Cardiovascular Magnetic Resonance Exam Research Articles

Regional variability of cardiovascular magnetic resonance access and utilization in the United States

Clinical guidelines and scientific data increasingly support the appropriate use of cardiovascular magnetic resonance (CMR) . The extent of CMR adoption across the United States (US) remains unclear. This observational analysis aims to capture CMR practice patterns in the US. Commissioned reports from the Society for Cardiovascular Magnetic Resonance (SCMR), pre-existing survey data from CMR centers, and socioeconomic and coronary heart disease data from the Centers for Disease Control and Prevention were used. The location of imaging centers performing CMR was based on 2018 Medicare claims. Secondary analysis was performed on center-specific survey data from 2017-2019, which were collected by members of the SCMR US Advocacy Subcommittee for quality improvement purposes. The correlation between the number of imaging centers billing for CMR services per million persons, socioeconomic determinants, and coronary heart disease epidemiology was determined. A total of 591 imaging centers billed the Center for Medicare & Medicaid Services for CMR services in 2018 and 112 (of 155) unique CMR centers responded to the survey. In 2018, CMR services were available in almost all 50 states. Minnesota was the state with the highest number of CMR centers per million Medicare beneficiaries (52.6 centers per million), and Maine had the lowest (4.4 per million). The total density of CMR centers was 16 per million for US Medicare beneficiaries. Sixty-eight percent (83 of 112) of survey responders were cardiologists, and 28% (31/112) were radiologists. In 72% (71/112) of centers, academic health care systems performed 81%-100% of CMR exams. The number of high-volume centers (>500 scans per year) increased by seven between 2017 and 2019. In 2019, 53% (59/112) of centers were considered high-volume centers and had an average of 19years of experience. Centers performing <50 scans had on average 3.5years of experience. Approximate patient wait time for a CMR exam was 2weeks to 1month. Despite increasing volume and availability in almost all 50 states, CMR access remains geographically variable. Advocacy efforts to improve access and innovations that reduce imaging time and exam complexity have the potential to increase the adoption of CMR technology.

Recommendations for cardiovascular magnetic resonance and computed tomography in congenital heart disease: a consensus paper from the CMR/CCT Working Group of the Italian Society of Pediatric Cardiology and the Italian College of Cardiac Radiology endorsed by the Italian Society of Medical and Interventional Radiology (Part II).

Cardiovascular magnetic resonance (CMR) and computed tomography (CCT) are advanced imaging modalities that recently revolutionized the conventional diagnostic approach to congenital heart diseases (CHD), supporting echocardiography and often replacing cardiac catheterization. This is the second of two complementary documents, endorsed by experts from the Working Group of the Italian Society of Pediatric Cardiology and the Italian College of Cardiac Radiology of the Italian Society of Medical and Interventional Radiology, aimed at giving updated indications on the appropriate use of CMR and CCT in different clinical CHD settings, in both pediatrics and adults. In this article, support is also given to radiologists, pediatricians, cardiologists, and cardiac surgeons for indications and appropriateness criteria for CMR and CCT in the most referred CHD, following the proposed new criteria presented and discussed in the first document. This second document also examines the impact of devices and prostheses for CMR and CCT in CHD and additionally presents some indications for CMR and CCT exams when sedation or narcosis is needed.

Deep cardiac phenotyping by cardiovascular magnetic resonance reveals subclinical focal and diffuse myocardial injury in patients with psoriasis (PSOR-COR study).

Psoriasis vulgaris (PV) is a chronic inflammatory disorder frequently associated with cardiovascular disease (CVD). This study aims to provide a prospective tissue characterization in patients with PV without major CVD using cardiovascular magnetic resonance (CMR). Patients with PV underwent laboratory assessment, a 12-lead and 24-h ECG, and a CMR exam at a 1.5-T scanner. Scan protocol included assessment of left (LV) and right (RV) ventricular function and strain analysis, native and post-contrast T1 mapping, T2 mapping and late gadolinium enhancement (LGE). In total, 60 PV patients (median(IQR) age in years: 50.0 (36.0-60.8); 34 men (56.7%)) were recruited and compared to 40 healthy volunteers (age in years: 49.5 (37.3-57.8); 21 men (53.0%)). No differences were found regarding LV and RV function (p = 0.78 and p = 0.75). Global radial and circumferential strains were lower in patients (p < 0.001 and p < 0.001, respectively). PV had higher global T1 times (1001 (982-1026) ms vs. 991 (968-1005) ms; p = 0.01) and lower global T2 times (48 (47-49) ms vs. 50 (48-51) ms; p < 0.001); however, all values were within local reference ranges. Focal non-ischemic fibrosis was observed in 17 (28.3%) PV patients. Deep cardiac phenotyping by CMR revealed subclinical myocardial injury in patients with PV without major CVD, despite preserved LV and RV function. Diffuse and focal fibrosis might be the first detectable signs of adverse tissue remodeling leading to reduced circumferential and radial myocardial deformation. In the background of local and systemic immunomodulatory therapy, no signs of myocardial inflammation were detected. The exact impact of immunomodulatory therapies on the myocardium needs to be addressed in future studies. ISRCTN71534700.

