Improvements to Quantification Algorithms for Myocardial Infarction in CMR Images - Validation in Human and Animal Studies

Cardiac magnetic resonance (CMR) images are used to investigate the heart for medical and research purposes. By injecting a contrast substance into the patient, myocardial infarctions (heart attacks) can be visualized in CMR image sets consisting of a number of image slices at different levels of the heart. Analysis of these images can detect an infarction, delineate it and estimate its size. This information is then processed by physicians in order to make a diagnosis and decide the course of treatment. Manual delineations are time consuming and observer dependent, why an automated algorithm is desired. Previous work presents a validated automatic segmentation algorithm that calculates a threshold used to separate the healthy tissue pixels from the infarction pixels, based on a fixed number of standard deviations. Theoretically, it is known that algorithms based on standard deviations are likely to be influenced by noise. Therefore, the aim of this thesis was to investigate if other techniques could be used to compute a threshold that is less noise sensitive in both humans and animals. The study included 40 humans and 18 pigs. Two different techniques based on an Expectation-Maximization algorithm for threshold calculation was developed and implemented into the previous presented method. One implementation analyses each image slice separately (the slice method), and one takes all slices into account at once (the set method). The algorithms were evaluated by comparing computed infarction volume to volumes computed from manual delineations. Both algorithms show good agreement and low bias with the reference standard. The slice method yielded the best results on animal data with a high resolution. The set method yielded the best results in human CMR images, and it show an improved robustness for increasing noise levels. Both implementations show potential for fully automatic quantification of myocardial infarction

Connecting CMR and Physiology : Expanding the capabilities of cardiovascular magnetic resonance in quantifying physiology

The assessment of cardiovascular physiology is crucial to facilitate clinical diagnostics, treatment, and research. Physiology and anatomy can be assessed noninvasively using cardiovascular magnetic resonance (CMR), a versatile and reliable medical imaging modality free from ionizing radiation. CMR is capable of providing a vast amount of information such as displacement, velocity, flow, length, area, volume, and tissue properties. Considered the gold standard for noninvasive quantification of cardiac function and morphology, CMR is increasingly envisioned as a future one-stop-shop imaging examination for cardiovascular disease. However, quantification of important physiological aspects such as valvular motion, pressure, and force are still not accessible or readily available when using CMR. The general aim of this thesis was therefore to expand the current capabilities of CMR to include new reliable methods and tools for quantification of the atrioventricular plane displacement, transmitral flow, pressure, and ventricular force-length loops, hence allowing a more complete assessment of subject-specific cardiovascular physiology that could potentially be achieved in a single noninvasive examination.In this thesis, the current capabilities of CMR were expanded by developing and validating four new methods for quantification of physiology. In Study I, an imaging processing algorithm for feature-tracking of the atrioventricular plane displacement was proposed. The combination of this algorithm and a phase contrast CMR sequence was proposed in Study II to improve measurements of transvalvular flow, which are challenging due to the significant movement of the atrioventricular valves over the cardiac cycle. In Study III, CMR imaging, a noninvasive brachial pressure, and mathematical modelling was combined to enable a noninvasive quantification of left ventricular pressure-volume loops. Study IV used the atrioventricular plane displacement algorithm and the noninvasive pressure-volume loop technique to propose a novel method for evaluation of ventricular force-length loops, which was used to describe the energetics of longitudinal and radial pumping mechanics.The proposed methods in Study I, II, and IV require only brachial pressure and images which are typically acquired during standard clinical CMR scanning. Addition of the sequence in Study II would prolong a CMR protocol by a few minutes, suggesting that the capabilities of CMR to evaluate cardiovascular physiology during a single noninvasive examination have been expanded, thus getting closer to the one-stop-shop vision for CMR

2.5D Flow MRI: 2D phase-contrast of the tricuspid valvular flow with automated valve-tracking

Tricuspid regurgitant velocity is a crucial biomarker in identifying pressure overload in the right heart, associated with diastolic dysfunction and pulmonary hypertension. 2D phase-contrast cannot quantify this flow, and echocardiography is used clinically. We developed a phase-contrast method which utilizes deep-learning algorithms to track the valvular slice in a cardiac phasedependent manner, which we call 2.5D flow. We studied its performance in nine healthy subjects and patients with tricuspid regurgitation. RV stroke volumes correlated better to forward flow volumes by 2.5D flow vs. static 2D phase-contrast (ICC=0.88 vs. 0.62). 2.5D flow characterized regurgitation in a patient

