Abstract

Magnetic Resonance Elastography (MRE) has emerged as a powerful non-invasive modality to quantify tissue biomechanics, extending the clinical intuition of manual palpation into a quantitative, spatially resolved imaging biomarker. In this work, we present recent advances in gravitational transducer–based 3D MRE and demonstrate how full complex shear modulus measurements enable refined characterization of liver disease pathways, assessment of therapeutic response in oncology, and inference of underlying vascular architecture.

A robust gravitational MRE (gMRE) driver, based on an eccentric rotating mass, was developed to deliver stable, harmonic-free mechanical excitation with high efficiency. Following its translation from an EU Horizon 2020 research project into an FDA-approved clinical product, the technology enables reproducible whole-organ 3D MRE acquisitions integrated into standard clinical MRI workflows. Unlike conventional 2D MRE, which reports only the magnitude of the complex shear modulus |G*|, 3D MRE provides access to both stiffness and wave attenuation (phase angle), yielding enhanced sensitivity to microstructural changes.

In the liver, we show that 3D MRE identifies a pre-fibrotic biomechanical niche characterized by reduced shear wave attenuation despite only modest increases in stiffness, consistent with early collagen III deposition from activated hepatic stellate cells. This biomechanical signature precedes conventional fibrosis markers and correlates with biochemical tests and histology, enabling early detection of liver damage and identification of mechanical states associated with increased hepatocellular carcinoma (HCC) risk. Beyond hepatology, we demonstrate the value of MRE for early response assessment to neoadjuvant chemotherapy in breast cancer, where collagen remodeling following initial treatment cycles predicts therapeutic outcome with higher precision than current imaging standards.

Finally, leveraging wave dispersion induced by multiple scattering, we illustrate how macroscopic MRE measurements can probe microscopic vascular architecture, bridging several orders of magnitude in scale and opening new avenues for non-invasive characterization of tumor microenvironments and treatment response. Together, these results position advanced 3D MRE as a versatile, physics-informed biomarker platform for precision medicine across liver disease and oncology. 

Abstract

Abstract

Metabolic imaging technologies have the potential to transform the field of diagnostic radiology by offering novel insights into tissue function and disease. These technologies, including advanced MR spectroscopy, chemical exchange saturation transfer (CEST) MRI, and X nuclei imaging, enable non-invasive characterization of metabolic processes in vivo. This presentation will discuss recent advances in metabolic MR imaging, their clinical applications in diagnosing and monitoring diseases, and the challenges in translating these methods from research to practice. Highlights will include applications in neuro-oncology and neurodegenerative diseases. The role of new MR technologies, such as ultra-high field strength and high-performance gradient systems, will also be highlighted for their potential to further enhance metabolic imaging capabilities.

Bio

Daniel Paech, MD, PhD, MSc, is an Associate Professor of Radiology at Harvard Medical School and Medical Director of the Brigham Research Imaging Core and the Mass General Brigham (MGB) Ultra-High-Field MRI Center. He is a board-certified radiologist and neuroradiologist (diagnostic and neuro-interventional) and serves as attending neuroradiologist in the Division of Neuroradiology at MGB.

Dr. Paech’s research focuses on the development and clinical translation of novel imaging technologies, with a particular emphasis on ultra-high-field MRI. His expertise is in metabolic imaging, with applications in neuro-oncology, neurodegenerative disease, and ischemic stroke.

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Abstract

Developing artificial intelligence (AI) schemes to assist the clinician towards enabling precision medicine approaches requires development of objective markers that are predictive of disease response to treatment or prognostic of longer-term patient survival. The solutions being developed in my group in this regard involve designing computational imaging features together with histology or molecular data for detailed tissue and disease characterization in vivo as well be associated with patient outcomes. The key innovation in this approach lies in “handcrafting” unique tools that can capture biologically relevant and clinically intuitive measurements from routinely acquired imaging (MRI, CT, PET) or digitized images of tissue specimens. Further, by conducting cross-scale associations between imaging, pathology, and -omics, we can not only “unlock” and integrate the information captured by these different, disparate data modalities but also develop an interpretable and intuitive understanding of what drives their performance. Specific problems addressed via the new computerized imaging markers we have developed include: (a) predicting response to treatment to identify optimal therapeutic pathways, as well as (b) evaluating therapeutic response to guide follow-up procedures. We will further examine how to account for differences between sites, scanners, and acquisition parameters to ensure generalizable performance of AI tools and computational imaging features; crucial for wider clinical translation and widespread adoption. These will be discussed in the context of clinical applications in colorectal and renal cancers, digestive diseases, as well as pediatric conditions.

