Journal of Cardiovascular Magnetic Resonance最新文献

Background: Physiological remodeling of the athlete's heart can resemble certain cardiomyopathies, underscoring the importance of robust reference standards. However, most cardiac magnetic resonance imaging (CMR) based studies focus on a narrow subset of adult athletes, providing limited insight into the broader spectrum of exercise-induced changes. Here, we aimed to characterize volumetric, functional, and strain-based adaptations across varying physical activity levels, age groups, and sexes and to establish reference ranges.

Methods: We enrolled 656 participants (13-35 years) in a cardiovascular screening program at our tertiary center (2009-2020). We excluded individuals with cardiac disease, risk factors, or abnormal screening findings. Participants were categorized as sedentary (≤3hours/week), recreational (4-6hours/week), or highly trained (>6hours/week) athletes. CMR was performed using 1.5T scanners to assess ventricular and atrial volumes, myocardial mass, ejection fractions, and feature-tracking strain. We derived 95% prediction intervals stratified by age, sex, and training volume.

Results: Of the 575 healthy subjects, 390 were highly trained athletes (22±6 years, 64% male, 19±7 training hours/week), 102 recreational athletes (23±6 years, 60% male, 4±1 training hours/week), and 83 sedentary individuals (26±4 years, 42% male, 1±1 training hours/week). Increasing weekly training hours were associated with larger ventricular volumes, higher myocardial mass, lower ejection fractions, and strain. Compared to sedentary individuals, highly trained athletes had significantly larger left and right ventricular volumes (LVEDVi estimate [95% CI]: 0.82 [0.52-1.12], p<0.001), higher myocardial mass (LVMI 0.59 [0.31-0.86], p<0.001), and increased left and right atrial volumes, even after adjusting for age, sex, and weekly training hours. We observed a non-uniform dose-response relationship across activity levels, with the most prominent cardiac adaptations occurring in highly trained athletes. Endurance athletes exhibited the most pronounced volumetric changes among the sport types. Finally, we derived stratified prediction intervals to provide CMR reference ranges in young, healthy individuals stratified by age, sex, general activity level, and weekly training hours.

Conclusions: This work underscores the influence of age, sex, physical activity level, and type of sports on cardiac adaptation. We provide prediction interval-based CMR reference ranges of volumes, mass, ejection fraction, and strain to improve disease discrimination in athletes.

Background: Cardiovascular magnetic resonance (CMR) imaging with contrast enhancement (CE) of the coronary artery wall was proved effective for detecting coronary involvement in IgG4-related disease (IgG4-RD). This study seeks to further investigate the value of coronary wall CE on CMR in assessing treatment response.

Methods: We prospectively enrolled 30 IgG4-RD patients with coronary involvement and conducted follow-up evaluations. All participants underwent coronary wall imaging with CMR, both before and after treatment with a combination of glucocorticoids and steroid-sparing immunosuppression. Concurrently, inflammatory-related laboratory markers and IgG4-RD Responder Index (RI) scores were collected and analyzed.

Results: Most patients (87%) exhibited a significant monthly reduction in total coronary wall CE area (ΔCE area/months=0.32 [IQR: 0.03-0.88] cm²/month) and contrast-to-noise ratio (CNR) (ΔCNR/months=0.09 [IQR: 0.01-0.41]/month). Both parameters were positively correlated with monthly changes in inflammatory markers, including ΔIgG4/months (r=0.366 and 0.388, respectively), ΔESR/months (r=0.617 and 0.539), ΔIgG/months (r=0.565 and 0.578), and ΔIgE/months (r=0.512 and 0.499) (all P<0.05). In the "heart/pericardium" organ-specific domain of the IgG4-RD RI, the rate of change in the modified index (RI') incorporating coronary wall CE was significantly greater than that of the standard RI (ΔRI'/months vs. ΔRI/months: 0.1 vs. 0, P=0.006). Similarly, in the overall multi-organ assessment, ΔRI'/months showed a significant improvement over ΔRI/months (0.68 vs. 0.67, P=0.006). Moreover, ΔCE area/months correlated positively with both ΔRI/months (r =0.627, P<0.001) and ΔRI'/months (r=0.683, P< 0.001). ΔCNR/months also correlated positively with ΔRI/months (r=0.500, P =0.005) and ΔRI'/months (r=0.548, P=0.002).

