Scientific & Clinical Applications of New Biomedical Imaging Technologies
The ultimate goal of researchers at NYU Langone’s Department of Radiology is the improvement of human health. In clinical practice, doctors rely on imaging to accurately diagnose diseases and effectively guide therapies. In medical research, scientists depend on imaging to study basic phenomena and to evaluate the safety and efficacy of new treatments. Our researchers develop novel imaging technologies to advance medical science and clinical care in several areas.
We create and adapt novel imaging technologies to learn more about the brain and the neurological diseases that affect it. Investigators in our department develop advanced MR spectroscopy methods to study the earliest manifestations of Alzheimer’s disease, detect early-stage neurodegeneration in multiple sclerosis, and investigate the role of demyelination in a range of cognitive disorders. Our researchers combine MR spectroscopy with sodium MRI to better understand the metabolic damage that accompanies traumatic brain injury.
Through specialized methods like MRI oximetry, we study neurobiochemistry and stroke risk. We also develop methods to evaluate the damage caused by stroke. Our researchers use novel radiotracers and develop sophisticated radioligands for PET/MR imaging of the brain to investigate the role of cell receptors in amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig’s disease, and examine the mechanism and effects of Tau protein buildup, a phenomenon that accompanies many neurodegenerative conditions.
In preclinical research, we develop and use leading-edge diffusion MRI in combination with MR microscopy and computational neuroanatomy to investigate how genetic mutations and early brain injuries affect neural development. We are also making theoretical and technical advances to obtain cellular-level information about the brain’s micro-neuroanatomy in vivo through diffusion MRI.
We create new imaging methods and tools for the diagnosis, treatment, and study of muscle and joint conditions. Our scientists pioneered the application of artificial intelligence (AI) to MR image reconstruction, significantly accelerating MRI exams of the knee. We invented ultraflexible low-impedance MRI coils that open the door to noninvasive study of the biodynamics of the hand. We’ve also trained deep learning algorithms to predict which patients with early symptoms of osteoarthritis are likely to need total knee replacement within a decade of diagnosis.
Our department is currently developing a variety of sophisticated methods, such as diffusion MRI and MR fingerprinting, to obtain precise quantitative maps and biophysical measurements of articular cartilage. The technology has the potential to help guide hip and knee replacements, enable earlier diagnosis of degenerative joint disease, and facilitate the search for effective treatment of osteoarthritis.
Other areas of research include imaging methods to assess bone quality and predict fracture risk and patient responses to osteoporosis therapy. We also develop advanced MRI techniques, like diffusion tensor imaging, to investigate the biokinetics and physiology of muscle tissue with the aim of advancing knowledge and treatment of conditions such as dermatomyositis and diabetic neuropathy.
We develop leading-edge imaging methods to study cancer and guide oncologic therapies. Our researchers create AI algorithms that improve the accuracy of breast cancer detection from mammograms and design neural networks that learn from a combination of mammograms and clinical data in order to lower recall rates for mammography screening. We tailor specialized imaging methods, such as gradient–echo spectroscopic MRI, to aid in the search for new biomarkers of breast cancer. Our research teams also apply vanguard imaging technologies, such as metabolic sodium MRI, to assess early response of breast cancer to neoadjuvant chemotherapy.
Our team developed a method to obtain high-quality MRI of the liver in the presence of respiratory motion, eliminating the need to have patients hold their breath during imaging. The technique, called GRASP, makes small lesions easier to identify and is now clinically available worldwide. We are expanding this technology and adapting it to applications in abdominal and breast MRI.
We also apply sophisticated imaging methods like diffusion MRI to the study, diagnosis, and evaluation of prostate cancer, and create new, highly accurate ways of imaging white matter nerve bundles to provide precise information about where and how neuronal tracts adjoin brain tumors.
We develop new methods for imaging of the heart and the vasculature of muscles and organs to study cardiovascular diseases and advance treatment. Our team has invented an MRI technique called XD-GRASP that produces high-quality heart images from a continuous scan. Conventional cardiac imaging protocols rely on a battery of carefully calibrated acquisitions—an error-prone and time-consuming approach that is labor intensive for the technologists who are tasked with management of complex settings and burdensome for the patients who are repeatedly required to hold their breath.
Our XD-GRASP technique solves these problems and indexes the acquired MR signal in relation to the periodic beating of the heart and inflations of the lungs. The resulting image data can be sorted in reconstruction to “freeze” either kind of motion. The method allows scientists to study cardiac physiology and the relationship between breathing and heartbeat with unprecedented detail, especially in conditions with challenging cardiac dynamics like arrhythmia. Our scientists are combining this technique with sodium MRI to better understand how the heart handles one of its fundamental metabolites. The technology also applies to the imaging of other organs in which contrast-enhanced MRI can indicate pathology by tracing vasculature.
We are currently developing sodium MRI methods to investigate the metabolism of leg muscles. In particular, we use sodium imaging to study the relationship between exercise and microvascular dilation, oxidative stress, and biomolecules that promote the health of nerve cells. We do so to determine whether supervised exercise can reverse diabetic neuropathy. Our researchers also investigate how circulation in small vessels affects the brain in a condition known as small vessel disease.