Dynamic contrast enhanced (DCE) MRI estimation of vascular parameters using knowledge-based adaptive models

We introduce and validate four adaptive models (AMs) to perform a physiologically based Nested-Model-Selection (NMS) estimation of such microvascular parameters as forward volumetric transfer constant, K(trans), plasma volume fraction, v(p), and extravascular, extracellular space, v(e), directly from Dynamic Contrast-Enhanced (DCE) MRI raw information without the need for an Arterial-Input Function (AIF). In sixty-six immune-compromised-RNU rats implanted with human U-251 cancer cells, DCE-MRI studies estimated pharmacokinetic (PK) parameters using a group-averaged radiological AIF and an extended Patlak-based NMS paradigm. One-hundred-ninety features extracted from raw DCE-MRI information were used to construct and validate (nested-cross-validation, NCV) four AMs for estimation of model-based regions and their three PK parameters. An NMS-based a priori knowledge was used to fine-tune the AMs to improve their performance. Compared to the conventional analysis, AMs produced stable maps of vascular parameters and nested-model regions less impacted by AIF-dispersion. The performance (Correlation coefficient and Adjusted R-squared for NCV test cohorts) of the AMs were: 0.914/0.834, 0.825/0.720, 0.938/0.880, and 0.890/0.792 for predictions of nested model regions, v(p), K(trans), and v(e), respectively. This study demonstrates an application of AMs that quickens and improves DCE-MRI based quantification of microvasculature properties of tumors and normal tissues relative to conventional approaches

3D single breath-hold MR methodology for measuring cardiac parametric mapping at 3T

