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Image Acquisition and Reconstruction (pre-2019)

High-resolution whole-heart parameter mapping using image-based respiratory navigation and compressed sensing.

Project ID: 2014_104

Student: Giovanna Nordio

1st supervisor: Rene Botnar, King’s College London
2nd supervisor: Gerald Greil, King’s College London

T1 and T2 mapping techniques are becoming increasingly important for myocardial tissue characterization in patients with diffuse fibrosis such as in amyloidosis, cardiac hypertrophy and diabetes (Kellman P et al. JCMR 2012). Emerging applications include coronary artery vasculopathy in patients after heart transplantation (preliminary data Dedieu N et al.).  In this PhD project we want to extend the commonly used breath hold approaches with a free breathing high resolution whole heart approach to allow for complete myocardial coverage but also to allow for coronary plaque characterization, which includes the detection of intraplaque haemorrhage (Noguchi T et al. JACC 2013) and coronary fibrosis (Yeon S et al. JACC 2007). With the advent of clinically approved target specific contrast agents this will also allow the quantification of coronary endothelial permeability (Phinikaridou A et al. Circulation 2012) (gadofosveset, Lantheus Medical Systems), inflammation (Alam SR et al. Circulation Imaging 2012) (ferumoxytol, AMAG Pharmaceuticals) and matrix remodelling (Makowski M et al. Nature Medicine 2011) (ESMA, Lantheus Medical Systems), all biomarkers of plaque activity.

To generate parameter maps, multiple images are typically acquired with varying degrees of T1 or T2 weighting using magnetization preparation pulses such as inversion pulses (T1 weighting) or T2 preparation (T2 weighting). As a large set of images may be needed to calculate the parameters (up to 11 separate images for T1 mapping), the scans are typically limited to 2D acquisitions acquired during breath-holding. This, in turn, limits the achievable spatial resolution and signal-to-noise ratio. Recently, we have demonstrated that T1 mapping can be obtained during free breathing using image-based respiratory navigation (Henningsson M et al. ISMRM abstract 2014) by exploiting the flexibility of a new interleaved scanning (IScan) framework (Henningsson M et al. Magn Reson Med. 2014 (in press)). The use of IScan facilitates the implementation of multiple independent navigators, which is essential for parameter mapping as each navigator will have different contrast which is defined by the temporal distance from the magnetization preparation pulse. This technique can be used to effectively minimize adverse effects of respiratory motion on the T1 maps and enable the use of high resolution T1 mapping of the whole heart with 100% scan efficiency. However, with current image acceleration techniques (parallel imaging and half Fourier) the scan time is still too long for most clinical purposes. In a recent study it has been shown (Prieto C et al. J Magn Reson Imaging. 2012, Akçakaya M et al. Magn Reson Med. 2013) that compressed sensing outperforms parallel imaging for high acceleration factors and may be more suitable to reduce acquisition time for parameter mapping. The proposed project will consist of extending our image navigator framework to parametric mapping and to combine it with compressed sensing methods which can be used to accelerate the acquisition of whole-heart parameter mapping. The novel sequences will be first tested in T1/T2 phantoms and healthy subjects and towards the end of the project in patients with native and transplantation related coronary artery disease.

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