Journal of Cardiovascular Magnetic Resonance最新文献

Background: Timing of pulmonary valve intervention (PVI) for pulmonary regurgitation in patients with repaired tetralogy of Fallot (TOF) is guided by right ventricle (RV) volumetric/function assessment on cardiac magnetic resonance (CMR) indexed to actual body surface area (BSA). However, different RV contouring techniques and BSA formulae exist with significant variability in reported measurements. We aimed to review the protocols reported in CMR studies of PVI in TOF.

Methods: A search of electronic databases (Embase and MEDLINE) was performed to identify studies published between February 28, 2010 and February 28, 2025 which assessed adults with repaired TOF before and after PVI using CMR. RV contouring methods and BSA formulae were reviewed.

Results: After screening 610 references, a total of 27 studies met the criteria and were included. All studies were of only level III or level IV (lowest) levels of evidence. Most studies (81%, 22/27) did not specify the RV contouring technique used and none defined the RV basal slice. Of the five studies describing the RV contouring technique, four excluded trabeculations/papillary muscles from the RV volume and one included these structures. No studies reported the formula used to calculate actual BSA.

Conclusion: RV contouring technique and BSA methodology utilized in CMR studies of PVI in TOF is poorly reported. Given the importance of severity thresholds for RV volumes in triggering intervention in clinical practice, clear reporting and standardization of RV contouring and BSA methodology should be mandatory. Further research into the optimal RV thresholds for PVI based on clear contouring methods is required.

Introduction: Mitral annular disjunction (MAD) is a pathologic fibrous separation of the mitral valve hinge point from the ventricular myocardium. The aims of this study were to describe the range of MAD distance by cardiovascular magnetic resonance (CMR) in children and young adults with connective tissue disorders (CTDs) versus a healthy control sample, and to assess the MAD distance as a predictor of adverse cardiovascular outcomes.

Methods: This was a retrospective, single-center study of healthy subjects and patients with Marfan syndrome, Loeys-Dietz syndrome, Ehlers-Danlos syndrome, or nonspecific CTD who underwent CMR between January 01, 2000 and January 01, 2020. The MAD distance was measured from the 2-chamber, 4-chamber, and left ventricular outflow tract views in systole and diastole and analyzed as absolute values as well as indexed to BSA and height. The primary outcome was a composite defined as the presence of significant ventricular arrhythmias, cardiac arrest, and/or death. Age-adjusted odds ratios with 95% confidence intervals and c-statistic are reported. Classification and Regression Tree analysis was performed to identify the most discriminating binary threshold to predict the occurrence of the composite outcome.

Results: Around 30 healthy control subjects and 254 patients with CTD met inclusion criteria. The mean ± SD age at initial CMR was 17±6years for patients with CTD and 14±3years for controls. The mean MAD distance was larger in patients with CTD compared to the control sample, and the maximum MAD distance in the control sample was 3.6 mm. Median follow-up in the CTD group was 5 years (IQR 3-11years). Thirty-four (15%) patients met the composite outcome. Systolic MAD distance was positively associated with the composite outcome. The optimal binary threshold for height-indexed maximum systolic MAD distance was 0.033 mm/cm with an event rate of 18.6% at/above threshold versus 2.6% below threshold (AUC 0.74). The association was independent of other important clinical predictors.

Conclusion: A small MAD distance can be measured in healthy children and young adults. Children and young adults with CTD have a longer MAD distance than healthy control subjects, and a longer MAD distance is associated with adverse outcomes.

Background: Exercise cardiovascular magnetic resonance (ExCMR) imaging using supine in-scanner ergometer has shown promise in differentiating pathological dilated cardiomyopathy (DCM) from physiological exercise-induced cardiac remodeling. Since 2020, the National Heart Centre Singapore (NHCS) has incorporated ExCMR into its clinical workflow for patients with suspected DCM. This study aims to compare the costs associated with ExCMR versus conventional CMR in the evaluation of DCM.

Methods: A retrospective analysis was conducted on patients referred for conventional CMR between 2016 and 2019, and those referred for ExCMR from 2020 to 2023. Both imaging modalities followed standardized protocols, with ExCMR incorporating additional assessments during peak exercise. Costs were recorded in Singapore dollars (SGD) prior to the application of healthcare subsidies.

