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Project

Dynamic imaging for segmentation and computational modelling of the heart (DIASTOLE).

Cardiac imaging plays an important role in the detection of pathologies of the heart, including coronary and valvular heart disease. It is also increasingly used for planning of complex surgery, and for the patient-specific fitting of medical implants such as artificial valves. Up till recent, dynamic imaging of the heart motion was limited to fast ultrasound (US) imaging, or MRI and CT limited to 2D or a reduced axial field of view. The advent of wide-area detectors with high tube rotation speeds has now enabled acquiring CT volumes covering the entire heart, several times per second. Dynamic or 4D (3D+T) CT is of great promise to clinical cardiac imaging. The modality is particularly suited for applications requiring image processing such as physics-based modelling, in which models of the anatomy are extracted from the image as a starting point for computer simulations. In comparison to US, CT offers a larger field of view and superior signal to noise ratio, making it far better suited for whole-heart segmentation and geometric modelling. Conversely, 4D US offers superior temporal resolution, and provides greater detail on fine structures such as heart valves. Combining dynamic CT with US, would allow benefiting from the advantages of both modalities, and could lead to a robust and accurate workflow for extracting detailed, patient-specific information on heart anatomy and motion. Inclusion of 4D models in physics-based modelling could bring such simulations to a new level of realism, enabling their use for planning of complex interventions and in-silico trials of cardiovascular devices affected by motion. In term, this will reduce the uncertainties associated with such interventions through more accurate device sizing and positioning, and accelerate the development of novel cardiovascular implants. The DIASTOLE consortium aims to develop a novel 4D workflow for performing physics-based simulations for cardiovascular procedures in a dynamic environment, using patient-specific parametric models of the heart and main arteries, obtained from dynamic CT and US.
Date:1 Jun 2017 →  30 Nov 2019
Keywords:FLUID MODELS
Disciplines:Classical physics, Elementary particle and high energy physics, Other physical sciences
Project type:Collaboration project