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Imaging techniques could help predict ovarian cancer, one of the deadliest tumors because most cases are late diagnosis due to the absence of symptoms. According to a study published in the journal “Radiology”, the appearance of ovarian lesions on ultrasound is an effective symptom of cancer risk that can help women avoid unnecessary surgery.
Ovarian cancer is the deadliest of gynecologic cancers. In Spain, some 3,300 annual cases of ovarian cancerwhich represents 5.1 percent of cancers among women, behind breast, colorectal and corpus uteri
Characterization of adnexal lesions, or lumps or cysts near the uterus, on ultrasound examination is crucial for proper patient management, as some adnexal lesions can develop into cancer, while many others are benign and do not require treatment. .
“Based on the features we see on ultrasound, we try to assess whether a finding needs further analysis and where the patient should go from there,” says study lead author Akshya Gupta, of the University of Rochester in Rochester. (USA.). “There are a lot of nuances because injuries can be difficult to assess.”
Current risk stratification systems work well, but their multiple subcategories and multifaceted approach can make it difficult for radiologists in busy clinical practices to master.
In the new study, Gupta and colleagues evaluated a method that uses ultrasound images to classify these cysts into one of two categories: classic or nonclassic.
Classic lesions are those that are commonly detected, such as fluid-filled cysts, which have a very low risk of malignancy. Nonclassical lesions include lesions with a solid component and blood flow detected on Doppler ultrasound. A classical versus nonclassical approach to these lesions could help radiologists in a busy clinical practice to more quickly assess a lesion.
The researchers looked at 970 isolated adnexal lesions in 878 women, aged average 42 yearswith an average risk of ovarian cancer, meaning they had no family history or genetic markers linked to the disease.
Of the 970 lesions, 53 (6%) were malignant. The classic ultrasound-based categorization approach versus non-classical achieved a sensitivity of 92.5% and a specificity of 73.1% for the diagnosis of malignancy in ovarian cancer.
The frequency of malignancy was less than 1% in lesions with classic ultrasound characteristics. In contrast, lesions that had a solid component with blood flow had a malignancy rate of 32% in the overall study group and the 50% in study participants who were over 60 years old.
“If you have something that follows the classic imaging patterns described for these lesions, then the cancer risk is really low,” Gupta said. “If you have something that doesn’t have a classic look, then the presence of solid components and, in particular, the presence of blood flow Doppler is really what increases the risk of malignancy.”
When a classic benign lesion is found, patients can be assured that a benign lesion exists, avoiding further extensive study. If additional research supports the study’s findings, then the system could end up being a useful tool for radiologists that would save many women the cost, stress, and complications of surgery.
“We hope that by using the ultrasound features we will be able to classify which patients need follow-up imaging. with ultrasound or MRI and which patients should be referred for surgery,” says Gupta.
While these diagnostic ultrasound findings provide valuable staging information, ultrasound has not been shown to be of benefit specifically for ovarian cancer screening.
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