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
GLOBETECH PUBLISHING LLC

Download Mobile App




AI Algorithm Twice As Accurate As Biopsy at Grading Cancer Aggressiveness from CT Scans

By MedImaging International staff writers
Posted on 02 Nov 2023
Print article
Image: Histopathology image of leiomyosarcoma (Photo courtesy of ICR)
Image: Histopathology image of leiomyosarcoma (Photo courtesy of ICR)

Soft tissue sarcomas are cancers that originate in the connective tissues of the body, such as fat, muscle, nerves, as well as blood and lymph vessels. These sarcomas are a diverse and biologically intricate set of cancers, occurring so rarely that a clinician may encounter only a couple of cases throughout their career, leading to potential delays in diagnosis. The visual differentiation of these sarcomas, especially outside specialized centers, is highly challenging. Now, new research has revealed that artificial intelligence (AI) could double the accuracy of current methods, such as biopsies, in determining the severity of some sarcomas using CT imaging.

Results from the study by researchers from The Royal Marsden NHS Foundation Trust (London, UK) and The Institute of Cancer Research (ICR, London, UK) suggest that a novel AI algorithm could provide a more precise and non-invasive approach to personalizing treatment for sarcoma patients compared to biopsies, which are invasive and currently standard practice. The study also suggests that this AI could help in quicker identification of the specific sarcoma subtypes. This technique, researchers anticipate, could also extend its benefits to the diagnosis and treatment of other cancer forms, aiding a large number of patients annually.

For developing the AI algorithm, researchers used CT scans from 170 patients at The Royal Marsden diagnosed with leiomyosarcoma or liposarcoma, two prevalent forms of retroperitoneal sarcoma. The AI was then validated using data from almost 90 patients across Europe and the United States. The AI's analysis, called radiomics, scrutinizes CT scan data to discern disease characteristics that are not visible to the naked eye. This AI model successfully determined the aggressiveness of 82% of the tumors it analyzed, whereas biopsies achieved correct grading in about 44% of cases. It could also correctly identify the sarcoma type in 84% of the cases it was tested on, distinguishing effectively between leiomyosaroma and liposarcoma, unlike radiologists who could not diagnose 35% of the cases.

The researchers expect the AI technology to enhance the clinical management and outcomes of the disease. For instance, identifying high-grade tumors, which may indicate a more aggressive cancer, could mean that high-risk patients receive more intensive treatment while those at lower risk might avoid unnecessary treatments, excessive follow-up scans, and hospital stays. Additionally, this tool could speed up the diagnosis process by aiding clinicians in more confidently identifying the subtype of a sarcoma they might not have encountered before due to its rarity. The research team plans to further evaluate this AI model in a clinical setting with patients who may have retroperitoneal sarcomas to verify its accuracy in real-world diagnosis and observe the technology's performance over time.

“Through this early research, we’ve developed an innovative AI tool using imaging data that could help us more accurately and quickly identify the type and grade of retroperitoneal sarcomas than current methods,” said Dr. Amani Arthur, Clinical Research Fellow at The Institute of Cancer Research, London. “This could improve patient outcomes by helping to speed up diagnosis of the disease, and better tailor treatment by reliably identifying the risk of each patient’s disease.”

“We’re incredibly excited by the potential of this state-of-the-art technology, which could lead to patients having better outcomes through faster diagnosis and more effectively personalized treatment. As patients with retroperitoneal sarcoma are routinely scanned with CT, we hope this tool will eventually be used globally, ensuring that not just specialist centers – who see sarcoma patients every day – can reliably identify and grade the disease,” added Professor Christina Messiou, Consultant Radiologist at The Royal Marsden NHS Foundation Trust and Professor in Imaging for Personalised Oncology at The Institute of Cancer Research, London. “In the future, this approach may help characterize other types of cancer, not just retroperitoneal sarcoma. Our novel approach used features specific to this disease, but by refining the algorithm, this technology could one day improve the outcomes of thousands of patients each year.”

Related Links:
The Royal Marsden NHS Foundation Trust 
The Institute of Cancer Research 

Gold Supplier
Conductive Gel
Tensive
Gold Supplier
Ultrasound System
FUTUS LE
Afterloader For Brachytherapy
Flexitron
New
Ultrasonic Diagnostic System
K10

Print article
Radcal

Channels

Radiography

view channel
Image: Intelligent NR provides high-quality diagnostic images containing significantly less grainy noise (Photo courtesy of Canon)

AI-Driven DR System Produces Higher Quality Images While Limiting Radiation Doses in Pediatric Patients

Ionizing radiation is a fundamental element in producing diagnostic X-rays, yet it's widely acknowledged for its cancer risk potential. Digital projection radiography, a vital imaging modality, accounts... Read more

MRI

view channel
Image: The researchers are using MRI-guided radiation therapy that pairs daily MRIs with radiation treatment (Photo courtesy of Sylvester)

AI Technique Automatically Traces Tumors in Large MRI Datasets to Guide Real-time Glioblastoma Treatment

Treating glioblastoma, a prevalent and aggressive brain cancer, involves the use of radiation therapy guided by CT imaging. While this method is effective in targeting radiation, it doesn't provide real-time... Read more

Ultrasound

view channel
Image: The new ultrasound patch can measure how full the bladder is (Photo courtesy of MIT)

Ultrasound Patch Designed to Monitor Bladder and Kidney Health Could Enable Earlier Cancer Diagnosis

Bladder dysfunction and related health issues affect millions worldwide. Monitoring bladder volume is crucial for assessing kidney health. Traditionally, this requires a visit to a medical facility and... Read more

Nuclear Medicine

view channel
Image: A novel PET radiotracer facilitates early, noninvasive detection of IBD (Photo courtesy of Karmanos)

New PET Radiotracer Aids Early, Noninvasive Detection of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), which includes Crohn’s disease and ulcerative colitis, is an inflammatory condition of the gastrointestinal tract affecting roughly seven million individuals globally.... 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

Industry News

view channel
Image: Attendees can discover innovative products and technology in the RSNA 2023 Technical Exhibits (Photo courtesy of RSNA)

RSNA 2023 Technical Exhibits to Offer Innovations in AI, 3D Printing and More

The 109th Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA, Oak Brook, IL, USA) to be held in Chicago, Nov. 26 to 30 is all set to offer a vast array of medical... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.