3D late gadolinium enhanced cardiovascular MR with CENTRA-PLUS profile/view ordering: Feasibility of right ventricular myocardial damage assessment using a swine animal model

Kawaji, Keigo; Tanaka, Akiko; Patel, Mita; Wang, Hui; Maffessanti, Francesco; Ota, Takeyoshi; Patel, Amit R.

doi:10.1016/j.mri.2017.01.015

Cited by 7 publications

(6 citation statements)

References 21 publications

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“…Nevertheless, pig model is a well-stablished model for cardiac research and in vivo pig acquisitions can be performed under free-breathing conditions without significantly decreasing image quality [35][36][37]. Additionally, feasibility studies of new cardiac acquisitions have been successfully performed on pigs [40][41][42][43]. A clinical study will be required to evaluate the performance of 3D SACORA (single breath-hold of 15s, for a heart rate of 60 bpm) in patients with ischemic and non-ischemic cardiomyopathies.…”

Section: Discussionmentioning

confidence: 99%

Single breath-hold saturation recovery 3D cardiac T1 mapping via compressed SENSE at 3T

Silva

Galán‐Arriola

Montesinos

et al. 2020

Magn Reson Mater Phy

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Objectives To propose and validate a novel imaging sequence that uses a single breath-hold whole-heart 3D T1 saturation recovery compressed SENSE rapid acquisition (SACORA) at 3T. Methods The proposed sequence combines flexible saturation time sampling, compressed SENSE, and sharing of saturation pulses between two readouts acquired at different RR intervals. The sequence was compared with a 3D saturation recovery single-shot acquisition (SASHA) implementation with phantom and in vivo experiments (pre and post contrast; 7 pigs) and was validated against the reference inversion recovery spin echo (IR-SE) sequence in phantom experiments. Results Phantom experiments showed that the T1 maps acquired by 3D SACORA and 3D SASHA agree well with IR-SE. In vivo experiments showed that the pre-contrast and post-contrast T1 maps acquired by 3D SACORA are comparable to the corresponding 3D SASHA maps, despite the shorter acquisition time (15s vs. 188s, for a heart rate of 60 bpm). Mean septal pre-contrast T1 was 1453 ± 44 ms with 3D SACORA and 1460 ± 60 ms with 3D SASHA. Mean septal post-contrast T1 was 824 ± 66 ms and 824 ± 60 ms. Conclusion 3D SACORA acquires 3D T1 maps in 15 heart beats (heart rate, 60 bpm) at 3T. In addition to its short acquisition time, the sequence achieves good T1 estimation precision and accuracy.

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Section: Discussionmentioning

confidence: 99%

Single breath-hold saturation recovery 3D cardiac T1 mapping via compressed SENSE at 3T

Silva

Galán‐Arriola

Montesinos

et al. 2020

Magn Reson Mater Phy

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“…However, the suitability of the proposed method for detecting coronary thrombus still needs to be investigated. Nevertheless, this indicates that the proposed framework is quite versatile and could potentially be used with other free-breathing LGE or PSIR techniques [ 38 , 39 ].…”

Section: Discussionmentioning

confidence: 99%

Accelerated high-resolution free-breathing 3D whole-heart T2-prepared black-blood and bright-blood cardiovascular magnetic resonance

Correia

Ginami

Rashid

et al. 2020

Journal of Cardiovascular Magnetic Resonance

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Background The free-breathing 3D whole-heart T2-prepared Bright-blood and black-blOOd phase SensiTive inversion recovery (BOOST) cardiovascular magnetic resonance (CMR) sequence was recently proposed for simultaneous bright-blood coronary CMR angiography and black-blood late gadolinium enhancement (LGE) imaging. This sequence enables simultaneous visualization of cardiac anatomy, coronary arteries and fibrosis. However, high-resolution (< 1.4 × 1.4 × 1.4 mm3) fully-sampled BOOST requires long acquisition times of ~ 20 min. Methods In this work, we propose to extend a highly efficient respiratory-resolved motion-corrected reconstruction framework (XD-ORCCA) to T2-prepared BOOST to enable high-resolution 3D whole-heart coronary CMR angiography and black-blood LGE in a clinically feasible scan time. Twelve healthy subjects were imaged without contrast injection (pre-contrast BOOST) and 10 patients with suspected cardiovascular disease were imaged after contrast injection (post-contrast BOOST). A quantitative analysis software was used to compare accelerated pre-contrast BOOST against the fully-sampled counterpart (vessel sharpness and length of the left and right coronary arteries). Moreover, three cardiologists performed diagnostic image quality scoring for clinical 2D LGE and both bright- and black-blood 3D BOOST imaging using a 4-point scale (1–4, non-diagnostic–fully diagnostic). A two one-sided test of equivalence (TOST) was performed to compare the pre-contrast BOOST images. Nonparametric TOST was performed to compare post-contrast BOOST image quality scores. Results The proposed method produces images from 3.8 × accelerated non-contrast-enhanced BOOST acquisitions with comparable vessel length and sharpness to those obtained from fully- sampled scans in healthy subjects. Moreover, in terms of visual grading, the 3D BOOST LGE datasets (median 4) and the clinical 2D counterpart (median 3.5) were found to be statistically equivalent (p < 0.05). In addition, bright-blood BOOST images allowed for visualization of the proximal and middle left anterior descending and right coronary sections with high diagnostic quality (mean score > 3.5). Conclusions The proposed framework provides high‐resolution 3D whole-heart BOOST images from a single free-breathing acquisition in ~ 7 min.

