standard ROI during the sampling of the T2* measurement.There was moderate agreement between pancreas and cardiac T2findings , 20, 21.findings . There w studies , which s* and ferritin that is in line with previous studies  to quantify T2culation . If the * values , 29.* online tool is a more user-friendly software for estimating iron content, especially for severe iron load, relative to the commercial color RGB map pixel-based approach. Although both software can give approximately similar results, the latter software involves tedious work to manually omit the background noise values at higher TE values (* value range for each liver haemosiderosis category is close to each other and small in their value ranges, in comparison with the pancreas and the heart. Therefore, a small increase in the T2* value would result in different categories of liver haemosiderosis when using these two software.The automated truncated T2E values , 30. Thi* signal. The pancreatic T2* measurements are more difficult than the liver or cardiac T2* because the pancreas is an irregularly structured gland with a variable course. The splenic vein and portal venous confluence can be a useful landmark but this landmark is not present in splenectomised patients. In addition, bowel gas can artificially lower the T2* values in the pancreas but never <10 ms; this is a reason why 10 ms is a better threshold for significant pancreatic iron overload. Older patients also had a significant fatty replacement with high iron concentrations and gland involution over time makes it harder to define the gland boundaries.This study's limitations include the lack of gold standard biopsy data to verify the pancreatic MRI T2* relaxation time for the pancreas in addition to the heart and liver during the routine annual MRI T2* scanning has proven to be useful for regularly transfused patients with thalassemia major without actually increasing the MRI scanning time by more than 5 min. Pancreatic haemosiderosis precedes cardiac haemosiderosis. The online open-source software is useful and user-friendly and is able to provide reliable T2* methods for quantifying organ iron deposition.T2Data are available on request due to privacy or other restrictions.The studies involving human participants were reviewed and approved by Research Ethics Committee, Universiti Kebangsaan Malaysia. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.HH: conceived the presented idea and planned and executed the study. K-AG: conceived the presented idea and planned the study. C-KL, ZA, and JH: verified the analytical methods and clinical advice. WW: coordinate and perform the examination. HA: verified the analytical methods. FM: conceived the presented idea, planned and executed the study, supervised the findings of this study, and edited the manuscript. All authors discussed the results and contributed to the final manuscript.This research has been funded by institution research grant FF-2017-122.The 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In aortic stenosis (AS), the heart transitions from adaptive compensation to an AS cardiomyopathy and eventually leads to decompensation with heart failure. Better understanding of the underpinning pathophysiological mechanisms is required in order to inform strategies to prevent decompensation.In this review, we therefore aim to appraise the current pathophysiological understanding of adaptive and maladaptive processes in AS, appraise potential avenues of adjunctive therapy before or after AVR and highlight areas of further research in the management of heart failure post AVR.Tailored strategies for the timing of intervention accounting for individual patient’s response to the afterload insult are underway, and promise to guide better management in the future. Further clinical trials of adjunctive pharmacological and device therapy to either cardioprotect prior to intervention or promote reverse remodeling and recovery after intervention are needed to mitigate the risk of heart failure and excess mortality. The true global burden remains unknown in the absence of universal availability of cardiovascular imaging ,2. AortiThis excess risk has been poorly captured in the literature, with lack of evidence about the mechanisms of excess mortality which could guide potential treatment options. As a result, current VHD guidelines offer limited guidance on the management of valvular heart failure after valve intervention.Identification of pathological mechanisms underlying heart failure post AVR and appropriate therapeutic strategies post intervention may enhance our precision treatment of patients referred for AVR and improve general AS management beyond valve replacement. In this review, we therefore aim to appraise the current evidence of heart failure mechanisms in AS (before and after AVR) and highlight areas of further research in the management of heart failure post-AVR.1.1.The natural history of AS is largely determined by the interplay between the stenotic valve, the myocardium, and the vasculature, where the response of the LV ultimately determines symptoms and outcomes. AS has historically been attributed to age-related ‘wear and tear,’ however its pathogenesis occurs as a result of complex processes similar to those occurring in atherosclerosis. The