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The Digital Mammography DREAM Challenge

September 7, 2016

The Digital Mammography DREAM Challenge

_pressrelease_DMChallenge$1.2 M Digital Mammography Challenge Aims to Improve the Accuracy of Mammograms

Contest aims to crowd-source machine learning algorithms to help reduce the false positive mammography rate

SEATTLE, WA – September 7, 2016 – A coalition of oncology and technology partners led by Sage Bionetworks and DREAM Challenges today announced the opening of the training phase for the Digital Mammography DREAM Challenge, an open-science data competition designed to improve the accuracy of mammography screening. With funding from Laura and John Arnold foundation (LJAF), the Challenge will award up to $1.2 million to data scientists, researchers, and coding experts who develop predictive algorithms that achieve milestone goals related to reducing the recall rate of mammography screening. Interested participants can sign up at https://www.synapse.org/Digital_Mammography_DREAM_Challenge.

The coalition supporting the Challenge as organizers, sponsors, partners and advisors from the health, tech, regulatory and for-profit competition sectors includes: Amazon Web Services (AWS), FDA, Group Health Cooperative, IBM, Icahn School of Medicine at Mount Sinai, Innocentive, NCI, Radish Medical, and Seattle Cancer Care Alliance.

Each year, more than 40 million women in the United States undergo routine mammogram testing to screen for breast cancer. Mammograms are widely considered to be the most accessible and cost-effective breast cancer screening method. However, the United States Preventive Services Task Force and the American Cancer Society recently issued changes to recommendations regarding start age and frequency of screening. These changes are due, in part, to the large number of false-positive mammograms. One in 10 women undergoing screening mammography are recalled for diagnostic workup, of which fewer than 5 percent will eventually be found to have cancer. Recalled patients often experience stress and additional medical costs, and some require interventions including unnecessary biopsies.

The Digital Mammography DREAM Challenge, running from June 2016 through mid-2017, will seek to attract data experts from both inside and outside the medical field to develop predictive algorithms that will reduce false-positive mammograms while maintaining or improving cancer detection. Participants will be asked to create algorithms that will help doctors determine whether a patient’s mammogram has a high or low likelihood of harboring a breast cancer, and whether or not a patient should undergo additional testing. New algorithms may allow doctors to customize screening regimens for patients and identify women who would benefit from more or less frequent screening.

“Our goal is for the Challenge to demonstrate that we can extract more information from mammograms than what meets the eye. Now that we are in an age where machines can train and learn how to recognize images, there is the possibility that machines can learn to recognize cancer-specific pixelated patterns in a digital mammogram that humans cannot detect. If highly accurate algorithms can help provide women with more clinically relevant and accurate information, then we can dramatically change the field of breast cancer screening,” Dr. Christoph Lee of the Seattle Cancer Care Alliance and clinical advisor to the challenge, explained.

To create the algorithms, participants will use anonymous patient data including nearly 650,000 digitized mammograms provided by the Group Health Cooperative through the NCI-funded Breast Cancer Surveillance Consortium and by the Icahn School of Medicine at Mount Sinai. Solvers’ algorithms will be evaluated against corresponding data on known patient outcomes, and scores will be assigned based on measures of accuracy. Algorithms that identify the fewest false positives while maintaining high rates of cancer detection will receive the highest ranking on the publicly accessible Challenge leaderboard. These medical images will be securely stored in the Amazon and IBM clouds.

“This Challenge holds great promise to improve breast cancer screening,” Group Health Cooperative Senior Investigator Dr. Diana Buist said. “It is only possible through the long-term investment the National Cancer Institute has made in the Breast Cancer Surveillance Consortium, which provides real clinical data harmonized with gold standard cancer ascertainment.”

Challenge organizers are working to maximize the level of solver participation through a targeted marketing campaign and by directly engaging the combined solver communities of DREAM and Innocentive that together include more than 370,000 registered individuals from over 200 countries.

The Challenge is also part of the Coding4Cancer initiative that was featured at Vice President Biden’s June 2016 National Cancer Moonshot Summit. Coding4Cancer seeks to drive improvements in cancer detection methods through the development of better algorithms for imaging tools. Coding4Cancer will hold a second Challenge in 2017 to improve lung cancer screening techniques.

