Dr. Bader is an Assistant Professor in the Department of Radiology at the University of Chicago. His primary research focus is image-guidance and treatment monitoring for therapeutic ultrasound, in particular, histotripsy. Histotripsy is a novel form of therapeutic ultrasound that relies on the mechanical action of acoustic cavitation to liquefy tissue transcutaneously for ablation of prostate tumors and deep vein thrombi. Image-guidance techniques are necessary to monitor cavitation and the resultant tissue response as histotripsy transitions from pre-clinical studies and into clinic use. Dr. Bader is highly motivated to expedite the use of acoustic cavitation, or the oscillations of microbubbles induced by ultrasound, into clinical use for therapy and imaging.
Dr. Bucknor’s main research interest is centered on the development of oncological and musculoskeletal applications of an exciting new image-guided therapy: MR-guided Focused Ultrasound (MRgFUS, also known as HIFU). HIFU is a new non-invasive thermal ablation technique being developed for the treatment of bone and soft tissue tumors and more broadly as an adjunct to chemotherapy for advanced stage malignancies. As an NIH T32 research fellow during his final year of residency, Dr. Bucknor made a number of important discoveries regarding the importance of different HIFU technical parameters. His research has been published in high-impact peer-reviewed journals and he was also awarded the very prestigious Radiological Society of North America Trainee Research Prize. He now oversees the HIFU oncological interventions at UCSF including clinical trials of HIFU for treatment of bone metastases and osteoid osteomas.
Dr. Burris completed his residency and cardiothoracic fellowship training at University of California, San Francisco. Hi work included 17 scientific manuscripts, 9 of which were as first author in impactful journals, such as Radiology, Investigative Radiology and Academic Radiology, and a competitive RSNA Fellow Grant. Dr. Burris has received mentorship from NIH-funded clinical investigators and completed a year-long NIH funded Institutional Research Training Fellowship (T32) to refine his research skills through coursework in epidemiology, biostatistics, study design, research ethics and grant writing. He has presented his research at numerous national and international scientific meetings, and received Magna Cum Laude honors for the scientific merit of his oral presentation at the 2015 ISMRM Annual Meeting. Since arriving at the University of Michigan, he has developed strong interdisciplinary collaborations with faculty in the Departments of Cardiac Surgery, Cardiology, Biomedical Engineering and lnterventional Radiology.
Dr. Costa’s prostate-related research has resulted in high impact peer-reviewed publications in periodicals such as The Journal of Urology, RadioGraphics, and European Radiology. He was awarded the Lauterbur Award, the most prestigious MR-related award granted by the Society of Body Computed Tomography and Magnetic Resonance for his research on MRI of prostate cancer. Dr. Costa’s research is focused on prostate cancer imaging and includes developing new strategies to better diagnose this disease with the use of MR imaging, improving pretreatment detection and risk stratification.
Dr. Hsiao’s research Interests lie at the intersection of cutting- edge imaging research and pragmatic clinical problems that require immediate solutions. Currently, this includes 4D Flow MRI, an imaging technology that promises to be transformative for evaluating the structure of the heart, simplifying an MRI exam previously requiring 1-2 hours to perform to a much more efficient 10 minute exam. While a resident, fellow and early faculty at Stanford, Dr. Hsiao wrote prototype software, validated this over the course of several research papers, and jointly founded Arterys, to bring this product more broadly to market. A second major prong of his research is now applying Deep Learning to the clinical practice of Radiology: As reimbursements for medical imaging continue to decline, Radiology requires a transformative technology to maximally utilize machine learning and deep learning to more efficiently interpret medical imaging exams. To this end, Arterys recently received SlO(k) approval for its first Deep Learning application, which is the first FDA-approved cloud-based application of Deep Learning.
Dr. Huang’s current research centers on the development and translation of advanced diffusion MRI methods for probing tissue microstructure. She seeks to achieve in vivo histologic-level detail with micron-level resolution of neuronal and axonal structure. Dr. Huang has recently introduced a method known as TractCaliber MRI for estimating axonal size and packing density across white matter tracts throughout the living human brain.
Dr. Ippolito is a physician scientist trained in MR oncologic and molecular imaging. He has 17 years of research experience in the pathophysiology of neuroendocrine prostate cancer (NEPC), an aggressive cancer that is associated with castrate-resistant growth, metastasis, and shortened survival. His ultimate goal is to develop a laboratory research program that uses knowledge derived from mechanistic studies of cancer metabolism to develop a clinically-based workflow that integrates laboratory diagnostics, imaging, and therapeutics to eradicate cancer. Dr. Ippolito is working on merging advanced metabolomics techniques (i.e. mass spectrometry and NMR) with C-11 PET radiopharmaceuticals (and soon, hyperpolarized C-13 MRS) to identify the metabolic fates of key nutrients in cancer cells in vivo and understand how aggressive forms of prostate cancer survive therapy. In tandem, we are developing a translational imaging platform using clinical PET/MR merged with matrix assisted laser desorption ionization (MALDI) molecular imaging of histologic slide sections to identify prostate cancer with neuroendocrine features in treatment-naive patients. We anticipate that this technology will have the potential to identify therapeutic non-responder patients at initial diagnosis, which will be critical in active surveillance.