Non-invasive quantification of pressure-volume loops from cardiovascular magnetic resonance at rest and during dobutamine stress

Non-invasive quantification of pressure-volume (PV) loops from brachial pressure and cardiovascular magnetic resonance is a validated method but its application has been limited to resting heart rates. The aim of this study was to improve the previous method and validate it against invasive left-ventricular pressure measurements in an experimental porcine model, and further apply it to 16 healthy humans at rest and during dobutamine stress. In addition, the improved method calculates the arterial elastance which provides the computation of the ratio of effective arterial (Ea) to maximal ventricular elastance (Emax) representing the ventricular-arterial coupling. In the porcine model, the differences between the improved non-invasively derived PV loops and invasively measured PV loops were for stroke work (mean ± SD) 0.00 ± 0.03 J, ventricular efficiency −1.1 ± 0.4%, and contractility 1.1 ± 0.1 mmHg/ml. In human subjects during dobutamine stress, stroke work increased from 1.3 ± 0.3 to 1.7 ± 0.4 J, ventricular efficiency from 71 ± 4 to 82 ± 4%, contractility from 1.3 ± 0.2 to 2.3 ± 0.6 mmHg/ml, and the ratio of arterial to ventricular elastance decreased from 0.96 to 0.56. The improved method for non-invasive PV loops constitutes a more robust diagnostic tool for cardiac disease states in a wider range of study cohorts at both rest and during stress

Valvular imaging in the era of feature-tracking: A slice-following cardiac MR sequence to measure mitral flow

Background: In mitral valve dysfunction, noninvasive measurement of transmitral blood flow is an important clinical examination. Flow imaging of the mitral valve, however, is challenging, since it moves in and out of the image plane during the cardiac cycle. Purpose: To more accurately measure mitral flow, a slice-following MRI phase contrast sequence is proposed. This study aimed to implement such a sequence, validate its slice-following functionality in a phantom and healthy subjects, and test its feasibility in patients with mitral valve dysfunction. Study Type: Prospective. Phantom and Subjects: The slice-following functionality was validated in a cone-shaped phantom by measuring the depicted slice radius. Sixteen healthy subjects and 10 mitral valve dysfunction patients were enrolled at two sites. Field Strength/Sequence: 1.5T and 3T gradient echo cine phase contrast. Assessment: A single breath-hold retrospectively gated sequence using offline feature-tracking of the mitral valve was developed. Valve displacements were measured and imported to the scanner, allowing the slice position to change dynamically based on the cardiac phase. Mitral valve imaging was performed with slice-following and static imaging planes. Validation was performed by comparing mitral stroke volume with planimetric and aortic stroke volume. Statistical Tests: Measurements were compared using linear regression, Pearson's R, parametric paired t-tests, Bland–Altman analysis, and intraclass correlation coefficient (ICC). Results: Phantom experiments confirmed accurate slice displacements. Slice-following was feasible in all subjects, yielding physiologically accurate mitral flow patterns. In healthy subjects, mitral and aortic stroke volumes agreed, with ICC = 0.72 and 0.90 for static and slice-following planes; with bias ±1 SDs 23.2 ± 13.2 mls and 8.4 ± 10.8 mls, respectively. Agreement with planimetry was stronger, with ICC = 0.84 and 0.96; bias ±1 SDs 13.7 ± 13.7 mls and –2.0 ± 8.8 mls for static and slice-following planes, respectively. Data Conclusion: Slice-following outperformed the conventional sequence and improved the accuracy of transmitral flow, which is important for assessment of diastolic function and mitral regurgitation

Automated Measurements of Mitral and Tricuspid Annular Dimensions in Cardiovascular Magnetic Resonance

