Structural and functional mapping of the brainstem with MRI

The brainstem plays a central role in the central nervous system, relaying signals between the cerebrum and cerebellum and the rest of the body. This makes it vital to motor function, quality of life and life expectancy in age-related disorders. Parkinsons disease is a neurodegenerative disorder which affects midbrain and brainstem structures, leading to muscle rigidity, tremors and difficulty speaking and walking. Medication can help relieve symptoms in some patients, but many eventually suffer a general decline in motor function. Deep brain stimulation is an effective treatment option for many Parkinsons patients who do not respond to medication. A surgically implanted electric unit stimulates specific areas of the deep brain or brainstem, reducing motor disability. Currently, the stimulation electrodes are placed on the basis of atlases related to magnetic resonance images (MRI) of the patient. This approach is limited, because only a small number of brainstem nuclei are depicted in atlases, and also unreliable, because of the anatomic variability between patients. Deep brain stimulation could be greatly improved by being able to identify deep brain and brainstem targets in each individual patient. These structures are hard to see on conventional MRI because of their small size and limited contrast but they are well visualized on a MRI images generated with a recently-developed MRI method called Quantitative Susceptibility Mapping (QSM). They can also be seen in functional MRI (fMRI), which shows which parts of the brain are active when a patient performs a task. These two methods QSM and fMRI cannot currently be used to plan deep brain stimulation because they involve two quite long scans for which patients have to stay extremely still, a particular problem for many Parkinsons patients. This project proposes the development of a new fast MRI method which will generate high resolution QSM and fMRI images from the same scan. This project will be carried out with one of the latest generation of ultra-high magnetic field (7 T) MRI scanners, which allow higher resolution imaging. In addition to realizing this combined structural and functional scan, the project will i) develop methods to remove any distortion from the fMRI data, which would otherwise make it difficult to accurately localize the structures of the brainstem ii) identify and remove breathing and cardiac pulse-related signal fluctuations in the fMRI data which mask neuronal activation and iii) generate a motion-corrected and a super-resolution QSM. Combined with suitable tasks, this sequence for simultaneous Functional And Structural identification of Targets in the Brainstem (FAST-STEM) will be capable of identifying multiple midbrain and brainstem targets for deep brain stimulation in a scan time which will tolerable by Parkinsons patients. Finally, this new approach to imaging the brainstem will be transferred to a clinical 3 T MRI scanner to ensure that patients can benefit from it in future studies. Eventually, it is hoped that this approach to brainstem imaging will allow new, effective targets for deep brain stimulation to be identified and accurately localized, leading to a relief from debilitating symptoms and an improvement in quality of life for patients with Parkinsons disease.

Parkinson's disease (PD) is a neurodegenerative disease characterized by the death of neurons which produce and release the neurotransmitter dopamine. This occurs in a number of midbrain and brainstem structures and leads to patients suffering tremor, postural instability, rigidity, and an eventual general decline in motor function. Deep brain stimulation (DBS) is an effective treatment option for many patients who don't respond well to medication. A surgically implanted electric unit stimulates neurons in specific grey matter and brainstem regions reducing motor disability. The aim of this project was to develop MRI methods which will help in the identification of new targets for DBS in the deep brain and brainstem. MRI is capable of producing a wide variety of images which reflect particular aspects of structure or function. For instance, the deep-lying grey matter regions of interest in DBS can be well visualized on Quantitative Susceptibility Maps (QSM), which show iron-rich areas of the brain. The same areas can also be seen 'lighting up' when they are activated by a relevant task in functional Magnetic Resonance Imaging, or fMRI. QSM and fMRI both benefit from using MRI scanner with ultra-high magnetic field, such as the 7 Tesla system at the High Field MR Centre, Vienna. Imaging at 7T allows small grey matter targets to be visualized with high sensitivity and exquisite resolution, but the use of ultra-high field also carries with it a number of challenges. Researchers in this project first developed a method to generate both QSMs and fMRI from the same 7T data, and new approaches for correcting for distortion and physiological noise; essential if results are to be used in neurosurgery. They then applied those methods to a fast imaging method called 3D EPI and to even faster, motion-robust imaging using 2D EPI and a 'super-resolution' reconstruction, which allows high resolution images to be generated from multiple sets of low-resolution images acquired in different planes. Finally, they found out how to solve the imaging problem posed by the presence of fat in the head and neck; their Simultaneous, MUltiple Resonance Frequency (SMURF) approach to fat-water imaging allows separate images of fat and water to be generated simultaneously, in an approach which won the international Young Investigator Award of the International Society of Magnetic Resonance in Medicine. The methods developed in this project have been distributed to over half of the approximately 100 ultra-high field MRI sites around the world and have been adopted by MRI vendors in their research packages. These innovations have improved Quantitative Susceptibility Mapping and functional Magnetic Resonance Imaging in the inferior brain and brainstem for the identification of targets for deep brain stimulation.