Mención Internacional en el título de doctorOne of the foremost and challenging subfields of MRI is cardiac magnetic resonance imaging (CMR). CMR is becoming an indispensable tool in cardiovascular medicine by acquiring data about anatomy and function simultaneously. For instance, it allows the non-invasive characterization of myocardial tissues via parametric mapping techniques. These mapping techniques provide a spatial visualization of quantitative changes in the myocardial parameters. Inspired by the need to develop novel high-quality parametric sequences for 3T, this thesis's primary goal is to introduce an accurate and efficient 3D single breath-hold MR methodology for measuring cardiac parametric mapping at 3T. This thesis is divided into two main parts: i) research and development of a new 3D T1 saturation recovery mapping technique (3D SACORA), together with a feasibility study regarding the possibility of adding a T2 mapping feature to 3D SACORA concepts, and ii) research and implementation of a deep learning-based post-processing method to improve the T1 maps obtained with 3D SACORA. In the first part of the thesis, 3D SACORA was developed as a new 3D T1 mapping sequence to speed up T1 mapping acquisition of the whole heart. The proposed sequence was validated in phantoms against the gold standard technique IR-SE and in-vivo against the reference sequence 3D SASHA. The 3D SACORA pulse sequence design was focused on acquiring the entire left ventricle in a single breath-hold while achieving good quality T1 mapping and stability over a wide range of heart rates (HRs). The precision and accuracy of 3D SACORA were assessed in phantom experiments. Reference T1 values were obtained using IR-SE. In order to further validate 3D SACORA T1 estimation accuracy and precision, T1 values were also estimated using an in-house version of 3D SASHA. For in-vivo validation, seven large healthy pigs were scanned with 3D SACORA and 3D SASHA. In all pigs, images were acquired before and after administration of MR contrast agent. The phantom results showed good agreement and no significant bias between methods. In the in-vivo experiments, all T1-weighted images showed good contrast and quality, and the T1 maps correctly represented the information contained in the T1-weighted images. Septal T1s and coefficients of variation did not considerably differ between the two sequences, confirming good accuracy and precision. 3D SACORA images showed good contrast, homogeneity and were comparable to corresponding 3D SASHA images, despite the shorter acquisition time (15s vs. 188s, for a heart rate of 60 bpm). In conclusion, the proposed 3D SACORA successfully acquired a whole-heart 3D T1 map in a single breath-hold at 3T, estimating T1 values in agreement with those obtained with the IR-SE and 3D SASHA sequences. Following the successful validation of 3D SACORA, a feasibility study was performed to assess the potential of modifying the acquisition scheme of 3D SACORA in order to obtain T1 and T2 maps simultaneously in a single breath-hold. This 3D T1/T2 sequence was named 3D dual saturation-recovery compressed SENSE rapid acquisition (3D dual-SACORA). A phantom of eight tubes was built to validate the proposed sequence. The phantom was scanned with 3D dual-SACORA with a simulated heart rate of 60 bpm. Reference T1 and T2 values were estimated using IR-SE and GraSE sequences, respectively. An in-vivo study was performed with a healthy volunteer to evaluate the parametric maps' image quality obtained with the 3D dual-SACORA sequence. T1 and T2 maps of the phantom were successfully obtained with the 3D dual-SACORA sequence. The results show that the proposed sequence achieved good precision and accuracy for most values. A volunteer was successfully scanned with the proposed sequence (acquisition duration of approximately 20s) in a single breath-hold. The saturation time images and the parametric maps obtained with the 3D dual-SACORA sequence showed good contrast and homogeneity. The septal T1 and T2 values are in good agreement with reference sequences and published work. In conclusion, this feasibility study's findings open the door to the possibility of using 3D SACORA concepts to develop a successful 3D T1/T2 sequence. In the second part of the thesis, a deep learning-based super-resolution model was implemented to improve the image quality of the T1 maps of 3D SACORA, and a comprehensive study of the performance of the model in different MR image datasets and sequences was performed. After careful consideration, the selected convolutional neural network to improve the image quality of the T1 maps was the Residual Dense Network (RDN). This network has shown outstanding performance against state-of-the-art methods on benchmark datasets; however, it has not been validated on MR datasets. In this way, the RDN model was initially validated on cardiac and brain benchmark datasets. After this validation, the model was validated on a self-acquired cardiac dataset and on improving T1 maps. The RDN model improved the images successfully for the two benchmark datasets, achieving better performance with the brain dataset than with the cardiac dataset. This result was expected as the brain images have more well-defined edges than the cardiac images, making the resolution enhancement more evident. On the self-acquired cardiac dataset, the model also obtained an enhanced performance on image quality assessment metrics and improved visual assessment, particularly on well-defined edges. Regarding the T1 mapping sequences, the model improved the image quality of the saturation time images and the T1 maps. The model was able to enhance the T1 maps analytically and visually. Analytically, the model did not considerably modify the T1 values while improving the standard deviation in both myocardium and blood. Visually, the model improved the T1 maps by removing noise and motion artifacts without losing resolution on the edges. In conclusion, the RDN model was validated on three different MR datasets and used to improve the image quality of the T1 maps obtained with 3D SACORA and 3D SASHA. In summary, a 3D single breath-hold MR methodology was introduced, including a ready to-go 3D single breath-hold T1 mapping sequence for 3T (3D SACORA), together with the ideas for a new 3D T1/T2 mapping sequence (3D dual-SACORA); and a deep learning-based post-processing implementation capable of improving the image quality of 3D SACORA T1 maps.This thesis has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement N722427.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Carlos Alberola López.- Secretario: María Jesús Ledesma Carbayo.- Vocal: Nathan Mewto

T2 and T2⁎ mapping and weighted imaging in cardiac MRI

Cardiac imaging is progressing from simple imaging of heart structure and function to techniques visualizing and measuring underlying tissue biological changes that can potentially define disease and therapeutic options. These techniques exploit underlying tissue magnetic relaxation times: T1, T2 and T2*. Initial weighting methods showed myocardial heterogeneity, detecting regional disease. Current methods are now fully quantitative generating intuitive color maps that do not only expose regionality, but also diffuse changes – meaning that between-scan comparisons can be made to define disease (compared to normal) and to monitor interval change (compared to old scans). T1 is now familiar and used clinically in multiple scenarios, yet some technical challenges remain. T2 is elevated with increased tissue water – edema. Should there also be blood troponin elevation, this edema likely reflects inflammation, a key biological process. T2* falls in the presence of magnetic/paramagnetic materials – practically, this means it measures tissue iron, either after myocardial hemorrhage or in myocardial iron overload. This review discusses how T2 and T2⁎ imaging work (underlying physics, innovations, dependencies, performance), current and emerging use cases, quality assurance processes for global delivery and future research directions

