Browsing by Author "Prieto C."

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    Coronary Magnetic Resonance Angiography: Technical Innovations Leading Us to the Promised Land?
    (Elsevier Inc., 2020) Hajhosseiny R.; Bustin A.; Munoz C.; Rashid I.; Cruz G.; Prieto C.; Botnar R.M.; Hajhosseiny R.; Manning W.J.; Prieto C.; Botnar R.M.
    © 2020 American College of Cardiology FoundationCoronary artery disease remains the leading cause of cardiovascular morbidity and mortality. Invasive X-ray angiography and coronary computed tomography angiography are established gold standards for coronary luminography. However, they expose patients to invasive complications, ionizing radiation, and iodinated contrast agents. Among a number of imaging modalities, coronary cardiovascular magnetic resonance (CMR) angiography may be used in some cases as an alternative for the detection and monitoring of coronary arterial stenosis, with advantages including its versatility, excellent soft tissue characterization, and avoidance of ionizing radiation and iodinated contrast agents. In this review, we explore the recent advances in motion correction, image acceleration, and reconstruction technologies that are bringing coronary CMR angiography closer to widespread clinical implementation.
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    Deep-learning based super-resolution for 3D isotropic coronary MR angiography in less than a minute
    (John Wiley and Sons Inc, 2021) Küstner T.; Munoz C.; Psenicny A.; Bustin A.; Fuin N.; Qi H.; Neji R.; Kunze K.; Hajhosseiny R.; Prieto C.; Botnar R.; Küstner T.; Bustin A.; Neji R.; Kunze K.; Prieto C.; Botnar R.
    © 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in MedicinePurpose: To develop and evaluate a novel and generalizable super-resolution (SR) deep-learning framework for motion-compensated isotropic 3D coronary MR angiography (CMRA), which allows free-breathing acquisitions in less than a minute. Methods: Undersampled motion-corrected reconstructions have enabled free-breathing isotropic 3D CMRA in ~5-10 min acquisition times. In this work, we propose a deep-learning–based SR framework, combined with non-rigid respiratory motion compensation, to shorten the acquisition time to less than 1 min. A generative adversarial network (GAN) is proposed consisting of two cascaded Enhanced Deep Residual Network generator, a trainable discriminator, and a perceptual loss network. A 16-fold increase in spatial resolution is achieved by reconstructing a high-resolution (HR) isotropic CMRA (0.9 mm3 or 1.2 mm3) from a low-resolution (LR) anisotropic CMRA (0.9 × 3.6 × 3.6 mm3 or 1.2 × 4.8 × 4.8 mm3). The impact and generalization of the proposed SRGAN approach to different input resolutions and operation on image and patch-level is investigated. SRGAN was evaluated on a retrospective downsampled cohort of 50 patients and on 16 prospective patients that were scanned with LR-CMRA in ~50 s under free-breathing. Vessel sharpness and length of the coronary arteries from the SR-CMRA is compared against the HR-CMRA. Results: SR-CMRA showed statistically significant (P <.001) improved vessel sharpness 34.1% ± 12.3% and length 41.5% ± 8.1% compared with LR-CMRA. Good generalization to input resolution and image/patch-level processing was found. SR-CMRA enabled recovery of coronary stenosis similar to HR-CMRA with comparable qualitative performance. Conclusion: The proposed SR-CMRA provides a 16-fold increase in spatial resolution with comparable image quality to HR-CMRA while reducing the predictable scan time to <1 min.
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    Image navigator–based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis
    (Elsevier B.V., 2024) Wood G.; Hajhosseiny R.; Pedersen A.U.; Littlewood S.; Hansen T.J.; Neji R.; Kunze K.P.; Wetzl J.; Norgaard B.L.; Jensen J.M.; Maeng M.; Madsen P.L.; Vejlstrup N.; Prieto C.; Botnar, Rene Michael; Kim W.Y.
    Coronary computed tomography angiography (CCTA) is recommended as the first-line diagnostic imaging modality in low-to-intermediate-risk individuals suspected of stable coronary artery disease (CAD). However, CCTA exposes patients to ionizing radiation and potentially nephrotoxic contrast agents. Invasive coronary angiography is the gold-standard investigation to guide coronary revascularisation strategy; however, invasive procedures incur an inherent risk to the patient. Coronary magnetic resonance angiography (CMRA) avoids these issues. Nevertheless, clinical implementation is currently limited due to extended scanning durations, inconsistent image quality, and consequent lack of diagnostic accuracy. Several technical CMRA innovations, including advanced respiratory motion correction with 100% scan efficiency (no data rejection), fast image acquisition with motion-corrected undersampled image reconstruction, and deep-learning–based automated planning, have been implemented and now await clinical validation in multi-center trials. Methods: The objective of the image navigator–based, automated CMRA prospective multi-center study is to evaluate the diagnostic accuracy of a newly developed, state-of-the-art, standardized, and automated CMRA framework compared to CCTA in 201 patients undergoing clinical investigation for CAD. The study protocol mandates the administration of oral beta-blockers to decrease heart rate to below 60 bpm and the use of sublingual nitroglycerine spray to induce vasodilation. Additionally, the study incorporates the utilization of standardized postprocessing with sliding-thin-slab multiplanar reformatting, in combination with evaluation of the source images, to optimize the visualization of coronary artery stenosis. Discussion: If proven effective, CMRA could provide a non-invasive, needle-free, yet also clinically viable, alternative to CCTA. Trial Registration: This study is registered at ClinicalTrials.gov (NCT05473117).