Isabel Montón Quesada

Purpose: To develop, optimize, and characterize a respiratory motion‐resolved free‐running isotropic 3D carotid vessel wall T ₁ mapping technique named CARISMAT1C. Methods: An inversion‐recovery gradient‐echo free‐running pulse sequence with interleaved double flip‐angle (2FA) was implemented, and an extended‐phase‐graph dictionary was used to map the T ₁ relaxation time. In a phantom, the T ₁ accuracy was compared to that of a single‐flip‐angle (1FA) variant, the inversion‐recovery spin‐echo reference, and clinical routine MOLLI, while the T ₁ precision of several phyllotaxis‐based radial trajectories was compared. The most precise sequence was used in 11 healthy volunteers (25 ± 3Y, 3F). A synthetic 3D gray‐blood image was reconstructed from the source images and used to delineate the internal, external, and common carotid arteries. T ₁ values across artery sections were compared to those of MOLLI. Results: In the phantom, the 2FA variant had higher T ₁ agreement with the IR‐SE reference than 1FA or MOLLI. The top‐to‐bottom phyllotaxis trajectory with golden‐step shuffling was the most precise and was retained for in vivo scans. End‐expiratory carotid vessel wall T ₁ values (1185 ± 42 ms) were similar to those obtained with MOLLI (1162 ± 84 ms, p = 0.37) and showed less intersubject variability and high interscan repeatability. No significant differences were found across arterial segments in the vessel wall T ₁ values. Conclusion: CARISMAT1C had high T ₁ accuracy in phantoms and high T ₁ precision in vivo in different sections of the carotid artery tree.

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 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 < 2 mL for EDV/ESV, < 1% for EF), while RV metrics remained clinically reliable (ICC > 0.93 for EDV/ESV/EF, bias < 1 mL 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.

Purpose: To optimize and characterize an interrupted 5D free‐running framework at 3 T for detailed cardiac function assessment without the use of breath holding or contrast agents. Methods: A free‐running 3D radial gradient echo sequence was periodically interrupted with a preparation and a recovery module to optimize native blood‐to‐myocardium contrast at 3 T. Lipid signal was suppressed using a numerically optimized water‐excitation RF pulse to reduce lipid streaking artifacts and to improve overall image quality. Optimal acquisition parameters were established for a 5‐min scan time using extended phase graph simulations. A compressed sensing‐based reconstruction incorporating cardiac and respiratory inter‐bin deformation fields was employed to generate 5D images of the whole heart. The sharpness and contrast between the left ventricular blood pool and myocardium, along with the functional measurements of the left ventricle from the 5D datasets, were compared to routine 2D cine imaging in 16 healthy volunteers and three patients referred for clinically indicated CMR. Results: The proposed method resulted in lower contrast vs. and sharpness vs. , but enabled similar left‐ventricle ejection fraction assessment , limits of , intraclass correlation with high reproducibility compared to 2D cine. Conclusion: The proposed contrast‐free, interrupted free‐running 5D imaging provides left ventricular functional assessments comparable to 2D cine at 3 T, while offering an improved patient experience through shorter scan times and free breathing.

Purpose: To compare two blind source separation (BSS) techniques to principal component analysis and the electrocardiogram for the identification of cardiac triggers in self‐gated free‐running 5D whole‐heart MRI. To ascertain the precision and robustness of the techniques, they were compared in three different noise and contrast regimes.Methods: The repeated superior–inferior (SI) projections of a 3D radial trajectory were used to extract the physiological signals in three cardiac MRI cohorts: (1) 9 healthy volunteers without contrast agent injection at 1.5T, (2) 30 ferumoxytol‐injected congenital heart disease patients at 1.5T, and (3) 12 gadobutrol‐injected patients with suspected coronary artery disease at 3T. Self‐gated cardiac triggers were extracted with the three algorithms (principal component analysis [PCA], second‐order blind identification [SOBI], and independent component analysis [ICA]) and the difference with the electrocardiogram triggers was calculated. PCA and SOBI triggers were retained for image reconstruction. The image sharpness was ascertained on whole‐heart 5D images obtained with PCA and SOBI and compared among the three cohorts.Results: SOBI resulted in smaller trigger differences in Cohorts 1 and 3 compared to PCA (p < 0.01) and in all cohorts compared to ICA (p < 0.04). In Cohorts 1 and 3, the sharpness increased significantly in the reconstructed images when using SOBI instead of PCA (p < 0.03), but not in Cohort 2 (p = 0.4).Conclusion: We have shown that SOBI results in more precisely extracted self‐gated triggers than PCA and ICA. The validation across three diverse cohorts demonstrates the robustness of the method against acquisition variability.