MRI methods to evaluate diffuse hepatic diseases have advanced substantially in recent years, with a particular focus on chemical shift encoded (CSE)-MRI. However, the systematic evaluation of these methods requires the development of highly controlled quantitative imaging test objects ("phantoms"). In addition, CSE-MRI methods face major limitations, particularly their high sensitivity to physiological motion, and challenges in measuring parameters such as magnetic susceptibility (an emerging biomarker for tissue iron deposition). In this thesis, technical developments are introduced to address these challenges in both quantitative imaging phantoms and quantitative liver MRI methods. Novel quantitative MRI phantoms were designed and developed to mimic the simultaneous presence of fat, iron, and fibrosis in the liver by controlling different MR biomarkers while mimicking in vivo liver signals. An MRI and CT compatible fat phantom was developed and evaluated in a round-robin multi-center multi-vendor study. Motion-robust free breathing 2D sequential CSE-MRI method with flip angle modulation (FAM) and centric encoding approach was developed to achieve high SNR performance and minimal T1 bias simultaneously for liver fat and iron quantification. To further boost SNR performance, motion-corrected averaging method was combined with FAM CSE-MRI. Finally, a recently proposed liver quantitative susceptibility mapping (QSM) method was evaluated across iron levels and acquisition protocols at 1.5T and 3.0T, using superconducting quantum interference device (SQUID) liver susceptometry as the reference. Overall, these developments in this thesis have advanced MRI of the liver towards becoming a truly quantitative imaging modality.

MRI methods to evaluate diffuse hepatic diseases have advanced substantially in recent years, with a particular focus on chemical shift encoded (CSE)-MRI. However, the systematic evaluation of these methods requires the development of highly controlled quantitative imaging test objects ("phantoms"). In addition, CSE-MRI methods face major limitations, particularly their high sensitivity to physiological motion, and challenges in measuring parameters such as magnetic susceptibility (an emerging biomarker for tissue iron deposition). In this thesis, technical developments are introduced to address these challenges in both quantitative imaging phantoms and quantitative liver MRI methods. Novel quantitative MRI phantoms were designed and developed to mimic the simultaneous presence of fat, iron, and fibrosis in the liver by controlling different MR biomarkers while mimicking in vivo liver signals. An MRI and CT compatible fat phantom was developed and evaluated in a round-robin multi-center multi-vendor study. Motion-robust free breathing 2D sequential CSE-MRI method with flip angle modulation (FAM) and centric encoding approach was developed to achieve high SNR performance and minimal T1 bias simultaneously for liver fat and iron quantification. To further boost SNR performance, motion-corrected averaging method was combined with FAM CSE-MRI. Finally, a recently proposed liver quantitative susceptibility mapping (QSM) method was evaluated across iron levels and acquisition protocols at 1.5T and 3.0T, using superconducting quantum interference device (SQUID) liver susceptometry as the reference. Overall, these developments in this thesis have advanced MRI of the liver towards becoming a truly quantitative imaging modality.

Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

The World Health Organization stated that approximately two-thirds of the world’s population lacks adequate access to medical imaging. The scarcity of imaging services in developing regions contributes to a widening disparity of health care and limits global public health programs that require imaging. Radiology is an important component of many global health programs, including those that address tuberculosis, AIDS-related disease, trauma, occupational and environmental exposures, breast cancer screening, and maternal-infant health care. There is a growing need for medical imaging in global health efforts and humanitarian outreach, particularly as an increasing number of academic, government, and non-governmental organizations expand delivery of health care to disadvantaged people worldwide. To systematically deploy clinical imaging services to low-resource settings requires contributions from a variety of disciplines such as clinical radiology, epidemiology, public health, finance, radiation physics, information technology, engineering, and others. This book will review critical concepts for those interested in managing, establishing, or participating in a medical imaging program for resource-limited environments and diverse cross-cultural contexts undergoing imaging technology adaptation.

Each year more than 180,000 new cases of breast cancer are diagnosed in women in the U.S. If cancer is detected when small and local, treatment options are less dangerous, intrusive, and costly-and more likely to lead to a cure. Yet those simple facts belie the complexity of developing and disseminating acceptable techniques for breast cancer diagnosis. Even the most exciting new technologies remain clouded with uncertainty. Mammography and Beyond provides a comprehensive and up-to-date perspective on the state of breast cancer screening and diagnosis and recommends steps for developing the most reliable breast cancer detection methods possible. This book reviews the dramatic expansion of breast cancer awareness and screening, examining the capabilities and limitations of current and emerging technologies for breast cancer detection and their effectiveness at actually reducing deaths. The committee discusses issues including national policy toward breast cancer detection, roles of public and private agencies, problems in determining the success of a technique, availability of detection methods to specific populations of women, women's experience during the detection process, cost-benefit analyses, and more. Examining current practices and specifying research and other needs, Mammography and Beyond will be an indispensable resource to policy makers, public health officials, medical practitioners, researchers, women's health advocates, and concerned women and their families.

Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

This book describes the basics, the challenges and the limitations of state of the art brain tumor imaging and examines in detail its impact on diagnosis and treatment monitoring. It opens with an introduction to the clinically relevant physical principles of brain imaging. Since MR methodology plays a crucial role in brain imaging, the fundamental aspects of MR spectroscopy, MR perfusion and diffusion-weighted MR methods are described, focusing on the specific demands of brain tumor imaging. The potential and the limits of new imaging methodology are carefully addressed and compared to conventional MR imaging. In the main part of the book, the most important imaging criteria for the differential diagnosis of solid and necrotic brain tumors are delineated and illustrated in examples. A closing section is devoted to the use of MR methods for the monitoring of brain tumor therapy. The book is intended for radiologists, neurologists, neurosurgeons, oncologists and other scientists in the biomedical field with an interest in neuro-oncology.