A single-center, observational, prospective study evaluated a clinical ultrasound-based algorithm for identifying malignancy risks in patients with myometrial lesions.

While ultrasound is the first-line diagnostic tool for evaluating myometrial lesions, evidence of its role in identifying malignant uterine mesenchymal tumors (MUMs) has been limited to retrospective case series. No prospective studies have validated specific diagnostic criteria to differentiate between benign and malignant lesions, especially when combined with magnetic resonance imaging (MRI).

The research, conducted at Fondazione Policlinico Universitario A. Gemelli, IRCCS in Rome, Italy, and published in the American Journal of Obstetrics and Gynecology, presented 12-month data.

An international panel of experts analyzed a series of histologically confirmed uterine sarcomas, documenting common ultrasound features. The analysis became the basis for a combined clinical and ultrasound algorithm utilizing a color-coded system to guide patient management.

The study examined the diagnostic accuracy of the 3-class algorithm. The research team, led by Francesca Ciccarone, M.D., enrolled 2,268 women aged 18 years or older with at least 1 myometrial lesion measuring 3 cm or more. Based on clinical symptoms and ultrasound features, patients were classified into three categories with specific follow-up protocols:

• "White" patients underwent annual telephone follow-ups for 2 years.
• "Green" patients received clinical and ultrasound follow-up at 6, 12, and 24 months.
• "Orange" patients underwent surgery.

Of the examined lesions, 95.1% were benign, 2.6% were other malignancies, and 2.3% were mesenchymal uterine malignancies. The "orange" criteria demonstrated a sensitivity of 98.1%, specificity of 58.3%, and positive and negative likelihood ratios of 2.35 and 0.03, respectively.

The study identified several independent risk factors for malignancies: age (OR 1.05, 95% CI 1.03–1.07), tumor diameter over 8 cm (OR 5.92, 95% CI 2.87–12.24), irregular margins (OR 2.34, 95% CI 1.09–4.98), and a color score of 4 (OR 2.73, 95% CI 1.28–5.82). Acoustic shadowing was identified as a protective factor (OR 0.39, 95% CI 0.19–0.82).

The researchers developed a risk stratification system:

• Low risk (predictive model value less than 0.39%): 0 of 606 malignancies, risk 0%
• Intermediate risk (predictive model value 0.40% to 2.2%): 9 of 1,093 malignancies, risk 0.8%
• High risk (predictive model value 2.3%or more: 43 of 566 malignancies, risk 7.6%

The predictive model achieved an area under the curve of 0.87 (95% CI 0.82–0.91). 

"The preoperative 3-class diagnostic algorithm and risk class system can stratify women according to risk of malignancy," Dr. Ciccarone and colleagues wrote, adding that their "findings, if confirmed in a multicenter study, will permit differentiation between benign and mesenchymal uterine malignancies allowing a personalized clinical approach."

The researchers concluded multicenter studies are needed to confirm the algorithm's clinical applicability.

They declared no conflict of interest.