Person:

Nezafat, Reza

Electro-anatomical voltage mapping (EAM) is an invasive technique used for the identification of ventricular tachycardia (VT) substrate and subsequent guidance of VT ablation [1]. The mapping of VT substrate is very time consuming procedure, requires highly skilled electrophysiologist, is associated with patient risk and is an invasive procedure. Late gadolinium enhancement (LGE) MRI allows non-invasive evaluation of 3D structure of scar. Therefore, LGE has the potential to identify the VT substrate and can now be integrated in the current clinical platform for guidance of VT ablation as a roadmap. However, fusion of the two imaging modality is very challenging due to respiratory and cardiac motion during the mapping which results in large errors in data fusion. Our aim in this study is to develop a novel algorithm to detect the respiratory and cardiac-induced motion of the mapping catheter during the VT ablation to facilitate integration of LGE MRI to EAM data.

Summary. We assess left atrial scar using late gadolinium enhancement (LGE) with isotropic spatial resolution of (1.4^3 mm^3) by using highly accelerated LOST [1] reconstruction. Background. Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia [2]. Pulmonary vein isolation (PVI) using radiofrequency (RF)-ablation is the leading treatment for AF. Recently, LGE imaging of the LA has been used to identify atrial wall scar due to RF-ablation [3]. However, current LGE methods have limited spatial resolution that substantially impact assessment of scar in the complex geometry of PVs and LA. In this study, we sought to utilize prospective random k-space sampling and LOST [1] for accelerated LGE imaging, where reduction in imaging time was traded-off for improved isotropic spatial-resolution. Methods. 23 patients with history of AF (6 females, (58.1 \pm 9.6) years, 9 pre-PVI, 2 with history of PVI; 8 post-PVI; 3 with both pre and post-PVI) were recruited for this study. LGE images were acquired 10-to-20 minutes after bolus infusion of 0.2 mmol/kg Gd-DTPA. Free-breathing ECG-triggered navigator-gated inversion-recovery GRE sequences were used for all acquisitions ((TR/TE/ \alpha = 5.2/2.6ms/25°, FOV=320×320×100mm)). The PV inflow artifact reduction technique in [4] was also utilized. For each patient, a standard non-isotropic 3D LGE scan ((1.4×1.4×4.0mm^3)) and a 3-fold-accelerated highresolution 3D LGE scan ((1.4^3 mm^3)) were performed, with randomized acquisition order. For random undersampling, central k-space (45×35 in ky-kz) was fullysampled, edges randomly discarded, and phase reordering performed as in [5]. Acquisition times were ~4 mins assuming 100% scan-efficiency at 70bpm for both scans. All undersampled data were reconstructed offline using LOST [1]. LOST-reconstructed high-resolution, and standard LGE images were scored by two blinded readers for diagnostic value, presence of LGE(yes/no); and image quality in axial(Ax), coronal(Co) and sagittal (Sa) views (1=poor,4=excellent). Results. Three cases were declared non-diagnostic due to contrast-washout and imperfect inversion-time. LGE was visually present in 14 of the remaining 20 patients based on standard-LGE images, and 12 based on LOST-reconstructed ones (disagreement on one pre- and one postPVI patient). Figure 1 and 2 show comparisons of isotropic vs. non-isotropic LGE images in two patients. Image scores for LOST-LGE: ( Ax=2.90 \pm 0.70, Sa=3.33 \pm 0.66, Co=3.00 \pm 0.63); and standard LGE: (Ax=3.76 \pm 0.54, Sa=2.48 \pm 0.60, Co=2.24 \pm 0.44), where differences were significant in all views. Conclusions. LOST allows isotropic spatial-resolution in LGE for assessment of LA and PV scar. Isotropic resolution allows reformatting LGE images in any orientation and facilitates assessment of scar. Further clinical study is needed to assess if the improved spatial resolution will impact the diagnostic interpretation of data.

Background. In conventional prospective respiratory navigator (NAV) acquisitions, 40-60% of the acquired data are discarded resulting in low efficiency and long scan times [1,2].Compressed-sensing Motion Compensation (CosMo) has a shorter fixed scan time by acquiring the full inner k-space and estimating the NAV-rejected outer k-space lines [3]. Respiratory motion will mainly manifest itself as phase variation in the acquired k-space data. We sought to determine if the addition of the magnitude of the rejected k-space lines as a constraint in image reconstruction will improve the performance of CosMo. Methods. To investigate the variability of the magnitude of kspace lines at different respiratory phases, free-breathing, ECG-triggered, targeted right coronary images with multiple averages were acquired from 10 healthy adult subjects. Magnitude variability was investigated quantitatively by calculating the cross-correlation between accepted and rejected k-space lines. CosMo was implemented retrospectively on one acquisition from each subject. The inner k-space (31 ky by 7 kz lines) was filled with lines acquired within the 5mm gating window from all acquisitions. The outer kspace was then filled only with lines from the first average acquired within the 5 mm gating window, resulting in an undersampled k-space with a fully sampled center. For reliable image reconstruction with CosMo, 10-20% of the inner k-space must be fully-sampled. The missing outer k-space lines were then estimated using LOST with an additional magnitude constraint within each estimation iteration or in the final iteration for each coil [4]. The results were compared with prospective NAVgating with a gating window of 5 mm and CosMo reconstruction without the magnitude constraint. Results. Figure 1 shows the cross-correlation between the accepted and worst rejected k-space lines for each position. The correlation is close to 1 at the center of kspace where the majority of image information is contained, indicating low variability in magnitude information at different respiratory phases. Figure 2 shows right coronary images acquired using a) fully-sampled, 5-mm gated data, b) the original CosMo, and CosMo with the additional magnitude constraint c) inside each iteration and d) in the final iteration. The relative signal-to-noise in the left ventricle blood pool is: (30.71 \pm 6.5; 40.32 \pm 14.2; 53.9 \pm 26.8; 56.8 \pm 25.9) for each reconstruction, respectively. Significant differences (p<0.05) are present for all measurements except between the original CosMo and the CosMo image with the magnitude constraint in each iteration (p=0.09). Conclusions. The addition of the magnitude of rejected lines, readily available in all navigator-gated scans, as a constraint in CosMo results in improved image quality as measured by relative SNR. Funding. NIH R01EB008743-01A2.