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
GLOBETECH PUBLISHING LLC

Download Mobile App




Ultrasound Can Effectively Predict Ovarian Cancer and Prevent Unnecessary Surgery

By MedImaging International staff writers
Posted on 24 Mar 2022
Print article
Image: Appearance of ovarian lesions on ultrasound is an effective predictor of cancer risk (Photo courtesy of Unsplash)
Image: Appearance of ovarian lesions on ultrasound is an effective predictor of cancer risk (Photo courtesy of Unsplash)

Ovarian cancer is the deadliest of the gynecologic cancers. Characterization of adnexal lesions, or lumps near the uterus, on ultrasound examination is crucial for appropriate patient management, as some adnexal lesions can progress to cancer, while many others are benign and do not require treatment. Current risk stratification systems perform well, but their multiple sub-categories and multifaceted approach may make them difficult for radiologists in busy clinical practices to master. According to a new study, the appearance of ovarian lesions on ultrasound is an effective predictor of cancer risk that can help women avoid unnecessary surgery.

In the new study, researchers at the University of Rochester Medical Center (Rochester, NY, USA) assessed a method that uses ultrasound images to classify adnexal lesions into one of two categories: classic or non-classic. Classic lesions are the commonly detected ones such as fluid-filled cysts that carry a very low risk of malignancy. Non-classic lesions include lesions with a solid component and blood flow detected on Doppler ultrasound. A classic versus non-classic approach to these lesions could help radiologists in a busy clinical practice more quickly assess a lesion.

The researchers looked at 970 isolated adnexal lesions in 878 women, mean age 42 years, at average risk of ovarian cancer, meaning they had no family history or genetic markers linked with the disease. Of the 970 lesions, 53 (6%) were malignant. The classic versus non-classic ultrasound-based categorization approach achieved a sensitivity of 92.5% and a specificity of 73.1% for diagnosing malignancy in ovarian cancer. The frequency of malignancy was less than 1% in lesions with classic ultrasound features. In contrast, lesions that had a solid component with blood flow had a malignancy frequency of 32% in the overall study group and 50% in study participants who were more than 60 years old.

When a classic benign lesion is encountered, patients may be reassured a benign lesion is present, avoiding extensive further work-up. If additional research supports the study findings, then the system could end up being a useful tool for radiologists that would spare many women the costs, stress and complications of surgery. While these findings on diagnostic ultrasound exams offer valuable triaging information, ultrasound has not been proven beneficial specifically as a screening exam for ovarian cancer.

"If you have something that follows the classic imaging patterns described for these lesions, then the risk of cancer is really low," said study lead author Akshya Gupta, M.D., from the University of Rochester Medical Center. "If you have something that's not classic in appearance, then the presence of solid components and particularly the presence of Doppler blood flow is really what drives the risk of malignancy."

"Ultimately, we're hoping that by using the ultrasound features we can triage which patients need follow-up imaging with ultrasound or MRI and which patients should be referred to surgery," Dr. Gupta said.

Related Links:
University of Rochester Medical Center 

New
Gold Member
X-Ray QA Meter
T3 AD Pro
New
Computed Tomography System
Aquilion ONE / INSIGHT Edition
New
Multi-Use Ultrasound Table
Clinton
New
Diagnostic Ultrasound System
MS1700C

Print article
Radcal

Channels

Radiography

view channel
Image: The new X-ray detector produces a high-quality radiograph (Photo courtesy of ACS Central Science 2024, DOI: https://doi.org/10.1021/acscentsci.4c01296)

Highly Sensitive, Foldable Detector to Make X-Rays Safer

X-rays are widely used in diagnostic testing and industrial monitoring, from dental checkups to airport luggage scans. However, these high-energy rays emit ionizing radiation, which can pose risks after... Read more

MRI

view channel
Image: Artificial intelligence models can be trained to distinguish brain tumors from healthy tissue (Photo courtesy of 123RF)

AI Can Distinguish Brain Tumors from Healthy Tissue

Researchers have made significant advancements in artificial intelligence (AI) for medical applications. AI holds particular promise in radiology, where delays in processing medical images can often postpone... Read more

Nuclear Medicine

view channel
Image: Example of AI analysis of PET/CT images (Photo courtesy of Academic Radiology; DOI: 10.1016/j.acra.2024.08.043)

AI Analysis of PET/CT Images Predicts Side Effects of Immunotherapy in Lung Cancer

Immunotherapy has significantly advanced the treatment of primary lung cancer, but it can sometimes lead to a severe side effect known as interstitial lung disease. This condition is characterized by lung... Read more

General/Advanced Imaging

view channel
Image: Cleerly offers an AI-enabled CCTA solution for personalized, precise and measurable assessment of plaque, stenosis and ischemia (Photo courtesy of Cleerly)

AI-Enabled Plaque Assessments Help Cardiologists Identify High-Risk CAD Patients

Groundbreaking research has shown that a non-invasive, artificial intelligence (AI)-based analysis of cardiac computed tomography (CT) can predict severe heart-related events in patients exhibiting symptoms... 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 © 2000-2024 Globetech Media. All rights reserved.