We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.

AI Tool Predicts Lung Cancer Risk from Low-Dose Chest CT Scans

By MedImaging International staff writers
Posted on 16 Jan 2023
Print article
AI tool accurately predicts lung cancer risk for individuals (Photo courtesy of Mass General Cancer Center)
AI tool accurately predicts lung cancer risk for individuals (Photo courtesy of Mass General Cancer Center)

Lung cancer is the leading cause of cancer death in the world. Low-dose chest computed tomography (LDCT) is recommended to screen people in the age group of 50 to 80 years who have a significant history of smoking or who currently smoke. Studies have shown that LDCT screening can reduce the risk of death from lung cancer by up to 24%. However, with the rates of lung cancer rising among non-smokers, there is a need for new strategies to screen and accurately predict lung cancer risk among a wider population. Now, researchers have developed and tested an artificial intelligence (AI) tool that accurately predicts the risk of lung cancer for individuals with or without a significant smoking history based on analysis of LDCT scans from patients.

In order to help improve the efficiency of lung cancer screening and provide individualized assessments, investigators from the Mass General Cancer Center (Boston, MA, US), in collaboration with researchers at the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), have developed Sybil, a deep-learning model that analyzes scans and predicts lung cancer risk for the next one to six years. In their study, the team validated Sybil using three independent data sets - a set of scans from more than 6,000 NLST participants who Sybil had not previously seen; 8,821 LDCTs from the US; and 12,280 LDCTs from Taiwan. The latter set of scans included people with a range of smoking history, including those who never smoked.

The researchers found that Sybil could accurately predict risk of lung cancer across these sets. The team determined Sybil’s accuracy using Area Under the Curve (AUC), which measures how well a test distinguishes between disease and normal samples and in which 1.0 is considered to be a perfect score. Sybil was able to predict cancer within one year with AUCs of 0.92 for the additional NLST participants, 0.86 for the MGH dataset, and 0.94 for the dataset from Taiwan. Sybil predicted lung cancer within six years with AUCs of 0.75, 0.81, and 0.80, respectively, for the three datasets. The researchers will now begin a prospective clinical trial to test Sybil in the real world and see how it can aid radiologists..

“Sybil requires only one LDCT and does not depend on clinical data or radiologist annotations,” said co-author Florian Fintelmann, MD, of the Department of Radiology, Division of Thoracic Imaging & Intervention at Massachusetts General Hospital. “It was designed to run in real-time in the background of a standard radiology reading station which enables point-of care clinical decision support.”


Gold Supplier
Portable X-Ray System
FDR Xair
Premium Ultrasound System
RS85 Prestige
X-Ray Wall Stand
Image Acquisition Software
ExamVue Duo

Print article
FIME - Informa
Sun Nuclear -    Mirion



view channel
Image: BiOI ruby-like crystals can improve medical imaging safety by lowering intensities of harmful X-rays (Photo courtesy of University of Cambridge)

Sustainable Solar Cell Material Could Revolutionize Medical Imaging

The use of X-rays for internal body imaging has dramatically changed non-invasive medical diagnostics. Yet, the high dose of X-rays required for these imaging techniques, due to the poor performance of... Read more


view channel
Image: An international, multi-institutional project aims to develop a radically new MRI scanner that is compact and transportable (Photo courtesy of U of M Medical School)

Compact and Portable MRI Scanner to Expand Existing Imaging Capabilities and Accessibility

Magnetic Resonance Imaging (MRI) technology which provides detailed images of the human brain is instrumental in understanding brain functions and diagnosing medical conditions. MRI has become indispensable... Read more


view channel
Image: A new study has shown the value of endoscopic ultrasound in NSCLC (Photo courtesy of Freepik)

Endoscopic Ultrasound Can Provide Value in NSCLC, Finds Study

The usefulness of confirmatory mediastinoscopy following tumor-negative results on endoscopic ultrasound still remains debatable among researchers. This procedure is often employed for mediastinal staging... Read more

Nuclear Medicine

view channel
Image: New imaging method offers potential for diagnosing, staging, and treating multiple types of cancer (Photo courtesy of SNMMI)

New Imaging Method Superior for Diagnosing Multiple Types of Cancer

Cancer-associated fibroblasts play a significant role in tumor development, migration, and progression. A subset of these fibroblasts expresses fibroblast activation protein (FAP), a protein prominently... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more

Industry News

view channel
Image: The global AI-enabled medical imaging solutions market is expected to reach USD 18.36 billion in 2032 (Photo courtesy of Freepik)

Global AI-Enabled Medical Imaging Solutions Market Driven by Need for Early Disease Detection

The AI-enabled medical imaging solutions market is currently in its developmental stages, following the significant role of AI-based tools in combating the COVID-19 pandemic. The pandemic saw an upswing... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.