Browsing by Author "Cruz, Gastao"
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- ItemA Spatial Off-Resonance Correction in Spirals for Magnetic Resonance Fingerprinting(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021) Coronado, Ronal; Cruz, Gastao; Castillo Passi, Carlos; Tejos, Cristian; Uribe, Sergio; Prieto, Claudia; Irarrazaval, PabloIn MR Fingerprinting (MRF), balanced Steady-State Free Precession (bSSFP) has advantages over unbalanced SSFP because it retains the spin history achieving a higher signal-to-noise ratio (SNR) and scan efficiency. However, bSSFP-MRF is not frequently used because it is sensitive to off-resonance, producing artifacts and blurring, and affecting the parametric map quality. Here we propose a novel Spatial Off-resonance Correction (SOC) approach for reducing these artifacts in bSSFP-MRF with spiral trajectories. SOC-MRF uses each pixel's Point Spread Function to create system matrices that encode both off-resonance and gridding effects. We iteratively compute the inverse of these matrices to reduce the artifacts. We evaluated the proposed method using brain simulations and actual MRF acquisitions of a standardized T1/T2 phantom and five healthy subjects. The results show that the off-resonance distortions in T1/T2 maps were considerably reduced using SOC-MRF. For T2, the Normalized Root Mean Square Error (NRMSE) was reduced from 17.3 to 8.3% (simulations) and from 35.1 to 14.9% (phantom). For T1, the NRMS was reduced from 14.7 to 7.7% (simulations) and from 17.7 to 6.7% (phantom). For in-vivo, the mean and standard deviation in different ROI in white and gray matter were significantly improved. For example, SOC-MRF estimated an average T2 for white matter of 77ms (the ground truth was 74ms) versus 50 ms of MRF. For the same example the standard deviation was reduced from 18 ms to 6ms. The corrections achieved with the proposed SOC-MRF may expand the potential applications of bSSFP-MRF, taking advantage of its better SNR property.
- ItemAccelerated magnetic resonance fingerprinting using soft-weighted key-hole (MRF-SOHO)(2018) Cruz, Gastao; Schneider, Torben; Bruijnen, Tom; Gaspar, Andreia S.; Botnar, Rene A. M.; Prieto Vásquez, Claudia
- ItemAccelerated motion corrected three-dimensional abdominal MRI. using total variation regularized SENSE. reconstruction(2016) Cruz, Gastao; Atkinson, David; Buerger, Christian; Schaeffter, Tobias; Prieto Vásquez, Claudia
- ItemCardiac Magnetic Resonance Fingerprinting : Technical Developments and Initial Clinical Validation(2019) Cruz, Gastao; Jaubert, O.; Botnar, René Michael; Prieto Vásquez, Claudia
- ItemClinical comparison of sub-mm high-resolution non-contrast coronary CMR angiography against coronary CT angiography in patients with low-intermediate risk of coronary artery disease: a single center trial(2021) Hajhosseiny, R.; Rashid, Imran; Bustin, Aurélien; Munoz, Camila; Cruz, Gastao; Nazir, Muhummad Sohaib; Grigoryan, Karine; Ismail, Tevfk F.; Prieto Vásquez, Claudia; Botnar, René MichaelAbstract Background The widespread clinical application of coronary cardiovascular magnetic resonance (CMR) angiography (CMRA) for the assessment of coronary artery disease (CAD) remains limited due to low scan efficiency leading to prolonged and unpredictable acquisition times; low spatial-resolution; and residual respiratory motion artefacts resulting in limited image quality. To overcome these limitations, we have integrated highly undersampled acquisitions with image-based navigators and non-rigid motion correction to enable high resolution (sub-1 mm3) free-breathing, contrast-free 3D whole-heart coronary CMRA with 100% respiratory scan efficiency in a clinically feasible and predictable acquisition time. Objectives To evaluate the diagnostic performance of this coronary CMRA framework against coronary computed tomography angiography (CTA) in patients with suspected CAD. Methods Consecutive patients (n = 50) with suspected CAD were examined on a 1.5T CMR scanner. We compared the diagnostic accuracy of coronary CMRA against coronary CTA for detecting a ≥ 50% reduction in luminal diameter. Results The 50 recruited patients (55 ± 9 years, 33 male) completed coronary CMRA in 10.7 ± 1.4 min. Twelve (24%) had significant CAD on coronary CTA. Coronary CMRA obtained diagnostic image quality in 95% of all, 97% of proximal, 97% of middle and 90% of distal coronary segments. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy were: per patient (100%, 74%, 55%, 100% and 80%), per vessel (81%, 88%, 46%, 97% and 88%) and per segment (76%, 95%, 44%, 99% and 94%) respectively. Conclusions The high diagnostic image quality and diagnostic performance of coronary CMRA compared against coronary CTA demonstrates the potential of coronary CMRA as a robust and safe non-invasive alternative for excluding significant disease in patients at low-intermediate risk of CAD.