Cardiovascular magnetic resonance characterization of myocardial tissue injury in a miniature swine model of cancer therapy-related cardiovascular toxicity

BackgroundLeft ventricular ejection fraction (LVEF) is the most commonly clinically used imaging parameter for assessing cancer therapy-related cardiac dysfunction (CTRCD). However, LVEF declines may occur late, after substantial injury. This study sought to investigate cardiovascular magnetic resonance (CMR) imaging markers of subclinical cardiac injury in a miniature swine model. MethodsFemale Yucatan miniature swine (n=14) received doxorubicin (2mg/kg) every 3 weeks for 4 cycles. CMR, including cine, tissue characterization via T1 and T2 mapping, and late gadolinium enhancement (LGE) was performed on the same day as doxorubicin administration and three weeks after the final chemotherapy cycle. In addition, MR spectroscopy (MRS) was performed during the 3 weeks after the final chemotherapy in 7 pigs. A single CMR and MRS exam was also performed in three Yucatan miniature swine that were age- and weight-matched to the final imaging exam of the doxorubicin-treated swine to serve as controls. CTRCD was defined as histological early morphologic changes, including cytoplasmic vacuolization and myofibrillar loss of myocytes, based on post-mortem analysis of humanely euthanized pigs after the final CMR exam. ResultsOf 13 swine completing five serial CMR scans, 10 (77%) had histological evidence of CTRCD. Three animals had neither histological evidence nor changes in LVEF from baseline. No absolute LVEF <40% or LGE were observed. Native T1, extracellular volume (ECV), and T2 at 12 weeks were significantly higher in swine with CTRCD than those without CTRCD (1178 ms vs. 1134 ms, p=0.002, 27.4% vs. 24.5%, p=0.03, and 38.1 ms vs. 36.4 ms, p=0.02, respectively). There were no significant changes in strain parameters. The temporal trajectories in native T1, ECV, and T2 in swine with CTRCD showed similar and statistically significant increases. At the same time, there were no differences in their temporal changes between those with and without CTRCD. MRS myocardial triglyceride content substantially differed among controls, swine with and without CTRCD (0.89%, 0.30%, 0.54%, respectively, ANOVA, p=0.01), and associated with the severity of histological findings and incidence of vacuolated cardiomyocytes. ConclusionsSerial CMR imaging alone has a limited ability to detect histologic CTRCD beyond LVEF. Integrating MRS myocardial triglyceride content may be useful for detection of early potential CTRCD.

Cardiac MR Fingerprinting: Overview, Technical Developments, and Applications.

Cardiovascular magnetic resonance (CMR) is an established imaging modality with proven utility in assessing cardiovascular diseases. The ability of CMR to characterize myocardial tissue using T1- and T2-weighted imaging, parametric mapping, and late gadolinium enhancement has allowed for the non-invasive identification of specific pathologies not previously possible with modalities like echocardiography. However, CMR examinations are lengthy and technically complex, requiring multiple pulse sequences and different anatomical planes to comprehensively assess myocardial structure, function, and tissue composition. To increase the overall impact of this modality, there is a need to simplify and shorten CMR exams to improve access and efficiency, while also providing reproducible quantitative measurements. Multiparametric MRI techniques that measure multiple tissue properties offer one potential solution to this problem. This review provides an in-depth look at one such multiparametric approach, cardiac magnetic resonance fingerprinting (MRF). The article is structured as follows. First, a brief review of single-parametric and (non-Fingerprinting) multiparametric CMR mapping techniques is presented. Second, a general overview of cardiac MRF is provided covering pulse sequence implementation, dictionary generation, fast k-space sampling methods, and pattern recognition. Third, recent technical advances in cardiac MRF are covered spanning a variety of topics, including simultaneous multislice and 3D sampling, motion correction algorithms, cine MRF, synthetic multicontrast imaging, extensions to measure additional clinically important tissue properties (proton density fat fraction, T2*, and T1ρ), and deep learning methods for image reconstruction and parameter estimation. The last section will discuss potential clinical applications, concluding with a perspective on how multiparametric techniques like MRF may enable streamlined CMR protocols. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.

Incremental prognostic value of fully-automatic machine-learning based global circumferential strain during a stress CMR exam

