Director, Canon Stroke & Vascular Research Center
Associate Professor of Neurosurgery
Associate Professor of Radiology
Dr. Adnan Siddiqui, MD, PhD, is a Professor of Neurosurgery and Radiology who joined UBNS in January 2007. He completed fellowship training in Interventional Neuroradiology, Cerebrovascular Surgery and Neurocritical Care from Thomas Jefferson University in Philadelphia. Dr. Siddiqui has special interest and expertise in the performance of complementary microsurgical, radiosurgical and endovascular techniques for the comprehensive management of cerebrovascular conditions. This spectrum of disease includes aneurysms and arteriovenous malformations, as well as dural, cavernous and spinal fistulae.
Assistant Professor of Neurosurgery
Dr. Jason Davies is an Assistant Professor of Neurosurgery and Biomedical Informatics
at the State University of New York (SUNY) at Buffalo, where he joined the department in 2016. His active research interests focus on using bioinformatics tools to advance personalized
medicine. He is working to develop of bioinformatics tools to improve the quantity and quality of data available for medical research, and to lower barriers to entry for all clinicians to contribute to medical knowledge. Furthermore, he is working to bring to bear more advanced machine learning and data analytic methods to
better understand the insights contained within these rich data resources.
Assistant Professor of Neurosurgery
Dr. Snyder joined UBNS in 2011 after completing his fellowship training in endovascular
neurosurgery with UB Neurosurgery and spent 6 months as a research fellow at the Barrow Neurological Institute under Dr. Robert Spetzler. He completed his neurosurgical residency at UB and received his PhD in biophysics under the guidance of Dr. Frederick Sachs specializing in mechanoelectric transduction of cellular membranes. Active research interests include use of CT Perfusion (CTP) for acute stroke management, application of perfusion imaging to on table angiography, glasses free 3D imaging in both the operating room and endovascular suite, as well as basic science research on the role of mechanosensitive ion channels in both in aneurysm formation and vasospasm.
Co-Director, Imaging Division
SUNY Distinguished Professor;
Director, Division of Radiation Physics
Education and research in medical imaging have been Dr. Rudin’s main interests during his rich career at CSVRC. His research pursuits have primarily involved the development of improved medical imaging methods to increase resolution and lower dose. His projects to develop high spatial resolution detectors that allow for better guidance and treatments during minimally invasive endovascular procedures have culminated in systems that are now in clinics world-wide. Current work is focused on high speed image development.
Department of Radiology
A specialist in radiological imaging physics and radiation safety, Dr. Bednarek is board certified in Diagnostic, Therapeutic and Medical Nuclear Physics by the American Board of Radiology. His research focus is on region-of-interest imaging including development and evaluation of limited-field-of-view, high resolution and, recently, high-speed imaging detectors with specific application to neuroimaging. Recent work has focused on methods for determination of patient and staff radiation dose and development of a real-time dose-tracking system (DTS) for interventional fluoroscopic procedures that culminated in a licensed, FDA approved product with worldwide distribution.
Co-Director, Engineering Division
Assistant Professor, Biomedical Engineering
Within the scientific community, Dr. Ionita has become deeply involved with the effort to implement the new advances of 3D printing into a clinical setting. Using his experience in CT reconstruction algorithms and 3D data analysis, he has developed a complex 3D printed vascular patient specific phantom, based on 3D imaging. Current work includes development of a DICOM standard associated with the workflow and manufacturing of 3D printed medical objects, developing implantable devices, and improving printed models by creating digital structures capable of simulating vascular tissue.
Dr. Nagesh’s current work focuses on further improving quality of treatment by
proving superior imaging solutions are possible at lower x-ray doses. By using his novel artificial intelligence based image processing techniques, image quality can actually be restored in lower dose images. These images can then be
used during interventions without compromising the safety of the procedure. Additionally, Dr. Nagesh collaborates closely with Dr. Rudin on the development of the new, 1,000 frames per second, high speed angiography project to image blood flow patterns in real time during interventions. The resulting flow pattern details provide critical information that aid in treatment of a variety of diseases and offer never before seen views into treatment outcome.