initiating process is thought to be endothelial damage secondary to mechanical wall stress and reduced shear stress, which combined with lipid deposition can trigger valvular inflammation. Later pathology is dominated by valvular fibrosis, calcification, and neo-angiogenesis within close proximity of areas of inflammation .The stages of AS can be defined according to the anatomy of the valve, the presence of symptoms, valve hemodynamics and the consequences of these for the structure and function of the LV. A patient with normal valve hemodynamics at risk of developing AS (Stage A) progresses to valvular obstruction with hemodynamic changes (Stage B), with no symptoms at this stage. This may develop into asymptomatic severe AS . Ultimately, the patient may experience symptoms (Stage D), which can be further subdivided based on the hemodynamic profile: high gradient (D1), low-gradient and low-flow with impaired LV systolic function (D2), or with low-gradient and low-flow but preserved systolic function or paradoxical low-flow (D3) . GenereuThe pressure overload due to the stenotic aortic valve triggers a hypertrophic response within the LV myocardium. The pattern of remodeling can vary between individuals, under the influence of factors including sex, age, the presence of co-existent coronary artery disease (CAD) or hypertension . AS prog1.2.Our understanding of AS-related mortality and the technology to treat it have dramatically changed over the last 50 years. First, the availability of surgical AVR (SAVR) and transcatheter aortic valve implantation (TAVI) has transformed outcomes for patients with AS. Improvement of surgical techniques has led to a reduction in mortality risk associated with isolated SAVR, now quoted to be as low as 1% . Recent Despite advances in aortic valve procedures, outcomes remain poor. Timing of intervention is critical to mitigate irreversible damage. There is trial evidence that intervention in asymptomatic patients with severe or very severe AS translates into reduced mortality, regression of LVH and sustained LV systolic function, suggestive of reverse remodeling prior to irreversible myocardial damage . Randomi1.3.Presentation with heart failure prior to AVR is common, and is an overlooked and life- threatening problem. Wald et al showed that out of 684 patient admissions coded with a diagnosis of aortic stenosis, 141 (21%) emergencies admission with decompensation of AS and these patients had a high in-hospital mortality of 16% . Across Although AVR significantly attenuates the natural history of AS and reduces subsequent progression to heart failure and death , it is nPost TAVI, 11.7% of patients experience a readmission due to a cardiovascular cause at 1 year, with heart failure the most common cause, and being associated with increased mortality . In the 2.2.1.Although there have been significant advances in the implantation techniques and longevity of prosthetic valves, complications affecting their structure and hemodynamic performance persist. These may be evaluated as structural valve dysfunction, due to problems inherent in the prosthesis, or non-structural valve dysfunction, in the absence of these using a defined staging system as proposed by Pibarot and colleagues . Explori2.1.1.Patient prosthesis mismatch (PPM) occurs where the effective orifice area of the prosthetic valve is too small relative to the patient’s body habitus, resulting in high transvalvular gradients. The incidence of PPM is different according to the type of intervention and the bioprosthetic model used. A higher prevalence and severity of PPM has been demonstrated for SAVR compared to TAVI; the PARTNER trial investigators demonstrated an incidence of 46.4% in patients following TAVI compared with 60% following SAVR . HoweverGiven these potentially detrimental effects of PPM, clinicians efforts should be maximized to avoid PPM. Re-intervention may be indicated if the patient develops symptoms attributable to PPM or if unfavorable hemodynamic effects develop, with the options of re-do surgery or a transcatheter valve-in-valve (ViV) procedure, with fracturing of the surgical valve stent . As demo2.1.2.Another important hemodynamic sequela after AVR is paravalvular regurgitation (PVR), which can contribute to the residual hemodynamic load of the LV and can also be associated with reduced regression of LVH. PVR can occur due to undersizing, malpositioning, or lack of adequate sealing due to irregularities or calcification of the native AV annulus. While PPM is more frequent after SAVR, significant PVR is observed predominantly following TAVI rather than SAVR . There i2.1.3.Structural deterioration is the major determinant of bioprosthetic longevity. Serial echocardiographic assessment is the principal modality to assess longitudinal hemodynamic changes of the prosthetic performance and establish a diagnosis of structural valve deterioration (SVD). SVD rates of surgical aortic bioprostheses from real-world data are in the range of 4% to 5% per valve-year ,44. 