Model-driven registration for multi-parametric renal MRI

The use of MR imaging biomarkers is a promising technique that may assist towards faster prognosis and more accurate diagnosis of diseases like diabetic kidney disease (DKD). The quantification of MR Imaging renal biomarkers from multiparametric MRI is a process that requires a physiological model to be fitted on the data. This process can provide accurate estimates only under the assumption that there is pixelto-pixel correspondence between images acquired over different time points. However, this is rarely the case due to motion artifacts (breathing, involuntary muscle relaxation) introduced during the acquisition. Hence, it is of vital importance for a biomarkers quantification pipeline to include a motion correctionstep in order to properly align the images and enable a more accurate parameter estimation. This study aims in testing whether a Model Driven Registration (MDR), which integrates physiological models in the registration process itself, can serve as a universal solution for the registration of multiparametric renal MRI. MDR is compared with a state-of-the-art model-free motion correction approach for multiparametric MRI, that minimizes a Principal Components Analysis based metric, performing a groupwise registration. The results of the two methods are compared on T1, DTI and DCE-MRI data for a small cohort of 10 DKD patients, obtained from BEAt-DKD project’s digital database. The majority of the evaluation metrics used to compare the two methods indicated that MDR achieved better registration results, while requiring significantly lower computational times. In conclusion, MDR could be considered as the method of choice for motion correction of multiparametric quantitative renal MRI

Simultaneous Multiparametric and Multidimensional Cardiovascular Magnetic Resonance Imaging

No abstract available

Steady-state anatomical and quantitative magnetic resonance imaging of the heart using RF-frequencymodulated techniques