Bio

Dr. Viswanath is an Associate Professor in the Departments of Pediatrics and Biomedical Engineering at Emory University, since Fall 2025. He is also a Research Scientist & Biomedical Engineer at the Cleveland VA Medical Center. Previously, he was an Associate Professor of Biomedical Engineering at Case Western Reserve University. The primary focus of his research has been developing new artificial intelligence (AI) approaches including image analytics, radiomics, and machine learning schemes; applied to problems in computer-aided diagnosis & detection, disease characterization, as well as quantitative evaluation of response to treatment; in gastrointestinal cancers and digestive diseases. He has authored over 55 peer-reviewed journal publications, over 120 conference papers & abstracts, 1 book chapter, as well as delivered over 90 invited talks and panel discussions both in the US and abroad. He has 10 issued patents in the areas of medical image analysis, computer-aided diagnosis, and pattern recognition. Dr. Viswanath is an Associate Editor or Editorial Board Member for 9 leading international peer-reviewed journals, serves as Program Committee Member or Area Chair for 3 major medical imaging conferences, and has been elected to Senior Member in the National Academy of Inventors, the IEEE, and the SPIE. He has been selected for the Fulbright Specialist Award, in addition to multiple awards from SIIM, SPIE, and Crain’s Cleveland Business. His lab’s research has been funded since 2016 through the DOD/CDMRP, the NIH (NCI, NIBIB, NINR, NHLBI), the VA, and the State of Ohio.

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Abstract

The glymphatic system is increasingly recognized as a critical pathway for brain waste clearance, with implications for aging and neurodegenerative diseases. However, imaging glymphatic function in humans remains a major challenge due to the system’s complex, multiscale dynamics. In this talk, I will present a multimodal imaging approach using PET and MRI to achieve a more comprehensive and clinically translatable assessment of glymphatic function. 

I will review the limitations of current MRI-based methods—including phase-contrast MRI, DWI, and DTI-ALPS—which primarily infer fluid motion indirectly and often lack sensitivity to the slow and heterogeneous flow patterns characteristic of glymphatic transport. In contrast, PET imaging enables direct quantification of solute clearance over time, offering a complementary view of net mass transport. I will highlight recent work using dynamic 18F-FDG PET to quantify ventricular CSF clearance and demonstrate its sensitivity to age-related decline, test–retest reliability, and independence from brain metabolism.

Bio

Dr. Chuan Huang is an Associate Professor of Radiology and Imaging Sciences and the Director of PET-MRI Research at Emory University School of Medicine. He was named a Distinguished Investigator by the Academy for Radiology & Biomedical Imaging Research in 2023.

Dr. Huang’s research focuses on PET/MR neuroimaging and its broader clinical and translational applications. He has authored over 70 peer-reviewed publications and holds three patents. Prior to joining Emory in November 2022, he was a tenured Associate Professor of Radiology and Psychiatry at the State University of New York at Stony Brook. He completed his postdoctoral training at Massachusetts General Hospital and Harvard Medical School in 2014, where he was subsequently promoted to Instructor.

He previously served as Chair of the ISMRM PET/MR Study Group and was a member of the organizing committee for the 2023 SNMMI–ISMRM co-sponsored PET/MR Workshop. He currently serves on the committee of the ISMRM MR in Psychiatry Study Group.

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Abstract

All MRI scanners must have an RF coil or array for transmitting/receiving the RF signal during imaging regardless of field strength or magnet design. In this talk, we will explore the next generation of multi-purpose integrated RF/wireless (iRFW) coil designs, which can perform simultaneous MR signal reception and wireless data transfer by allowing RF currents at the Larmor frequency and in a wireless communication band(s) to flow on the same conductor. These coils can wirelessly transmit MRI images, enable wireless MRI clock synchronization via Global Navigation Satellite System (GNSS) signals from satellite atomic clocks, and support wireless ultrasound-based respiratory monitoring from within the bore to the scanner console or cloud. In low-field applications, the iRFW coil design, termed an iRFW-Cellular coil design, can further enable wireless data transmission of image data over cellular or satellite networks while imaging. In total, the RF coil array is not only essential for imaging but a natural data hub for wirelessly moving data out of the scanner bore.

Bio

Dr. Darnell earned his PhD in physics in 2005 and spent eight years at Apple Inc. designing antenna systems for multiple iPhone generations. Since joining Duke University’s Brain Imaging and Analysis Center in 2013, his research has focused on novel RF coil technologies for MRI, including wireless coil designs, MR-compliant in-bore computing, and wireless transmission for portable low-field MRI. His current funded projects include developing a flexible wireless coil array for neonatal imaging and a cloud based, platform independent wireless MRI system.