5-ye2.1.4.Valve thrombosis is a recognized structural complication following both TAVI and SAVR. The risk of valve thrombosis in mechanical valves is largely mitigated by therapeutic oral anticoagulation. Bioprosthetic valve material is also thrombogenic, with the risk of thrombosis remaining highest within 3 months of implantation until endothelialisation of the stent material occurs. Nevertheless, the risk of thrombosis of bioprosthetic aortic valves remains low, with a rate of 3% per 100 patient years according to a large meta-analysis . Valve t2.2.Myocardial stressors during cardiac surgery such as ischemia, ischemia-reperfusion injury, cardioplegia, inflammation and myocyte necrosis can influence the post-operative course in the short term and prognosis in the long term. It is well recognized that cardiac surgery and cardiopulmonary bypass (CPB) present a significant physiological and immunological injury to the body. Ischemia-reperfusion injury following CPB can induce a pro-inflammatory response, both secondary to contact of patient blood with the CPB tube system as well as to ischemic-perfusion injury . Pro-inf2.3.AVR decision making mainly relies upon the presence of symptoms attributable to AS in association with echocardiographic criteria of severe AS. Other than reduced LVEF, there are no recommendations with regard to anatomic or functional consequences of AS on the myocardium, despite evidence of the prognostic significance of cardiac damage. As aforementioned, a staging system has been developed according to the extent of cardiac damage and has been correlated with worse outcomes post AVR . Biomark2.4.As discussed above, AS is not solely a disease of the valve but also of the myocardium. The response of the myocardium to the increased hemodynamic load presented by the stenotic valve is a significant determinant of outcome and early identification may therefore potentially guide timely valvular intervention. Severe AS is associated with alterations in myocyte architecture, accumulation of interstitial myocardial fibrosis and edema, and may co-exist with infiltrative myocardial disease.2.4.1.LVH in AS develops in order to reduce wall stress and maintain cardiac output. Increase in myocellular volume is accompanied by intracellular changes such as modification of intracellular proteins . Despite LVH representing a hallmark of LV adaptation to AS, there is considerable heterogeneity in the degree of hypertrophy for a given stenosis severity. Reported factors affecting the magnitude of LVH in AS include presence of arterial hypertension, age, early decline of glomerular filtration rate, metabolic syndrome and obesity, and angiotensin-converting enzyme polymorphism ,67.2.4.2.With progressive stenosis, microvascular dysfunction and reduced capillary density ensue, accompanied by impaired myocardial blood flow, diminished coronary reserve, compensatory vasodilation of the remaining vessels, and anginal symptoms. Following observations from CMR-biopsy studies which showed an endo- to epicardial gradient for focal fibrosis, microvascular ischemia is hypothesized to be the main driver of replacement fibrosis in AS . Whether2.4.3.With progressive LVH, changes in collagen quality and quantity results in diffuse interstitial matrix expansion or diffuse fibrosis. Diffuse fibrosis is assessed via CMR pre- and post-Gadolinium contrast T1 mapping to calculate the extracellular volume fraction (ECV). ECV has been extensively validated against histological fibrosis . OutcomeParadoxically, at one-year after successful AVR, CMR-ECV was found to increase when compared to preprocedural assessment due to a higher reduction in myocellular volume relative to extracellular space . Novel p2.4.4.Eventually, hypertrophy and resultant microvascular ischemia results in apoptosis of hypertrophied cardiomyocytes with subsequent replacement by fibrotic tissue . Identif2.4.5.Recent AS studies have proposed a potential role of oedematous/inflammatory processes in myocardial remodeling using CMR T2 mapping, a technique that is well established in the assessment of myocardial edema ,82,83. TCardiac decompensation resulting in peripheral edema is a frequent finding in the advanced stages of AS and has been shown to also lead to myocardial edema, thereby also affecting CMR-ECV measurements 76]. Moreover, higher degrees of fluid overload – as determined by quantitative assessment – are associated with progressively worse post-interventional outcomes . Moreove.2.4.6.Expansion of extracellular space in AS may in some patients encompass mechanisms beyond fibrosis and edema. Cardiac amyloidosis (CA) is an infiltrative disorder which involves the myocardial deposition of misfolded proteins – with transthyretin (ATTR) CA as the most common CA subtype identified in elderly AS patients. As a result of active screening ascertainments, a considerable overlap of severe AS and CA has been found – affecting approximately 1 in 8 patients undergoing TAVI ,86.Despite the double hit of AS and CA, no mid-term survival difference after TAVI has been demonstrated for AS-ATTR compared to lone AS ,86. Howe3.While the hemodynamic effects of AVR on the stenotic valve are immediate, the prognosis of AS is largely determined by the ventricular response to relief of outflow obstruction. Regression of remodeling following AVR can predict outcomes ,90. ThisEchocardiography remains the first-line assessment tool, providing information on valve structure; valve hemodynamics, using Doppler-derived measurements; ventricular geometry using LV