83 research outputs found
Cardiac left atrium CT image segmentation for ablation guidance
Catheter ablation is an increasingly important curative procedure for atrial fibrillation. Knowledge of the local wall thickness is essential to determine the proper ablation energy. This paper presents the first semi-automatic atrial wall thickness measurement method for ablation guidance. It includes both endocardial and epicardial atrial wall segmentation on CT image data. Segmentation is based on active contours, Otsu's multiple threshold method and hysteresis thresholding. Segmentation results were compared to contours manually drawn by two experts, using repeated measures analysis of variance. The root mean square differences between the semi-automatic and the manually drawn contours were comparable to intra-observer variation (endocardium: p = 0.23, epicardium: p = 0.18). Mean wall thickness difference is significant between one of the experts on one side, and the presented method and the other expert on the other side (
Cardiac motion estimation using multi-scale feature points
Heart illnesses influence the functioning of the cardiac muscle and are the major causes of death inthe world. Optic flow methods are essential tools to assess and quantify the contraction of the cardiacwalls, but are hampered by the aperture problem. Harmonic phase (HARP) techniques measure thephase in magnetic resonance (MR) tagged images. Due to the regular geometry, patterns generated bya combination of HARPs and sine HARPs represent a suitable framework to extract landmark features.In this paper we introduce a new aperture-problem free method to study the cardiac motion by trackingmulti-scale features such as maxima, minima, saddles and corners, on HARP and sine HARP taggedimages
Evolution equations on Gabor transforms and their applications
We introduce a systematic approach to the design, implementation and analysis of left-invariant evolution schemes acting on Gabor transform, primarily for applications in signal and image analysis. Within this approach we relate operators on signals to operators on Gabor transforms. In order to obtain a translation and modulation invariant operator on the space of signals, the corresponding operator on the reproducing kernel space of Gabor transforms must be left invariant, i.e. it should commute with the left regular action of the reduced Heisenberg group H_r. By using the left-invariant vector fields on H_r in the generators of our evolution equations on Gabor transforms, we naturally employ the essential group structure on the domain of a Gabor transform. Here we distinguish between two tasks. Firstly, we consider non-linear adaptive left-invariant convection (reassignment) to sharpen Gabor transforms, while maintaining the original signal. Secondly, we consider signal enhancement via left-invariant diffusion on the corresponding Gabor transform. We provide numerical experiments and analytical evidence for our methods and we consider an explicit medical imaging application
Phenotyping of left and right ventricular function in mouse models of compensated hypertrophy and heart failure with cardiac MRI
Background: Left ventricular (LV) and right ventricular (RV) function have an important impact on symptom occurrence, disease progression and exercise tolerance in pressure overload-induced heart failure, but particularly RV functional changes are not well described in the relevant aortic banding mouse model. Therefore, we quantified time-dependent alterations in the ventricular morphology and function in two models of hypertrophy and heart failure and we studied the relationship between RV and LV function during the transition from hypertrophy to heart failure. Methods: MRI was used to quantify RV and LV function and morphology in healthy (n = 4) and sham operated (n = 3) C57BL/6 mice, and animals with a mild (n = 5) and a severe aortic constriction (n = 10). Results: Mice subjected to a mild constriction showed increased LV mass (P,0.01) and depressed LV ejection fraction (EF) (P,0.05) as compared to controls, but had similar RVEF (P.0.05). Animals with a severe constriction progressively developed LV hypertrophy (P,0.001), depressed LVEF (P,0.001), followed by a declining RVEF (P,0.001) and the development of pulmonary remodeling, as compared to controls during a 10-week follow-up. Myocardial strain, as a measure for local cardiac function, decreased in mice with a severe constriction compared to controls (P,0.05). Conclusions: Relevant changes in mouse RV and LV function following an aortic constriction could be quantified using MRI. The well-controlled models described here open opportunities to assess the added value of new MRI techniques for the diagnosis of heart failure and to study the impact of new therapeutic strategies on disease progression and symptom occurrence
Abnormal vortex formation in the right pulmonary artery after the arterial switch operation
Cardiovascular Aspects of Radiolog
Cardiac motion estimation using covariant derivatives and Helmholtz decomposition
The investigation and quantification of cardiac movement is important for assessment of cardiac abnormalities and treatment effectiveness. Therefore we consider new aperture problem-free methods to track cardiac motion from 2-dimensional MR tagged images and corresponding sine-phase images. Tracking is achieved by following the movement of scale-space maxima, yielding a sparse set of linear features of the unknown optic flow vector field. Interpolation/reconstruction of the velocity field is then carried out by minimizing an energy functional which is a Sobolev-norm expressed in covariant derivatives (rather than standard derivatives). These covariant derivatives are used to express prior knowledge about the velocity field in the variational framework employed. They are defined on a fiber bundle where sections coincide with vector fields. Furthermore, the optic flow vector field is decomposed in a divergence free and a rotation free part, using our multi-scale Helmholtz decomposition algorithm that combines diffusion and Helmholtz decomposition in a single non-singular analytic kernel operator. Finally, we combine this multi-scale Helmholtz decomposition with vector field reconstruction (based on covariant derivatives) in a single algorithm and present some experiments of cardiac motion estimation. Further experiments on phantom data with ground truth show that both the inclusion of covariant derivatives and the inclusion of the multi-scale Helmholtz decomposition improves the optic flow reconstruction
