Interventional heart wall motion analysis with cardiac C-arm CT systems

Müller, Kerstin; Maier, Andreas; Zheng, Yefeng; Wang, Yang; Lauritsch, Guenter; Schwemmer, Chris; Rohkohl, Christopher; Hornegger, Joachim; Fahrig, Rebecca

doi:10.1088/0031-9155/59/9/2265

Cited by 6 publications

(5 citation statements)

References 32 publications

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“…From the segmented surfaces, the blood pool volumes in end-diastole and end-systole are calculated. In addition, similar to previous work of (Müller, Maier, Zheng, Wang, Lauritsch, Schwemmer, Rohkohl, Hornegger & Fahrig 2014), a visualization of the contraction pattern is provided by color-coding the displacement of each vertex between end-systole and end-diastole and projecting the resulting mesh onto a polar map according to the 16-segment model suggested by the American Heart Association (Cerqueira et al 2002) (Fig. 2, right).…”

Section: Volumetry and Motion Visualizationmentioning

confidence: 99%

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Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

et al. 2017

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Time-resolved tomographic cardiac imaging using an angiographic C-arm device may support clinicians during minimally invasive therapy by enabling a thorough analysis of the heart function directly in the catheter laboratory. However, clinically feasible acquisition protocols entail a highly challenging reconstruction problem which suffers from sparse angular sampling of the trajectory. Compressed sensing theory promises that useful images can be recovered despite massive undersampling by means of sparsity-based regularization. For a multitude of reasons-most notably the desired reduction of scan time, dose and contrast agent required-it is of great interest to know just how little data is actually sufficient for a certain task. In this work, we apply a convex optimization approach based on primal-dual splitting to 4D cardiac C-arm computed tomography. We examine how the quality of spatially and temporally total-variation-regularized reconstruction degrades when using as few as [Formula: see text] projection views per heart phase. First, feasible regularization weights are determined in a numerical phantom study, demonstrating the individual benefits of both regularizers. Secondly, a task-based evaluation is performed in eight clinical patients. Semi-automatic segmentation-based volume measurements of the left ventricular blood pool performed on strongly undersampled images show a correlation of close to 99% with measurements obtained from less sparsely sampled data.

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Section: Volumetry and Motion Visualizationmentioning

confidence: 99%

“…the need for a prolonged contrast injection which may be harmful for the patient. In prior work, scan protocols with acquisition durations of about 10 s and 15 s (Müller et al 2014b) were used.…”

Section: Practical Considerationsmentioning

confidence: 99%

Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

et al. 2017

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“…A ventricle dataset (Müller et al 2013a, Maier et al 2012 of a similar design to the XCAT phantom (Segars et al 2008) was simulated. It was assumed that all materials have the same spectral absorption behaviour as water.…”

Section: Phantom Modelsmentioning

confidence: 99%

Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT

Müller¹,

Maier²,

Schwemmer³

et al. 2014

Phys. Med. Biol.

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The acquisition of data for cardiac imaging using a C-arm CT system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable 3-D/3-D registration performed on initial 3-D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3-D images. In this paper, the sensitivity of the 3-D/3-D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3-D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc.) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing (PICCS) combined with the improved total variation (iTV) algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical phantom data set with and without a catheter and on two porcine models using qualitative and quantitative measures. The quantitative results of the phantom experiments show that if no dense object is present within the scan field of view, the quality of the FDK initial images is sufficient for motion estimation via 3-D/3-D registration. When a catheter or pacing electrode is present, the shadow of these objects needs to be removed before the initial image reconstruction. An additional bilateral filter shows no major improvement with respect to the final motion-compensated reconstruction quality. The results with respect to image quality of the cathFDK, cathFFDK and FV images are comparable. As conclusion, in terms of computational complexity, the algorithm of choice is the cathFDK algorithm.

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“…In the field of cardiovascular imaging, artifacts can be reduced by clustering consistent projection images using an ECG signal (Schaefer et al; 2006). Subsequently, the image may be further improved via registration in projection (Schwemmer et al; 2013) or reconstruction domain (Müller et al; 2014). Another type of motion estimation uses fiducial markers, that are identified in projection images and tracked over time (Li et al; 2006; Choi et al; 2014).…”

Section: Introductionmentioning

confidence: 99%

Motion compensation for cone-beam CT using Fourier consistency conditions

et al. 2017

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In cone-beam CT, involuntary patient motion and inaccurate or irreproducible scanner motion substantially degrades image quality. To avoid artifacts this motion needs to be estimated and compensated during image reconstruction. In previous work we showed that Fourier Consistency Conditions (FCC) can be used in fan-beam CT to estimate motion in the sinogram domain. This work extends the FCC to 3-D cone-beam CT. We derive an efficient cost function to compensate for 3-D motion using 2-D detector translations. The extended FCC method have been tested with five translational motion patterns, using a challenging numerical phantom. We evaluated the root-mean-square-error (RMSE) and the structural-similarity-index (SSIM) between motion corrected and motion-free reconstructions. Additionally, we computed the mean-absolute-difference (MAD) between the estimated and the ground-truth motion. The practical applicability of the method is demonstrated by application to respiratory motion estimation in rotational angiography, but also to motion correction for weight-bearing imaging of knees. Where the latter makes use of specifically modified FCC version which is robust to axial truncation. The results show a great reduction of motion artifacts. Accurate estimation results were achieved with a maximum MAD value of 708 µm and 1184 µm for motion along the vertical and horizontal detector direction, respectively. The image quality of reconstructions obtained with the proposed method is close to that of motion corrected reconstructions based on the ground-truth motion. Simulations using noise-free and noisy data demonstrate that FCC are robust to noise. Even high-frequency motion was accurately estimated leading to a considerable reduction of streaking artifacts. The method is purely image-based and therefore independent of any auxiliary data.

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Interventional heart wall motion analysis with cardiac C-arm CT systems

Cited by 6 publications

References 32 publications

Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT

Motion compensation for cone-beam CT using Fourier consistency conditions

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