mass calculations; and numerous parameters of ventricular function including LVEF, strain, and diastology ,92. FollDiastolic dysfunction improves later (~3 years) with further regression of LVH out to 10 years dependent on baseline hypertrophy and co-existent arterial hypertension with other factors likely to play a role as well  ,97. Base4.Conduction abnormalities commonly complicate AVRs and are caused by direct mechanical insult from valve implantation to the intrinsic conduction system ,101. In Beta-blockers are commonly used to control tachyarrhythmias and other common indications such as previous myocardial infarction or heart failure. There is paucity of evidence on the association between beta blockade and long-term outcome following AVR. Data from the SWEDEHEART registry demonstrated an increased all-cause mortality risk associated with beta-blocker use in patients post AVR, which persisted upon post subgroup analysis of patients with AF . While a5.Outcomes following AVR remain a key focus of study and may inform management strategies to enhance these, such as for post-operative arrhythmias and heart failure . MedicalActivation of the renin-angiotensin-aldosterone system (RAAS) is implicated in the myocardial remodeling in AS; raised myocardial angiotensin converting enzyme (ACE) concentrations are associated with AS and AR, which in turn is associated with increased collagen and fibronectin synthesis, leading to myocardial fibrosis . Drugs iOther strategies may include the anti-fibrotic effect of torasemide affecting the extracellular collagen processing, sodium–glucose cotransporter 2 inhibitors via their metabolic pathway effect, TGFβ1 signaling inhibitors like pirfenidone, and immunomodulators via reduction of myocardial inflammation . Beyond 6.Aortic valve stenosis causes adverse cardiac remodeling that is only partially reversed by AVR. Multi-modality imaging plays an essential role in not only diagnosing the valvular stenosis but also the myocardial and cardiac damage resulting from AS. Myocardial fibrosis and scarring is associated with excess morbidity, hospitalization for heart failure and mortality after AVR. Heart failure management is currently not tailored to patients with valvular heart disease after valve intervention, and further trials of drug therapies are required to prove efficacy in this patient population.7.Aortic stenosis has implications for patient outcomes, with even moderate aortic stenosis being associated with excess mortality . TherefoIntervening at the right time  is essential to balance upfront risk of intervention and the lifetime risk of a prosthetic valve against progressive cardiac damage due to AS. Multiple randomized clinical trials are trying to define this ‘sweet spot’ for intervention. But valve intervention is not a total cure, and no matter how well we screen or surveil, there will always be some patients who present late – we therefore need therapies beyond AVR.We do not know why people die after AVR, but death rates are high . Without understanding the most prevalent mode of death , knowing where to direct research efforts into potential therapeutic strategies (drug or device-based) is challenging. Furthermore, conventional heart failure therapy (drug or device-based) relies on LVEF cutoffs, which are poor measures of LV systolic performance in AS before and after AVR when hypertrophy is present and LVEF is supra-normal, like in hypertrophic cardiomyopathy; ‘AS cardiomyopathy’ is essentially a HFpEF phenotype. Currently after successful SAVR or TAVI, AS patients are typically discharged without assessment or active management of residual risk; current guidelines offer no specific guidance on assessing risk post-AVR, particularly detecting and managing heart failure in VHD, with the exception of anticoagulation for atrial fibrillation and pacemaker implantation for high-grade atrio-ventricular block.So how may peri-AVR valve care look differently in 5–10 years’ time ? With be


In addition to evaluation of ischemia, the assessment of cardiac function and remodeling is important in all cardiac diseases. However, since 15O-water is freely diffusible and standard uptake images show little contrast between the myocardium and blood pool, the assessment of left-ventricular (LV) volumes and ejection fraction (EF) is challenging. Therefore, the aim of the present study was to investigate the feasibility of calculating LV volumes and EF from first-pass analysis of 15O-water PET, by comparison with cardiac magnetic resonance imaging (CMR) using a hybrid PET/MR scanner.15O-water first-pass images (0-50 seconds) were analyzed using the CarPET software and the CMR images were analyzed using the software Segment, for LV volumes and EF calculations. The LV volumes and EF were compared using correlation and Bland–Altman analysis. In addition, inter- and intra-observer variability of LV volumes and EF were assessed for both modalities.Twenty-four patients with known or suspected CAD underwent a simultaneous ECG-gated cardiac PET/MR scan. The r > 0.84) and moderate for EF (r = 0.52), where the moderate correlation for EF was partly due to the small range of EF values. Agreement was high for all parameters, with a slight overestimation of PET values for end-diastolic volume but with no significant