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




MRI-Based Imaging Technique Enables Rapid Assessment of Ovarian Cancer Subtypes and Treatment Response

By MedImaging International staff writers
Posted on 10 Dec 2024
Print article
Image: The MRI-based imaging technique allows rapid assessment of ovarian cancer subtypes and their response to treatment (Photo courtesy of University of Cambridge)
Image: The MRI-based imaging technique allows rapid assessment of ovarian cancer subtypes and their response to treatment (Photo courtesy of University of Cambridge)

Ovarian cancer patients often have multiple tumors spread across their abdomen, making it difficult to biopsy all of them, especially since they may belong to different subtypes that respond differently to treatments. Current testing methods usually result in patients waiting weeks or even months to learn whether their cancer is responding to treatment. Now, a new MRI-based imaging technique can predict how ovarian cancer tumors will respond to treatment and provide rapid feedback on the therapy's effectiveness using patient-derived cell models.

This innovative technique, developed by scientists at the University of Cambridge (Cambridge, UK), is known as hyperpolarized carbon-13 imaging. It amplifies the MRI signal by more than 10,000 times, allowing for more detailed observation. The technique works by using an injectable solution that contains a labeled form of pyruvate, a naturally occurring molecule. Once injected, the pyruvate enters the body’s cells, and the MRI scan detects how quickly it is metabolized into lactate. The rate of this metabolic process helps reveal the tumor’s subtype and its sensitivity to treatment. The researchers found that hyperpolarized carbon-13 imaging could distinguish between two ovarian cancer subtypes, providing insight into their treatment responses. They used this method to examine patient-derived cell models that closely replicate the behavior of high-grade serous ovarian cancer, the most common and lethal type of the disease.

This imaging technique can clearly identify whether a tumor is sensitive or resistant to Carboplatin, a common first-line chemotherapy drug for ovarian cancer. This capability allows oncologists to predict how well a patient will respond to treatment and assess the treatment’s effectiveness within the first 48 hours. The fast feedback from this technique enables oncologists to tailor and adjust treatment plans for each patient much sooner. In their study, published in the journal Oncogene, the scientists compared hyperpolarized carbon-13 imaging with Positron Emission Tomography (PET), which is widely used in clinical practice. They found that PET scans failed to detect the metabolic differences between tumor subtypes, meaning it couldn’t predict the type of tumor present. This study further supports the potential of hyperpolarized carbon-13 imaging for broader clinical use, and the next step will involve testing the technique in ovarian cancer patients, which the researchers expect to begin in the next few years.

“This technique tells us how aggressive an ovarian cancer tumor is, and could allow doctors to assess multiple tumors in a patient to give a more holistic assessment of disease prognosis so the most appropriate treatment can be selected,” said Professor Kevin Brindle in the University of Cambridge’s Department of Biochemistry, senior author of the report. “We can image a tumor pre-treatment to predict how likely it is to respond, and then we can image again immediately after treatment to confirm whether it has indeed responded. This will help doctors to select the most appropriate treatment for each patient and adjust this as necessary.”

Radiology Software
DxWorks
NMUS & MSK Ultrasound
InVisus Pro
New
Mini C-arm Imaging System
Fluoroscan InSight FD
New
Diagnostic Ultrasound System
MS1700C

Print article

Channels

Ultrasound

view channel
Image: The addition of POC ultrasound can enhance first trimester obstetrical care (Photo courtesy of 123RF)

POC Ultrasound Enhances Early Pregnancy Care and Cuts Emergency Visits

A new study has found that implementing point-of-care ultrasounds (POCUS) in clinics to assess the viability and gestational age of pregnancies in the first trimester improved care for pregnant patients... Read more

Nuclear Medicine

view channel
Image: PSMA-PET/CT images of an 85-year-old patient with hormone-sensitive prostate cancer (Photo courtesy of Dr. Adrien Holzgreve)

Advanced Imaging Reveals Hidden Metastases in High-Risk Prostate Cancer Patients

Prostate-specific membrane antigen–portron emission tomography (PSMA-PET) imaging has become an essential tool in transforming the way prostate cancer is staged. Using small amounts of radioactive “tracers,”... Read more

General/Advanced Imaging

view channel
Image: Automated methods enable the analysis of PET/CT scans (left) to accurately predict tumor location and size (right) (Photo courtesy of Nature Machine Intelligence, 2024. DOI: 10.1038/s42256-024-00912-9)

Deep Learning Based Algorithms Improve Tumor Detection in PET/CT Scans

Imaging techniques are essential for cancer diagnosis, as accurately determining the location, size, and type of tumors is critical for selecting the appropriate treatment. The key imaging methods include... 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.