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“…6 This has been catalyzed by the capacity of 3D LGE-MR images to provide improved spatial resolution, while enabling volumetric reconstruction of scar geometry. [7][8][9][10] Compared to 2D techniques, 3D LGE-MR images have been shown to provide higher signal intensity and contrast for myocardial scar with reduced overall acquisition times. [11][12][13] However, the segmentation of scar from 3D LGE-MR images is highly tedious, time-consuming (%54 min 14 ), and subject to high observer variability.…”

Section: Introductionmentioning

confidence: 99%

“…However, the use of three‐dimensional (3D) acquisition techniques is rapidly growing due to advancement in both hardware technology and experience, as well as strong interest from the electrophysiology community to use such images to guide interventions . This has been catalyzed by the capacity of 3D LGE‐MR images to provide improved spatial resolution, while enabling volumetric reconstruction of scar geometry . Compared to 2D techniques, 3D LGE‐MR images have been shown to provide higher signal intensity and contrast for myocardial scar with reduced overall acquisition times .…”

Section: Introductionmentioning

confidence: 99%

Fully automated segmentation of left ventricular scar from 3D late gadolinium enhancement magnetic resonance imaging using a cascaded multi‐planar U‐Net (CMPU‐Net)

et al. 2020

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Purpose: Three-dimensional (3D) late gadolinium enhancement magnetic resonance (LGE-MR) imaging enables the quantification of myocardial scar at high resolution with unprecedented volumetric visualization. Automated segmentation of myocardial scar is critical for the potential clinical translation of this technique given the number of tomographic images acquired. Methods: In this paper, we describe the development of cascaded multi-planar U-Net (CMPU-Net) to efficiently segment the boundary of the left ventricle (LV) myocardium and scar from 3D LGE-MR images. In this approach, two subnets, each containing three U-Nets, were cascaded to first segment the LV myocardium and then segment the scar within the presegmented LV myocardium. The U-Nets were trained separately using two-dimensional (2D) slices extracted from axial, sagittal, and coronal slices of 3D LGE-MR images. We used 3D LGE-MR images from 34 subjects with chronic ischemic cardiomyopathy. The U-Nets were trained using 8430 slices, extracted in three orthogonal directions from 18 images. In the testing phase, the outputs of U-Nets of each subnet were combined using the majority voting system for final label prediction of each voxel in the image. The developed method was tested for accuracy by comparing its results to manual segmentations of LV myocardium and LV scar from 7250 slices extracted from 16 3D LGE-MR images. Our method was also compared to numerous alternative methods based on machine learning, energy minimization, and intensity-thresholds. Results: Our algorithm reported a mean dice similarity coefficient (DSC), absolute volume difference (AVD), and Hausdorff distance (HD) of 85.14% AE 3.36%, 43.72 AE 27.18 cm 3 , and 19.21 AE 4.74 mm for determining the boundaries of LV myocardium from LGE-MR images. Our method also yielded a mean DSC, AVD, and HD of 88.61% AE 2.54%, 9.33 AE 7.24 cm 3 , and 17.04 AE 9.93 mm for LV scar segmentation on the unobserved test dataset. Our method significantly outperformed the alternative techniques in segmentation accuracy (P < 0.05). Conclusions: The CMPU-Net method provided fully automated segmentation of LV scar from 3DLGE-MR images and outperformed the alternative techniques.

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3D late gadolinium enhanced cardiovascular MR with CENTRA-PLUS profile/view ordering: Feasibility of right ventricular myocardial damage assessment using a swine animal model

Cited by 7 publications

References 21 publications

Single breath-hold saturation recovery 3D cardiac T1 mapping via compressed SENSE at 3T

Single breath-hold saturation recovery 3D cardiac T1 mapping via compressed SENSE at 3T

Accelerated high-resolution free-breathing 3D whole-heart T2-prepared black-blood and bright-blood cardiovascular magnetic resonance

Fully automated segmentation of left ventricular scar from 3D late gadolinium enhancement magnetic resonance imaging using a cascaded multi‐planar U‐Net (CMPU‐Net)

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