Validation of Quantitative Myocardial Perfusion Magnetic Resonance Imaging

Abstract

Cardiovascular magnetic resonance (CMR) perfusion imaging has been shown to accurately detect significant coronary artery stenoses and is of potential use to detect patients for early treatment and to improve prognosis. New techniques yield a superb spatial resolution and may allow for full quantification of perfusion. Novel CMR techniques and imaging biomarkers are often validated in small animal models or empirically in patients. The direct translation of small animal magnetic resonance (MR) imaging protocols to humans is rarely possible, while validation in humans is often difficult, slow and occasionally not possible due to ethical considerations. -- The aim of the thesis was to develop an MR-compatible isolated blood-perfused pig heart model, which closely resembles human physiology, anatomy and size and to utilize it for controlled validation of quantitative perfusion at the segmental and voxel level using standard clinical sequences and MR scanners. To enable accurate quantification a universal dual-bolus method was developed. The design of the heart allowed exquisite control regarding overall and regional blood-flow and imaging by identical equipment used for humans. Quantitative perfusion imaging showed a good correlation with microspheres, which was most apparent with Fermi function constrained deconvolution regardless of sequence or field strength. Fermi deconvolution based voxel-wise quantitative perfusion values also correlated well with microspheres throughout the myocardial wall. The validated sequences proved useful for the detection of significant coronary artery disease in a small feasibility study in patients analysing perfusion at the segmental level. In conclusion this work has resulted in an accurate validation of quantitative perfusion CMR at a segmental and voxel level at common clinical field strengths.

Date of Award	2012
Original language	English
Awarding Institution	King's College London
Supervisor	Eike Nagel (Supervisor) & Divaka Perera (Supervisor)