There are several ongoing projects in Dr. Tutino’s lab that are focused on addressing
clinical challenges related to acute ischemic stroke. Using advanced 3D analysis software and deep learning, he is automatically analyzing patient CT imaging, and coupling it with histology to create better tools for physicians to diagnose
and treat strokes. He is also using cutting-edge molecular techniques to develop biomarkers of stroke pathogenesis and outcomes based on RNA expression profiles in patients’ blood and thrombotic tissue. Furthermore, in collaboration
with other mechanical engineers, he is leading an effort to numerically model stroke treatments in order to enable in silico treatment planning
and device development/prototyping and testing.
Currently, Dr. Rajabzadeh-Oghaz’s primary research focus is on understanding the rupture mechanism of intracranial aneurysms. In particular, he is exploring the underlying mechanism behind vessel wall enhancement and inflammation and its association with aneurysm natural history and rupture, using a combination
of imaging, histology, and computational analysis of biological data derived from human subjects and rodent models. He is also active in transitional/clinical research, in particular, establishing the clinical utility of modeling tools, primarily computational fluid dynamics, as an adjunct in guiding the management of a
variety of vascular diseases.
Dr. Pinter leads the neuroimaging research program at the Dent Neurologic Institute
with the goal of promoting the clinical adaptation of advanced imaging techniques
and fostering clinically focused product development in radiology and now
joins his expertise with the CSVRC MRI group. Dr. Pinter’s primary area of practice is diagnostic neuroradiology, focusing on
speed, reproducibility, and accuracy. His collaborations with Drs. Zhang and Ying
round out a dynamic MRI research group within CSVRC, encompassing software,
hardware, and clinical expertise that not only provides comprehensive solutions to
current MRI challenges, but also envisions the future of MRI.
Dr. Ying is currently a full professor of Biomedical Engineering and Electrical
Engineering at the University at Buffalo and an expert and technical leader in
the field of biomedical imaging. Her research interests include magnetic resonance imaging, compressed
sensing, image reconstruction, and machine learning. Dr. Ying has been well recognized as one of the pioneers in compressed
sensing MRI, which has recently been approved by FDA and will be the future in
routine clinical MRI scans. More recently, she published the first paper on deep
learning for MR image reconstruction, which opened up a completely new field
in MRI. The paper has received more than 100 citations in two years.
SUNY Empire Innovation Professor of
Dr. Zhang is currently the SUNY Empire Innovation Professor in the De-partment of Biomedical Engineering at University at Buffalo. Dr. Zhang is a pioneer and has made tremendous contributions in the development of the early ultrahigh field whole-body MR imaging instrumentation, a highly sensitive imaging tool for better delineating morphology, function, and metabolism of living systems non-invasively. He, as one of the key researchers, participated in the development of world’s first 8-Tesla (8T) whole body MR system and also the world’s first 7-Tesla (7T) whole body MR system. In the past 10 years, Dr. Zhang’s MR research has expanded to the technical development and clinical translation of hyperpolarized C-13 metabolic imaging and interventional neurovascular MR imaging.
Liza joined CSVRC in 2009 as a Research Associate with the role of supporting in vivo research and general laboratory management. By 2014, she completed her graduate studies in Neuroscience, which rounded out her prior training in Veterinary Technology, Biology, and previous experience in cancer research and rodent models to uniquely equip her for a supportive role in the lab.
Liza has experience in a wide range of both in vivo and in vitro models and is very passionate about supporting and improving the Center’s research. She has facilitated the variety of industry and internal projects that enter the lab, determining needs, addressing complications, and fostering communication between surgeons, staff, students, and collaborators.
In 2018, Liza became CSVRC’s Laboratory Director, and as such has assisted in the growth and development of the Center under Dr. Siddiqui’s leadership.
Carmon graduated from Michigan State University with a bachelor’s degree in Veterinary Technology. She has held a license in veterinary technology since 2004, became a Registered Laboratory Animal Technician in 2018 and completed a certificate in Clinical Trials Design and Management in 2020. Carmon is dedicated to research and expanding the goals of CSVRC. Her interests are in surgery and nursing care of laboratory animals, data organization, and laboratory management.
Carmon previously worked with ovine models of transition at birth, in the Department of Pediatrics, before joining CSVRC in March of 2020. She played a major role in implementing Good Laboratory Practice guidelines for pre-clinical studies conducted at the Center and works to maintain compliance.
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