Cardiovascular magnetic resonance (CMR) imaging is a powerful tool for assessing the function and structure of the heart. An emerging application of CMR is quantitative tissue characterization of the myocardial substrate, which can potentially provide earlier and more sensitive detection of various pathologies than conventional qualitative imaging. Some of the most commonly measured tissue properties are the MRI relaxation time constants T1 and T2. Recently, novel methods including cardiac Magnetic Resonance Fingerprinting (MRF) have been proposed to simultaneously quantify multiple tissue properties during a single rapid acquisition. By combining a fast undersampled data acquisition with dictionary-based pattern matching, cardiac MRF has the potential to streamline CMR exams and provide highly accurate, precise, and reproducible measurements. However, the processes of MRF dictionary generation and pattern matching can be time-consuming and memory-intensive, especially in applications that seek to quantify a large number of tissue properties simultaneously or that require frequent dictionary generation. The combination of deep learning methods with MRF is an emerging research field that may address many of the limitations of dictionary-based MRF and may facilitate the clinical translation of novel cardiac MRF technology. This chapter will begin by providing an overview of conventional methods for CMR tissue parameter mapping before introducing the concept of MRF. We will discuss some challenges associated with current implementations of cardiac MRF and how these may be overcome using artificial intelligence (AI), including a review of several state-of-the-art deep learning methods.
Purpose This study explores the possibility of using a gradient moment balanced sequence with a quadratically varied RF excitation phase in the magnetic resonance fingerprinting (MRF) framework to quantify T 2 * in addition to , T 1 , and T 2 tissue properties. Methods The proposed quadratic RF phase‐based MRF method (qRF‐MRF) combined a varied RF excitation phase with the existing balanced SSFP (bSSFP)‐based MRF method to generate signals that were uniquely sensitive to , T 1 , T 2 , as well as the distribution width of intravoxel frequency dispersion, . A dictionary, generated through Bloch simulation, containing possible signal evolutions within the physiological range of , T 1 , T 2 , and , was used to perform parameter estimation. The estimated T 2 and were subsequently used to estimate T 2 * . The proposed method was evaluated in phantom experiments and healthy volunteers ( N = 5). Results The T 1 and T 2 values from the phantom by qRF‐MRF demonstrated good agreement with values obtained by traditional gold standard methods (r 2 = 0.995 and 0.997, respectively; concordance correlation coefficient = 0.978 and 0.995, respectively). The T 2 * values from the phantom demonstrated good agreement with values obtained through the multi‐echo gradient‐echo method (r 2 = 0.972, concordance correlation coefficient = 0.983). In vivo qRF‐MRF‐measured T 1 , T 2 , and T 2 * values were compared with measurements by existing methods and literature values. Conclusion The proposed qRF‐MRF method demonstrated the potential for simultaneous quantification of , T 1 , T 2 , and T 2 * tissue properties.
This study introduces a technique for simultaneous multislice (SMS) cardiac magnetic resonance fingerprinting (cMRF), which improves the slice coverage when quantifying myocardial T 1, T 2 , and M 0 . The single‐slice cMRF pulse sequence was modified to use multiband (MB) RF pulses for SMS imaging. Different RF phase schedules were used to excite each slice, similar to POMP or CAIPIRINHA, which imparts tissues with a distinguishable and slice‐specific magnetization evolution over time. Because of the high net acceleration factor ( R = 48 in plane combined with the slice acceleration), images were first reconstructed with a low rank technique before matching data to a dictionary of signal timecourses generated by a Bloch equation simulation. The proposed method was tested in simulations with a numerical relaxation phantom. Phantom and in vivo cardiac scans of 10 healthy volunteers were also performed at 3 T. With single‐slice acquisitions, the mean relaxation times obtained using the low rank cMRF reconstruction agree with reference values. The low rank method improves the precision in T 1 and T 2 for both single‐slice and SMS cMRF, and it enables the acquisition of maps with fewer artifacts when using SMS cMRF at higher MB factors. With this technique, in vivo cardiac maps were acquired from three slices simultaneously during a breathhold lasting 16 heartbeats. SMS cMRF improves the efficiency and slice coverage of myocardial T 1 and T 2 mapping compared with both single‐slice cMRF and conventional cardiac mapping sequences. Thus, this technique is a first step toward whole‐heart simultaneous T 1 and T 2 quantification with cMRF.
