Tag Archive for: radiology

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Federated learning: A solution to AI’s data-sharing challenges

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Federated learning can solve data-sharing challenges, allowing nimble collaboration across institutions to drive medical advances using artificial intelligence (AI).

Federated learning can solve data-sharing challenges, allowing nimble collaboration across institutions to drive medical advances using artificial intelligence (AI), according to a new manuscript from 10 thought leaders in AI and machine learning in medicine.

In Health Informatics Journal, these leading experts on how technology is shaping medicine shared a conversation that they had at the Radiology Society of North America’s conference. They weighed challenges facing AI, including barriers to data sharing because of privacy rules that prevent the distribution of information to different institutions. With federated learning, models are shared – rather than data – allowing institutions to aggregate information and collaborate with a master model.

“Federated learning offers tremendous promise,” said Marius George Linguraru, D.Phil., M.A., M.Sc., the Connor Family Professor of Research and Innovation, principal investigator at the Sheikh Zayed Institute of Pediatric Surgical Innovation and senior author on the manuscript. “As a community of experts, we have found that federated learning allows us to move away from the challenges of sharing data in central repositories. Instead, we share the models, which can be designed to protect privacy by limiting what’s shared outside of any given institution.”

A champion of pediatric health, Linguraru wants to ensure that children are represented in the development of models that advance science and medicine. “Sharing data is even more crucial when there are few patients, such as in rare diseases or pediatric populations,” he said. “In general, healthcare data suffers from inequitable representation in our public health systems and services.”

Learn more here about the challenges and potential solutions from experts at Rhino Health, Johns Hopkins University School of Medicine, NVIDIA, University of Cambridge, Ben-Gurion University Israel, MD Anderson Cancer Center, Dana-Farber Cancer Institute and Children’s National Hospital.

Hyperfine Swoop System

$1.6m grant to boost MRI access globally for maternal, child health

Researchers at Children’s National Hospital are investigating ways to bring more portable and accessible low-field magnetic resonance imaging (MRI) to parts of the world that lack access to this critical diagnostic tool, thanks to a grant from the Bill & Melinda Gates Foundation.

The nearly $1.6 million in funding will enable clinicians to better treat pediatric neurological conditions including ischemic brain injury, hydrocephalus, micro- and macrocephaly and more, using analysis tools that are designed to handle the loss in image quality and related challenges inherent to low-field MRI. The research brings together teams at Children’s National and Children’s Hospital Los Angeles — two organizations with extensive experience in designing processing software tools for pediatric brain MRI analysis and data enhancement.

The patient benefit

“For 30 years, MRI has primarily helped patients in high-income countries. Our team is thrilled by the prospect of expanding this powerful tool to patients coming from a wide range of nations, geographies and socioeconomic backgrounds,” said Marius George Linguraru, D.Phil., M.A., M.Sc., principal investigator at the Sheikh Zayed Institute for Pediatric Surgical Innovation (SZI). “Low-field MRI comes with great advantages including portability at the point of care of patients, lower clinical costs and the elimination of sedation for young children.”

Linguraru and his long-time collaborator, Natasha Lepore, Ph.D., principal investigator at The Saban Research Institute at Children’s Hospital Los Angeles, will analyze data from the brains of children from birth for the maternal and child health studies. The MRI data analyzed will form the basis for future studies of children’s brain anatomy in health and disease.

The big picture

Through the new grant, researchers will develop a suite of tools to help clinicians better analyze data and images from low-field MRI systems. These systems already have been integrated into interventional and observational studies to help characterize early neurodevelopmental patterns and identify drivers of abnormal development. They are also evaluating the efficacy of maternal and infant-focused interventions aimed at improving neurodevelopmental outcomes.

Why we’re excited

At Children’s National, SZI has installed a Hyperfine Swoop system, and Linguraru’s team is creating image enhancement tools tailored to the unique challenges of low-field MRI. Chief among them, conventional processing tools developed over the past several decades remain incompatible with the low-field data and require new software to take full advantage of the diagnostic power of imaging.

The work brings together a prestigious international consortium of scientists and clinicians from around the world to harness the power of computing and expand the reach of diagnostic imaging. Lepore said the team is eager to bring modern medical imaging to parts of the world that have missed its many benefits.

