Cardiovascular magnetic resonance feature tracking in pigs: a reproducibility and sample size calculation study

Cardiovascular magnetic resonance feature tracking (CMR-FT) is a novel technique for non-invasive assessment of myocardial motion and deformation. Although CMR-FT is standardized in humans, literature on comparative analysis from animal models is scarce. In this study, we measured the reproducibility of global strain under various inotropic states and the sample size needed to test its relative changes in pigs. Ten anesthetized healthy Landrace pigs were investigated. After baseline (BL), two further steps were performed: (I) dobutamine-induced hyper-contractility (Dob) and (II) verapamil-induced hypocontractility (Ver). Global longitudinal (GLS), circumferential (GCS) and radial strain (GRS) were assessed. This study shows a good to excellent inter- and intra-observer reproducibility of CMR-FT in pigs under various inotropic states. The highest inter-observer reproducibility was observed for GLS at both BL (ICC 0.88) and Ver (ICC 0.79). According to the sample size calculation for GLS, a small number of animals could be used for future trials

Bayesian intravoxel incoherent motion parameter mapping in the human heart

Background: Intravoxel incoherent motion (IVIM) imaging of diffusion and perfusion in the heart suffers from high parameter estimation error. The purpose of this work is to improve cardiac IVIM parameter mapping using Bayesian inference. Methods: A second-order motion-compensated diffusion weighted spin-echo sequence with navigator-based slice tracking was implemented to collect cardiac IVIM data in early systole in eight healthy subjects on a clinical 1.5 T CMR system. IVIM data were encoded along six gradient optimized directions with b-values of 0–300 s/mm2. Subjects were scanned twice in two scan sessions one week apart to assess intra-subject reproducibility. Bayesian shrinkage prior (BSP) inference was implemented to determine IVIM parameters (diffusion D, perfusion fraction F and pseudo-diffusion D*). Results were compared to least-squares (LSQ) parameter estimation. Signal-to-noise ratio (SNR) requirements for a given fitting error were assessed for the two methods using simulated data. Reproducibility analysis of parameter estimation in-vivo using BSP and LSQ was performed. Results: BSP resulted in reduced SNR requirements when compared to LSQ in simulations. In-vivo, BSP analysis yielded IVIM parameter maps with smaller intra-myocardial variability and higher estimation certainty relative to LSQ. Mean IVIM parameter estimates in eight healthy subjects were (LSQ/BSP): 1.63 ± 0.28/1.51 ± 0.14·10−3 mm2/s for D, 13.13 ± 19.81/13.11 ± 5.95% for F and 201.45 ± 313.23/13.11 ± 14.53·10−3 mm2/s for D ∗. Parameter variation across all volunteers and measurements was lower with BSP compared to LSQ (coefficient of variation BSP vs. LSQ: 9% vs. 17% for D, 45% vs. 151% for F and 111% vs. 155% for D ∗). In addition, reproducibility of the IVIM parameter estimates was higher with BSP compared to LSQ (Bland-Altman coefficients of repeatability BSP vs. LSQ: 0.21 vs. 0.26·10−3 mm2/s for D, 5.55 vs. 6.91% for F and 15.06 vs. 422.80·10−3 mm2/s for D*). Conclusion: Robust free-breathing cardiac IVIM data acquisition in early systole is possible with the proposed method. BSP analysis yields improved IVIM parameter maps relative to conventional LSQ fitting with fewer outliers, improved estimation certainty and higher reproducibility. IVIM parameter mapping holds promise for myocardial perfusion measurements without the need for contrast agents

Analyse der linksventrikulären Strain mittels kardiovaskulärer Magnetresonanztomographie (CMR-FT): eine Studie an Landrassenschweinen