Results: The total cost for conventional CMR was SGD 1831.36, while ExCMR was associated with a higher initial cost of SGD 2336.48. However, ExCMR resulted in significantly fewer abnormal imaging findings and a reduced need for follow-up investigations (6.5% (9/139) vs 56.8% (71/125), p<0.001). A decision tree analysis and probabilistic sensitivity analysis (PSA) revealed that diagnosing 1000 suspected DCM patients with ExCMR could result in a cost savings of approximately SGD 182,323 compared to conventional CMR, with a 64% probability of being cost-effective.

Conclusion: These findings indicate that ExCMR offers a physiologically informative approach for diagnosing DCM, with the potential to reduce overdiagnosis of cardiac dilatation in active, healthy adults. Although further research is necessary to assess long-term outcomes, ExCMR appears to be a cost-effective imaging modality for DCM diagnosis, warranting reconsideration of its perceived higher cost.

Myocardial perfusion imaging plays a central role in the management of patients with known or suspected coronary artery disease (CAD) and increasingly in patients with suspected ischemia with normal coronary arteries (INOCA) as well as anomalous origins of the coronary arteries and Kawasaki disease. Stress perfusion cardiovascular magnetic resonance (CMR) is recognized by international guidelines, with several Class 1 indications for the detection of abnormal myocardial blood flow in these clinical scenarios and offers excellent diagnostic accuracy and independent prognostic value. While visual interpretation of the perfusion data is the prevailing analysis method in clinical practice, quantitative perfusion CMR is at least as accurate for the detection of significant obstructive CAD and provides a more accurate estimation of the total ischemic burden in patients with CAD. Moreover, quantitative myocardial perfusion analysis provides unique insights into the pathophysiology of myocardial ischemia, including microvascular disease in INOCA. Quantitative perfusion CMR can be fully automated, is user-independent, and may facilitate more widespread use of the modality. The aim of this Society for Cardiovascular Magnetic Resonance (SCMR) expert consensus document is to provide recommendations for the acquisition and analysis of quantitative myocardial perfusion CMR to facilitate standardization of methodology. This paper also discusses research and development goals to address current limitations, to ensure data reliability and validity, to create the basis for future multi-vendor and multicenter research, and to broaden the clinical use of quantitative perfusion CMR.

Background: Cardiac magnetic resonance imaging (CMR) studies contain a wealth of information on a patient's cardiovascular status. The ability to extract this data from free-text reports could serve to automate clinical decision support tools and generate data for retrospective clinical knowledge discovery, and clinical operational purposes. Few studies have examined the automatic extraction of data from free-text CMR reports, and the existing studies that do have key limitations, including small sample size and disease-specific data extraction. Existing studies also fail to extract features associated with the cardiovascular conditions that reflect nuances in natural language, such as uncertainty, severity, subtype, and anatomical locations of the condition. The goal of this study was to build a broad named entity recognition model to automatically extract a broad variety of common CMR findings and their associated attributes from CMR reports.

Methods: We fine-tuned a Large Language Model Meta AI (LLaMA) model trained to identify 34 cardiovascular conditions and their associated attributes, including certainty, severity, location, and subtype of the condition. This model was trained on 1778 MRI reports and tested on 397 reports in an held-out test set and another 428 reports from another site in our hospital system with independent radiology practice and scanners.

Results: Our model shows robust performance in predicting the mention of the 31 cardiovascular conditions (average F1=0.85). It also showed strong performance predicting attributes, including certainty (average F1=0.97) and severity (average F1=0.97). Model performance on the external validation set was generally slightly lower than the internal validation set, but performance was still strong (average F1=0.78 for mention, 0.97 for certainty, and 0.96 for severity).

Conclusion: CMR-LLaMA has strong performance identifying a variety of concept mentions and moderate accuracies in extracting a selection of other associated attributes. NLP models can be used to automate the extraction of data from CMR reports to potentially assist with clinical and research workflow.