Abstract Background Left ventricular global circumferential strain using cardiovascular magnetic resonance (CMR) is an accurate indicator to predict cardiovascular events. Although several studies have shown the excellent prognostic value of stress CMR, the prognostic value of stress global circumferential strain (sGCS) remains unknown. Purpose To investigate the prognostic value of sGCS for predicting cardiovascular events using a fully automatic machine learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular death or nonfatal myocardial infarction (MI). A fully automatic machine learning algorithm was trained and validated on unseen CMR studies (MAGNETOM Aera and Skyra, Siemens Healthcare, Erlangen, Germany) to assess the sGCS from short-axis cine images at stress. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of sGCS. Results Among 2,906 consecutive patients who underwent stress CMR, the automatic sGCS was successfully computed in 2,859 (98.4%) patients (68% male, mean age 64±12 years). A total of 256 (8.8%) MACEs were observed during a median (IQR) follow-up period of 4.5 (3.7-5.3) years. Using Kaplan-Meier analysis, sGCS and the presence of inducible ischemia were significantly associated with the occurrence of MACE (hazard ratio, HR: 1.12 [95% CI, 1.08-1.17]; and HR: 8.48 [95% CI, 6.05-11.91], both p&amp;lt;0.001; respectively). After adjustment for traditional risk factors, inducible ischemia and late gadolinium enhancement (LGE), sGCS was an independent predictor of a higher incidence of MACE (adjusted HR: 1.12 [95% CI, 1.05-1.20]). Finally, sGCS showed an incremental prognostic value to predict MACE compared to a multivariable model including traditional risk factors, the presence of inducible ischemia and LGE (C-statistic improvement: 0.05, p=0.007; NRI= 0.169; IDI= 0.097; both p&amp;lt;0.001). Conclusions Automatic sGCS has an incremental prognostic value to predict MACE above traditional risk factors, and other stress CMR parameters.Survival curvesIncremental prognostic value

Abstract 16291: Regional Variability in Cardiovascular MRI Access and Utilization in the U.S. Population From 2017 to 2019

Background: Despite clinical guidelines and scientific data supporting the use of cardiovascular magnetic resonance (CMR) imaging in multiple applications, CMR continues to be underutilized in the United States (U.S.). Objective: This study aims to capture geographic variability, access, and CMR practice patterns in the U.S. between 2017 and 2019. Methods: Commissioned reports from the Society of Cardiovascular Magnetic Resonance (SCMR), and data from a nationwide survey of CMR centers were used. Medicare claims for CMR studies from 2019 were compiled by the Moran Company. Surveys designed to collect data on center-specific characteristics were sent to 155 CMR centers identified through SCMR email listserve and Medicare claims data. Survey responses were reviewed to ensure only one response was captured from each center. Results: A total of 592 imaging centers were included in the Moran report and 112 unique centers responded to the survey. Of the centers included in the report, 47% billed for less than 10 of the most frequent study (CMR for morphology w/ dye) in 2019. The total density of CMR centers was 15.6 centers per million U.S. Medicare Part B beneficiaries. CMR centers are more dense in geographic areas of lowest socioeconomic disadvantage (based on the Area Deprivation Index), low poverty, and lowest percent of people lacking health insurance. Sixty-eight percent of survey responders were cardiologists, and 28% were radiologists. Seventy-two percent of centers reported performing 81-100% of their CMR exams in an academic healthcare system. Centers performing &gt;500 scans per year had an average of 19 years of experience, whereas centers performing &lt;50 scans had an average 3.5 years’ experience. The most common response for approximate patient wait time for CMR was 2 weeks to 1 month (45% of responses). Conclusions: Although CMR volume is increasing in the U.S., CMR access continues to demonstrate marked geographic variability. While almost half of centers are performing just a handful of scans annually, the greatest volumes are noted in well-established programs with years of experience. Identification of specific barriers to CMR access will be useful for future advocacy efforts and quality improvement initiatives.

Automated segmentation of 3D cine cardiovascular magnetic resonance imaging.

As the life expectancy of children with congenital heart disease (CHD) is rapidly increasing and the adult population with CHD is growing, there is an unmet need to improve clinical workflow and efficiency of analysis. Cardiovascular magnetic resonance (CMR) is a noninvasive imaging modality for monitoring patients with CHD. CMR exam is based on multiple breath-hold 2-dimensional (2D) cine acquisitions that should be precisely prescribed and is expert and institution dependent. Moreover, 2D cine images have relatively thick slices, which does not allow for isotropic delineation of ventricular structures. Thus, development of an isotropic 3D cine acquisition and automatic segmentation method is worthwhile to make CMR workflow straightforward and efficient, as the present work aims to establish. Ninety-nine patients with many types of CHD were imaged using a non-angulated 3D cine CMR sequence covering the whole-heart and great vessels. Automatic supervised and semi-supervised deep-learning-based methods were developed for whole-heart segmentation of 3D cine images to separately delineate the cardiac structures, including both atria, both ventricles, aorta, pulmonary arteries, and superior and inferior vena cavae. The segmentation results derived from the two methods were compared with the manual segmentation in terms of Dice score, a degree of overlap agreement, and atrial and ventricular volume measurements. The semi-supervised method resulted in a better overlap agreement with the manual segmentation than the supervised method for all 8 structures (Dice score 83.23 ± 16.76% vs. 77.98 ± 19.64%; P-value ≤0.001). The mean difference error in atrial and ventricular volumetric measurements between manual segmentation and semi-supervised method was lower (bias ≤ 5.2 ml) than the supervised method (bias ≤ 10.1 ml). The proposed semi-supervised method is capable of cardiac segmentation and chamber volume quantification in a CHD population with wide anatomical variability. It accurately delineates the heart chambers and great vessels and can be used to accurately calculate ventricular and atrial volumes throughout the cardiac cycle. Such a segmentation method can reduce inter- and intra- observer variability and make CMR exams more standardized and efficient.