Background: Left ventricular (LV) strain imaging is a validated imaging technique able to quantify myocardial function. While the assessment of LV strain is an established clinical routine in echocardiography, cardiovascular magnetic resonance (CMR) LV strain analysis is, instead, a newly emerging method. In specific, CMR feature tracking (CMR-FT) is a promising tracking technique for tissue developed for evaluating myocardial movement and deformation. However, to what extent CMR-FT LV systolic strain reflects the LV mechanical function of the heart still needs to be fully understood. For this reason, the aim of our study was to compare the non-invasive CMR-FT LV strain against invasive hemodynamic parameters representative of the mechanical function of the heart. This includes the cardiac index (CI), cardiac power output (CPO) and end-systolic elastance (Ees), and the data was compared by analyzing them at different inotropic states (hypercontractility and hypocontractility). Methods: Ten healthy Landrace pigs were instrumented, intubated, mechanically ventilated, and transported to the 3-Tesla MRI facility. After baseline measurements (BL), two steps were performed: I) dobutamine-induced hyper-contractility (Dob) and II) verapamil-induced hypocontractility (Ver). At each step, MRI images were acquired at short axis (SAX), 2Ch, 3Ch and 4Ch views. The software MEDIS was utilized to assess the LV mechanical parameters such as global longitudinal strain (GLS), global circumferential strain (GCS) and global radial strain (GRS). Additionally, we calculated the sample size required for the detection of a relative change in baseline strain. Results: Dob demonstrated a noteworthy increased heart rate, CI, CPO and Ees, while Ver decreased them. GLS, GCS and GRS accordingly increased (in absolute value) during Dob infusion, while GLS and GCS decreased (in absolute value) during Ver. Linear regression analysis demonstrated a moderate correlation between GLS, GCS and LV hemodynamic parameters, while GRS correlated poorly. The correlations were significantly improved by indexing global strain parameters for indirect afterload measures such as mean aortic pressure or wall stress. Conclusions: Global longitudinal and circumferential strain moderately correlate with LV invasive parameters such as cardiac power output, cardiac index and end-systolic elastance under various inotropic states. Indexing strain parameters for indirect afterload measures greatly improves this correlation. CMR FT LV strain imaging may be a useful tool in the clinical routine to characterize the LV hemodynamics in patients experiencing different degrees of LV dysfunction.Hintergrund: Die Bildgebung bei linksventrikulärer (LV) Strain ist eine validierte Bildgebungstechnik, die in der Lage ist, die myokardiale Funktion zu quantifizieren. Während die echokardiographische Beurteilung des LV-Strain eine etablierte klinische Routine ist, ist die Analyse des LV-Strain mittels kardiovaskulärer Magnetresonanz (CMR) stattdessen eine neu aufkommende Methode. Im Besonderen ist die CMR-Feature Tracking (CMR-FT) eine vielversprechende Gewebeverfolgungstechnik, die für die Beurteilung der myokardialen Bewegung und Deformation entwickelt wurde. Inwieweit der systolische LV-Strain der CMR FT die mechanische Funktion des Herzens widerspiegelt, muss jedoch noch vollständig verstanden werden. Aus diesem Grund war es das Ziel unserer Studie, die nicht-invasive CMR-FT LV-Strain mit invasiven hämodynamischen Parametern zu vergleichen, die für die mechanische Funktion des Herzens repräsentativ sind, wie z.B. Herzindex (CI), Herzleistung (CPO) und end-systolische Elastanz (Ees), indem sie bei verschiedenen inotropen Zuständen analysiert wurden. Methoden: Zehn gesunde Landrace-Schweine wurden intubiert, mechanisch beatmet und in die 3-Tesla-MRT-Einrichtung transportiert. Nach den Basislinienmessungen (BL) wurden zwei Schritte durchgeführt: I) dobutamininduzierte Hyperkontraktilität (Dob) und II) verapamilinduzierte Hypokontraktilität (Ver). In jedem Schritt wurden MRT-Bilder in Kurzachsen- (SAX), 2Ch, 3Ch und 4Ch-Ansicht aufgenommen. Die Software MEDIS wurde zur Beurteilung der globalen Längs- (GLS), Zirkumferentiell- (GCS) und Radial Strain (GRS) verwendet. Die zum Nachweis einer relativen Änderung der BL-Strain erforderliche Probengröße wurde berechnet. Ergebnisse: Dob erhöhte signifikant die Herzfrequenz, CI, CPO und Ees, während Ver sie verringerte. GLS, GCS und GRS stiegen dementsprechend (im absoluten Wert) während der Dob-Infusion an, während GLS und GCS (im absoluten Wert) während der Ver abnahmen. Die lineare Regressionsanalyse zeigte eine mäßige Korrelation zwischen GLS, GCS und den hämodynamischen LV-Parametern, während GRS schlecht korrelierte. Die Indizierung globaler Strain Parameter für indirekte Messungen der Nachlast, wie z.B. mittlerer Aortendruck oder Wandspannung, verbesserte diese Korrelationen signifikant. Schlussfolgerungen: Die globale Längs- und Zirkumferentiell Strain korreliert mäßig mit LV invasiven Parametern wie der kardialen Leistung, dem kardialen Index und der end systolischen Elastanz unter verschiedenen inotropen Zuständen. Die Indexierung von Strain Parametern für indirekte Messungen der Nachlast verbessert diese Korrelation erheblich. Die CMR-FT-LV-Strain kann in der klinischen Routine ein nützliches Instrument zur Charakterisierung der LV-Hämodynamik bei Patienten mit unterschiedlichem Grad der LV Dysfunktion sein

Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images

Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging—they are relatively invisible via angiography—and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R^2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images

Modified mass-spring system for physically based deformation modeling

Mass-spring systems are considered the simplest and most intuitive of all deformable models. They are computationally efficient, and can handle large deformations with ease. But they suffer several intrinsic limitations. In this book a modified mass-spring system for physically based deformation modeling that addresses the limitations and solves them elegantly is presented. Several implementations in modeling breast mechanics, heart mechanics and for elastic images registration are presented

Modified mass-spring system for physically based deformation modeling

Mass-spring systems are considered the simplest and most intuitive of all deformable models. They are computationally efficient, and can handle large deformations with ease. But they suffer several intrinsic limitations. In this book a modified mass-spring system for physically based deformation modeling that addresses the limitations and solves them elegantly is presented. Several implementations in modeling breast mechanics, heart mechanics and for elastic images registration are presented

Statistical Modelling

The book collects the proceedings of the 19th International Workshop on Statistical Modelling held in Florence on July 2004. Statistical modelling is an important cornerstone in many scientific disciplines, and the workshop has provided a rich environment for cross-fertilization of ideas from different disciplines. It consists in four invited lectures, 48 contributed papers and 47 posters. The contributions are arranged in sessions: Statistical Modelling; Statistical Modelling in Genomics; Semi-parametric Regression Models; Generalized Linear Mixed Models; Correlated Data Modelling; Missing Data, Measurement of Error and Survival Analysis; Spatial Data Modelling and Time Series and Econometrics

Unraveling the intricacies of spatial organization of the ErbB receptors and downstream signaling pathways

Faced with the complexity of diseases such as cancer which has 1012 mutations, altering gene expression, and disrupting regulatory networks, there has been a paradigm shift in the biological sciences and what has emerged is a much more quantitative field of biology. Mathematical modeling can aid in biological discovery with the development of predictive models that provide future direction for experimentalist. In this work, I have contributed to the development of novel computational approaches which explore mechanisms of receptor aggregation and predict the effects of downstream signaling. The coupled spatial non-spatial simulation algorithm, CSNSA is a tool that I took part in developing, which implements a spatial kinetic Monte Carlo for capturing receptor interactions on the cell membrane with Gillespies stochastic simulation algorithm, SSA, for temporal cytosolic interactions. Using this framework we determine that receptor clustering significantly enhances downstream signaling. In the next study the goal was to understand mechanisms of clustering. Cytoskeletal interactions with mobile proteins are known to hinder diffusion. Using a Monte Carlo approach we simulate these interactions, determining at what cytoskeletal distribution and receptor concentration optimal clustering occurs and when it is inhibited. We investigate oligomerization induced trapping to determine mechanisms of clustering, and our results show that the cytoskeletal interactions lead to receptor clustering. After exploring the mechanisms of clustering we determine how receptor aggregation effects downstream signaling. We further proceed by implementing the adaptively coarse grained Monte Carlo, ACGMC to determine if \u27receptor-sharing\u27 occurs when receptors are clustered. In our proposed \u27receptor-sharing\u27 mechanism a cytosolic species binds with a receptor then disassociates and rebinds a neighboring receptor. We tested our hypothesis using a novel computational approach, the ACGMC, an algorithm which enables the spatial temporal evolution of the system in three dimensions by using a coarse graining approach. In this framework we are modeling EGFR reaction-diffusion events on the plasma membrane while capturing the spatial-temporal dynamics of proteins in the cytosol. From this framework we observe \u27receptor-sharing\u27 which may be an important mechanism in the regulation and overall efficiency of signal transduction. In summary, I have helped to develop predictive computational tools that take systems biology in a new direction.\u2