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 hp
Sign In
Advertise with Us
Radcal IBA  Group

Download Mobile App




AI Identifies Noncancerous Thyroid Nodules on Ultrasound Images and Reduces Biopsies

By MedImaging International staff writers
Posted on 13 Jun 2022
Image: AI can be used to identify benign thyroid nodules and reduce unnecessary biopsies (Photo courtesy of Pexels)
Image: AI can be used to identify benign thyroid nodules and reduce unnecessary biopsies (Photo courtesy of Pexels)

Thyroid nodules are very common. Fine needle aspiration biopsy is used to diagnose thyroid cancer. However most biopsies produce benign (non-cancerous) results and are potentially avoidable. Now, a new study has found that artificial intelligence (AI) can be used to identify thyroid nodules seen on thyroid ultrasound that are very unlikely to be cancerous, reducing a large number of unnecessary biopsies.

In the new study, researchers at the University of Colorado Anschutz Medical Campus (Aurora, CO, USA) used machine learning, a type of AI, to analyze ultrasound images of thyroid nodules. Machine learning is the process of using mathematical models of data to help a computer learn without direct instruction. More than 30,000 images from 621 thyroid nodules were used to train the machine-learning model that classifies thyroid nodules as “cancer” or “no cancer.” The model was tested on a different set of 145 nodules collected at another healthcare system. The AI-based model achieved a sensitivity (ability to not miss cancer) of 97%, and a specificity (ability to correctly identify a cancer) of 61%.

“This study demonstrates that the ultrasound-based AI classifier of thyroid nodules achieves sensitivity comparable to that of thyroid biopsy with fine needle aspiration,” said study lead researcher Nikita Pozdeyev, M.D., Ph.D., of the University of Colorado Anschutz Medical Campus.

“We believe this is a good next step to improving patient care and avoiding unnecessary procedures,” he said. He noted that prospective clinical trials are needed before this tool can be accepted as a standard of care.

“We demonstrated that using AI analysis of ultrasound images to rule out thyroid cancer and avoid biopsy is definitely possible,” he said. “This technology could assist radiologists and endocrinologists in choosing which thyroid nodules should undergo biopsy, especially those in the community who may not review a large number of thyroid ultrasound images.”

Related Links:
University of Colorado Anschutz Medical Campus 

Silver Member
X-Ray QA Device
Accu-Gold+ Touch Pro
Mobile X-Ray System
K4W
Ultrasonic Pocket Doppler
SD1
MRI System
nanoScan MRI 3T/7T

Channels

Nuclear Medicine

view channel
Image: LHSCRI scientist Dr. Glenn Bauman stands in front of the PET scanner (Photo courtesy of LHSCRI)

New Imaging Solution Improves Survival for Patients with Recurring Prostate Cancer

Detecting recurrent prostate cancer remains one of the most difficult challenges in oncology, as standard imaging methods such as bone scans and CT scans often fail to accurately locate small or early-stage tumors.... Read more

General/Advanced Imaging

view channel
Image: Concept of the photo-thermoresponsive SCNPs (J F Thümmler et al., Commun Chem (2025). DOI: 10.1038/s42004-025-01518-x)

New Ultrasmall, Light-Sensitive Nanoparticles Could Serve as Contrast Agents

Medical imaging technologies face ongoing challenges in capturing accurate, detailed views of internal processes, especially in conditions like cancer, where tracking disease development and treatment... 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 © 2000-2025 Globetech Media. All rights reserved.