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Abstract

The use of wearable electronic devices that can acquire vital signs from the human body noninvasively and continuously is a significant trend for healthcare. The combination of materials design and advanced microfabrication techniques enables the integration of various components and devices onto a wearable platform, resulting in functional systems with minimal limitations on the human body. Physiological signals from deep tissues are particularly valuable as they have a stronger and faster correlation with the internal events within the body compared to signals obtained from the surface of the skin. In this presentation, I will demonstrate a soft ultrasonic technology that can noninvasively and continuously acquire dynamic information about deep tissues and central organs. I will also showcase examples of this technology’s use in recording blood pressure and flow waveforms in central vessels, monitoring cardiac chamber activities, and measuring core body temperatures. The soft ultrasonic technology presented represents a platform with vast potential for applications in consumer electronics, defense medicine, and clinical practices.

Bio

Dr. Sheng Xu is a Professor and Jacobs Faculty Scholar at UC San Diego. He earned his B.S. degree in Chemistry from Peking University and his Ph.D. in Materials Science and Engineering from the Georgia Institute of Technology. Subsequently, he pursued postdoctoral studies at the Materials Research Laboratory at the University of Illinois at Urbana-Champaign. His research group is interested in developing new materials and fabrication methods for soft electronics, with a particular focus on wearable ultrasound technology. His research has been presented to the United States Congress as a testimony to the importance and impact of funding from the National Institutes of Health. He has received numerous honors, including the NIH Maximizing Investigators’ Research Award, NIH Trailblazer Award, Sloan Fellowship, IEEE EMBS Technical Achievement Award, ETH Zürich Materials Research Prize for Young Investigators, MRS Outstanding Early Career Investigator Award, and a finalist of the Blavatnik National Awards for Young Scientists. He is a Fellow of AIMBE and IEEE.

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Abstract

Multifunctional sensing capability, ‘unusual’ formats with flexible/stretchable designs, lightweight construction, and self-powered operation are desired attributes for electronics that directly interface with the human body. Today’s electronics are stiffer by up to six orders of magnitude compared to soft tissue. Thus, present systems limit intimate integration with biology. I have focused on novel microfabrication techniques and tricks to use active piezoelectric materials and required electronic components, which have the shape and the mechanical properties that match with those of human tissues, in order to allow intimate integration without any irritation and/or harm to the body.

In this talk, I describe novel materials, mechanics and device designs for emerging classes of wearable health monitoring systems and implantable, minimally invasive medical devices. These include a variety of electrodes, sensors, and energy harvesting components, with promising applications in bio-integrated electronics, such as self-powered cardiac pacemakers, wearable blood pressure sensors, modulus sensor patches, and brain injectrodes. The devices can be twisted, folded, stretched/flexed and wrapped onto curvilinear surfaces or implanted without damage or significant alteration in operation. The fabrication strategies and design concepts can be applied to various biological substrates and geometries of interest, and thus have the potential to broadly bridge the gap that exists between rigid, boxy electronics and soft, curvy biology.

Bio

Canan Dagdeviren is an Associate Professor at MIT Media Lab, where she leads the Conformable Decoders research group. The group aims to convert the patterns of nature and the human body into beneficial signals and energy.

Dagdeviren earned her Ph.D. in Materials Science and Engineering from the University of Illinois at Urbana-Champaign, where she focused on exploring patterning techniques and creating piezoelectric biomedical systems. Her collective Ph.D. research involved flexible mechanical energy harvesters, multi-functional cardiac vessel stents, wearable blood pressure sensors, and stretchable skin modulus sensing bio-patches.

As a Junior Fellow of the Society of Fellows at Harvard University, she conducted her postdoctoral research at the MIT David H. Koch Institute for Integrative Cancer Research. Here, she designed and fabricated multi-functional, minimally invasive brain probes that can simultaneously deliver drugs on demand and electrically modulate neural activity precisely and selectively for the treatment of neurological disorders, such as Parkinson’s disease.

Dagdeviren’s work has been featured in many media outlets, including TIME, Washington Post, Smithsonian Magazine, Popular Mechanics, CBS News, BBC News and Physics World. In 2015, MIT Technology Review named her among the “Top 35 Innovators Under 35” and Forbes selected her as one of the “Top 30 Under 30 in Science”. Recently, Dagdeviren has been named as a Spotlight Health Scholar by Aspen Institute and World #1 in Medical Innovation Category of Ten Outstanding Young Persons of the World (TOYP) by Junior Chamber International. In 2016, Dr. Dagdeviren was awarded the Science&Sci Life Prize for Young Scientists in Translational Medicine Category and invited to attend Nobel Prize Ceremony in Stockholm, Sweden. Dr. Dagdeviren has been named as 2017 Innovation and Technology Delegate by the American Academy of Achievement. In 2019 Dr. Dagdeviren was among 87 of the nation’s brightest young engineers who have been selected to take part in the National Academy of Engineering’s (NAE) 25th annual U.S. Frontiers of Engineering (USFOE) symposium, hosted by Boeing in Charleston, South Carolina. Dagdeviren also named the BBC’s Top 100 Women List in 2023