mean bias for other parameters. Inter- and intra-observer agreement of volumes was high and comparable between PET and CMR. For EF, inter-observer agreement was higher for PET and intra-observer agreement was higher for CMR.The correlation between PET and CMR was strong for volumes (15O-water PET scan with high accuracy and comparable precision as with CMR.LV volumes and EF can be calculated by first-pass analysis of a The online version contains supplementary material available at 10.1007/s12350-022-03154-7. Clinical representation of different remodeling patterns varies and the need for a classification is emphasized. For example, the end-diastolic volume (EDV) differentiates between concentric and eccentric remodeling patterns9 and the left-ventricular ejection fraction (LVEF) or LV systolic function is a powerful predictor of cardiac mortality on its own.13 Furthermore, differentiation of heart failure with reduced EF (HFrEF) from heart failure with preserved EF (HFpEF) is important since there exist clinically proven treatments to improve morbidity and mortality in HFrEF but for HFpEF there is only the recently approved SGLT2-inhibitors.15Positron emission tomography (PET) is a beneficial tool in both diagnosis and prognosis of coronary artery disease (CAD) and is a recommended tool in the assessment of obstructive CAD and ischemia.82Rb and 13N-ammonia, LV volumes and EF are routinely assessed through ECG-gated late-uptake images.17 This is not feasible for 15O-water, while considered the gold standard for noninvasive MBF measurements, the lack of net uptake rules out the use of such ECG-gated late-uptake images. The feasibility of calculating LV volumes and EF from 15O-water PET has been shown in two previous studies utilizing ECG-gated first-pass or parametric images.19 In one of those studies, the optimal time range for the first pass was defined after inspection of the dynamic images, resulting in ECG-gated images of the time points in which the 15O-water is confined to the left side of the heart. The other study used a time consuming approach and imported ECG-gated parametric or first-pass images into a commercially available SPECT software. While both studies showed promising results toward the feasibility of calculating LV volumes and EF, their approaches are less suitable for a rapid clinical workflow.For PET uptake tracers including 22 In this study, LV volumes and EF were assessed with 15O-water PET and CMR simultaneously in a hybrid PET/MR scanner with the aim to verify a method for measurement of LV volumes and EF calculations from 15O-water PET feasible for clinical practice. To the best of our knowledge, this is the first study that assessed LV volumes and EF from 15O-water PET simultaneously with CMR using a hybrid PET/MR, which should be considered the ultimate reference standard.In this study, a faster approach ready for clinical implementation is presented by using a standardized fixed time range for the first pass and a highly automated analysis performed in the same software used for standard MBF calculations. Cardiac magnetic resonance imaging (CMR) is considered the gold standard for volume and ejection-fraction estimation due to the method’s excellent differentiation of myocardium from the blood pool and the lung tissue with high reproducibility of volume estimates. 23 and none had any known history of ST-elevation myocardial infarction. Patient characteristics are described in Table Twenty-four patients with known or suspected CAD were included. All had intermediate pre-test probability of CAD according to ESC guidelines 2013All patients underwent a simultaneous ECG-gated cardiac PET/MR scan. Data were acquired using an integrated 3 T PET/MR scanner .15O-water . A two-point Dixon sequence was acquired during end-expiration breath hold for the creation of an attenuation correction map. Images were reconstructed using a time-of-flight ordered subsets expectation maximization  algorithm both as gated first-pass images and as nongated dynamic images sorted into 22 frames . Data from the first 10 to 50 seconds of the scan were reconstructed as 8-bin cardiac-gated blood-pool images.A standard clinical protocol was used where a 6 minutes ECG-gated scan, acquired in list mode, was started simultaneously with an automated fast bolus injection of 400 MBq xy: 380 mm, in plane pixel size: 1.48 mm, and slice thickness: 8 mm). The whole heart was covered in 10 to 12 slices, depending on the size of the heart. Data were ECG gated, and the cardiac cycle was divided into 20 gating bins.A balanced steady-state gradient-echo (FIESTA) cine sequence was acquired in short-axis view during breath hold  and venous (VV) spill-over fraction, computed in the MBF analysis,25 enables each seed to be assigned to the left or right heart, based on the VA and VV value of the voxel with the maximum of each seed, respectively.PET images were analyzed using a prototype first-pass gating module in the in-house CarPET software. First, the left and right side of the heart in the first-pass images were separated using a steepest-path approach.15O-water concentration, and voxels on either side of the valves will reach a different seed. Identifying seeds on either side of the mitral valve plane will result in identification of the LV