Background: Extracellular volume (ECV) determined by cardiovascular magnetic resonance (CMR) is considered a marker of diffuse myocardial fibrosis and a predictor of mortality. Using personalized computational models, we investigated the relationship between ECV, conduction velocity (CV), and cell radius in aortic stenosis (AS) patients.

Methods: CMR was performed on 12 AS patients (6 males, 6 females) before and three months after surgical aortic valve replacement (AVR). All patients had a QRS duration ≤110ms, and no scar on late gadolinium enhanced (LGE) CMR. Computational biventricular models were developed from each CMR dataset. Using patient-specific ECV and the relative change in cell radius between the time points as inputs, tissue conductivity was adjusted in each model to match the patient's QRS duration. A physiological pattern of ventricular depolarization was mimicked by simultaneously pacing each model from five activation sites. CV was measured during a simulation of apical pacing, using two points positioned at the right ventricular septum of the model.

Results: Left ventricular mass decreased after AVR (62 [58-79] vs 51 [41-60]g/m², p=0.0005) while ECV increased (24.2 [20.6-24.8] vs 28.0 [25.1-29.5] %, p=0.0008). No changes in the patient's QRS duration (89.0 [80.5-99.0] vs 88 [78.5-99.5]ms, p=0.2148) were observed. No changes in the CV obtained from the models (64.3 [61.9-72.8] vs 66.0 [60.0-74.5]cm/s, p=0.5186) were found between the time points, suggesting there was no substantial increase in diffuse fibrosis. ECV was negatively correlated with cell radius (r=-0.5267, p=0.0082), but not correlated with CV obtained from the models (r=-0.2036, p=0.3399).

Conclusion: Increased ECV three months after AVR in patients with no LGE scar and with normal ventricular conduction appears to be a footprint of reverse ventricular remodeling that does not necessarily translate into changes in myocardial CV.

Background: Cardiac diffusion tensor imaging (cDTI) is sensitive to imaging parameters, including the number of unique diffusion encoding directions (ND) and number of repetitions (NR; analogous to number of signal averages). However, there is no clear guidance for optimizing these parameters in the clinical setting.

Methods: Spin echo cDTI data with second-order motion-compensated diffusion encoding gradients were acquired in 10 healthy volunteers on a 3T magnetic resonance imaging scanner with different diffusion encoding schemes in pseudo-randomized order. The data were subsampled to yield 96 acquisition schemes with 6 ≤ ND ≤ 30 and 33 ≤ total number of acquisitions (NA_all) ≤ 180. Stratified bootstrapping with robust fitting was performed to assess the accuracy and precision of each acquisition scheme. This was quantified across a mid-ventricular short-axis slice in terms of root mean squared difference (RMSD), with respect to the full reference dataset, and standard deviation (SD) across bootstrap samples, respectively.

Results: For the same acquisition time, the ND = 30 schemes had on average 48%, 40%, 34%, and 34% lower RMSD and 6.2%, 7.4%, 10%, and 5.6% lower SD in mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and absolute sheetlet angle (|E2A|) compared to the ND = 6 schemes. Given a fixed number of high b-value acquisitions, there was a trend toward lower RMSD and SD of MD and FA with increasing numbers of low b-value acquisitions. Higher NA_all with longer acquisition times led to improved accuracy in all metrics, whereby quadrupling NA_all from 40 to 160 volumes led to a 20%, 39%, 11%, and 5.4% reduction in RMSD of MD, FA, HA, and |E2A|, respectively, averaged across six diffusion encoding schemes. Precision was also improved with a corresponding 53%, 50%, 53%, and 36% reduction in SD.

Conclusion: We observed that accuracy and precision were enhanced by (i) prioritizing number of diffusion encoding directions over NR given a fixed acquisition time, (ii) acquiring sufficient low b-value data, and (iii) using longer protocols where feasible. For clinically relevant protocols, our findings support the use of ND = 30 and NA_b50:NA_b500 ≥ 1/3 for better accuracy and precision in cDTI parameters. These findings are intended to help guide protocol optimization for harmonization of cDTI.

Background: Acute aortic syndromes in Marfan syndrome (MFS) often occur before reaching the surgical diameter threshold, highlighting the need for new imaging biomarkers.