- ItemCoronary Magnetic Resonance Angiography in Chronic Coronary Syndromes(FRONTIERS MEDIA SA, 2021) Hajhosseiny, Reza; Munoz, Camila; Cruz, Gastao; Khamis, Ramzi; Kim, Won Yong; Prieto, Claudia; Botnar, Rene M.Cardiovascular disease is the leading cause of mortality worldwide, with atherosclerotic coronary artery disease (CAD) accounting for the majority of cases. X-ray coronary angiography and computed tomography coronary angiography (CCTA) are the imaging modalities of choice for the assessment of CAD. However, the use of ionising radiation and iodinated contrast agents remain drawbacks. There is therefore a clinical need for an alternative modality for the early identification and longitudinal monitoring of CAD without these associated drawbacks. Coronary magnetic resonance angiography (CMRA) could be a potential alternative for the detection and monitoring of coronary arterial stenosis, without exposing patients to ionising radiation or iodinated contrast agents. Further advantages include its versatility, excellent soft tissue characterisation and suitability for repeat imaging. Despite the early promise of CMRA, widespread clinical utilisation remains limited due to long and unpredictable scan times, onerous scan planning, lower spatial resolution, as well as motion related image quality degradation. The past decade has brought about a resurgence in CMRA technology, with significant leaps in image acceleration, respiratory and cardiac motion estimation and advanced motion corrected or motion-resolved image reconstruction. With the advent of artificial intelligence, great advances are also seen in deep learning-based motion estimation, undersampled and super-resolution reconstruction promising further improvements of CMRA. This has enabled high spatial resolution (1 mm isotropic), 3D whole heart CMRA in a clinically feasible and reliable acquisition time of under 10 min. Furthermore, latest super-resolution image reconstruction approaches which are currently under evaluation promise acquisitions as short as 1 min. In this review, we will explore the recent technological advances that are designed to bring CMRA closer to clinical reality.
- ItemEnd-to-end deep learning nonrigid motion-corrected reconstruction for highly accelerated free-breathing coronary MRA(2021) Qi, Haikun; Hajhosseiny, Reza; Cruz, Gastao; Kuestner, Thomas; Kunze, Karl; Neji, Radhouene; Botnar, René Michael; Prieto Vásquez, ClaudiaPurpose: To develop an end-to-end deep learning technique for nonrigid motion-corrected (MoCo) reconstruction of ninefold undersampled free-breathing whole-heart coronary MRA (CMRA).