Our recent work on mitral and tricuspid valve tracking in cardiovascular magnetic resonance (CMR) imaging to obtain accurate evaluations of longitudinal myocardial valve motion (both relaxation and contraction) has enabled an automated diastolic function assessment (e') with CMR. Its time-resolved capability allows a further evaluation of the valve dynamics by providing valve dimension measurements, which are essential to define the etiologies and mechanisms of valve regurgitation. In this paper, we extended the framework to automatically measure mitral annular (MA) and tricuspid annular (TA) dimensions in CMR long-axis cines with a residual neural network backbone. The framework is able to measure MA and TA diameters with an overall excellent accuracy (mean ICC=0.92), on par with an evaluated inter-observer variability (mean ICC=0.92), and to distinguish valvular dimensions between healthy controls and patients with chronic heart failure (p<0.001). Dimension measurements may benefit patients requiring annular sizing and planning of valvular interventions

Quantification of left ventricular contribution to stroke work by longitudinal and radial force-length loops

Left ventricular (LV) stroke work (SW) is calculated from the pressure-volume (PV) loop. PV loops do not contain information on longitudinal and radial pumping, leaving their contributions to SW unknown. A conceptual framework is proposed to derive the longitudinal and radial contributions to SW, using ventricular force-length loops reflecting longitudinal and radial pumping. The aim of this study was to develop and validate this framework experimentally and to explore these contributions in healthy controls and heart failure patients. Thirteen swine underwent cardiovascular magnetic resonance (CMR) and LV pressure catheterization at baseline (n = 7) or 1 wk after myocardial infarction (n = 6). CMR and noninvasive PV loop quantification were performed on 26 human controls and 14 patients. Longitudinal and radial forces were calculated as LV pressure multiplied by the myocardial surface areas in the respective directions. Length components were defined as the atrioventricular plane and epicardial displacements, respectively. Contributions to SW were calculated as the area within the respective force-length loop. Summation of longitudinal and radial SW had excellent agreement with PV loop-derived SW (ICC = 0.95, R = 0.96, bias + SD = = 4.5 + 5.4%) in swine. Longitudinal and radial contributions to SW were ~50/50% in swine and human controls, and 44/56% in patients. Longitudinal pumping required less work than radial to deliver stroke volume in swine (6.8 + 0.8 vs. 8.7 + 1.2 mJ/mL, P = 0.0002) and in humans (11 + 2.1 vs. 17 + 4.7 mJ/mL, P < 0.0001). In conclusion, longitudinal and radial pumping contribute ~50/50% to SW in swine and human controls and 44/56% in heart failure patients. Longitudinal pumping is more energy efficient than radial pumping in delivering stroke volume

Noninvasive Quantification of Pressure-Volume Loops From Brachial Pressure and Cardiovascular Magnetic Resonance

BACKGROUND: Pressure-volume (PV) loops provide a wealth of information on cardiac function but are not readily available in clinical routine or in clinical trials. This study aimed to develop and validate a noninvasive method to compute individualized left ventricular PV loops. METHODS: The proposed method is based on time-varying elastance, with experimentally optimized model parameters from a training set (n=5 pigs), yielding individualized PV loops. Model inputs are left ventricular volume curves from cardiovascular magnetic resonance imaging and brachial pressure. The method was experimentally validated in a separate set (n=9 pig experiments) using invasive pressure measurements and cardiovascular magnetic resonance images and subsequently applied to human healthy controls (n=13) and patients with heart failure (n=28). RESULTS: There was a moderate-to-excellent agreement between in vivo-measured and model-calculated stroke work (intraclass correlation coefficient, 0.93; bias, -0.02±0.03 J), mechanical potential energy (intraclass correlation coefficient, 0.57; bias, -0.04±0.03 J), and ventricular efficiency (intraclass correlation coefficient, 0.84; bias, 3.5±2.1%). The model yielded lower ventricular efficiency ( P<0.0001) and contractility ( P<0.0001) in patients with heart failure compared with controls, as well as a higher potential energy ( P<0.0001) and energy per ejected volume ( P<0.0001). Furthermore, the model produced realistic values of stroke work and physiologically representative PV loops. CONCLUSIONS: We have developed the first experimentally validated, noninvasive method to compute left ventricular PV loops and associated quantitative measures. The proposed method shows significant agreement with in vivo-derived measurements and could support clinical decision-making and provide surrogate end points in clinical heart failure trials