Diagnostic algorithm improves detection of uterine malignancies

Diagnostic algorithm improves detection of uterine malignancies | Image Credit: © cameravit - © cameravit - stock.adobe.com.

A 3-class diagnostic algorithm and risk class system can stratify patients based on mesenchymal uterine malignancies (MUMs), according to a recent study published in the American Journal of Obstetrics & Gynecology.¹

The algorithm has a 98.1% sensitivity and 58.3% specificity toward predicting target-lesion outcome. This allows for improved differentiation between benign and malignant lesions.

Three percent to 7% of uterine malignancies are identified as MUMs.² Types of MUMs include endometrial stromal sarcoma (ESS), leiomyosarcoma (LMS), adenosarcoma, undifferentiated uterine sarcoma (UUS), epithelioid sarcoma, and smooth muscle tumors of uncertain malignant potential (STUMPs).¹

MUMs have poor prognosis, according to the authors, and 5-year survival is under 50%. Data about ultrasound features of MUMs remains limited to retrospective case series, and investigators wrote, “neither accurate diagnostic criteria to discriminate between benign and malignant lesions have been prospectively validated with magnetic resonance imaging (MRI).”

Investigators conducted an observational prospective single-center study to evaluate the accuracy of an ultrasound algorithm in predicting MUMs. Participants were aged at least 18 years and had at least 1 myometrial lesion of at least 3 cm on ultrasound examination.

Exclusion criteria included embolization and hormonal therapy treatment within the past 6 months. An examiner performed medical evaluation and transvaginal ultrasound examination on participants.

Standardized transvaginal examination included color or power Doppler examination conducted using high-end ultrasound equipment. Morphological Uterus Sonographic Assessment terminology was used to record ultrasound features.

Patient classification was based on a diagnostic algorithm employing patient symptoms and morphological and color Doppler ultrasound features. When patients presented with multiple lesions of similar morphology, the largest one was selected.

Parameters considered more suspicious for malignancy were used to select the target lesion in patients with multiple lesions of different morphologies. First step criteria for diagnosis included maximum lesion size of 5 cm or more, symptoms, largest diameter rapid growth, irregular cystic areas, and rich lesion vascularization.

Patients not meeting first step criteria were classified as “White.” The second step for diagnosis included criteria of being aged at least 45 years old, presenting with relevant symptoms, and maximum lesion size of at least 8 cm.

Patients meeting at least 2 second step criteria were classified as “Orange,” while those who did not meet these criteria were classified as “Green.” Follow-up included annual telephone discussions for 2 years in “White” patients, longitudinal follow-up at 6, 12, and 24 months for “Green” patients, and MRI and surgery in “Orange” patients.

Lesion benignity was defined as the primary outcome of the analysis. This was determined based on histology in case of surgery or clinical judgement without surgery.

There were 2268 patients included in the final analysis, 271 of whom were “White,” 1023 “Green,” and 974 “Orange.” MUMs were identified in 52 patients, with 23 being LMS, 17 STUMPs, 7 UUS, and 5 ESS.

Benign myometrial lesions were identified in 2158 patients, with 23% being defined as variants. Fifty-eight patients presented with other malignancies. Participants with MUMs were often older than those with benign myometrial lesions, with an overall mean age of 46.7 years. An increased prevalence of symptoms was also found in patients with MUMs.

Similar distribution of target lesions was reported between MUMs and benign lesions. MUMs were also larger than benign lesions and grew more rapidly, with characteristics of MUMs including ill-defined borders, moderate and rich vascularization, mixed echogenicity, nonuniform echostructure, irregular cystic areas, and single lesion.

Visible normal myometrium and acoustic shadows were more common in benign lesions. Ultrasound examiners correctly classified 63.5% of MUMs as malignant, alongside 96.58% of other malignancies and 87.8% of benign myomas.

The Orange criteria had a 98.1% sensitivity and 58.3% specificity toward predicting target-lesion outcome. For patient outcome, these rates were 92.7% and 58.3%, respectively. Finally, rates were 63.5% and 85.6%, respectively, for subjective assessment toward target-lesion outcome.

These results indicated success from the 3-class diagnostic algorithm and risk assessment toward stratifying women based on malignancy risk. Investigators concluded these findings “will permit differentiation between benign and mesenchymal uterine malignancies allowing a personalized clinical approach” if confirmed in a multicenter study.

References

1. Ciccarone F, Biscione A, Robba E, et al. A clinical ultrasound algorithm to identify uterine sarcoma and smooth muscle tumors of uncertain malignant potential in patients with myometrial lesions: the MYometrial Lesion UltrasouNd And mRi study. Am J Obstet Gynecol. 2025;232:108.e1-22. doi:10.1016/j.ajog.2024.07.027
2. Mbatani N, Olawaiye AB, Prat J. Uterine sarcomas. Int J Gynaecol Obstet. 2018;143(2):51-58. doi:10.1002/ijgo.12613