cavity. To identify the likely location of the valve plane, indentations in the long-axis profile are identified for multiple angles around the long axis. For each angle, a mask of low-activity voxels is defined and the distance from one to the other side is computed. Local minima in this distance are considered an indentation in the activity, and at one of these indentations is assumed to be the atrioventricular border. Once a set of possible indentations are found, the set most likely to represent the border is identified and a 3D plane is fitted through the points. This 3D plane is stored as initial suggestion of the mitral valve plane, which the user can adjust prior to final calculations of the cardiac volumes. In Fig. 1S, a graphical representation is shown.It is assumed that the cardiac valves, while below the resolution of the PET scanner, result in a lowered Finally, all seeds on the apical side of the valve plane were included in the final volume, and final volumes of EDV and end-systolic volume (ESV) were obtained using a count-based approach. Stroke volume (SV) was calculated as SV = EDV − ESV and ejection fraction as EF = SV/EDV.The analysis was performed blinded by two observers to estimate the inter-observer variability of the method. For estimation of the intra-observer variability, one of the observers performed a second blinded analysis of the data. To avoid recognition bias, a time interval of at least 4 weeks passed between the first and second intra-observer analyses.26 Endocardial borders were manually contoured in short-axis view, both in the end-diastolic and end-systolic phase of the cardiac cycle. The trabeculae and papillary muscles volume were included in the left-ventricular blood pool. The most basal slice needed to display at least 50% visible myocardial circumference to be included in the analysis. The LV outflow tract was included in the blood volume by using the aortic valve as the lateral border when drawing the endocardial contour. Stroke volume was calculated as SV = EDV − ESV and ejection fraction as EF = SV/EDV.CMR images were analyzed using the freely available software Segment .LV contouring was performed blinded by two observers to estimate the inter-observer variability of the method. For estimation of the intra-observer variability, one of the observers performed a second blinded analysis of the data. To avoid recognition bias, a time interval of at least 4 weeks passed between the first and second intra-observer analyses.r). Agreement was assessed using Bland–Altman analysis, the nonparametric paired Wilcoxon sign-rank test, and the intra-class correlation coefficient (ICC). The repeatability coefficient (RPC) was calculated as 1.96 × SD of differences. Inter- and intra-observer variability was assessed using ICC for agreement and Bland–Altman analysis. Statistical analysis was performed in Matlab .Data are presented as mean values ± standard deviation (SD). Correlation of LV volumes and EF from PET compared with CMR was assessed using linear regression and the Pearson’s correlation coefficient  and EF .There is one outlier in the results where PET clearly underestimates EF and SV. For this patient, the results showed high inter-observer agreement for both PET and CMR. No explanation for the underestimation of values by PET could be found. If the outlier was removed from the results correlation and/or agreement increased for SV  so increasing the activity comes at a fairly low cost of additional radiation dose, and the trade-off between image quality versus the ALARA principle could be revisited. Furthermore, the spatial resolution differs between the methods where PET is limited by a low resolution compared to CMR, but on the other hand, PET has the advantage of being a very sensitive method where even small changes in tracer uptake can be identified and implemented in model calculation for improving the estimation of functional measures.32 Also, the inherent difference of blood-pool segmentation of the PET images to edge detection of the CMR images may contribute to an impaired agreement of the two methods. However, as CMR is the gold standard for LV volumes and EF estimates, it is the measure we want to compare to for a proper clinical validation. Finally, EDV was the only parameter with a statistically significant mean bias. The reason for this is unclear but it is probably inherent to the implementation of the method. The seed approach requires a gradient, which is present when the atrioventricular valves are closed. EDV is the time point at which the valves close and if a bin is chosen when the valves are still open, it may challenge the valve plane positioning.Even if agreement of LV volumes and EF between 15O-water PET evaluations. For evaluation of concomitant structural heart disease such as LV dilation or decreased systolic function, echocardiography or CMR are recommended as the baseline test in recent guidelines.1 However, there are several clinical scenarios were assessment of LV volumes and EF from PET would add clinical value, e.g., for patients with inconclusive echocardiography and contraindications for CMR, when PET is performed prior to echocardiography, or when PET is performed long after echocardiography.The PET analysis method used in this study is highly