Feasibility of free-breathing quantitative myocardial perfusion using multi-echo Dixon magnetic resonance imaging

Abstract

Dynamic contrast-enhanced quantitative first-pass perfusion using magnetic resonance imaging enables non-invasive objective assessment of myocardial ischemia without ionizing radiation. However, quantification of perfusion is challenging due to the non-linearity between the magnetic resonance signal intensity and contrast agent concentration. furthermore, respiratory motion during data acquisition precludes quantification of perfusion. While motion correction techniques have been proposed, they have been hampered by the challenge of accounting for dramatic contrast changes during the bolus and long execution times. in this work we investigate the use of a novel free-breathing multi-echo Dixon technique for quantitative myocardial perfusion. the Dixon fat images, unaffected by the dynamic contrast-enhancement, are used to efficiently estimate rigid-body respiratory motion and the computed transformations are applied to the corresponding diagnostic water images. this is followed by a second non-linear correction step using the Dixon water images to remove residual motion. the proposed Dixon motion correction technique was compared to the stateof-the-art technique (spatiotemporal based registration). We demonstrate that the proposed method performs comparably to the state-of-the-art but is significantly faster to execute. Furthermore, the proposed technique can be used to correct for the decay of signal due to T2* effects to improve quantification and additionally, yields fat-free diagnostic images. Myocardial perfusion can be assessed using dynamic MRI during first-pass of a contrast agent 1. While the images are routinely reviewed visually in the clinic, quantification is desirable as it is user-independent 2. Quantification of myocardial perfusion can be challenging mainly due to the non-linearity between the signal intensity and contrast agent concentration at concentrations necessary to observe potential perfusion abnormalities within the myocardium 3. Furthermore, respiratory motion makes the quantification of perfusion difficult, and may even preclude it. Although most commonly used to mitigate respiratory motion, breath-holding for at least 40 s (to cover the full first pass of the contrast bolus) is challenging for many patients, particularly under stress conditions. Moreover, long breath-holds can lead to changes in heart rate, resulting in images being acquired at slightly different cardiac phases thus introducing cardiac motion. Conversely, if patients are allowed to breathe normally, respiratory motion tends to be more regular and shallower when compared to the large gasps that may occur when the patient can no longer hold their breath. Therefore, acquisitions in free-breathing are easier to correct for respiratory motion using image registration compared to breath-holding with intermittent breathing. The problem of registering myocardial perfusion MR images is, however, challenging due to the rapid change in signal intensity during the contrast bolus transit. The dynamic contrast-enhancement invalidate...

High-Resolution Free-Breathing Quantitative First-Pass Perfusion Cardiac MR Using Dual-Echo Dixon With Spatio-Temporal Acceleration

“…From this binary mask, a bounding box was automatically placed around the epicardial fat and was used to estimate rigid respiratory motion using the Fast Elastic Image Registration (FEIR) toolbox (24) with normalized gradient fields as an image similarity measure. Fat images were used as a stable reference for the anatomy because they do not show contrast uptake-related image intensity changes, as proposed by Scannell et al (19). A reference time frame, with superior-inferior (SI) motion displacement closest to the mean SI position, was selected.…”

“…This model comprises four neural networks applied sequentially: a convolutional neural network (CNN) to detect the timeframe with peak left ventricle (LV) enhancement, a CNN to select a bounding box that encompasses the LV cavity and myocardium, a U-Net to segment the myocardium, and a U-Net to detect the right ventricle insertion points that define the 16 AHA-segments. In addition, the dual-echo images were used for estimating the AIF and T * 2 -related signal loss by fitting the mean signal magnitude to an exponential decay model (19). Quantitative MBF values were estimated on a pixel-wise level by fitting the observed AIF and myocardial tissue curves to a two-compartment exchange model, using Bayesian inference (26).…”

“…Finally, MBF quantification may be biased by signal nonlinearities at very high contrast agent concentrations due to T 1 saturation and T * 2 -related signal loss (5,(16)(17)(18). Recently, a dual-bolus multi-echo Dixon QFPP-CMR framework has been proposed to address in-plane respiratory motion, T * 2 -related signal loss, and fat suppression (19). This method provides fat-only images, which were used to estimate respiratory motion, while motion-corrected water-only images were used for visual assessment and MBF quantification.…”

Cardiac adiposity as a modulator of cardiovascular disease in HIV

“…Further research is needed to investigate whether cardiac steatosis is linked to HIV infection and HFpEF among PLWH, in order to develop therapeutic strategies targeting markers of chronic inflammation and immune activation resulting in optimization of long‐term CV health in PLWH. Additionally, the application of multi‑echo Dixon magnetic resonance imaging, which is easier to use, might be a better option than MRS in quantifying cardiac steatosis, as the technical complexity of the latter may limit its application in clinical practice [15].…”

“…Cardiac magnetic resonance is regarded as the gold standard for pericardium visualization and has the advantage over CT that it lacks radiation exposure [12]. In addition, magnetic resonance spectroscopy (MRS) is considered the reference standard for the diagnosis of cardiac steatosis; moreover, newer CMR techniques such as multi‐echo Dixon methods, are also useful tools in quantifying myocardial triglyceride content [14,15]. The EAT/PAT thickness and volume have been associated with presence of coronary artery disease, atrial fibrillation, HFpEF and adverse outcomes in the general population [8,16‐18].…”