Cardiovascular disease (CVD) is the leading cause of death in the United States and Europe and generates healthcare costs of hundreds of billions of dollars annually. Conventional methods of diagnosing CVD are often invasive and carry risks for the patient. For example, the gold standard for diagnosing coronary artery disease, a major class of CVD, is x-ray coronary angiography, which has the disadvantages of being invasive, being expensive, using ionizing radiation, and having a ris k of complications. Conversely, coronary MR angiography (MRA) does not use ionizing radiation, can effectively visualize tissues without the need for exogenous contrast agents, and benefits from an adaptable temporal resolution. However, the acquisition time of cardiac MRI is far longer than the temporal scales of cardiac and respiratory motion, necessitating some method of compensating for this motion. The free-running framework is a novel development in our lab, benefitting from advances over the past three decades, that attempts to address disadvantages of previous cardiac MRI approaches: it provides fully self-gated 5D cardiac MRI with a simplified workflow, improved ease-of-use, reduced operator dependence, and automatic patient-specific motion detection. Free-running imaging increases the amount of information available to the clinician and is flexible enough to be translated to different app lications within cardiac MRI. Moreover, the self-gating of the free-running framework decoupled the acquisition from the motion compensation and thereby opened up cardiac MRI to the wider class of steady-state-based techniques utilizing balanced steady-state free precession (bSSFP) sequences, which have the benefits of practical simplicity and high signal-to-noise ratio. The focus of this thesis was therefore on the application of steady- state techniques to cardiac MRI. The first part addressed the long acquisition time of the current free-running framework and focused on anatomical coronary imaging. The published protocol of the free- running framework used an interrupted bSSFP acquisition where CHESS fat saturation modules were inserted to provide blood-fat contrast, as they suppress the signal of fat tissue surrounding the coronary arteries, and were followed by ramp-up pulses to reduce artefacts arising from the return to steady-state. This interrupted acquisition, however, suffered from an interrupted steady-state, reduced time efficiency, and higher specific absorption rate (SAR). Using novel lipid-insensitive binomial off-resonant RF excitation (LIBRE) pulses developed in our lab, the first project showed that LIBRE pulses incorporated into an uninterrupted free-running bSSFP sequence could be successfully used for 5D cardiac MRI at 1.5T. The free-running LIBRE approach reduced the acquisition time and SAR relative to the previous interrupted approach while maintaining image quality and vessel conspicuity. Furthermore, this had been the first successful use of a fat-suppressing RF excitation pulse in an uninterrupted bSSFP sequence for cardiac imaging, demonstrating that uninterrupted bSSFP can be used for cardiac MRI and addressing the problem of clinical sequence availability. Inspired by the feasibility of uninterrupted bSSFP for cardiac MRI, the second part investigated the potential of PLANET, a novel 3D multiparametric mapping technique, for free-running 5D myocardial mapping. PLANET utilizes a phase-cycled bSSFP acquisition and a direct ellipse-fitting algorithm to calculate T1 and T2 relaxation times, which suggested that it could be readily integrated into the free-running framework without interrupting the steady-state. After initially calibrating the acquisition, the possibility of accelerating the static PLANET acquisition was explored prior to applying it to the moving heart. It was shown that PLANET accuracy and precision could be maintained with two-fold acceleration with a 3D Cartesian spiral trajectory, suggesting that PLANET for myocardial mapping with the free-running 5D radial acquisition is feasible. Further work should investigate optimizing the reconstruction scheme, improving the coil sensitivity estimate, and examining the use of the radial trajectory with a view to implementing free-running 5D myocardial T1 and T2 mapping. This thesis presents two approaches utilizing RF-frequency-modulated steady-state techniques for cardiac MRI. The first approach involved the novel application of an uninterrupted bSSFP acquisition with off-resonant RF excitation for anatomical coronary imaging. The second approach investigated the use of phase-cycled bSSFP for free-running 5D myocardial T1 and T2 mapping. Both methods addressed the challenge of clinical availability of sequences in cardiac MRI, by showing that a common and simple sequence like bSSFP can be used for acquisition while the steps of motion compensation and reconstruction can be handled offline, and thus have the potential to improve adoption of cardiac MRI. -- Les maladies cardiovasculaires (MCV) représentent la principale cause de décès aux États-Unis et en Europe et génèrent des coûts de santé de plusieurs centaines de milliards de dollars par an. Les méthodes conventionnelles de diagnostic des MCV sont souvent invasives et comportent des risques pour le patient. Par exemple, la méthode de référence pour le diagnostic de la maladie coronarienne, une catégorie majeure de MCV, est la coronarographie par rayons X qui a comme inconvénients son caractère invasif, son