Ultrasound transducer positioning aid for fetal heart rate monitoring
Fetal heart rate (fHR) monitoring is usually performed by Doppler ultrasound (US) techniques. For reliable fHR measurements it is required that the fetal heart is located within the US beam. In clinical practice, clinicians palpate the maternal abdomen to identify the fetal presentation and then the US transducer is fixated on the maternal abdomen where the best fHR signal can be obtained. Finding the optimal transducer position is done by listening to the strength of the Doppler audio output and relying on a signal quality indicator of the cardiotocographic (CTG) measurement system. Due to displacement of the US transducer or displacement of the fetal heart out of the US beam, the fHR signal may be lost. Therefore, it is often necessary that the obstetrician repeats the tedious procedure of US transducer positioning to avoid long periods of fHR signal loss. An intuitive US transducer positioning aid would be highly desirable to increase the work flow for the clinical staff. In this paper, the possibility to determine the fetal heart location with respect to the transducer by exploiting the received signal power in the transducer elements is shown. A commercially available US transducer used for fHR monitoring is connected to an US open platform, which allows individual driving of the elements and raw US data acquisition. Based on the power of the received Doppler signals in the transducer elements, the fetal heart location can be estimated. A beating fetal heart setup was designed and realized for validation. The experimental results show the feasibility of estimating the fetal heart location with the proposed method. This can be used to support clinicians in finding the optimal transducer position for fHR monitoring more easily
Phenotyping of Left and Right Ventricular Function in Mouse Models of Compensated Hypertrophy and Heart Failure with Cardiac MRI
Background: Left ventricular (LV) and right ventricular (RV) function have an important impact on symptom occurrence, disease progression and exercise tolerance in pressure overload-induced heart failure, but particularly RV functional changes are not well described in the relevant aortic banding mouse model. Therefore, we quantified time-dependent alterations in the ventricular morphology and function in two models of hypertrophy and heart failure and we studied the relationship between RV and LV function during the transition from hypertrophy to heart failure. Methods: MRI was used to quantify RV and LV function and morphology in healthy (n = 4) and sham operated (n = 3) C57BL/6 mice, and animals with a mild (n = 5) and a severe aortic constriction (n = 10). Results: Mice subjected to a mild constriction showed increased LV mass (P0.05). Animals with a severe constriction progressively developed LV hypertrophy (P<0.001), depressed LVEF (P<0.001), followed by a declining RVEF (P<0.001) and the development of pulmonary remodeling, as compared to controls during a 10-week follow-up. Myocardial strain, as a measure for local cardiac function, decreased in mice with a severe constriction compared to controls (P<0.05). Conclusions: Relevant changes in mouse RV and LV function following an aortic constriction could be quantified using MRI. The well-controlled models described here open opportunities to assess the added value of new MRI techniques for the diagnosis of heart failure and to study the impact of new therapeutic strategies on disease progression and symptom occurrence
Muscle fiber strain rates in the lower leg during ankle dorsi-/plantarflexion exercise
Static quantitative magnetic resonance imaging (MRI) provides readouts of structural changes in diseased muscle, but current approaches lack the ability to fully explain the loss of contractile function. Muscle contractile function can be assessed using various techniques including phase-contrast MRI (PC-MRI), where strain rates are quantified. However, current two-dimensional implementations are limited in capturing the complex motion of contracting muscle in the context of its three-dimensional (3D) fiber architecture. The MR acquisitions (chemical shift-encoded water–fat separation scan, spin echo-echoplanar imaging with diffusion weighting, and two time-resolved 3D PC-MRI) wereperformed at 3 T. PC-MRI acquisitions and performed with and without load at 7.5% of the maximum voluntary dorsiflexion contraction force. Acquisitions (3 T, chemical shift-encoded water–fat separation scan, spin echo-echo planar imaging with diffusion weighting, and two time-resolved 3D PC-MRI) were performed with and without load at 7.5% of the maximum voluntary dorsiflexion contraction force. Strain rates and diffusion tensors were calculated and combined to obtain strain rates along and perpendicular to the muscle fibers in seven lower leg muscles during the dynamic dorsi-/plantarflexion movement cycle. To evaluate strain rates along the proximodistal muscle axis, muscles were divided into five equal segments. t-tests were used to test if cyclic strain rate patterns (amplitude > 0) were present along and perpendicular to the muscle fibers. The effects of proximal-distal location and load were evaluated using repeated measures ANOVAs. Cyclic temporal strain rate patterns along and perpendicular to the fiber were found in all muscles involved in dorsi-/plantarflexion movement (p p p Radiolog
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