• #32 - MEDICA & RSNA Special Issue • MedicalExpo e-Magazine

    November 30, 2017

    The e-Magazine About Medical Technology Innovation

    #32

    Artificial Intelligence in the Spotlight

    Pediatric Bone Challenge: Boning Up

    3D Printing Pioneer


    MEDICA & RSNA Special Issue




    This new edition explores two major medical trade shows that marked the end of the year: MEDICA, held in Düsseldorf from November 13-16, and the RSNA conference in Chicago from Nov 26-Dec 1.

    Artificial intelligence with ever more sophisticated algorithms was a key topic at both events. Another focus was the increased use of 3D printing in healthcare. We’re also offering you a taste of some of the most innovative products presented at the fairs, including a non-invasive treatment for benign tumors, a virtual reality massage chair and an easy-to-use blood test that indicates risks for stomach cancer.

     

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    AI can be trained to identify microcalcifications in the breast or small nodules in the lung.
    Artificial intelligence was a key topic at MEDICA and RSNA this year (iStock)

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    Artificial intelligence (AI) was a key topic at both MEDICA and the RSNA conference this year. But what are its applications in healthcare in general and radiology in particular? And what are the barriers? Dr. Michael Forsting, director of the Institute of Diagnostic and Interventional Radiology and Neuroradiology at...

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    These algorithms are becoming more and more sophisticated.
    Develop an algorithm for determining bone age from pediatric hand radiographs (Courtesy of RSNA)

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    The RSNA‘s most recent challenge highlights the potential of machine learning in radiology. The goal? To develop an algorithm for accurately determining bone age from pediatric hand radiographs.

     

    This year’s annual RSNA meeting focused on how artificial intelligence and machine learning (ML) can aid radiologists and other imaging professionals. In this context, the society’s high-profile Pediatric Bone Age Challenge ran from August to October under the auspices of the group’s Radiology Informatics Committee (RIC). Keenly contested, the challenge called on participants to develop an algorithm for accurately determining bone age using X-rays of children’s hands.

    The bone age of a child indicates the level of biological and skeletal maturity, and is typically used in the evaluation of endocrine and metabolic disorders.

    “The participating teams were judged by how well their algorithm-derived bone age evaluations matched the evaluations of expert human observers,” explained leading radiologist Dr. Adam Flanders, chairman of the RIC. “The results were both surprising and exciting.”

    Will Radiologists Follow the Dodo?

    The challenge’s top 20 algorithmic results surpassed the accuracy of all previous evaluations of this type.

    “We’re now talking accuracy to within one hundredth of one percent of the human evaluations.”

    “These algorithms are becoming more and more sophisticated,” said Flanders. “We’re now talking accuracy to within one hundredth of one percent of the human evaluations.” Such results make it clear that computer-aided radiological diagnosis will soon incorporate hugely complex and incredibly accurate ML algorithms. Some fear this could make radiologists obsolete.

    But Dr. Flanders believes such fears are unfounded. “This technology is not about replacing humans, but helping radiologists do their job more efficiently. ML-empowered devices could be hugely effective tools for precision medicine. By saving time and by allowing radiologists to focus on doing other things better, they could raise the bar for the entire discipline.”

    What You Can’t See…

    In fact, radiological algorithms simply compare image pixels. By doing so logically and mathematically, they can see things that are imperceptible to humans. “They can see trends, relationships that we might miss,” says Flanders.

    Algorithms may also help diagnose problems in parts of the world where there is no access to a radiologist. “Take the villages of sub-Saharan Africa,” says Flanders. “It is here that a reliable, portable, networked algorithm-based device could be used as a life-changing first step in diagnosis.”

    The challenge’s top 20 algorithmic results surpassed the accuracy of all previous evaluations of this type (Courtesy of RSNA)


    Banner GOSSEN METRAWAT
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    3D printed models bring human anatomy to life.
    Five-year-old Mia Gonzalez holds a 3D printed replica of her heart (Courtesy of Stratasys)

    Dr. Jonathan Morris, a diagnostic and interventional neuroradiologist, is co-director of the 3D printing laboratory at the world-renowned Mayo Clinic, and chairman of the 3D Printing Special Interest Group of the Radiological Society of North America (RSNA). We caught up with him to discuss the rise of 3D printing in...

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    CONTRIBUTORS



    Dimitri Dubuisson

    Journalist for 12 years, Dimitri Dubuisson is based in Brussels and covers mainly medical, health and social topics.


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    Hermine Donceel

    Hermine Donceel is a Brussels-based freelance journalist. She has lived in Southeast Asia for ten years, and has covered public health and environment, nutrition and climate change.


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    Michael Halpern

    Michael Halpern is a US-born and bred writer with experience in radio. He has lived in southern France for 15 years.


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    Daniel Allen

    Daniel Allen is a writer and a photographer.


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    Celia Sampol

    Celia Sampol is a journalist with 13 years of experience in Paris, Brussels and Washington. She’s now the editor-in-chief of MedicalExpo e-magazine.


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