Incremental prognostic value of fully-automatic machine-learning based global circumferential strain during a stress CMR exam

Abstract Funding Acknowledgements Type of funding sources: None. Background Left ventricular global circumferential strain using cardiovascular magnetic resonance (CMR) is an accurate indicator to predict cardiovascular events. Although several studies have shown the excellent prognostic value of stress CMR, the prognostic value of stress global circumferential strain (sGCS) remains unknown. Aim To investigate the prognostic value of sGCS for predicting cardiovascular events using a fully automatic machine learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular death or nonfatal myocardial infarction (MI). A fully automatic machine learning algorithm was trained and validated on unseen CMR studies (MAGNETOM Aera and Skyra, Siemens Healthcare, Erlangen, Germany) to assess the sGCS from short-axis cine images at stress. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of sGCS. Results Among 2,906 consecutive patients who underwent stress CMR, the automatic sGCS was successfully computed in 2,859 (98.4%) patients (68% male, mean age 64±12 years). A total of 256 (8.8%) MACEs were observed during a median (IQR) follow-up period of 4.5 (3.7–5.3) years. Using Kaplan-Meier analysis, sGCS and the presence of inducible ischemia were significantly associated with the occurrence of MACE (hazard ratio, HR: 1.12 [95% CI, 1.08–1.17]; and HR: 8.48 [95% CI, 6.05–11.91], both p&amp;lt;0.001; respectively). After adjustment for traditional risk factors, inducible ischemia and late gadolinium enhancement (LGE), sGCS was an independent predictor of a higher incidence of MACE (adjusted HR: 1.12 [95% CI, 1.05–1.20]). Finally, sGCS showed an incremental prognostic value to predict MACE compared to a multivariable model including traditional risk factors, the presence of inducible ischemia and LGE (C-statistic improvement: 0.05, p = 0.007; NRI= 0.169; IDI= 0.097; both p&amp;lt;0.001). Conclusions Automatic sGCS has an incremental prognostic value to predict MACE above traditional risk factors, and other stress CMR parameters.

Additional prognostic value of fully-automatic Global Longitudinal Strain using machine learning

Abstract Funding Acknowledgements Type of funding sources: None. Background Several studies described the independent prognostic value of left ventricular global longitudinal strain (GLS) using cardiovascular magnetic resonance (CMR) to predict cardiovascular events. However, the potential interest of GLS using a fully automatic method assessed at rest during a stress CMR exam was not well established. Aim To assess the prognostic value of GLS to predict all-cause death using a fully automatic machine learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of all-cause death. A fully automatic machine learning algorithm was trained and validated unseen CMR studies (MAGNETOM Aera and Skyra, Siemens Healthcare, Erlangen, Germany) to assess the GLS from long-axis cine images acquired at rest. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of GLS. Results Among 9,883 consecutive patients who underwent stress CMR between 2016 and 2018 retrospectively included, the automatic GLS was successfully computed in 9,638 (97.5%) patients (67% male, mean age 66±12 years). A total of 510 (5.3%) deaths were observed during a median (IQR) follow-up period of 4.5 (3.7–5.2) years. GLS, the presence of inducible ischemia and late gadolinium enhancement (LGE) were significantly associated with the occurrence of death (hazard ratio, HR: 1.22 [95% CI, 1.17–1.26]; HR: 2.23 [95% CI, 1.61–3.10]; and HR: 2.04 [95% CI, 1.41–2.95], respectively, all p&amp;lt;0.001). After adjustment for traditional risk factors, inducible ischemia and LGE, GLS was an independent predictor of a higher incidence of death (adjusted HR: 1.14 [95% CI, 1.08–1.20]). Automatic GLS showed an incremental prognostic value to predict death compared to traditional risk factors, inducible ischemia and LGE (C-statistic improvement: 0.05; NRI=0.146; IDI=0.244; all p&amp;lt;0.001). Conclusions Automatic GLS measured at rest has an incremental prognostic value to predict all-cause death above traditional risk factors, and other stress CMR parameters.

Building a comprehensive cardiovascular magnetic resonance exam on a commercial 0.55 T system: A pictorial essay on potential applications.

Contemporary advances in low-field magnetic resonance imaging systems can potentially widen access to cardiovascular magnetic resonance (CMR) imaging. We present our initial experience in building a comprehensive CMR protocol on a commercial 0.55 T system with a gradient performance of 26 mT/m amplitude and 45 T/m/s slew rate. To achieve sufficient image quality, we adapted standard imaging techniques when possible, and implemented compressed-sensing (CS) based techniques when needed in an effort to compensate for the inherently low signal-to-noise ratio at lower field strength. A prototype CMR exam was built on an 80 cm, ultra-wide bore commercial 0.55 T MR system. Implementation of all components aimed to overcome the inherently lower signal of low-field and the relatively longer echo and repetition times owing to the slower gradients. CS-based breath-held and real-time cine imaging was built utilizing high acceleration rates to meet nominal spatial and temporal resolution recommendations. Similarly, CS 2D phase-contrast cine was implemented for flow. Dark-blood turbo spin echo sequences with deep learning based denoising were implemented for morphology assessment. Magnetization-prepared single-shot myocardial mapping techniques incorporated additional source images. CS-based dynamic contrast-enhanced imaging was implemented for myocardial perfusion and 3D MR angiography. Non-contrast 3D MR angiography was built with electrocardiogram-triggered, navigator-gated magnetization-prepared methods. Late gadolinium enhanced (LGE) tissue characterization methods included breath-held segmented and free-breathing single-shot imaging with motion correction and averaging using an increased number of source images. Proof-of-concept was demonstrated through porcine infarct model, healthy volunteer, and patient scans. Reasonable image quality was demonstrated for cardiovascular structure, function, flow, and LGE assessment. Low-field afforded utilization of higher flip angles for cine and MR angiography. CS-based techniques were able to overcome gradient speed limitations and meet spatial and temporal resolution recommendations with imaging times comparable to higher performance scanners. Tissue mapping and perfusion imaging require further development. We implemented cardiac applications demonstrating the potential for comprehensive CMR on a novel commercial 0.55 T system. Further development and validation studies are needed before this technology can be applied clinically.

