ArticlePhysics in medicine and biology2014
Interventional heart wall motion analysis with cardiac C-arm CT systems.
Article in Physics in medicine and biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: Technical advances and clinical applications.Medical physics · 2024Review
- Motion compensation for cone-beam CT using Fourier consistency conditions.Physics in medicine and biology · 2017Article
- Spatiotemporal Strategies for Joint Segmentation and Motion Tracking From Cardiac Image Sequences.IEEE journal of translational engineering in health and medicine · 2017Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Today, quantitative analysis of three-dimensional (3D) dynamics of the left ventricle (LV) cannot be performed directly in the catheter lab using a current angiographic C-arm system, which is the workhorse imaging modality for cardiac interventions. Therefore, myocardial wall analysis is completely based on the 2D angiographic images or pre-interventional 3D/4D imaging. In this paper, we present a complete framework to study the ventricular wall motion in 4D (3D+t) directly in the catheter lab. From the acquired 2D projection images, a dynamic 3D surface model of the LV is generated, which is then used to detect ventricular dyssynchrony. Different quantitative features to evaluate LV dynamics known from other modalities (ultrasound, magnetic resonance imaging) are transferred to the C-arm CT data. We use the ejection fraction, the systolic dyssynchrony index a 3D fractional shortening and the phase to maximal contraction (ϕi, max) to determine an indicator of LV dyssynchrony and to discriminate regionally pathological from normal myocardium. The proposed analysis tool was evaluated on simulated phantom LV data with and without pathological wall dysfunctions. The LV data used is publicly available online at https://conrad.stanford.edu/data/heart. In addition, the presented framework was tested on eight clinical patient data sets. The first clinical results demonstrate promising performance of the proposed analysis tool and encourage the application of the presented framework to a larger study in clinical practice.
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Registered trials
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