To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues.MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis.The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2 > 0.840).Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.
Women’s engagement in medicine, and more specifically cardiovascular imaging and cardiovascular MRI (CMR), has undergone a slow evolution over the past several decades. As a result, an increasing number of women have joined the cardiovascular imaging community to contribute their expertise. This collaborative work summarizes the barriers that women in cardiovascular imaging have overcome over the past several years, the positive interventions that have been implemented to better support women in the field of CMR, and the challenges that still remain, with a special emphasis on women physicians.
This study introduces a technique called cine magnetic resonance fingerprinting (cine‐MRF) for simultaneous T 1 , T 2 and ejection fraction (EF) quantification. Data acquired with a free‐running MRF sequence are retrospectively sorted into different cardiac phases using an external electrocardiogram (ECG) signal. A low‐rank reconstruction with a finite difference sparsity constraint along the cardiac motion dimension yields images resolved by cardiac phase. To improve SNR and precision in the parameter maps, these images are nonrigidly registered to the same phase and matched to a dictionary to generate T 1 and T 2 maps. Cine images for computing left ventricular volumes and EF are also derived from the same data. Cine‐MRF was tested in simulations using a numerical relaxation phantom. Phantom and in vivo scans of 19 subjects were performed at 3 T during a 10.9 seconds breath‐hold with an in‐plane resolution of 1.6 x 1.6 mm 2 and 24 cardiac phases. Left ventricular EF values obtained with cine‐MRF agreed with the conventional cine images (mean bias −1.0%). Average myocardial T 1 times in diastole/systole were 1398/1391 ms with cine‐MRF, 1394/1378 ms with ECG‐triggered cardiac MRF (cMRF) and 1234/1212 ms with MOLLI; and T 2 values were 30.7/30.3 ms with cine‐MRF, 32.6/32.9 ms with ECG‐triggered cMRF and 37.6/41.0 ms with T 2 ‐prepared FLASH. Cine‐MRF and ECG‐triggered cMRF relaxation times were in good agreement. Cine‐MRF T 1 values were significantly longer than MOLLI, and cine‐MRF T 2 values were significantly shorter than T 2 ‐prepared FLASH. In summary, cine‐MRF can potentially streamline cardiac MRI exams by combining left ventricle functional assessment and T 1 ‐T 2 mapping into one time‐efficient acquisition.
Despite decades of accruing evidence supporting the clinical utility of cardiovascular magnetic resonance (CMR), adoption of CMR in routine cardiovascular practice remains limited in many regions of the world. Persistent use of long scan times of 60 min or more contributes to limited adoption, though techniques available on most scanners afford routine CMR examination within 30 min. Incorporating such techniques into standardize protocols can answer common clinical questions in daily practice, including those related to heart failure, cardiomyopathy, ventricular arrhythmia, ischemic heart disease, and non-ischemic myocardial injury. In this white paper, we describe CMR protocols of 30 min or shorter duration with routine techniques with or without stress perfusion, plus specific approaches in patient and scanner room preparation for efficiency. Minimum requirements for the scanner gradient system, coil hardware and pulse sequences are detailed. Recent advances such as quantitative myocardial mapping and other add-on acquisitions can be incorporated into the proposed protocols without significant extension of scan duration for most patients. Common questions in clinical cardiovascular practice can be answered in routine CMR protocols under 30 min; their incorporation warrants consideration to facilitate increased access to CMR worldwide.
This paper presents the 3-D kinematic modeling of a novel steerable robotic ablation catheter system. The catheter, embedded with a set of current-carrying microcoils, is actuated by the magnetic forces generated by the magnetic field of the magnetic resonance imaging (MRI) scanner.This paper develops a 3-D model of the MRI-actuated steerable catheter system by using finite differences approach. For each finite segment, a quasi-static torque-deflection equilibrium equation is calculated using beam theory. By using the deflection displacements and torsion angles, the kinematic model of the catheter system is derived.The proposed models are validated by comparing the simulation results of the proposed model with the experimental results of a hardware prototype of the catheter design. The maximum tip deflection error is 4.70 mm and the maximum root-mean-square error of the shape estimation is 3.48 mm.The results demonstrate that the proposed model can successfully estimate the deflection motion of the catheter.The presented 3-D deflection model of the magnetically controlled catheter design paves the way to efficient control of the robotic catheter for the treatment of atrial fibrillation.