Cardiac Magnetic Resonance Predicts Heart Failure Mortality in Patients with Thalassemia Major

Iron-induced Heart Failure (HF) still remains the main cause of mortality in patients with thalassemia major (TM), although the introduction of the T2* Cardiovascular Magnetic Resonance (CMR) for the non-invasive assessment of Myocardial Iron Overload (MIO) led to a significant increase in survival rate. However, the pathophysiology of heart failure in TM can be multifactorial. Thanks to its multiparametric potential, CMR represents a unique tool for characterization of myocardial involvement. It is the gold standard for the quantification of biventricular size and function by cine images and for the detection of replacement fibrosis by late gadolinium enhancement (LGE) technique. The aim of this multicenter study was to evaluate the prognostic value of multiparametric CMR in predicting death for HF. We considered 1398 white TM patients who performed a baseline CMR exam within the Myocardial Iron Overload in Thalassemia (MIOT) network. As per inclusion criteria, no patient had a history of HF. Mean age was 30.8±8.9 years and 725 (51.9%) patients were females. During a mean follow-up of 4.83±2.05 years, 49.1% of the patients changed at least once the chelation regimen (i.e.: either switched to a different type of chelator or underwent dose/frequency modification); these patients were more likely to have a global heart T2* value<20ms than patients who maintained the same regimen (33.2% vs 19.7%; P<0.0001) Twelve (1.0%) patients died from heart failure. Table 1 shows the results, presented as hazard ratio (HR) with 95% confidence intervals (CI), of the univariate Cox Regression analysis, performed to test the association between the considered prognostic variables and the outcome. No association was detected between age or gender and HF mortality. Significant MIO (global heart T2*<20 ms), ventricular dysfunction, ventricular dilation, and replacement myocardial fibrosis were identified as significant univariate prognosticators. Due to the low number of deaths for HF, it was not possible to perform a multivariate model. However, based on the presence of the four CMR predictors of HF death, patients were divided into three subgroups: four markers (7 patients; one HF death-14.3%), one to four markers (617 patients, 9 HF deaths-1.5%), and none of the four markers (488 patients; one HF death-0.2%). Patients having all four markers had a significantly higher risk of dying for HF than patients without markers (HR=89.93; 95%CI=5.62-1439.46; P=0.001) or with one to three CMR markers (HR=12.69; 95%CI=1.60-100.36; P=0.016). In our homogeneous white and well-treated Italian/Mediterranean population, we detected a low incidence of deaths for HF, since the T2* report guided the patient-specific adjustment of the chelation regimen. As expected, MIO was a significant predictor of HF death but also other CMR parameters, namely ventricular dilatation, ventricular dysfunction, and replacement myocardial fibrosis emerged as unfavorable prognosis determinant. Importantly, when the four CMR indices were evaluated in combination, they fine-tuned the prognostic stratification of TM patients. Hence, the findings of the present study promote the exploitation of the full potential of CMR, including LGE, for a better risk stratification of TM patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Acute hemodynamic effects of biventricular pacing studied during cardiovascular magnetic resonance imaging: the PICARIA Trial

Abstract Background Cardiac resynchronization therapy (CRT) is hampered by a relative high rate of non-response whereby device optimization could aid in improving benefit from CRT. Nonetheless, a non-invasive and reproducible clinical tool for device optimization is currently lacking. Recently introduced cardiovascular magnetic resonance (CMR) compatible CRT devices may allow for patient follow-up and device optimization as biventricular (BIV) pacing can be performed during the CMR exam. However, to date, CMR evaluation of acute pump function changes during CRT is limited. Purpose To assess the effects of BIV-pacing on change in left ventricular (LV) function and contraction patterns using CMR. Methods Ten patients were included in this prospective pilot study. All patients underwent CMR imaging (1.5T system) prior to device implantation (baseline), and 6 weeks after device implantation (CRT-on and CRT-off). LV end systolic volume (ESV), end diastolic volume (EDV), ejection fraction (LVEF), and measures of LV dyssynchrony and dyscoordination (septal systolic rebound stretch (SRSseptal)) were assessed on cine images. Results LV function and contraction patterns before and after device implantation are compared and displayed in the figure. LV ESV and EDV decreased in all patients during BIV-pacing as compared to intrinsic rhythm (CRT-off) (ESV; 161.4±36.3ml vs. 194.9±37.1ml, p&amp;lt;0.01 and EDV; 236.2±31.8ml vs. 268.1±42.3ml, p&amp;lt;0.01). A significant improvement in LVEF was observed during BIV-pacing (32.2±8.7% vs. 27.4±5.9%, p&amp;lt;0.01). Both, regional dyssynchrony and regional dyscoordination significantly improved during CRT-on compared to CRT-off (peakseptal-peaklateral; 57±46ms vs. 183±86ms, p&amp;lt;0.01 and SRSseptal; 2.1±2.6% vs. 6.0±3.0%, p&amp;lt;0.01). Conclusions Post-CRT implantation CMR assessing acute pump function changes to different CRT pacing settings is feasible and provides important insights in the effects of BIV-pacing on cardiac function and contraction patterns. LV assessment using CMR, potentially in combination with non-invasive pressure measurements, may constitute a future CRT optimization strategy. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Biotronik (Berlin, Germany)