“Children’s brain development in underserved areas can be affected by so many factors, like malnutrition or anemia,” Lepore said. “The software we will design for the Hyperfine scanners will improve research into these factors, so the optimal interventions can be designed. We are excited to bring our expertise to this important and timely project.”

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How radiologists and data scientists can collaborate to advance AI in clinical practice

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The scientific community continues to debate AI’s possibility of outperforming humans in specific tasks. In the context of the machine’s performance versus the clinician, Linguraru et al. argue that the community must consider social, psychological and economic contexts in addition to the medical implications to answer this puzzling question.

In a special report published in Radiology: Artificial Intelligence, a Children’s National Hospital expert and other institutions discussed a shared multidisciplinary vision to develop radiologic and medical imaging techniques through advanced quantitative imaging biomarkers and artificial intelligence (AI).

“AI algorithms can construct, reconstruct and interpret radiologic images, but they also have the potential to guide the scanner and optimize its parameters,” said Marius George Linguraru, D.Phil., M.A., M.Sc., principal investigator in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National. “The acquisition and analysis of radiologic images is personalized, and radiologists and technologists adapt their approach to every patient based on their experience. AI can simplify this process and make it faster.”

The scientific community continues to debate AI’s possibility of outperforming humans in specific tasks. In the context of the machine’s performance versus the clinician, Linguraru et al. argue that the community must consider social, psychological and economic contexts in addition to the medical implications to answer this puzzling question.

Still, they believe that developing a useful radiologic AI system designed with the participation of radiologists could complement and possibly surpass human’s interpretation of the visuals.

Given AI’s potential applications, the authors encouraged radiologists to access many freely available resources to learn about machine learning, and radiomics to familiarize with basic concepts. Coursera, for example, can teach radiologists about convolutional neural networks and other techniques used by AI researchers.

Conversely, AI experts must reach out to radiologists and participate in public speaking events about their work. According to the researchers, during those engagement opportunities, clinicians understood the labor-saving benefits of automatic complex measurements on millions of images—something that they have been doing manually for years.

There are also hurdles around this quest of automation, which Linguraru et al. hope both fields can sort out by working together. A critical challenge that the experts mentioned was earning the trust of clinicians that are skeptical about the “black box” functionality of AI models, which makes it hard to understand and explain the behavior of a model.

Some questions, too, need answers on how to best leverage both human intelligence and AI by using human-in-the-loop where people train, tune, and test a particular algorithm, or AI in-the-loop where this different framing generates AI input and reflection in human systems.

“The key is to have a good scientific premise to adequately train and validate the algorithms and make them clinically useful. At that point, we can trust the box,” said Linguraru. “In radiology, we should focus on AI systems with radiologists in-the-loop, but also on training radiologists with AI in-the-loop, particularly as AI systems are getting smarter and learning to work better with radiologists.”

The experts also provided possible solutions to sharing large datasets, how to build datasets that allows robust investigations and how to improve the quality of a model that might be compared against human’s gold standard.

This special report is the second in a series of panel discussions hosted by the Radiological Society of North America and the Medical Image Computing and Computer Assisted Intervention Society. The discussion builds upon the first in the series “Machine Learning for Radiology from Challenges to Clinical Applications” that touched on how to incentivize annotators to participate in projects, the promotion of “team science” to address research questions and challenges, among other topics.

Gilbert Vezina

Gilbert Vezina, M.D., recognized with American Society of Pediatric Neuroradiology Gold Medal Award

Gilbert Vezina

Gilbert Vezina, M.D., Director of Neuroradiology in the Division of Diagnostic Imaging and Radiology at Children’s National Hospital, is being recognized at the 2020 American Society of Pediatric Neuroradiology 2nd Annual Meeting with the society’s most distinguished honor, the Gold Medal Award.

The American Society of Pediatric Neuroradiology (ASPNR) Gold Medal is awarded for both professional and personal excellence, honoring individuals who are superb pediatric neuroradiologists, scientists, and/or physicians, and mentors and who also are truly outstanding people. Recipients have consistently extended themselves beyond self-interest to make contributions to the field of pediatric neuroradiology and as such, have elevated the subspecialty. This medal recognizes the exceptional service and achievements of these individuals.