Dr Jonas is applying his skills in biophysics to the design and manufacture of microdevices that can be implanted into tumors via image-guided techniques. The devices are ‘loaded’ with more than 30 drugs that might be effective in treating the specific tumor. The device and surrounding tumor are later excised and a ‘personalized’ treatment regimen can begin.
One of the many translational research projects, for which Dr. King is the Principal Investigator, involves the use of CEUS in sentinel lymph node (SLN) detection in melanoma. His lab will be exploring the use of a special CEUS contrast agent, Sonazoid, which has the unique property of being taken up by cells of the reticu/oendothelial system (RES). Dr. King has published several peer-reviewed manuscripts focused on novel ultrasound applications and is a co-investigator on several funded ultrasound research projects in the Department of Radiology.
Dr. Lungren’s primary research interests are in applied artificial intelligence machine learning and clinical informatics big data science techniques in imaging clinical decision support and appropriate utilization tools with a focus on precision medicine integration at both the individual and the population health level. There are opportunities for breakthroughs in computer science to leverage radiology imaging and report data to allow for new patient-specific data-driven insights into medical imaging utilization and appropriateness criteria for point-of-care imaging recommendations.
As a neuroradiologist, Dr. Nickerson’s research interests focus on use of advanced MRI techniques for evaluation of the brain. He has published in the past on diffusion tensor imaging, tractography, susceptibility-weighted imaging, arterial spin labeling, and functional MRI. He is currently engaged in studies of multiple sclerosis using volumetric assessments as well as the emerging field of resting-state functional MRI where we hope to assess network connectivity changes in children who previously underwent general anesthesia within the first two years of life.
Several publications resulted from Dr. Penet’s Ph.D. thesis, including publications in PNAS, in Journal of Neurosciences, Journal of Clinical Investigation and in Journal of Biochemistry. Dr. Penet joined the Russell H. Morgan Department of Radiology and Radiological Science as a Postdoctoral Fellow in May 2006, immediately after completing her Ph.D. During her fellowship, she focused on combining magnetic resonance imaging and spectroscopy together with optical imaging and molecular analyses to study the tumor microenvironment and understand the role of hypoxia, vascularization, and metabolism in tumor progression and metastasis in an experimental model of prostate cancer. In 2009, Dr. Penet received a HERA Foundation Ovarian Cancer Outside-the-box (OSBl) Seed Grant to start focusing on ovarian cancer as her own independent research area to develop within the division. She was awarded the Honorable Tina Brozman Foundation Grant to develop imaging methods for early detection of ovarian cancer. Dr. Penet is now focusing on understanding the role of tumor-associated macrophages in the progression and formation of malignant ascites and metastases in ovarian cancer using multi-modality imaging.
Dr. Prevedello, a practicing CAQ Neuroradiologist, and a specialist in Medical Imaging Informatics (MIi) in Radiology, an area of imaging research with rapidly growing importance to the field. Most recently, Dr. Prevedello has led Wexner’s efforts in practical (e.g., image triaging for improved critical results detection) and advanced (e.g., processing of raw pre-reconstructed CT data for unique cancer characteristics) applications of machine learning/artificial intelligence.
Dr. Wang’s research involves using positron emission tomography (PET) to make “movies” of radiolabeled tracers or drugs moving through the human body. These movies can then be fed into new mathematical models to obtain critically important quantitative information on (1) how to diagnose, for example, cancer, heart and liver diseases, and (2) on how drugs act to treat these diseases. By developing advanced computational algorithms to exploit the most of the data we collect, imaging can be better, cheaper and more informative, and improve it’s efficacy in reducing the burden of disease. Dr. Wang is collaborating with investigators from the fields of Cardiology, Gastroenterology, Neuroscience, Surgery and Pathology to demonstrate the utility of his approaches. He has published 34 peer-reviewed journal or conference papers and 19 conference abstracts (a large number of these are first author). Dr. Wang is Pl on grants from the NIH, the American Heart Association, and the California Breast Cancer Research Program.
Dr. Yin’s research focuses on developing novel advanced MRI-based technology that is opening up new opportunities to noninvasively detect and monitor important disease processes in tissue. Her Ph.D. work was the project that resulted in the introduction of magnetic resonance elastography as a diagnostic tool for assessing liver fibrosis. She received an NIH R01 grant that is focused on developing more advanced methods that have the promise of providing an unprecedented level of detail about the status of abnormal processes at the tissue level, which could have an enormous benefit for patients with liver disease. This work involves understanding molecular mechanisms in cultured cells and mechanosensor principles underlying the effect of matrix the environment on cells — which is now understood to be an important contributor to the development of many diseases from fibrosis to cancer.