- ItemFive-minute whole-heart coronary MRA with sub-millimeter isotropic resolution, 100% respiratory scan efficiency, and 3D-PROST reconstruction(2019) Bustin, Aurelien; Ginami, Giulia; Cruz, Gastao; Correia, Teresa; Ismail, Tevfik F.; Rashid, Imran; Neji, Radhouene; Botnar, René Michael; Prieto Vásquez, Claudia
- ItemFree-running 3D whole heart myocardial T-1 mapping with isotropic spatial resolution(2019) Qi, Haikun; Jaubert, Olivier; Bustin, Aurélien; Cruz, Gastao; Chen, Huijun; Botnar, René Michael; Prieto Vásquez, Claudia
- ItemFree-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging(2020) Jaubert, Olivier Francois; Cruz, Gastao; Bustin, Aurelien; Schneider, Torben; Koken, Peter; Doneva, Mariya; Rueckert, Daniel; Botnar, René Michael; Prieto Vásquez, ClaudiaPurpose: To develop and evaluate a novel non-ECG triggered 2D magnetic resonance fingerprinting (MRF) sequence allowing for simultaneous myocardial T-1 and T-2 mapping and cardiac Cine imaging.
- ItemFree-running simultaneous myocardial T1/T2 mapping and cine imaging with 3D whole-heart coverage and isotropic spatial resolution(2019) Qi, Haikun; Bustin, Aurélien; Cruz, Gastao; Jaubert, Olivier; Chen, Huijun; Botnar, René Michael; Prieto Vásquez, Claudia
- ItemGeneralized low-rank nonrigid motion-corrected reconstruction for MR fingerprinting(WILEY, 2021) Cruz, Gastao; Qi, Haikun; Jaubert, Olivier; Kuestner, Thomas; Schneider, Torben; Michael Botnar, Rene; Prieto, ClaudiaPurpose: Develop a novel low-rank motion-corrected (LRMC) reconstruction for nonrigid motion-corrected MR fingerprinting (MRF).
- ItemHighly Efficient Nonrigid Motion-Corrected 3D Whole-Heart Coronary Vessel Wall Imaging(2017) Cruz, Gastao; Atkinson, David; Henningsson, Markus; Botnar, René Michael; Prieto Vásquez, Claudia
- ItemSelf-supervised learning-based diffeomorphic non-rigid motion estimation for fast motion-compensated coronary MR angiography(ELSEVIER SCIENCE INC, 2022) Munoz, Camila; Qi, Haikun; Cruz, Gastao; Kuestner, Thomas; Botnar, Rene M.; Prieto, ClaudiaPurpose: To accelerate non-rigid motion corrected coronary MR angiography (CMRA) reconstruction by developing a deep learning based non-rigid motion estimation network and combining this with an efficient implementation of the undersampled motion corrected reconstruction.
- ItemSelf-supervised motion-corrected image reconstruction network for 4D magnetic resonance imaging of the body trunk(Now Publishers Inc, 2022) Küstner, Thomas; Pan, Jiazhen; Gilliam, Christopher; Qi, Haikun; Cruz, Gastao; Hammernik, Kerstin; Blu, Thierry; Rueckert, Daniel; Botnar, René Michael; Prieto Vásquez, Claudia; Gatidis, SergiosRespiratory motion can cause artifacts in magnetic resonance imaging of the body trunk if patients cannot hold their breath or triggered acquisitions are not practical. Retrospective correction strategies usually cope with motion by fast imaging sequences under free-movement conditions followed by motion binning based on motion traces. These acquisitions yield sub-Nyquist sampled and motion-resolved k-space data. Motion states are linked to each other by non-rigid deformation fields. Usually, motion registration is formulated in image space which can however be impaired by aliasing artifacts or by estimation from low-resolution images. Subsequently, any motion-corrected reconstruction can be biased by errors in the deformation fields. In this work, we propose a deep-learning based motion-corrected 4D (3D spatial + time) image reconstruction which combines a non-rigid registration network and a 4D reconstruction network. Non-rigid motion is estimated in k-space and incorporated into the reconstruction network. The proposed method is evaluated on in-vivo 4D motion-resolved magnetic resonance images of patients with suspected liver or lung metastases and healthy subjects. The proposed approach provides 4D motion-corrected images and deformation fields. It enables a ∼ 14× accelerated acquisition with a 25- fold faster reconstruction than comparable approaches under consistent preservation of image quality for changing patients and motion patterns.