coût, l’utilisation de rayonnements ionisants et le risque de complications. A l’inverse, l'angiographie coronarienne par résonance magnétique (ARM) n'utilise pas de rayonnements ionisants, permet de visualiser efficacement les tissus sans avoir recours à des agents de contraste exogènes et bénéficie d'une résolution temporelle ajustable. Cependant, le temps d'acquisition en IRM cardiaque est bien plus long que les échelles temporelles des mouvements cardiaques et respiratoires en jeu, ce qui rend la compensation de ces mouvements indispensable. Le cadre dit de « free -running » est un nouveau développement de notre laboratoire qui bénéficie des progrès réalisés au cours des trois dernières décennies et tente de remédier aux inconvénients des approches précédentes pour l'IRM cardiaque : il fournit une IRM cardiaque en cinq dimensions (5D) complètement « self-gated » , c’est-à-dire capable de détecter les mouvements cardiaques et respiratoires, forte d’une implémentation simplifiée, d’une plus grande facilité d'utilisation, d’une dépendance réduite vis-à-vis de l'opérateur et d’une détection automatique des mouvements spécifiques du patient. L'imagerie « free- running » augmente la quantité d'informations à disposition du clinicien et est suffisamment flexible pour être appliquée à différents domaines de l'IRM cardiaque. De plus, le « self-gating » du cadre « free-running » a découplé l'acquisition de la compensation de mouvement et a ainsi ouvert l'IRM cardiaque à la classe plus large des techniques basées sur l'état stationnaire utilisant des séquences de précession libre équilibrée en état stationnaire (bSSFP), qui se distinguent par leur simplicité d’utilisation et leur rapport signal sur bruit élevé. Le thème de cette thèse est donc l'application des techniques basées sur l'état stationnaire à l'IRM cardiaque. La première partie porte sur le long temps d'acquisition de l'actuel cadre « free-running» et se concentre sur l'imagerie anatomique coronaire. Le protocole publié utilise une acquisition bSSFP interrompue où des modules de saturation de graisse (CHESS) sont insérés de façon à fournir un contraste sang-graisse puisqu’ils suppriment le signal du tissu graisseux entourant les artères coronaires, et sont suivis par des impulsions en rampe pour réduire les artefacts résultant du retour à l'état stable. Cette acquisition interrompue souffre cependant d'un état d'équilibre interrompu, d'une efficacité temporelle réduite et d'un débit d'absorption spécifique (DAS) plus élevé. En utilisant les nouvelles impulsions d'excitation radiofréquence (RF) binomiales hors -résonance insensibles aux lipides (LIBRE) développées dans notre laboratoi re, ce premier projet montre que les impulsions LIBRE incorporées dans une séquence bSSFP ininterrompue et « free-running » peuvent être utilisées avec succès pour l'IRM cardiaque 5D à 1,5 T. L'approche « free-running LIBRE » permet de réduire le temps d'acquisition et le DAS par rapport à l'approche interrompue précédente, tout en maintenant la perceptibilité des artères coronariennes. En outre, il s'agit de la première utilisation réussie d'une impulsion d'excitation RF supprimant la graisse dans une séquence bSSFP ininterrompue pour l'imagerie cardiaque, ce qui démontre le potentiel d’utilisation de la séquence bSSFP ininterrompue pour l'IRM cardiaque et résout le problème de la disponibilité de la séquence en clinique. Inspirée par la faisabilité d’utilisation de la séquence bSSFP ininterrompue pour l'IRM cardiaque, la deuxième partie étudie le potentiel de PLANET, une nouvelle technique de cartographie 3D multiparamétrique, pour la cartographie 5D du myocarde via l’imagerie « free-running ». PLANET utilise une acquisition bSSFP à cycle de phase et un algorithme d'ajustement d'ellipse direct pour calculer les temps de relaxation T1 et T2, ce qui suggère que cette méthode pourrait être facilement intégrée au cadre « free - running » sans interruption de l’état d'équilibre. Après calibration de l'acquisition, nous explorons la possibilité d'accélérer l'acquisition statique de PLANET pour l'appliquer au cœur. Nous démontrons que l'exactitude et la précision de PLANET peuvent être maintenues pour une accélération double avec une trajectoire 3D cartésienne en spirale, ce qui suggère que PLANET est réalisable pour la cartographie du myocarde avec une acquisition radiale 5D « free-running ». D'autres travaux devraient porter sur l'optimisation du schéma de reconstruction, l'amélioration de l'estimation de la sensibilité de l’antenne et l'examen de l'utilisation de la trajectoire radiale en vue de la mise en œuvre de la cartographie 5D « free-running » T1 et T2 du myocarde. Cette thèse présente deux approches utilisant des techniques de modulation de fréquence radio en état stationnaire pour l'IRM cardiaque. La première approche implique l'application nouvelle d'une acquisition bSSFP ininterrompue avec une excitation RF hors résonance pour l'imagerie anatomique coronaire. La seconde approche porte sur l'utilisation d’une séquence bSSFP à cycle de phase pour la cartographie 5D T1 et T2 du myocarde. Ces deux méthodes permettent de répondre au défi posé par la disponibilité des séquences en IRM cardiaque en montrant qu'une séquence commune et simple comme la bSSFP peut être utilisée pour l'acquisition, tandis que les étapes de compensation du mouvement et de reconstruction peuvent être traitées hors ligne. Ainsi, ces méthodes ont le potentiel de favoriser l'adoption de l'IRM cardiaque