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Abstract

Chronic inflammation and immune dysfunction have emerged as key factors in the pathogenesis of neurological disorders such as Alzheimer’s disease (AD). Non-invasive molecular imaging has the potential to reveal valuable insights into the complex neuroimmune interactions associated with neurodegeneration and injury. Here, we will summarize current and emerging biomarkers for positron emission tomography (PET) imaging of inflammation from cellular and functional specificity to radiotracer development and application.

Bio

Dr. Chaney is an assistant professor at Mallinckrodt Institute of Radiology (MIR) at Washington University in St. Louis. Her research is focused on the development and translation of novel non-invasive molecular imaging strategies to elucidate the inflammatory component of devastating neurological diseases. In particular, she is interested in the relationship between peripheral and central nervous system innate immune responses, and how this crosstalk affects disease development and progression. Dr. Chaney previously worked at Stanford University as a postdoctoral fellow and instructor in the radiology department. She earned her doctorate in neurosciences from the University of Manchester in the United Kingdom.

Abstract

Magnetic resonance imaging has been widely utilised to investigate physiological functions, including functional brain imaging, microvascular dynamics, molecular imaging, etc. In this talk, we introduce rapid high-resolution dynamic MRI exploiting both general spatiotemporal and domain-specific priors for dynamic contrast-enhanced imaging and chemical exchange saturation transfer imaging. Subsequently, we show utilities of these developed techniques on brain cancer and Alzheimer’s Disease.

Bio

Dr. Park is a professor in the Department of Biomedical Engineering at Sungkyunkwan University in the Republic of Korea, where he leads research at the intersection of MR imaging physics, signal processing, and machine learning for brain and cardiac applications. He currently serves as Director of the Brain Korea 21 Project on Intelligent Precision Healthcare Convergence.

Dr. Park brings extensive academic and industry experience, having previously held faculty positions at Korea University and Yonsei University, as well as a research role at Siemens Medical Solutions in Germany. He is Editor-in-Chief of Investigative MRI and serves on the editorial board of the Korean Journal of Radiology. A long-standing member of ISMRM and KSMRM, he has contributed as an ad hoc reviewer for numerous leading journals in the field of medical imaging.

He earned his Ph.D. in Biomedical Engineering from Northwestern University under the mentorship of Dr. Debiao Li.

Recording not available.

Abstract

Modeling human physiology, development, and disease in vitro is currently accomplished with iPSC derived spheroids and organ-on-chip devices. However, these are limited in that organ-on-chip systems lack important cellular diversity and microphysiology, and spheroids do not capture the tube-like geometry that is essential for most organ functions and multi-organ connectivity. To address the need for more accurate human organ models, we are developing a micro-organ-on-chip system in which iPSCs are seeded into a microfluidic chip and differentiated into tube-shaped organoids in situ, in a system that is guided, but not restricted, by the microfluidic geometry. Starting with the cardiovascular system as a proof of concept, this platform has the potential to simultaneously capture cellular diversity, microphysiology, organ function, and multi-organ connectivity. Custom robotic systems were also developed to control both the seeding and monitoring processes, achieving a controllable variety of micro-organ geometries. As natural organ development leverages continuous feedback from neighboring organ systems, our current engineering efforts are to shift our automation method to deep reinforcement learning, in order to increase the repeatability and throughput of the system via real-time feedback control of organ differentiation.

Bio

David Sachs, PhD, is an Assistant Professor of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai. He is developing a new micro-organ model of the human cardiovascular system,  grown from stem cells inside a microfluidic chip, under the control of a custom robotic platform. The chip will be used to study heart disease and development, including cardiovascular stiffening diseases due to microgravity, and is currently scheduled to launch to the International Space Station in March of 2025. Recent funding will expand the chip with the addition of a liver micro-organ, moving toward the longer term goal of AI guided manufacturing of a comprehensive human micro-organ-on-chip system designed to be readily accessible to a diversity of collaborators. Prior to his work at Mount Sinai, he led the Advanced Application Development group at the MEMS semiconductor startup InvenSense, including the algorithm and digital architecture design of motion sensing devices that have been distributed in billions of units. He has undergraduate degrees in physics and piano performance, a master’s degree from the MIT Media Lab, and a PhD in Biomedical Sciences from Mount Sinai.

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