- ItemSimultaneous T-1, T-2, and T-1 rho cardiac magnetic resonance fingerprinting for contrast agent-free myocardial tissue characterization(WILEY, 2021) Velasco, Carlos; Cruz, Gastao; Lavin, Begona; Hua, Alina; Fotaki, Anastasia; Botnar, Rene M.; Prieto, ClaudiaPurpose: To develop a simultaneous T-1, T-2, and T-1 rho cardiac magnetic resonance fingerprinting (MRF) approach to enable comprehensive contrast agent-free myocardial tissue characterization in a single breath-hold scan.
- ItemSynergistic multi-contrast cardiac magnetic resonance image reconstruction(ROYAL SOC, 2021) Qi, Haikun; Cruz, Gastao; Botnar, Rene; Prieto, ClaudiaCardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matching. Furthermore, extra efforts to deal with respiratory and cardiac motion by triggering and gating further increase the scan time. Several techniques have been developed to speed up CMR acquisitions, which usually acquire less data than that required by the Nyquist-Shannon sampling theorem, followed by regularized reconstruction to mitigate undersampling artefacts. Recent advances in CMR parametric mapping speed up CMR by synergistically exploiting spatial-temporal and contrast redundancies. In this article, we will review the recent developments in multi-contrast CMR image reconstruction for parametric mapping with special focus on low-rank and model-based reconstructions. Deep learning-based multi-contrast reconstruction has recently been proposed in other magnetic resonance applications. These developments will be covered to introduce the general methodology. Current technical limitations and potential future directions are discussed.
- ItemWhole-heart non-rigid motion corrected coronary MRA with autofocus virtual 3D iNAV(ELSEVIER SCIENCE INC, 2022) Schneider, Alina; Cruz, Gastao; Munoz, Camila; Hajhosseiny, Reza; Kuestner, Thomas; Kunze, Karl P.; Neji, Radhouene; Botnar, Rene M.; Prieto, ClaudiaPurpose: Respiratory motion-corrected coronary MR angiography (CMRA) has shown promise for assessing coronary disease. By incorporating coronal 2D image navigators (iNAVs), respiratory motion can be corrected for in a beat-to-beat basis using translational correction in the foot-head (FH) and right-left (RL) directions and in a bin-to-bin basis using non-rigid motion correction addressing the remaining FH, RL and anterior-posterior (AP) motion. However, with this approach beat-to-beat AP motion is not corrected for. In this work we investigate the effect of remaining beat-to-beat AP motion and propose a virtual 3D iNAV that exploits autofocus motion correction to enable beat-to-beat AP and improved RL intra-bin motion correction. Methods: Free-breathing 3D whole-heart CMRA was acquired using a 3-fold undersampled variable-density Cartesian trajectory. Beat-to-beat 3D translational respiratory motion was estimated from the 2D iNAVs in FH and RL directions, and in AP direction with autofocus assuming a linear relationship between FH and AP movement of the heart. Furthermore, motion in RL was also refined using autofocus. This virtual 3D (v3D) iNAV was incorporated in a non-rigid motion correction (NRMC) framework. The proposed approach was tested in 12 cardiac patients, and visible vessel length and vessel sharpness for the right (RCA) and left (LAD) coronary arteries were compared against 2D iNAV-based NRMC. Results: Average vessel sharpness and length in v3D iNAV NRMC was improved compared to 2D iNAV NRMC (vessel sharpness: RCA: 56 +/- 1% vs 52 +/- 11%, LAD: 49 +/- 8% vs 49 +/- 7%; visible vessel length: RCA: 5.98 +/- 1.37 cm vs 5.81 +/- 1.62 cm, LAD: 5.95 +/- 1.85 cm vs 4.83 +/- 1.56 cm), however these improvements were not statistically significant. Conclusion: The proposed virtual 3D iNAV NRMC reconstruction further improved NRMC CMRA image quality by reducing artefacts arising from residual AP motion, however the level of improvement was subject-dependent.