Racial differences of right ventricular remodelling in systemic hypertension unveiled by multiparametric cardiovascular magnetic resonance

Abstract Background Patients with systemic hypertension (HTN) of African ancestry (Afr-a) are at greater risk of heart failure (HF), hospitalisation and death than those of European ancestry (Eu-a). Compelling evidence suggests that left ventricular (LV) remodelling and hypertrophy are more prevalent in Afr-a than Eu-a hypertensives due to either a high clustering of cardiovascular risk-factors and/or a difference in genetic background. Prior studies in Eu-a subjects have shown that uncomplicated HTN is associated with right ventricular (RV) hypertrophy and remodelling which may contribute to development of HF. However, the impact of ethnicity on RV remodelling in HTN remains speculative. Purpose To investigate the influence of ethnicity on RV remodelling/hypertrophy in patients with HTN using cardiovascular magnetic resonance (CMR). Methods In this cross-sectional study we included 16 Afr-a and 32 Eu-a age- and sex-matched healthy-volunteers, and 63 Afr-a and 47 Eu-a hypertensives. All participants underwent a CMR exam (1.5-Tesla, Aera, Siemens-Healthcare, Erlangen-Germany). LV and RV volumes, masses and function were measured according to the current recommendations. Blood pressure was recorded during the CMR. Results Age- and sex-matched Afr-a and Eur-a healthy-volunteers (37±10 vs 37±12 years, P=0.975; male 53% vs 44%; P=0.539) exhibited closely comparable LV and RV volumes, masses, and end-diastolic volume/mass ratios. In the HTN group, despite Afr-a hypertensives being roughly 5 years older than Eu-a, baseline characteristics including cardiovascular risk factors, mean blood pressure, body-mass-index, and body composition metrics were similar between the two groups (Figure 1). Afr-a hypertensives also had greater LV and RV masses and mass/end-diastolic volume ratios than Eur-a hypertensives (Figure 2). RV mass correlated with LV mass in both ethnic groups (r=0.593 in Eu-a and r=0.569 in Afr-a; both P&amp;lt;0.001). Multivariable linear regression analysis showed that RV mass was independently associated with African descendance after correction for major confounders including LV mass, biventricular volumes, and body composition. Conclusion Our findings support the notion that Afr-a and Eur-a healthy-volunteers have comparable left and right ventricular geometry and masses, arguing against genetic-determinate ventricular geometry and myocardial mass in this population. However, Afr-a individuals exhibit higher sensitivity to myocardial hypertrophy in response to HTN which translates into greater biventricular masses and remodelling, compared to Eu-a hypertensives. Funding Acknowledgement Type of funding sources: None.

P1514: MULTI-PARAMETRIC CARDIAC MAGNETIC RESONANCE FOR RISK PREDICTION OF HEART FAILURE DEATH IN THALASSEMIA MAJOR

Background: Iron-induced heart failure (HF) is the main cause of mortality in patients with thalassemia major (TM). Cardiovascular Magnetic Resonance (CMR) plays a key role in the management of these patients, assessing myocardial iron overload (MIO), biventricular function, and myocardial fibrosis. Aims: We evaluated the prognostic value of CMR parameters in predicting death for HF. Methods: We followed prospectively 1681 white TM patients who performed a baseline CMR exam within the Myocardial Iron Overload in Thalassemia (MIOT) network. All prognostic variables associated with the outcome at the univariate Cox model were placed in the multivariate model and were ruled out if they did not significantly improve the adjustment. Results: At baseline the mean age was 31.11±9.01 years and 874 (52.0%) patients were females. During a mean follow-up of 4.76±2.07 years, 47.3% of the patients changed at least once the chelation regimen, that is switched to a different type of chelator or underwent dose/frequency modification. Sixteen (1.0%) patients died for heart failure. No association was detected between age or gender and HF mortality. Patients who died for HF had significantly lower baseline global heart T2* values (19.45±15.11 ms vs 29.52±12.02 ms, P=0.006) and significantly higher baseline MR liver iron concentration (LIC) values (19.17±15.95 mg/g dw vs 8.72±10.63 mg/g dw, P=0.005) than patients still alive or died for a different cause, but the presence of a pathologic MRI LIC (>3 mg/g dw) was not associated with an increased risk of HF mortality. Heart iron, ventricular dysfunction, and ventricular dilatation were significant univariate prognosticators. In the multivariate analysis the independent predictive factors were a global heart T2*<10 ms (compared to a global heart T2*≥20 ms) (hazard ratio-HR=5.38, 95%CI=1.79-16.22, P=0.003) and ventricular dilatation (HR=4.59, 95%CI=1.55-13.59, P=0.006). The Figure shows the Kaplan–Meier survival curves. The log-rank test revealed a significant difference in the curves for each predictor (severe MIO: P<0.0001 and ventricular dilatation: P<0.0001). Image:Summary/Conclusion: We detected few HF deaths thanks to a MR-guided patient-specific adjustment of the chelation therapy. Severe MIO and ventricular dilatation identified TM patients at high risk for heart failure death. So, a widespread program using CMR exploiting its multi-parametric potential can have considerable power for further opening the prognosis of TM patients.

