RadNet, Inc. (NASDAQ: RDNT), a national leader in
providing high-quality, cost-effective, fixed-site outpatient
diagnostic imaging services today reported that its lung artificial
intelligence subsidiary, Aidence, and Google Health, a division of
Alphabet, Inc. (NASDAQ: GOOG), announce an agreement to license
Google Health’s AI research model for lung nodule malignancy
prediction on CT imaging. Aidence will develop, validate and bring
this model to the market to support the early and accurate
diagnosis of lung cancer and the reduction of unnecessary
procedures in screening programs.
Lung cancer screening with low-dose CT has been
shown to significantly reduce lung cancer mortality by as high as
24% for men and 33% for women, according to the 2020 NELSON trial.
Screening initiatives are increasingly being implemented in Europe,
such as the UK’s Targeted Lung Health Checks. In the United States,
eligibility criteria have recently been broadened, further
reflecting the benefit of lung cancer screening.
A major difficulty in lung cancer screening is
establishing the nature of detected lung nodules. Most of these
nodules are not cancerous. However, properly identifying and
diagnosing such nodules can be time-consuming, costly,
anxiety-inducing for patients and their families and sometimes
invasive, requiring follow-up CTs or surgical interventions.
Dr Raymond Osarogiagbon, Chief Scientist,
Baptist Memorial Health Care Corporation and Director,
Multidisciplinary Thoracic Oncology Program, Baptist Cancer Center,
Memphis, Tennessee, explained, “One of the most exciting
developments in contemporary population healthcare is the early
detection of lung cancer. Unfortunately, the reality that most such
nodules will be benign represents a real challenge that cries out
for a technological solution. Artificial intelligence is one such
solution.”
Dr Osarogiagbon continued, “The world looks
forward to the rapid development and validation of software that
will enhance our ability to find the many lung cancer needles in
the giant haystack that is CT-detected lung nodules in today’s
clinical practice.”
Deep learning, a subset of AI, has been shown to
support the risk scoring of lung nodule malignancy. In a study
published in Nature in 2018, scientists affiliated with Google
Health presented a highly accurate model for malignancy
classification, consistently matching the performance of
experienced radiologists.
Aidence has also built a deep learning model for
this purpose. Aidence’s algorithm successfully predicts lung cancer
from a single scan and was awarded in the 2017 Kaggle challenge.
Its robust performance was later confirmed in a clinical study
comparing its performance to that of 11 radiologists on 300
cases.
Aidence and Google Health intend to complete an
AI application for lung nodule malignancy prediction. In this
collaboration, Google Health will provide its scientific expertise.
Aidence will further develop the model into a solution for clinical
practice and bring it to market, complying with relevant data
privacy requirements and regulatory standards. The development of
this AI application is a statement of intent and no regulatory
market applications have been made and no orders for sale are being
taken.
Outside of this collaboration with Google
Health, Aidence has a proven track record of deploying AI in
hospitals and clinics across Europe. Its application, Veye Lung
Nodules, is currently running in over 80 routine practice and lung
cancer screening sites.
Mark-Jan Harte, Aidence co-founder and CEO,
said, “Our mission at Aidence is to give lung cancer patients a
fighting chance. This strategic partnership with Google Health
allows us to accelerate and expand our efforts toward achieving
it.”
Mr. Harte continued, “We are enthusiastic about
working on a powerful deep learning model for lung nodule
malignancy prediction based on the work of the Aidence and Google
teams, as well as making sure that all the other requirements that
contribute to the successful deployment of AI in clinical practice
are in place, like clinical validation, certification and
integration into the clinical workflow.”
Akib Uddin, Product Manager at Google Health,
commented, “At Google Health, we want to be an active, catalytic
force in demonstrating the real-world benefits of AI in health. We
know just how important lung cancer screening is in saving lives,
and we are excited to play a role in driving impact at scale by
enabling great partners like Aidence with our research.”
About RadNet, Inc.
RadNet, Inc., is the leading national provider of
freestanding, fixed-site diagnostic imaging services and related
information technology solutions (including artificial
intelligence) in the United States based on the number of locations
and annual imaging revenue. RadNet has a network of 349 owned
and/or operated outpatient imaging centers. RadNet's markets
include Arizona, California, Delaware, Florida, Maryland, New
Jersey and New York. Together with affiliated radiologists,
inclusive of full-time and per diem employees and technologists,
RadNet has a total of approximately 9,000 employees. For more
information, visit http://www.radnet.com.
About Google Health
A division of Alphabet, Inc., Google Health is our
company-wide effort to help billions of people be healthier. We
work toward this vision by meeting people in their everyday moments
and empowering them to stay healthy and partnering with care teams
and the public health community to provide more accurate,
accessible and equitable care. Our teams are applying our expertise
and technology to improve health outcomes globally – with
high-quality information and tools to help people manage their
health and wellbeing, solutions to transform care delivery,
research to catalyze the use of artificial intelligence for the
screening and diagnosis of disease and data and insights to the
public health community. https://health.google/
CONTACTS:
RadNet, Inc.
Mark Stolper, 310-445-2800
Executive Vice President and Chief
Financial Officer
Alphabet (NASDAQ:GOOG)
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