Quantitative methods to assess cerebral haemodynamics

In this thesis methods for the assessment of cerebral haemodynamics using 7 T Magnetic Resonance Imaging (MRI) are described. The measurement of haemodynamic parameters, such as cerebral blood flow (CBF), is an important clinical tool. Arterial Spin Labelling (ASL) is a non-invasive technique for CBF measurement using MRI. ASL methodology for ultra high field (7 T) MRI was developed, including investigation of the optimal readout strategy. Look-Locker 3D-EPI is demonstrated to give large volume coverage improving on previous studies. Applications of methods developed to monitor functional activity, through flow or arterial blood volume, in healthy volunteers and in patients with low grade gliomas using Look-Locker ASL are described. The effect of an increased level of carbon dioxide in the blood (hypercapnia) was studied using ASL and functional MRI; hypercapnia is a potent vasodilator and has a large impact on haemodynamics. These measures were used to estimate the increase in oxygen metabolism associated with a simple motor task. To study the physiology behind the hypercapnic response, magnetoencephalography was used to measure the impact of hypercapnia on neuronal activity. It was shown that hypercapnia induces widespread desynchronisation in a wide frequency range, up to ~ 50 Hz, with peaks in the sensory-motor areas. This suggests that hypercapnia is not iso-metabolic, which is an assumption of calibrated BOLD. A Look-Locker gradient echo sequence is described for the quantitative monitoring of a gadolinium contrast agent uptake through the change in longitudinal relaxation rate. This sequence was used to measure cerebral blood volume in Multiple Sclerosis patients. Further development of the sequence yielded a high resolution anatomical scan with reduced artefacts due to field inhomogeneities associated with ultra high field imaging. This allows whole head images acquired at sub-millimetre resolution in a short scan time, for application in patient studies

Cram\'er-Rao Bound Optimized Subspace Reconstruction in Quantitative MRI

We extend the traditional framework for estimating subspace bases that maximize the preserved signal energy to additionally preserve the Cram\'er-Rao bound (CRB) of the biophysical parameters and, ultimately, improve accuracy and precision in the quantitative maps. To this end, we introduce an \textit{approximate compressed CRB} based on orthogonalized versions of the signal's derivatives with respect to the model parameters. This approximation permits singular value decomposition (SVD)-based minimization of both the CRB and signal losses during compression. Compared to the traditional SVD approach, the proposed method better preserves the CRB across all biophysical parameters with negligible cost to the preserved signal energy, leading to reduced bias and variance of the parameter estimates in simulation. In vivo, improved accuracy and precision are observed in two quantitative neuroimaging applications, permitting the use of smaller basis sizes in subspace reconstruction and offering significant computational savings

An Information Theory Model for Optimizing Quantitative Magnetic Resonance Imaging Acquisitions

Quantitative magnetic resonance imaging (qMRI) is a powerful group of imaging techniques with a growing number of clinical applications, including synthetic image generation in post-processing, automatic segmentation, and diagnosis of disease from quantitative parameter values. Currently, acquisition parameter selection is performed empirically for quantitative MRI. Tuning parameters for different scan times, tissues, and resolutions requires some measure of trial and error. There is an opportunity to quantitatively optimize these acquisition parameters in order to maximize image quality and the reliability of the previously mentioned methods which follow image acquisition. The objective of this work is to introduce and evaluate a quantitative method for selecting parameters that minimize image variability. An information theory framework was developed for this purpose and applied to a 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) signal model for synthetic MRI. In this framework, mutual information is used to measure the information gained by a measurement as a function of acquisition parameters, quantifying the information content of the acquisition parameters and allowing informed parameter selection. The information theory framework was tested on synthetic data generated from a representative mathematical phantom, measurements acquired on a qMRI multiparametric imaging standard phantom, and in vivo measurements in a human brain. The application of this information theory framework resulted in successful parameter optimization with respect to mutual information. Both the phantom and in vivo measurements showed that higher mutual information calculated by the model correlated with smaller standard deviation in the reconstructed parametric maps. With this framework, optimal acquisition parameters can be selected to improve image quality, image repeatability, or scan time. This method could reduce the time and labor necessary to achieve images of the desired quality. Making an informed acquisition parameter selection reduces uncertainty in the imaging output and optimizes information gain within the bounds of clinical constraints