Objectives: Aim was to compare cardiovascular magnetic resonance (CMR)-derived aortic three-dimensional (3D) distensibility and displacement in MFS patients with or without a history of aortic root surgery (RR or native) and healthy volunteers.

Methods: The participants underwent 3T CMR of the thoracic aorta using an accelerated non-contrast-enhanced, free breathing, 3D cine balanced steady state free precession sequence, with spatiotemporal resolution: (1.0 mm)³/∼33ms. A deep learning-based algorithm was used to obtain aorta segmentations. Non-rigid registration of these segmentations was subsequently used to calculate 3D distensibility and its separate components: 2-dimensional distensibility, longitudinal strain, and displacement in the ascending (AAo) and descending aorta (DAo).

Results: Forty-seven volunteers, 51 native, and 33 RR MFS patients were included. AAo and DAo distensibility (10^-3*mmHg^-1) were different for healthy volunteers vs native vs RR patients (AAo: 5.1±1.4 vs 3.6±1.4 vs. 1.4±0.7, p<0.001, DAo: 3.2±1.1 vs. 2.5±0.9 vs 2.4±1.0, p=0.001). Sinotubular junction displacement (mm) was significantly higher for healthy volunteers vs native MFS vs RR MFS patients (10.3±1.3 vs 8.7±2.1 vs 5.7±1.6, p<0.001). In native patients, age (β=-0.06 (95% CI:-0.10 to -0.01), p=0.014) and root diameter (β=-0.1 (95% CI: -0.19 to -0.02), p=0.018) were negatively associated with AAo 3D distensibility, independent of male sex, body surface area, and aortic tortuosity index.

Conclusion: Aortic 3D distensibility and displacement, derived from 4-dimensional CMR, were significantly diminished in MFS compared to volunteers and should be investigated longitudinally to assess their potential value in predicting aortic events and guiding therapy.

Background: First-pass stress-perfusion cardiovascular magnetic resonance (CMR) imaging is the guidelines-recommended non-invasive test for the detection of obstructive coronary artery disease (CAD). Recently developed quantitative perfusion CMR (QP CMR) allows quantification of myocardial blood flow. Moreover, the latest developments established several methods of CAD assessment without the need for a contrast agent, including stress T1 mapping reactivity (∆T1) and oxygenation-sensitive CMR (OS-CMR). These methods might eliminate the need for contrast administration in clinical practice, reducing time, invasiveness, and costs, thereby simplifying the evaluation of patients with suspected obstructive CAD. The ADVOCATE-CMR study aims to validate QP CMR, ∆T1, and OS-CMR imaging against invasive fractional flow reserve (FFR) for the detection of obstructive CAD. The study also aims to head-to-head compare the diagnostic accuracy of these CMR techniques with the conventional visual assessment of stress-perfusion CMR and to correlate them to short- and long-term clinical outcomes.

Study design and methodology: ADVOCATE-CMR is a single-center, observational, prospective, cross-sectional cohort study. The study will enroll 182 symptomatic patients with suspected obstructive CAD scheduled for invasive coronary angiography (ICA). Before ICA, all participants will undergo CMR imaging, including OS-CMR with breathing maneuvers, rest, and adenosine stress T1 mapping and rest and adenosine stress first-pass perfusion. Subsequently, ICA will be performed, including FFR, instantaneous wave-free ratio, resting Pd/Pa, coronary flow reserve, and index of microvascular resistance measurements in all main coronary arteries. A follow-up CMR scan with the same protocol will be performed at 3 months after ICA. Clinical follow-up will be performed at 3, 6 months, 1 and 3 years after ICA.

Conclusion: The ADVOCATE-CMR will be the first study comprehensively evaluating and comparing head-to-head the diagnostic performance of a range of contrast- and non-contrast agent-based CMR imaging methods (including QP CMR, ∆T1, and OS-CMR) for the detection of FFR-defined obstructive CAD. We expect to establish a validated and time-efficient diagnostic workflow available to a wide range of general CMR services. Finally, these improvements may enable CMR to become an effective non-invasive, radiation-free gatekeeper for ICA in patients with suspected obstructive CAD, potentially without the need for a contrast agent.