Four Dimensional MR Image Analysis of Dynamic Renography

A novel four dimensional image analysis approach including registration and segmentation of dynamic contrast enhanced renal MR images is presented. This integrated method is motivated by the observation of the reciprocity between registration and segmentation in 4D time-series images. Fully automated Fourier-based registration with sub-voxel accuracy and semi-automated time-series segmentation were intertwined to improve the accuracy in a multi-step fashion. We have tested our algorithm on several real patient data sets. Clinical validation showed remarkable and consistent agreement between the proposed method and manual segmentation by experts

Integrated Four Dimensional Registration and Segmentation of Dynamic Renal MR Images

In this paper a novel approach for the registration and segmentation of dynamic contrast enhanced renal MR images is presented. This integrated method is motivated by the observation of the reciprocity between registration and segmentation in 4D time-series images. Fully automated Fourier-based registration with sub-voxel accuracy and semi-automated time-series segmentation were intertwined to improve the accuracy in a multi-step fashion. We have tested our algorithm on several real patient data sets. Clinical validation showed remarkable and consistent agreement between the proposed method and manual segmentation by experts

Analysis of first pass myocardial perfusion imaging with magnetic resonance

Early diagnosis and localisation of myocardial perfusion defects is an important step in the treatment of coronary artery disease. Thus far, coronary angiography is the conventional standard investigation for patients with known or suspected coronary artery disease and it provides information about the presence and location of coronary stenoses. In recent years, the development of myocardial perfusion CMR has extended the role of MR in the evaluation of ischaemic heart disease beyond the situations where there have already been gross myocardial changes such as acute infarction or scarring. The ability to non-invasively evaluate cardiac perfusion abnormalities before pathologic effects occur, or as follow-up to therapy, is important to the management of patients with coronary artery disease. Whilst limited multi-slice 2D CMR perfusion studies are gaining increased clinical usage for quantifying gross ischaemic burden, research is now directed towards complete 3D coverage of the myocardium for accurate localisation of the extent of possible defects. In 3D myocardial perfusion imaging, a complete volumetric data set has to be acquired for each cardiac cycle in order to study the first pass of the contrast bolus. This normally requires a relatively large acquisition window within each cardiac cycle to ensure a comprehensive coverage of the myocardium and reasonably high resolution of the images. With multi-slice imaging, long axis cardiac motion during this large acquisition window can cause the myocardium imaged in different cross- sections to be mis-registered, i.e., some part of the myocardium may be imaged more than twice whereas other parts may be missed out completely. This type of mis-registration is difficult to correct for by using post-processing techniques. The purpose of this thesis is to investigate techniques for tracking through plane motion during 3D myocardial perfusion imaging, and a novel technique for extracting intrinsic relationships between 3D cardiac deformation due to respiration and multiple ID real-time measurable surface intensity traces is developed. Despite the fact that these surface intensity traces can be strongly coupled with each other but poorly correlated with respiratory induced cardiac deformation, we demonstrate how they can be used to accurately predict cardiac motion through the extraction of latent variables of both the input and output of the model. The proposed method allows cross-modality reconstruction of patient specific models for dense motion field prediction, which after initial modelling can be use in real-time prospective motion tracking or correction. In CMR, new imaging sequences have significantly reduced the acquisition window whilst maintaining the desired spatial resolution. Further improvements in perfusion imaging will require the application of parallel imaging techniques or making full use of the information content of the ¿-space data. With this thesis, we have proposed RR-UNFOLD and RR-RIGR for significantly reducing the amount of data that is required to reconstruct the perfusion image series. The methods use prospective diaphragmatic navigator echoes to ensure UNFOLD and RIGR are carried out on a series of images that are spatially registered. An adaptive real-time re-binning algorithm is developed for the creation of static image sub-series related to different levels of respiratory motion. Issues concerning temporal smoothing of tracer kinetic signals and residual motion artefact are discussed, and we have provided a critical comparison of the relative merit and potential pitfalls of the two techniques. In addition to the technical and theoretical descriptions of the new methods developed, we have also provided in this thesis a detailed literature review of the current state-of-the-art in myocardial perfusion imaging and some of the key technical challenges involved. Issues concerning the basic background of myocardial ischaemia and its functional significance are discussed. Practical solutions to motion tracking during imaging, predictive motion modelling, tracer kinetic modelling, RR-UNFOLD and RR-RIGR are discussed, all with validation using patient and normal subject data to demonstrate both the strength and potential clinical value of the proposed techniques.Open acces