Cardiac MR: From Theory to Practice.

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.

Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis.

The Multi-Ethnic Study of Atherosclerosis (MESA), begun in 2000, was the first large cohort study to incorporate cardiovascular magnetic resonance (CMR) to study the mechanisms of cardiovascular disease in over 5,000 initially asymptomatic participants, and there is now a wealth of follow-up data over 20 years. However, the imaging technology used to generate the CMR images is no longer in routine use, and methods trained on modern data fail when applied to such legacy datasets. This study aimed to develop a fully automated CMR analysis pipeline that leverages the ability of machine learning algorithms to enable extraction of additional information from such a large-scale legacy dataset, expanding on the original manual analyses. We combined the original study analyses with new annotations to develop a set of automated methods for customizing 3D left ventricular (LV) shape models to each CMR exam and build a statistical shape atlas. We trained VGGNet convolutional neural networks using a transfer learning sequence between two-chamber, four-chamber, and short-axis MRI views to detect landmarks. A U-Net architecture was used to detect the endocardial and epicardial boundaries in short-axis images. The landmark detection network accurately predicted mitral valve and right ventricular insertion points with average error distance <2.5 mm. The agreement of the network with two observers was excellent (intraclass correlation coefficient >0.9). The segmentation network produced average Dice score of 0.9 for both myocardium and LV cavity. Differences between the manual and automated analyses were small, i.e., <1.0 ± 2.6 mL/m2 for indexed LV volume, 3.0 ± 6.4 g/m2 for indexed LV mass, and 0.6 ± 3.3% for ejection fraction. In an independent atlas validation dataset, the LV atlas built from the fully automated pipeline showed similar statistical relationships to an atlas built from the manual analysis. Hence, the proposed pipeline is not only a promising framework to automatically assess additional measures of ventricular function, but also to study relationships between cardiac morphologies and future cardiac events, in a large-scale population study.

Insights Into Myocardial Oxygenation and Cardiovascular Magnetic Resonance Tissue Biomarkers in Heart Failure With Preserved Ejection Fraction.

The pathophysiology of heart failure with preserved ejection fraction is not well understood, but evidence strongly suggests involvement of microvascular dysfunction. We studied the myocardial oxygenation reserve as a direct marker of coronary vascular function and its relation to myocardial deformation and tissue characteristics by cardiovascular magnetic resonance (CMR). In a dual-center case-control study, patients with heart failure and preserved ejection fraction (>50%) and healthy controls older than 50 years underwent quantitative CMR for ventricular volumes and functional assessment with feature tracking, as well as tissue characterization (T1, T2, extracellular volume). Coronary vascular function was measured by oxygenation-sensitive (OS)-CMR of the myocardial oxygenation response to a vasoactive breathing maneuver. Twenty-nine patients completed the CMR exam. Compared with cutoffs derived from 12 control subjects, circumferential peak strain was attenuated in 97% of patients. Native T1 was elevated in 93%, extracellular volume was elevated in 83%. Sixty-six percent of patients revealed either regional or global myocardial edema, defined by an increased myocardial T2. An attenuated global myocardial oxygenation reserve (<4.4%) was observed in 96% of the patients (1.7±3.9% versus 9.1±5.3% in controls, P<0.001). This was correlated with septal wall thickness (r=-0.54, P=0.003), edema (myocardial T2; β=-0.26% oxygenation-sensitive/ms [95% CI, -0.49 to -0.03], P=0.029), and reduced diastolic strain rate (β=1.50% oxygenation-sensitive/s-1 [95% CI, 0.06-2.90], P=0.042). In patients with clinical heart failure with preserved ejection fraction, vascular dysfunction as measured by an attenuated myocardial oxygenation reserve is associated with myocardial edema, a thicker septum, and diastolic dysfunction. A quantitative comprehensive CMR exam including oxygenation-sensitive-CMR allows for comprehensive imaging-based phenotyping of heart failure with preserved ejection fraction.