automated and can be added as an additional analysis to the standard MBF quantification with a small increase of analysis time. The gated analysis takes no more than a few minutes which is in the same range or shorter than a typical CMR analysis. It could thereby easily be implemented in the clinical workflow of Limitations of the present study should be noted. The standardized time window of 10 to 50 seconds is beneficial in terms of automatization, decreased analysis time, and clinical utilization, but it does include one drawback. With a fixed time window, contrast between the right- and left ventricle and the myocardium is not individually optimized for every patient. For that, a scan-specific time window would need to be manually determined for every patient, which would impair the automatization and clinical utility of the present method. However, the fixed time window did work for every patient. Further on, the cohort is limited to patients with suspected or know CAD with preserved ejection fraction and further evaluations in other cohorts and in patients with reduced systolic function is needed. Nevertheless, it is not expected that larger hearts and/or poor systolic function would challenge the segmentation algorithm, as long as the atrioventricular border can be identified. The only challenge could be the definition of the timing interval of the first pass. For patients with known poor cardiac function, a longer interval may be used as the reduction in cardiac function and cardiac output may result in longer cardiopulmonary transit times and a later arrival of the bolus in the LV. For patients with EF on the high end of the range , partial volume effects may play a role, reducing in smaller physical volumes. However, as the software uses a low threshold count-based approach, the calculated volumes should still be accurate.Moreover, estimation of LV volumes and EF were performed in patients only during rest. Assessment of EDV and EF during stress could add information on transient ischemic dilation or a reduced EF, both of which are markers of advanced cardiac disease. However, stress induces challenges with increased atrioventricular plane motion as well as patient motion, and the time window for reconstruction of the first pass cannot be standardized as for rest. Therefore, further evaluation of the current methods feasibility during stress is needed.15O-water PET scan with high accuracy and comparable precision as with CMR. The method is fast, highly automated, requires minimal user intervention and could be implemented as a part of the clinical standard analysis of 15O-water PET.LV volumes and EF can be calculated from a single 15O-water PET utilizing an approach that is automated and fast enough for implementation in clinical practice.LV volumes and EF can be calculated from Supplementary file1 (DOCX 132 kb)Supplementary file2 (PPTX 346 kb)Supplementary file3 (MP3 7139 kb)Below is the link to the electronic supplementary material.


Right heart failure is a major challenge in clinical practice. Soluble Suppression of Tumorigenicity-2 (sST2), a member of the interleukin-1-receptor family, may have clinical prognostic value. The aim of this study was to analyze whether sST2 correlates with signs of acute right heart decompensation. This prospective single-center study included 50 patients admitted for clinical signs of predominant right heart decompensation. Signs of reduced blood supply to other organs , diuretics, and signs of venous congestion (inferior vena cava (IVC) diameter) with fluid retention  resulting from reduced RV function were analyzed. The degree of peripheral edema was defined as none, mild  or severe . sST2 levels were measured at the day of hospitalization. A total of 78.7% showed severe peripheral edema. The median concentration of sST2 was 35.2 ng/mL (25.–75. percentiles 17.2–46.7). sST2 is correlated with the peripheral edema degree (rSpearman = 0.427,  Acute heart failure (HF) is a major cause of hospitalization and mortality within Western countries . Right hAdditionally, many patients with preexisting chronic HF also suffer from impaired renal function or cardiorenal syndrome, which could further reduce the validity of previously established biomarkers. In recent years, a variety of new cardiac biomarkers have been identified . SolubleThe aim of this pilot study was to investigate the value of sST2 in patients with predominantly right HF. Our hypothesis was that sST2 might correlate with signs of decompensation in patients with predominantly right heart failure and, thus, could potentially be a valuable parameter to guide fluid management and diuretic dosing decisions.In this single-center, prospective cohort study, we analyzed data from 50 adult patients admitted to the University Hospital Heart Centre Brandenburg for acute decompensated predominantly right HF and indication for loop diuretics therapy between October 2019 and October 2021. The Ethics Committee of the Brandenburg Medical School approved this study (E-01-20190603). NT-proBNP, troponin-T, creatinine, cystatin C, and sST2 were determined at admission, the latter by a commercially available enzyme-linked immunosorbent assay (ELISA) kit . The Cobas e411 analyzer using the patented electrochemiluminescence technology for immunoassay analysis was used for NT-proBNP, troponin-T, and cystatin C measurement. Serum creatinine was measured by Beckman Coulter AU680 using the modified Jaffe method standardized by isotope dilution mass spectroscopy.Medical records were reviewed and the following information was obtained: demographics, comorbidities, echocardiographic data, laboratory parameters, length of stay in hospital, rehospitalization within 90 days after discharge, and 90-day mortality. