News | Artificial Intelligence | April 27, 2020

Artificial Intelligence Can Categorize Cancer Risk of Lung Nodules

Artificial intelligence can categorize cancer risk of lung nodules

April 27, 2020 — Computed tomography (CT) scans for people at risk for lung cancer lead to earlier diagnoses and improve survival rates, but they can also lead to overtreatment when suspicious nodules turn out to be benign.

A study published in American Journal of Respiratory and Critical Care Medicine indicates that an artificial intelligence strategy can correctly assess and categorize these indeterminate pulmonary nodules (IPNs). When compared to the conventional risk models clinicians currently use, the algorithm developed by the team of researchers in a very large dataset (15,693 nodules) reclassified IPNs into low-risk or high-risk categories in over a third of cancers and benign nodules.

"These results suggest the potential clinical utility of this deep learning algorithm to revise the probability of cancer among IPNs aiming to decrease invasive procedures and shorten time to diagnosis," said Pierre Massion, M.D., Cornelius Vanderbilt Chair in Medicine at Vanderbilt University, the study's lead author.

Currently, clinicians refer to guidelines issued by the American College of Radiology and the American College of Chest Physicians. Adherence to these guidelines can be variable, and how patient cases are classified can be subjective. With the goal of providing clinicians with an unbiased assessment tool, the researchers developed an algorithm based on datasets from the National Lung Screening Trial, Vanderbilt University Medical Center and Oxford University Hospital. Their study is the first to validate a risk stratification tool on multiple independent cohorts and to show reclassification performance that is significantly superior to existing risk models.

With IPNs, clinicians are often faced with the dilemma of weighing whether to advise a patient to undergo an invasive surgical procedure, which may be unnecessary, against a watch and wait strategy, which may result in delaying needed cancer treatment. A definitive diagnosis of an IPN can take up to two years.

Better assessment tools are needed by clinicians as screenings for patients at risk for lung cancer increase. Lung cancer is the leading cause of cancer-related death in the United States and globally. The overall five-year survival rate is 21.7 percent, but it is much greater (92 percent) for those patients who receive an early diagnosis of stage IA1 non-small cell cancer.

For more information: www.mc.vanderbilt.edu/npa

Related Content

AIR Recon DL delivers shorter scans and better image quality (Photo: Business Wire)

AIR Recon DL delivers shorter scans and better image quality (Photo: Business Wire).

News | Artificial Intelligence | May 29, 2020
May 29, 2020 — GE Healthcare announced U.S.
AI has the potential to help radiologists improve the efficiency and effectiveness of breast cancer imaging

Getty Images

Feature | Breast Imaging | May 28, 2020 | By January Lopez, M.D.
Headlines around the world the past several months declared that...
Miami Cancer Institute’s Proton Therapy Center is the first in South Florida and the region’s top destination for this leading-edge treatment. Proton therapy is an advanced form of radiation therapy that uses pencil beam scanning (PBS) technology.

Miami Cancer Institute’s Proton Therapy Center is the first in South Florida and the region’s top destination for this leading-edge treatment. Proton therapy is an advanced form of radiation therapy that uses pencil beam scanning (PBS) technology.

Feature | Proton Therapy | May 27, 2020 | By Minesh Mehta, M.D.
Radiation therapy has advanced significantly in the last few decades as a result of a continued technological revolut
Technology becomes a state-of-the-art tool when it gets exposed to a structure that constantly tests it and allows it to evolve.

Technology becomes a state-of-the-art tool when it gets exposed to a structure that constantly tests it and allows it to evolve. Getty Images

Feature | Oncology Information Management Systems (OIMS) | May 27, 2020 | By Reshu Gupta
In the history of medicine, researchers have found cures for many diseases, but cancer has been elusive.
Off-site imaging companies are playing a key role in the fight against COVID-19
Feature | Coronavirus (COVID-19) | May 26, 2020 | By Sean Zahniser
After the worst of the COVID-19 pandemic has pas
The Philips Lumify point-of-care ultrasound (POCUS) system assessing a patient in the emergency room combined with telehealth to enable real-time collaboration with other physicians.

The Philips Lumify point-of-care ultrasound (POCUS) system assessing a patient in the emergency room combined with telehealth to enable real-time collaboration with other physicians.

News | Coronavirus (COVID-19) | May 26, 2020
May 26, 2020  — Philips Healthcare recently received 510(k) clearance from the U.S.
An example of DiA'a automated ejection fraction AI software on the GE vScan POCUS system at RSNA 2019.

An example of DiA'a automated ejection fraction AI software on the GE vScan POCUS system at RSNA 2019. Photo by Dave Fornell.

News | Ultrasound Imaging | May 26, 2020
May 12, 2020 — DiA Imaging Analysis, a provider of AI based ultrasound analysis solutions, said it received a governm
a Schematic of the system. The entire solid tumour is illuminated from four sides by a four-arm fibre bundle. A cylindrically focused linear array is designed to detect optoacoustic signals from the tumour. In vivo imaging is performed in conical scanning geometry by controlling the rotation and translation stages. The sensing part of the transducer array and the tumour are submerged in water to provide acoustic coupling. b Maximum intensity projections of the optoacoustic reconstruction of a phantom of pol

a Schematic of the system. The entire solid tumour is illuminated from four sides by a four-arm fibre bundle. A cylindrically focused linear array is designed to detect optoacoustic signals from the tumour. In vivo imaging is performed in conical scanning geometry by controlling the rotation and translation stages. The sensing part of the transducer array and the tumour are submerged in water to provide acoustic coupling. b Maximum intensity projections of the optoacoustic reconstruction of a phantom of polyethylene microspheres (diameter, 20 μm) dispersed in agar. The inset shows a zoomed-in view of the region boxed with a yellow dashed line. In addition, the yellow boxes are signal profiles along the xy and z axes across the microsphere centre, as well as the corresponding full width at half-maximum values. c Normalized absorption spectra of Hb, HbO2 and gold nanoparticles (AuNPs). The spectrum for the AuNPs was obtained using a USB4000 spectrometer (Ocean Optics, Dunedin, FL, USA), while the spectra for Hb and HbO2 were taken from http://omlc.org/spectra/haemoglobin/index.html. The vertical dashed lines indicate the five wavelengths used to stimulate the three absorbers: 710, 750, 780, 810 and 850 nm. Optoacoustic signals were filtered into a low-frequency band (red) and high-frequency band (green), which were used to reconstruct separate images.

News | Breast Imaging | May 26, 2020
May 26, 2020 — Breast cancer is the most common cancer in women.
A new technique developed by researchers at UC Davis offers a significant advance in using magnetic resonance imaging to pick out even very small tumors from normal tissue. The team created a probe that generates two magnetic resonance signals that suppress each other until they reach the target, at which point they both increase contrast between the tumor and surrounding tissue

A new technique developed by researchers at UC Davis offers a significant advance in using magnetic resonance imaging to pick out even very small tumors from normal tissue. The team created a probe that generates two magnetic resonance signals that suppress each other until they reach the target, at which point they both increase contrast between the tumor and surrounding tissue. Image courtesy of Xiandoing Xue, UC Davis

News | Magnetic Resonance Imaging (MRI) | May 26, 2020
May 26, 2020 — Researchers at the University of California, Davis offers a...