Conclusion: Glucocorticoid combined with steroid-sparing immunosuppression therapy is effective in treating IgG4-RD with coronary involvement. Coronary wall CE on CMR emerges as a valuable imaging biomarker that complements serological markers in assessing treatment response. Incorporating coronary wall CE enhances Responder Index scoring, aiding therapeutic decisions and disease monitoring.

Background: Reduced biventricular global function index (BVGFI) is associated with adverse outcomes in repaired tetralogy of Fallot (rTOF). The change in BVGFI associated with pulmonary valve replacement (PVR) is unknown.

Objectives: To characterize BVGFI following PVR in rTOF and identify pre-PVR factors associated with severely depressed post-PVR BVGFI.

Methods: Single-center retrospective cohort study of rTOF patients with a cardiac magnetic resonance (CMR) examination within 1 year before and 2 years after their first PVR and no interval cardiac procedures (n=133). CMR parameters between rTOF and normal controls (n=136) were compared. BVGFI was categorized as normal (≥46.2), mild-moderately depressed (40.0-46.1), or severely depressed (<40.0). Pre- vs. post-PVR changes and pre-PVR correlates of severely depressed post-PVR BVGFI were explored.

Results: When adjusted for age and sex, pre-PVR BVGFI was lower in patients with rTOF compared to controls (47.7±0.6 vs. 56.0±0.5, p<0.001), with 48% of rTOF patients having subnormal pre-PVR BVGFI. Overall, compared with pre-PVR values, mean BVGFI did not change after PVR (46.6±7.7 vs. 45.6±6.7, p=0.28), while RVGFI declined from 49.6±10.2 pre-PVR to 46.1±9.0 post-PVR (p=0.003). Among patients with normal pre-PVR BVGFI (n=69), 64% remained normal, whereas 36% declined. Of those with severely depressed pre-PVR BVGFI (n=24), 50% remained severely depressed, and only 4% achieved normalization of BVGFI after PVR. Factors independently associated with severely depressed post-PVR BVGFI were lower pre-PVR BVGFI, male sex, moderate or severe pulmonary regurgitation (PR), and higher left ventricular end-systolic volume index (LVESVi). Type of pre-PVR hemodynamic load was not associated with the odds of severely depressed BVGFI post-PVR.

Conclusions: BVGFI is depressed in about half of rTOF patients pre-PVR and did not significantly change post-PVR remaining stable in most patients. Lower pre-PVR BVGFI, male sex, moderate or severe PR, and higher LVESVi are independently associated with severely depressed post-PVR BVGFI.

Background: Right heart catheterisation (RHC) with pulmonary capillary wedge pressure (PCWP) assessment is the reference standard for diagnosis of heart failure with preserved ejection fraction (HFpEF), remains however largely underused. Different approaches for non-invasive PCWP calculation have been proposed. However, as left atrial strain (LA Es) and volume index (ESVi) emerge as a key-criteria in HFpEF, we sought to investigate them for PCWP calculation.

Methods: The derivation population consisted of patients referred to RHC and cardiovascular magnetic resonance (CMR) imaging who were enrolled in a prospective monocentric registry. Patients were classified by RHC according to current guideline recommendations. The external validation population consisted of patients included in the HFpEF-Stress trial who underwent exercise-stress RHC and CMR with follow-up after 4 years for hospitalised cardiovascular events. Performance of strain-derived PCWP was compared to a published LA volume (LAV) and LV mass (LVM) derived method.

