Ultrasound test detects 96% of ovarian cancers in postmenopausal women

Ultrasound test detects 96% of ovarian cancers in postmenopausal women
Intermediate magnification micrograph of a low malignant potential (LMP) mucinous ovarian tumor. H&E stain. The micrograph shows: Simple mucinous epithelium (right) and mucinous epithelium that pseudo-stratifies (left – diagnostic of a LMP tumor). Epithelium in a frond-like architecture is seen at the top of image. Credit: Nephron /Wikipedia. CC BY-SA 3.0

An ultrasound test that detected 96% of ovarian cancers in postmenopausal women should replace the current standard of care test in the UK according to a new study.

In a paper published in The Lancet Oncology today, research led by Professor Sudha Sundar from the University of Birmingham compared all currently available tests to diagnose ovarian cancer in head-to-head in a high-quality diagnostic test accuracy study.

Of the six investigated, the IOTA ADNEX model which looks at ultrasound features (how the lump looked like on ultrasound) had the best accuracy of all and could detect up to 96% of women with ovarian cancer.

The outperforms the current standard of care in the UK significantly and so we recommend that the IOTA ultrasound ADNEX model should replace the current standard of care test called risk of malignancy (RMI1) test in the UK, which identifies 83% of .

Sudha Sundar, Professor of Gynecological Cancer at the University of Birmingham and consultant in gynecological cancer surgery at Sandwell and West Birmingham NHS Trust said,

“This is the first time that a head-to-head study of all available ovarian cancer tests has been done in the same population. Here we studied their use with symptomatic, postmenopausal women who are most at risk of this cancer. Our trial found that the IOTA ADNEX ultrasound protocol had the highest sensitivity for detecting ovarian cancer compared to the standard of care and other tests.

“The ultrasound test also performs well when delivered by a trained sonographer who have received specific training and certification and , and as the vast majority of ultrasound scans are performed by sonographers it is important that a new standard is able to be delivered by as many clinical professionals as possible.

“We found that the higher sensitivity of the IOTA ADNEX model is likely to lead to some women who don’t have cancer also being flagged up as having a higher risk of cancer. We, however, did discuss this extensively with patients, cancer charity Target ovarian cancer and NHS experts, who all agreed that in postmenopausal women who are at higher risk of ovarian cancer, picking up more women with cancer would benefit women overall.”

Annwen Jones OBE, Chief Executive at Target Ovarian Cancer said, “Early diagnosis of ovarian cancer is vital, and we are pleased to see this research demonstrate that there are more accurate ways of using ultrasound. The faster and earlier ovarian cancer is diagnosed, the easier it is to treat and the more successful the outcomes.

“Alongside this , we need to see greater awareness of the symptoms of so that women know to come forward to their GP for testing and receive the best possible treatment as quickly as possible. It is crucial that new ways of working like this are rolled out as quickly as possible.”

The research team notes that the IOTA ADNEX model achieved 96% accuracy when delivered by NHS sonographers who were appropriately trained and received quality assurance. As most scans worldwide are carried out by sonographers rather than gynecologists, introductory free online resources have been created by the researchers for NHS staff to undergo the specialist ultrasound training and get certification and quality assurance.

More information:
Risk-prediction models in postmenopausal patients with symptoms of suspected ovarian cancer in the UK (ROCkeTS): a multicentre, prospective diagnostic accuracy study, The Lancet Oncology (2024).

Citation:
Ultrasound test detects 96% of ovarian cancers in postmenopausal women (2024, September 30)
retrieved 1 October 2024
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