David S. Smith, Ph.D. - US grants

The objectives are to continue development of magnetic resonance spectroscopy (MRS) as a "tool" for exploring bioenergetic events in the brain in vivo. The present work proposes to explore two hypotheses: 1. That the severity of an hypoxemic insult in the adult brain can be predicted by MRS determination of phosphocreatine (PCr) concentration. 2. That brain work and brain bioenergetics are related by a Michaelis-Menten hyperbola and that metabolic instability can be predicted from MRS measurements. In pursuing these two hypotheses, the changes obtained with MRS will be related to measures of oxygen availability, brain redox state, cerebral metabolism of oxygen and glucose, cerebral production of lactate, brain intracellular pH, cerebral blood flow, neurophysiologic function (electroencephalography and somatosensory evoked potentials), and histopathology (by both light and electron microscopy). Finally, the findings with MRS will be compared to measurements of brain metabolites by standard biochemical techniques to determine the sensitivity and reproducibility of MRS measurements compared to traditional approaches. The experiments will be done on anesthetized dogs, intubated, mechanically ventilated and prepared for invasive monitoring of vital signs. Two different types of experiments will be done: In the first, the dog will be exposed to a period of "stabilized hypoxemia" in which the degree of metabolic stress is continuously adjusted according to "real time" determinations of PCr by MRS. At various times oxygen will be restored and the rate of recovery or the development of metabolic instability will be determined. In the second type of experiment, brain work will be increased by administration of a short acting epileptogenic gas. The ability to finely titrate the dose of this agent should allow graded increases in cerebral metabolic rate that will allow determination of the relationship of brain work to brain energy. These experiments have direct relevance to medicine. Many catastrophic brain events involve changes in brain energy production. MRS is the only technique with the potential of determining these changes in man, since it can measure brain energy non-invasively and non-destructively. Basic studies of MRS in animals are required to understand the meaning of the measurements when they are obtained from humans. In addition, the studies will add to the fundamental knowledge concerning the production and utilization of energy in the brain.

CLINICAL TRIALS OFFICE The Clinical Trials Office (CTO) provides infrastructure support for the conduct of clinical trials at the University of Michigan Comprehensive Cancer Center. CTO services are grouped into three major categories;regulatory services, data management services, and information technologies services. Major areas of responsibility include support for regulatory submissions to the IRB, two Protocol Review Committees (therapeutic and prevention), GCRC and other institutional review committees, FDA, and NCI. The CTO provides data management services for PRC-approved clinical trials as well as serving as a centralized data repository for research data generated on clinical trials. These services include study implementation, data collection and entry, and submission to investigators and outside sponsors. The information technology services include Case Report Form (CRF) development and database implementation and maintenance. The primary mission of the CTO is to assist the Cancer Center investigators in the development, conduct, and reporting of innovative clinical research in an efficient, regulatory compliant, and scientifically sound manner.

DESCRIPTION (provided by applicant): The goal of this proposal is to develop and validate novel compressed sensing (CS) approaches to dramatically improve the spatial and temporal resolution of quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). CS exploits prior information (assumptions) about MR images to infer missing data and produce high-quality images from significantly less data than previously thought possible. CS has already proven extremely successful in MR angiography and cardiac MRI, where it has accelerated some acquisitions by up to 10- to 100-fold, but is relatively unexplored in cancer imaging. DCE-MRI involves the serial acquisition of heavily T1-weighted images before and after the injection of a contrast agent to increase water relaxation rates in tissues. The resultin data can then be analyzed with appropriate pharmacokinetic models to extract quantitative parameters reporting on, for example, vessel perfusion and permeability, and tissue volume fractions. DCE-MRI has been applied to predict the early response to neoadjuvant chemotherapy in breast cancer, but the technique is not yet robust and accurate enough for the clinic. A fundamental practical limitation of DCE-MRI is the necessity to simultaneously acquire high temporal resolution, to adequately sample the contrast time course, and high spatial resolution, which is required for clinical morphological assessment and accurate tumor delineation. In traditional Cartesian MRI acquisitions, one must choose between high spatial or high temporal resolution before the scan. With a golden ratio acquisition, the tradeoff between spatial and temporal resolution is eliminated. A single DCE-MRI scan may then be used for both accurate kinetic modeling by slicing the data at high temporal cadence, while also allowing a high spatial resolution image to be formed by taking the data as a whole. Thus, a golden ratio acquisition coupled with CS has great potential to enable a clinically relevant DCE-MRI protocol that provides adequate temporal resolution for kinetic modeling without sacrificing the spatial resolution required for morphological evaluation. This project has three aims: (1) to develop a compressed sensing based high temporal resolution protocol for quantitative DCE-MRI, (2) to develop a compressed sensing based high spatial resolution T1-weighted anatomical imaging protocol for morphological evaluation, and (3) to apply the developed CS-based protocols in vivo for validation and evaluation. If this project is successful, it will significantly improve te ability to predict response to neoadjuvant chemotherapy, provide new CS methods for the community to apply to other in vivo applications, and validate CS in an important cancer imaging application.