Results: The derivation population consisted of n=209 patients, n=123 underwent exercise-stress RHC (n=55 without PH, n=72 pre-capillary, n=27 combined post- and pre-capillary pulmonary hypertension (CpcPH), n=15 isolated post-capillary pulmonary hypertension (IpcPH), n=34 exercise and n=6 unclassified PH). Linear regressions models identified the following formulae for functional PCWPrest 10.304-0.095*Es+0.098*ESVi and functional PCWPstress 24.666-0.251*Es+0.056*ESVi calculation. The validation population consisted of n=74 patients (n=15 without, n=5 pre-capillary, n=8 CpcPH, n=10 IpcPH and n=32 exercise PH with n=4 remaining unclassified). Functional PCWPrest (11.8) and RHC-derived PCWPrest (11mmHg) were statistically similar (p=0.285) and showed moderate correlation (r=0.53, p<0.001). Functional PCWPrest (AUC 0.80) and PCWPstress (AUC 0.85) accurately identified HFpEF patients, were superior to LAV/LVM based PCWP (AUC 0.67, p≤0.002) and showed prognostic implications (HR 1.37 (1.16-1.62) and 1.29 (1.14-1.46), p<0.001).

Conclusions: Functional PCWP may aide in the identification of post-capillary involvement in PH and HFpEF superiorly compared to morphology-derived PCWP and shows prognostic implications.

Background: Extracellular volume fraction (ECV) is an independent predictor of mortality in aortic stenosis (AS). ECV can be measured using myocardial T1 maps acquired before and after contrast administration. Standard ECV measurements do not consider the limited rate of water exchange (WX) between cardiomyocytes and the extracellular matrix which can result in underestimated ECV at higher contrast agent concentrations.

Objectives: The objective was to estimate ECV in patients with severe AS before and after surgical aortic valve replacement (AVR) using a 2-site exchange model (2SXM) that also enables estimates of the intracellular lifetime of water (τ_ic; an indicator of the minor diameter of the cardiomyocytes).

Methods: 20 patients (67±6 years) with severe AS, referred for AVR, underwent MRI on a 3 T MR system before and 6 months after AVR. T1 measurements were made using a multiparametric saturation-recovery single-shot acquisition before and at four time points post-injection of contrast agent. A 2SXM and standard linear model (LM) were used to estimate ECV and, when combined with indexed left ventricular mass (LVMI), to calculate cell and matrix volumes, (LVMI × (1-ECV)/1.05) and (LVMI × ECV/1.05), respectively. The 2SXM model was also used to estimate τ_ic.

Results: Data were acquired before and 174 (157 to 267) days after AVR. LVMI reduced following AVR, from 78±15 g/m² to 63±11 g/m² (p<0.001). ECV estimates increased from 22±3% to 28±5% (p<0.001) using the LM compared to 28±5% to 32±4% (p = 0.005) using the 2SXM. Indexed cell volume decreased from 58±12 cm³/m² to 43±9 cm³/m² (p<0.001; LM) and from 54±12 cm³/m² to 41±8 cm³/m² (p<0.001; 2SXM). Indexed matrix volume did not change significantly by either method (LM, 16±4 cm³/m² to 17±3 cm³/m²; 2SXM, 20±5 cm³/m² to 19±3 cm³/m²). τ_ic decreased from 0.21±0.12 s to 0.12±0.09 s (p = 0.007).

Conclusion: Cellular hypertrophy regressed 6 months following AVR; the extracellular matrix volume did not change significantly. τ_ic decreased post-AVR, indicating that the reduction in cell volume can be largely attributed to a reduction in cardiomyocyte diameter.

Background: Free-running (FR) cardiac MRI enables free-breathing ECG-free fully dynamic 5D (3D spatial+cardiac+respiration dimensions) imaging but poses significant challenges for clinical integration due to the volume of data and complexity of image analysis. Existing segmentation methods are tailored to 2D cine or static 3D acquisitions and cannot leverage the unique spatial-temporal wealth of FR data.

Purpose: To develop and validate a deep learning (DL)-based segmentation framework for isotropic 3D+cardiac cycle FR cardiac MRI that enables accurate, fast, and clinically meaningful anatomical and functional analysis.

Methods: Free-running, contrast-free bSSFP acquisitions at 1.5T and contrast-enhanced GRE acquisitions at 3T were used to reconstruct motion-resolved 5D datasets. From these, the end-expiratory respiratory phase was retained to yield fully isotropic 4D datasets. Automatic propagation of a limited set of manual segmentations was used to segment the left and right ventricular blood pool (LVB, RVB) and left ventricular myocardium (LVM) on reformatted short-axis (SAX) end-systolic (ES) and end-diastolic (ED) images. These were used to train a 3D nnU-Net model. Validation was performed using geometric metrics (Dice similarity coefficient [DSC], relative volume difference [RVD]), clinical metrics (ED and ES volumes, ejection fraction [EF]), and physiological consistency metrics (systole-diastole LVM volume mismatch and LV-RV stroke volume agreement). To assess the robustness and flexibility of the approach, we evaluated multiple additional DL training configurations such as using 4D propagation-based data augmentation to incorporate all cardiac phases into training.