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation . Follow-The primary endpoint of our study was the presence and degree of peripheral edema on clinical examination at the day of admission. We classified edema as follows: (1) no edema; (2) mild with 5–6 mm of depression and rebounding in 15–60 s or less; (3) severe edema with >7 mm of depression and rebounding in 2–3 min. In addition, laboratory parameters  were analyzed as secondary end points, possibly indicating early cardiorenal injury under diuretic use.Linear values are shown as median and IQR (25.–75. percentiles), and categorical variables are expressed as numeric values and percentages. Categorical variables were analyzed with Fisher’s exact or a chi-square test, and continuous variables with a nonparametric Mann–Whitney U-test and Kruskal–Wallis H-test. Spearman rank correlation was used to measure the degree of association between the degree of peripheral edema and the biomarker concentration at admission. Graphs were generated and data were analyzed using SPSS v27 .2. Most patients showed severe (78%), some moderate (16%), and no (6%) peripheral edema, while 70.5% had albuminuria at the time of admission. Twenty percent of patients were readmitted within 90 days for decompensated heart failure; 24% of patients died within 90 days of index hospitalization.The baseline characteristics of the study subjects are presented in p = 0.040; Overall, median sST2 concentration at admission was 35.2 (17.2–46.7) ng/mL. sST2 concentrations differed depending on the severity of peripheral edema (p = 0.004) and diameter of vena cava inferior , while biomarkers of renal function such as creatinine-based eGFR  and cystatin C-based eGFR , and established cardiac biomarkers, such as NT-proBNP  and troponin T , did not. Concentration of sST2 correlated with the degree of peripheral edema Levels of sST2 correlated with the degree of peripheral edema and vena cava width.(2)Soluble ST2 was found to be superior to established biomarkers for cardiorenal diseases. Numerous prospective studies have shown that the predominantly right cardiac diseases are associated with a particularly poor prognosis, especially in those patients with concomitant cardiorenal syndrome ,14.Our findings can be summarized as follows:Right heart failure is a complex disease with dysfunction of the right ventricular structures, which causes manifold issues and requires specific diagnostics. With improved imaging modalities and interventional approaches, the treatment os severe tricuspid regurgitation as a cause of right cardiac disease plays an increasingly important role in clinical practice . In receHowever, other underlying causes for right heart failure, such as pulmonary hypertension, sarcoidosis, and amyloidosis, often remain challenging to diagnosis and treatment options .Unfortunately, established biomarkers have their limitations in this setting, as they either correlate primarily with left cardiac disease, like natriuretic peptides, or have limited validity in the case of renal diseases ,18.Therefore, it would be of importance to have a biomarker available as an additional cornerstone for diagnosis, estimating the prognosis, but also as a follow-up parameter for monitoring and guidance for long-term treatment.Compared to our study, AbouEzzeddine et al. found similarly high sST-2 levels in patients with preserved pump function, which showed a correlation with edema burden . A correOur data indicate that sST2 could be a valuable link in clinical decision making on this issue, complementing the clinical impression. Moreover, in clinical practice, it often remains challenging, even for experienced physicians, to choose the right amount of loop diuretics in heart failure patients, who frequently show refractivity to diuretic drugs . Our datOur data indicate that sST2 may provide additional information compared with natriuretic peptides. It has been described that sST2 is not as affected by the actual kidney function as NT-proBNP . For thiOur study has some limitations. In particular, invasive measurement by right heart catheterization  was not performed because of its invasiveness. This could be of interest in future studies, though. Another limitation of this study is the small sample size and the short follow-up period. However, as this is a pilot study, we are confident that the conclusions drawn have potential for prospective investigation in a substantially larger cohort. Further studies related to sST2 levels in patients with predominantly right cardiac decompensation are essential, because only monocentric prospective studies with a small number of cases have been performed so far.Our data suggest that sST2, but no other established marker, is correlated with peripheral and central fluid status in patients with decompensated right heart failure.