Dr. Vezina completed his undergraduate degree at the Collège Jean-de-Brébeuf, Montréal, Canada and medical school at McGill Medical School, Montréal, Canada. He completed a mixed internship at Montreal General Hospital, Montreal, Canada; residency in Diagnostic Radiology, Massachusetts General Hospital, Boston, Massachusetts followed by a fellowship in Neuroradiology, Boston, Massachusetts.

He began his career at Children’s National Hospital in 1990. He is currently the Director of the Neuroradiology Program at Children’s National Hospital and Professor of Radiology and Pediatrics at George Washington University School of Medicine and Health Sciences, Washington DC. He created the Neuroradiology Fellowship Program in 1993 where he impacted medical students, residents and fellows from around the world. He served as president of ASPNR from 2001-2002 and past President from 2002-2005. He also served as the Interim Chief, Diagnostic Imaging and Radiology at Children’s National for a brief period in 2017.

Congratulations, Dr. Vezina!

Dorothy Bulas

Dorothy Bulas, M.D., receives the Society for Pediatric Radiology’s highest honor

Dorothy Bulas

Dorothy Bulas, M.D. F.A.C.R., F.A.I.U.M., F.S.R.U., chief of diagnostic imaging and radiology in the Division of Diagnostic Imaging and Radiology at Children’s National Health System, is being recognized at the 2018 Society for Pediatric Radiology Annual Meeting with their most distinguished honor, the Gold Medal.

The Society of Pediatric Radiology (SPR) Gold Medal is awarded to pediatric radiologists who have contributed greatly to the SPR and their subspecialty of pediatric radiology as a scientist, teacher, personal mentor and leader.

Initially, Dr. Bulas completed her residency in pediatrics. During a pediatric radiology rotation at John Hopkins University, she realized how much she loved problem solving and using emerging imaging modalities and went on to complete her radiology residency at Albert Einstein Hospital. Soon after, Dr. Bulas moved to Washington, D.C. to complete a pediatric radiology fellowship at her professional home, Children’s National.

Since the completion of her fellowship, Dr. Bulas views her role in the advancement of fetal imaging as her most significant professional contribution. She has published 131 papers, one of her most recent as a co-author on “Neuroimaging findings in normocephalic infants with Zika virus” in Pediatric Neurology. Dr. Bulas is also a co-author of the textbook entitled Fundamental and Advanced Fetal Imaging and has authored 35 book chapters.

She has served as program director of the Radiology Fellowship Program at Children’s National since 2005 where she has impacted medical students, residents and fellows from the United States and abroad.

As a previous chair member for numerous organizations, Dr. Bulas currently co-chairs the American College of Radiology’s pediatric radiology education committee. She is a founding member of the Image Gently Alliance, where she chaired the outreach campaign to parents and wrote brochures, web material and articles. Dr. Bulas is also a founder of the World Federation of Pediatric Imaging.

Dr. Bulas was honored as an outstanding teacher with the Edward Singleton-Hooshang Taybi Award for Excellence in Education from the SPR and this past fall and as the Outstanding Educator in 2017 by the Radiological Society of North America.

Dorothy Bulas

Congratulations to Dorothy Bulas, M.D. – 2017 RSNA Outstanding Educator recipient

Dorothy Bulas

Dorothy Bulas, M.D., section head of ultrasound and fetal imaging at Children’s National Health System, was honored with the RSNA 2017 Outstanding Educator award at the Radiological Society of North America’s (RSNA) Annual Meeting, held November 26 – December 1 in Chicago, Illinois.

The winner of the award is selected annually by the RSNA Board of Directors based on the awardee’s significant contributions and long-term commitment – 15 years or more – to radiologic education.

“In addition to being a talented clinician and an accomplished researcher, Dr. Bulas is an extraordinary teacher who has made tireless contributions to the educational programs of RSNA,” said RSNA President Richard L. Ehman, M.D. “For more than three decades, she has been a passionate and effective advocate for improving pediatric radiology worldwide – especially in poorly served countries – by participating in educational outreach.”