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




Events

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.

New AI Software Accurately Detects Lung Cancers on X-Rays and Cuts Unnecessary Chest CT Scans by 30%

By MedImaging International staff writers
Posted on 06 Aug 2021
Print article
Illustration
Illustration
A recent study has shown that a deep learning-based artificial intelligence (AI) algorithm can improve the performance of readers in detecting lung cancers on chest radiographs.

According to the second joint study conducted by Massachusetts General Hospital (Boston, MA, USA) and Lunit Inc. (Seoul, Korea), AI had 28% sensitivity benefit for radiology residents, helping them properly recommend CT exams for potential lung cancer patients, and 30% specificity benefit for radiologists in lung cancer detection, reducing unnecessary CT exams. The joint research team has previously focused on validating the accuracy of AI, and proved that Lunit INSIGHT CXR, an AI software for analyzing chest X-rays, can accurately detect malignant pulmonary nodules, which can cause lung cancer. In this consecutive study, the team focused on whether AI can affect the performance of medical professionals in finding lung cancers.

For the study, 519 images of cancer-positive and cancer-negative patients were selected from the National Lung Screening Trial (NLST). Eight readers, including three radiology residents and five board-certified radiologists, participated in the reading. By comparing the analysis of the readers and Lunit INSIGHT CXR, the result showed that AI could lead to more efficient and precise diagnosis for both doctors and patients. With AI, radiology residents were able to recommend 28% more chest CT examinations for patients who may have potential risk of lung cancer. Also, radiologists recommended about 30% lesser proportion of unnecessary chest CT examinations in cancer-negative patients.

"The use of AI could help to detect pulmonary nodules accurately with chest X-rays, as well as reduce the need for unnecessary chest CT exams in some patients," said Mannudeep K. Kalra, MD, a radiologist at the MGH and Co-investigator on the study. "This finding can benefit patients by enabling them to avoid unneeded radiation exposure, and it can benefit the healthcare system by preventing certain medical costs."

"Chest X-ray is the firsthand diagnostic tool to detect lung cancer, but it has limitations as it is a compressed 2D rendering of 3D human structures," said Brandon Suh, CEO of Lunit. "An accurate analysis through Lunit INSIGHT CXR can help medical professionals provide diagnosis to patients with increased efficiency - preventing potential cancer at an early stage, while saving time and cost for those who do not need a further examination."

Related Links:

Massachusetts General Hospital
Lunit Inc.


Gold Supplier
SBRT Phantom with Removable Spine
E2E SBRT Phantom with Removable Spine Model 036S-CVXX-xx
New
PACS System
Clario SmartWorklist
New
Elevating X-Ray Table
PROGNOST F
New
Fixed X-Ray System
MX Series

Print article
Radcal

Channels

MRI

view channel
Image: MRI scan showing the fetus and placental compartments (Photo courtesy of WUSTL)

New MRI Method Automatically Detects Placental Health during Pregnancy

Early monitoring of the placenta can improve detection and prevention of pregnancy complications, such as preterm birth, fetal growth disorders and preeclampsia. Currently, standard MRI analysis methods... Read more

Ultrasound

view channel
Image: The new Clarius MSK AI model speeds up diagnosis and treatment of musculoskeletal injuries (Photo courtesy of Clarius)

Handheld MSK Ultrasound Scanner Uses AI to Automatically Identify and Measure Tendons in Foot, Ankle and Knee

An artificial intelligence (AI) application for musculoskeletal (MSK) imaging that works with handheld point-of-care ultrasound devices automatically identifies, highlights, and measures tendon structures... Read more

Nuclear Medicine

view channel
Image: Tracking radiation treatment in real time promises safer, more effective cancer therapy (Photo courtesy of Pexels)

Real-Time 3D Imaging Provides First-of-Its-Kind View of X-Rays Hitting Inside Body During Radiation Therapy

Radiation is used in treatment for hundreds of thousands of cancer patients each year, bombarding an area of the body with high energy waves and particles, usually X-rays. The radiation can kill cancer... Read more

General/Advanced Imaging

view channel
Image: CZT gamma detector for SPECT imaging (Photo courtesy of Kromek)

Low-Dose Molecular Breast Imaging (MBI) Could Improve Cancer Detection in Dense Breast Tissue

Traditional mammography is often less able to clearly image tumors due to the density of the breast tissue. Molecular breast imaging (MBI) technology uses a radioactive tracer that ‘lights up’ areas of... 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
Copyright © 2000-2023 Globetech Media. All rights reserved.