Results: The main proposed method achieved automatic segmentation within a minute, delivering high geometric accuracy and consistency (DSC: 0.94 ± 0.01 [LVB], 0.86 ± 0.02 [LVM], 0.92 ± 0.01 [RVB]; RVD: 2.7%, 5.8%, 4.5%). Clinical LV metrics showed excellent agreement (ICC > 0.98 for EDV/ESV/EF, bias < 2mL for EDV/ESV, < 1% for EF), while RV metrics remained clinically reliable (ICC > 0.93 for EDV/ESV/EF, bias < 1mL for EDV/ESV, < 1% for EF) but exhibited wider limits of agreement. Training on all cardiac phases improved temporal coherence, reducing LVM volume mismatch from 4.0% to 2.6%.

Conclusion: This study validates a DL-based method for fast and accurate segmentation of whole-heart free-running 4D cardiac MRI. Robust performance across diverse protocols and evaluation with complementary metrics that match state-of-the-art benchmarks supports its integration into clinical and research workflows, helping to overcome a key barrier to the broader adoption of free-running imaging.

Background: Endomyocardial biopsy (EMB) is the standard invasive method for monitoring acute cardiac allograft rejection (ACAR); however, non-invasive alternatives are increasingly proving to be dependable.

Objectives: We aimed to identify and validate dependable cardiovascular magnetic resonance (CMR) strain indices for ACAR detection.

Methods: We analyzed 160 CMR scans, including long- and short-axis cines, as well as T1/T2 maps from 54 transplant recipients. Uniparametric and multiparametric models integrating left ventricular strain metrics and tissue characteristics were developed to classify histological rejection grades (0, 1 R, ≥2 R) and evaluate therapeutic response.

Results: Regression analysis using generalized linear mixed-models identified significant differences between rejection groups, with global radial strain (GRS) (z-value = 3.1, p = 0.002) and global circumferential strain (GCS) (z-value = 2.5 p<0.008) outperforming global longitudinal strain (GLS) in discriminating ≥2 R from 1 R rejection. Diagnostic performance for detecting ≥2 R rejection was excellent, particularly for GCS (AUC = 0.852, negative predictive value [NPV] = 98.3%) and GRS (AUC = 0.826, NPV = 95.8% (95.8/100)), with enhanced accuracy in the anterolateral mid-basal segments (AUC>0.886, NPV>97.9%). Strain metrics effectively monitored recovery post-therapy for ≥2 R rejection, showing significant improvements (GRS Δ24.5±7.1%, GCS Δ15.9±4.6%, GLS Δ27.4±11.8%, all p<0.02). Furthermore, as strained-based detection of ≥2 R rejection correlated with increases in edema detected using T1/T2 mapping (all p<0.001), integrating strain with T1/T2 mapping significantly enhanced diagnostic accuracy, with T2+GRS (AUC = 0.931, NPV = 98.2) and T1+T2+GCS (AUC = 0.943, NPV = 97.5) as the most effective models.

Conclusion: Segmental CMR strain analysis demonstrates excellent diagnostic accuracy and negative predictive value for detecting high-grade ACAR and monitoring post-therapy recovery. This non-invasive approach, particularly when integrated with multiparametric models combining global strain and tissue mapping, has the potential to reduce reliance on invasive EMBs for ACAR surveillance in cardiac transplant recipients.

Background: Quantitative perfusion cardiovascular magnetic resonance (QP-CMR) allows the generation of pixel-wise myocardial blood flow (MBF) maps using model-based deconvolution with several models including Tofts, modified-Tofts, and Fermi function models. However, the accuracy of pixel-wise MBF mapping has not been fully investigated in humans. The aim of this study was to evaluate the accuracy of advanced QP-CMR using ¹⁵O-water positron emission tomography (PET) as a reference.

