Irina Waechter-Stehle

FULLY AUTOMATED QUANTIFICATION OF LEFT VENTRICULAR AND LEFT ATRIAL VOLUMES FROM TRANSTHORACIC 3D ECHOCARDIOGRAPHY: A VALIDATION STUDY

Cardiac chamber quantification from 3D transthoracic echocardiography (3D TTE) has been shown to be superior to measurements obtained from 2D studies. However, integration of 3D TTE into routine clinical practice has been limited by the time-consuming workflow and need for 3D expertise. We assessed

Analysis of Mitral Valve Motion in 4D Transesophageal Echocardiography for Transcatheter Aortic Valve Implantation

Transcatheter aortic valve implantation (TAVI) is used to treat aortic stenosis in high-risk patients that cannot undergo cardiac surgery. Because it is minimally-invasive, it could be beneficial to treat patients in better conditions as well. Because their expected lifetime is much longer, the long-term benefit of the TAVI implant must be ensured. If the TAVI stent is placed too far into the left ventricular outflow tract it can impair movement of the anterior mitral leaftlet. Case reports demonstrated endocarditis and leaflet damage due to such friction.

Multi-modal Vertebra Segmentation from MR Dixon for Hybrid Whole-Body PET/MR

In this paper, a novel model-based segmentation of the vertebrae is introduced that uses multi-modal image features from Dixon MR images (i.e. water/fat separated). Our primary application is the segmentation of the bony anatomy for the generation of attenuation maps in hybrid PET/MR imaging systems. The focus of this work is on the geometric accuracy of the segmentation from MR. From ground-truth structure delineations on training data sets, image features for a model-based segmentation are trained on both the water and fat images from the Dixon series. For the actual segmentation, both features are used simultaneously to improve both robustness and accuracy compared to single image segmentations. The method is validated on 25 patients by comparing the results to semi-automatically generated ground truth annotations. A mean surface distance error of 1.69 mm over all vertebrae is achieved, leading to an improvement of up to 41 % compared to using a single image alone.

Comparison of CFD-Based and Bernoulli-Based Pressure Drop Estimates across the Aortic Valve Enabled by Shape-Constrained Deformable Segmentation of Cardiac CT Images

The aortic valve area (AVA) and the pressure drop (PD) across the aortic valve are important quantities for characterizing an aortic valve stenosis. Using the Bernoulli equation and mass conservation, a relation between both quantities can be derived. We developed a simulation pipeline to assess the accuracy of this relation for realistic patient anatomies and blood flow rates. The key element of the pipeline is a shape-constrained deformable model (SCDM) for the segmentation of the aortic valve, the ascending aorta and the left ventricle over the cardiac cycle in cardiac CT images. Efficient segmentation enabled application of the simulation pipeline to cardiac CT image sequences of 22 patients. Planimetric AVA and Bernoulli-based PD estimates were computed from the same segmentation results. The resulting PD estimates show a high correlation (R = 0.97), but Bernoulli-based PD results are on average 25% smaller than the CFD-based results. The results contribute to a better understanding and interpretation of clinically used quantities such as the AVA and the PD.

CFD‐ and Bernoulli‐based pressure drop estimates: A comparison using patient anatomies from heart and aortic valve segmentation of CT images

Purpose An aortic valve stenosis is an abnormal narrowing of the aortic valve (AV). It impedes blood flow and is often quantified by the geometric orifice area of the AV (AVA) and the pressure drop (PD). Using the Bernoulli equation, a relation between the PD and the effective orifice area (EOA) represented by the area of the vena contracta (VC) downstream of the AV can be derived. We investigate the relation between the AVA and the EOA using patient anatomies derived from cardiac computed tomography (CT) angiography images and computational fluid dynamic (CFD) simulations. Methods We developed a shape‐constrained deformable model for segmenting the AV, the ascending aorta (AA), and the left ventricle (LV) in cardiac CT images. In particular, we designed a structured AV mesh model, trained the model on CT scans, and integrated it with an available model for heart segmentation. The planimetric AVA was determined from the cross‐sectional slice with minimum AV opening area. In addition, the AVA was determined as the nonobstructed area along the AV axis by projecting the AV leaflet rims on a plane perpendicular to the AV axis. The flow rate was derived from the LV volume change. Steady‐state CFD simulations were performed on the patient anatomies resulting from segmentation. Results Heart and valve segmentation was used to retrospectively analyze 22 cardiac CT angiography image sequences of patients with noncalcified and (partially) severely calcified tricuspid AVs. Resulting AVAs were in the range of 1–4.5 cm2 and ejection fractions (EFs) between 20 and 75%. AVA values computed by projection were smaller than those computed by planimetry, and both were strongly correlated (R2 = 0.995). EOA values computed via the Bernoulli equation from CFD‐based PD results were strongly correlated with both AVA values (R2 = 0.97). EOA values were ∼10% smaller than planimetric AVA values. For EOA values < 2.0 cm2, the EOA was up to ∼15% larger than the projected AVA. Conclusions The presented segmentation algorithm allowed to construct detailed AV models for 22 patient cases. Because of the crown‐like 3D structure of the AV, the planimetric AVA is larger than the projected AVA formed by the free edges of the AV leaflets. The AVA formed by the free edges of the AV leaflets was smaller than the EOA for EOA values Symbol. This contradiction with respect to previous studies that reported the EOA to be always smaller or equal to the geometric AVA is explained by the more detailed AV models used within this study. Symbol. No caption available.