Linear motion correction in three dimensions applied to dynamic gadolinium enhanced breast imaging

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134776/1/mp8576.pd

MRI Studies of Appetite Centre Function in Rodents

Many different regions of the brain are involved in appetite control. A full understanding of their function and interaction requires studying neuronal activity at high resolution simultaneously in space and time. Two Magnetic Resonance Imaging (MRI) methods can potentially achieve this goal. Manganese-Enhanced (MEMRI) uses the accumulation of administered Mn[2+], which is paramagnetic (hence MRI visible) and taken up by active neurons through voltage-gated Ca[2+] channels during action potentials. Haemodynamic methods use one or more of many MRI-visible changes that occur to circulating blood in a brain region when it changes activity. These include blood-oxygenation level dependent (BOLD) and cerebral blood volume weighted (CBV) MRI. The aim of this project was to further develop, adapt and then use these methods to study the effects on neuronal activity of stimuli related to appetite and energy balance. The majority of work went towards adapting MEMRI for this. Amongst many tested changes, improvements were made to the MRI acquisition protocol (specifically using fast spin echo rather than spin-echo acquisition) to make it more sensitive to Mn-induced signal changes, increase spatial coverage from partial to whole brain and rostro-caudal spatial resolution from 1 to 0.4mm, all while maintaining the same temporal resolution. Most importantly, the neuroimaging analysis framework used in haemodynamic functional MRI was adapted for use with MEMRI. This included the adaptation of spatial normalization software to handle Mn-sensitive T[1]-weighted images dominated by non-brain tissue rather than brain dominated T[2]/T*[2]-weighted images, and the generation of a signal change model for use in GLM. This enabled much more objective, reproducible and less laborious data analysis than with previous hand drawn ROIs. Attempts were made to use BOLD- and CBV-fMRI to study the effects of potent, appetite-modulating gut hormones on appetite, though these failed to produce a response

Abdominal DCE‐MRI reconstruction with deformable motion correction for liver perfusion quantification

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146361/1/mp13118_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146361/2/mp13118.pd

Rigid‐body motion correction of the liver in image reconstruction for golden‐angle stack‐of‐stars DCE MRI

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141403/1/mrm26782_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141403/2/mrm26782.pd

Image processing techniques in nuclear medicine

The application of image processing techniques to radionuclide images acquired on a gamma camera - computer system has been investigated. Hepatic perfusion imaging studies with 99Tcm-tin colloid were performed in patients with primary colorectal carcimma. The hepatic perfusion index performed poorly in the detection of those patients with occult or overt hepatic metastastes, as did mean transit times of liver colloid flow derived from deconvolution analysis. A discriminant function was developed which separated those patients with occult metastases from those without liver disease. A fully automatic algorithm to derive a left ventricular edge from each frame of an ECG gated cardiac blood pool study was developed and validated in patient studies. Left ventricular ejection fractions calculated from count rates within the edge were reproducible and correlated well with ejection fractions derived from the same images by a manual technique, and with ejection fractions derived from left ventricular cineangiography. Studies were performed in patients to evaluate the effectiveness of tomographic imaging of the myocardial perfusion imaging agent 99Tcm-tBIN for detection of ischaemic heart disease. Tomographic reconstructions in the planes of the axes of the left ventricle gave better results than transaxial reconstructions or planar imaging. Choice of the optimum reconstruction filter for use in tomography using 99Tcm-tBIN was examined by means of patient am phantom studies. These showed that more accurate diagnoses and better reconstructions were obtained with smoothing filters than by the use of sharp reconstruction filters. This work shows that optimum image processing techniques must be established to attain the best possible results with new radiopharmaceuticals for nuclear medicine investigations