Methods: Thirty-nine patients (29 men, 68±11years) with known or suspected coronary artery disease underwent both CMR including stress and rest QP-CMR and ¹⁵O-water PET at a median interval of 13 days. QP-CMR was performed using dual-sequence technique and a single bolus of gadolinium contrast agent during adenosine triphosphate stress and at rest. MBF maps were generated using three different model-based deconvolution techniques as follows: Tofts, modified-Tofts, and Fermi function models. Agreement of MBF and myocardial perfusion reserve (MPR) between QP-CMR and ¹⁵O-water PET was evaluated using Pearson's correlation, Bland-Altman analysis, and intraclass correlation (ICC). The ability of CMR-derived stress MBF and MPR to detect PET-defined abnormal myocardial perfusion (stress MBF ≤2.3 mL/min/g and MPR ≤2.5) was evaluated by receiver operating characteristic (ROC) analysis.

Results: CMR-derived MBF showed a good linear correlation with ¹⁵O-water PET-derived MBF in each of the Tofts, modified-Tofts, and Fermi function models (r = 0.776, 0.752, 0.784, respectively; p<0.001 each) at the patient level. Bland-Altman analysis demonstrated measurement biases for MBF between CMR and ¹⁵O-water PET of 0.31±0.70, 0.05±0.63, and 0.26±0.68 mL/min/g for the Tofts, modified-Tofts, and Fermi function models, respectively. ICCs were 0.734, 0.747, and 0.750, respectively. The area under the ROC curves for stress MBF derived from the Tofts and Fermi function models (0.921 and 0.914, respectively) was significantly higher than that derived from the modified-Tofts model (0.861; p = 0.003 for both). However, there was no significant difference between the Tofts and Fermi function models (p = 0.618).

Conclusion: Advanced QP-CMR using three different model-based deconvolution techniques demonstrated strong agreement with ¹⁵O-water PET. Of these techniques, the Fermi function and Tofts models were more effective in detecting abnormal myocardial perfusion as determined by ¹⁵O-water PET. Considering our results, the model complexity, and its technical availability, the Fermi function model may possess a practical advantage.

Background: Commercial 0.55T low-field magnetic resonance imaging (MRI) systems have recently become available, offering the potential to enhance global accessibility to MRI. T1ρ mapping is an emerging quantitative cardiac MR imaging technique capable of detecting myocardial disease without the need for contrast administration. However, experience with cardiac T1ρ mapping at low-field strength remains limited. This study aims to develop and validate an efficient, free-breathing three-dimensional (3D) high-resolution adiabatic T1ρ mapping sequence for non-contrast whole-heart tissue characterization at 0.55T.

Methods: The proposed 3D T1ρ mapping research sequence acquires four interleaved volumes with different contrast weightings using saturation and adiabatic spin-lock preparation pulses, and a 3-parameter fitting method is used to calculate T1ρ maps. Two-dimensional (2D) image navigators are acquired for non-rigid motion-compensated image reconstruction, enabling 100% respiratory scan efficiency. Phantom and in-vivo experiments in 10 healthy volunteers were conducted to evaluate the accuracy and precision of the proposed 3D sequence in comparison with 2D T1ρ mapping sequences.

Results: Phantom T1ρ values measured using the proposed 3D sequence showed strong agreement with the 2D reference (R² = 0.997), demonstrating high accuracy and reduced sensitivity to heart rate variations. In-vivo experiments in healthy subjects demonstrated that the proposed sequence is feasible for acquiring whole-heart T1ρ maps with 2 mm isotropic resolution in an efficient scan time of 6.6±0.5 min. The mean myocardial T1ρ value obtained with the 3D sequence was slightly higher than that of a conventional 2D breath-hold sequence (112.8±16.7 vs. 106.1±15.1%, p<0.01), while coefficient of variation (CV) was slightly lower (10.2±5.2 vs. 11.4±4.4%, p = 0.02).

Conclusion: The proposed sequence enables 3D free-breathing high-resolution adiabatic T1ρ mapping and shows promising potential for non-contrast whole-heart tissue characterization at 0.55T.