“The Digital Mammography DREAM Challenge is the start of a larger movement focused on using prizes and Challenges to improve early cancer diagnosis,” LJAF Vice President of Science and Technology Michael Stebbins explained. “We are eager to hear more exciting ideas that will help to improve the use of medical imaging techniques to support early diagnosis.”

Due to the massive volume of data (more than 10 terabytes) and sensitivity of the Challenge’s digitized mammograms, solvers will not have direct access to the data. Rather than the usual approach of bringing the data to the algorithm, in this Challenge, organizers will bring solvers’ algorithms to the data for training and scoring. Generous sponsorships from both AWS and IBM are providing cloud computing for data hosting as well as the computational firepower needed to support solvers’ deep learning approaches for model training.

DREAM founder and IBM Research Director Dr. Gustavo Stolovitzky remarked, “We at DREAM are thrilled to be running this massive machine learning exercise on mammography data. And with Sage Bionetworks’ ability to host all the solvers’ re-runnable submissions and open source code after the Challenge, we are also creating a large resource of reproducible methods, all in a consistent, portable framework that can be run on any data set and developed further by any end-users to continue to advance the emerging opportunity to apply computer vision to medical imaging.”

Learn more and sign up at https://www.synapse.org/Digital_Mammography_DREAM_Challenge.

About Sage Bionetworks (www.sagebase.org)

Sage Bionetworks is a nonprofit biomedical research organization, founded in 2009, with a vision to promote innovations in personalized medicine by enabling a community-based approach to scientific inquiries and discoveries. In pursuit of this Mission, Sage Bionetworks is working with others to assemble an information Commons for biomedicine that (1) is supported by an open compute space (Synapse: www.synapse.org), (2) supports open research collaborations and innovative DREAM Challenges, and (3) empowers citizens and patients with the tools to partner with researchers and share their data through Sage’s BRIDGE platform (http://sagebase.org/bridge/) in order to drive the research studies that matter most to them.

About DREAM Challenges (www.dreamchallenges.org)

The Dialogue on Reverse Engineering Assessment and Methods (DREAM) Challenges pose fundamental questions about systems biology and translational medicine. A. Califano (Columbia University) and Gustavo Stolovitzky (IBM Research and the Icahn School of Medicine at Mount Sinai) founded the group in 2006. The DREAM Challenges, designed and run by a community of researchers from a variety of organizations, invite participants to propose solutions while fostering collaboration and building communities in the process. Expertise and institutional support are provided by Sage Bionetworks, along with the infrastructure to host challenges via their Synapse platform.

About Group Health Research Institute (www.grouphealthresearch.org)

Group Health Research Institute does practical research that helps people like you and your family stay healthy. The Institute is the research arm of Seattle-based Group Health Cooperative, which offers a unique health care system, care delivery, and health coverage, to achieve one goal—affordable, quality health care for all. Group Health’s innovative practices at 25 medical centers and within major Washington hospitals have earned national recognition for medical quality, disease prevention, and evidence-based treatments. These priorities have remained the same since it began serving patients in 1947. The Institute has conducted nonproprietary public-interest research on preventing, diagnosing, and treating major health problems since 1983. Government and private research grants provide its main funding. Follow Group Health research on TwitterFacebookPinterestLinkedIn, or YouTube. For more information about Group Health, visit www.ghc.org.

About IBM Research
For more than seven decades, IBM Research has defined the future of information technology with more than 3,000 researchers in 12 labs located across six continents. Scientists from IBM Research have produced six Nobel Laureates, 10 U.S. National Medals of Technology, five U.S. National Medals of Science, six Turing Awards, 19 inductees in the National Academy of Sciences and 20 inductees into the U.S. National Inventors Hall of Fame. For more information about IBM Research, visit www.ibm.com/research.

Contact: Sage Bionetworks

Thea Norman, (O) 206-667-3192
(M) 858-997-8598
thea.norman@sagebase.org