Implementation and prospective clinical validation of AI‐based planning and shimming techniques in cardiac MRI

PurposeCardiovascular magnetic resonance (CMR) is a vital diagnostic tool in the management of cardiovascular diseases. The advent of advanced CMR technologies combined with artificial intelligence (AI) has the potential to simplify imaging, reduce image acquisition time without compromising image quality (IQ), and improve magnetic field uniformity. Here, we aim to implement two AI‐based deep learning techniques for automatic slice alignment and cardiac shimming and evaluate their performance in clinical cardiac magnetic resonance imaging (MRI).MethodsTwo deep neural networks were developed, trained, and validated on pre‐acquired cardiac MRI datasets (>500 subjects) to achieve automatic slice planning and shimming (implemented in the scanner) for CMR. To examine the performance of our automated cardiac planning (EasyScan) and AI‐based shim (AI shim), two prospective studies were performed subsequently. For the EasyScan validation, 10 healthy subjects underwent two identical CMR protocols: with manual cardiac planning and with AI‐based EasyScan to assess protocol scan time difference and accuracy of cardiac plane prescriptions on a 1.5 T clinical MRI scanner. For the AI shim validation, a total of 20 subjects were recruited: 10 healthy and 10 cardio‐oncology patients with referrals for a CMR examination. Cine images were obtained with standard cardiac volume shim and with AI shim to assess signal‐to‐noise ratio (SNR), contrast‐to‐noise ratio (CNR), overall IQ (sharpness and MR image degradation), ejection fraction (EF), and absolute wall thickening. A hybrid statistical method using of nonparametric (Wilcoxon) and parametric (t‐test) assessments was employed for statistical analyses.ResultsCMR protocol with AI‐based plane prescriptions, EasyScan, minimized operator dependence and reduced overall scanning time by over 2 min (∼13 % faster, p < 0.001) compared to the protocol with manual cardiac planning. EasyScan plane prescriptions also demonstrated more accurate (less plane angulation errors from planes manually prescribed by a certified cardiac MRI technologist) cardiac planes than previously reported strategies. Additionally, AI shim resulted in improved B0 field homogeneity. Cine images obtained with AI shim revealed a significantly higher SNR (12.49%; p = 0.002) than those obtained with volume shim (volume shim: 32.90 ± 7.42 vs. AI shim: 37.01 ± 8.87) for the left ventricle (LV) myocardium. LV myocardium CNR was 12.48% higher for cine imaging with AI shim (149.02 ± 39.15) than volume shim (132.49 ± 33.94). Images obtained with AI shim resulted in sharper images than those obtained with volume shim (p = 0.012). The LVEF and absolute wall thickening also showed that differences exist between the two shimming methods. The LVEF by AI shim was shown to be slightly larger than LVEF by volume shim in two groups: 2.87% higher with AI shim for the healthy group and 1.70% higher with AI shim for the patient group. The LV absolute wall thickening (in mm) also showed that differences exist between shimming methods for each group with larger changes observed in the patient group (healthy: 3.31%, p = 0.234 and patient group: 7.29%, p = 0.059).ConclusionsCMR exams using EasyScan for cardiac planning demonstrated accelerated cardiac exam compared to the CMR protocol with manual cardiac planning. Improved and more uniform B0 magnetic field homogeneity also achieved using AI shim technique compared to volume shimming.

Abstract 12567: Reduced Myocardial Strain is Associated With Myocardial Inflammation and Fibrosis on Cardiovascular Magnetic Resonance Imaging in Collegiate Athletes Recovering From SARS-CoV-2 Infection

Introduction: Myocarditis is an important cause of sudden cardiac death in competitive athletes. There have been reports of myocardial inflammation on cardiovascular magnetic resonance (CMR) in athlete and non-athlete populations after SARS-CoV-2 infection; however, their clinical and functional significance is not known. We sought to investigate the relationship between left ventricular (LV) strain and other CMR markers suggestive of myocardial inflammation or fibrosis. Hypothesis: Reduced myocardial strain is associated with the presence of CMR abnormalities suggestive of inflammation, fibrosis, or necrosis in athletes recovering from SARS-CoV-2 infection. Methods: Collegiate athletes (N = 123) underwent a comprehensive CMR exam including strain encoded (SENC) imaging. We analyzed LV global longitudinal strain (GLS) across five groups defined by the presence or absence of late gadolinium enhancement (LGE), and T1 or T2 abnormalities. Myocarditis diagnosis on CMR required both abnormal T1 or LGE, and abnormal T2, in the same LV segment. Results: We enrolled 11 COVID negative control athletes (Group 1). Among COVID positive athletes, 42 had no abnormalities on CMR (Group 2), 31 had isolated right ventricular insertion point (RVIP) LGE (Group 3), 28 had LGE beyond RVIP (Group 4), and 11 athletes had myocarditis (Group 5). GLS was significantly lower in Groups 3, 4, and 5 compared with negative controls (p&lt;0.05, Figure 1). There was a deterioration in GLS as CMR abnormalities progressed from control athletes to those with LGE and myocarditis. There was no significant difference in LV ejection fraction between the 5 groups. Conclusions: In conclusion, SARS-CoV-2 infection in collegiate athletes leads to subtle abnormalities in cardiac function detected by GLS that correlate with abnormal mapping and LGE suggestive of myocardial inflammation and fibrosis. The clinical significance of these abnormalities remains to be determined.