Abdominal radiology (New York) · 2025
Biparametric MRI-based nomogram for differentiating malignant from atypical benign uterine smooth muscle tumors.
СтатьяНазвание и аннотация: Перевод в очереди
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Lakhani Aisha, Reddy Harshaveena, Augustine Antony, Simon Betty, Eapen Anu, Thomas Vinotha, Daniel Sherin, Reka K, Chandramohan Anuradha
Аннотация
PURPOSE: To develop and validate a biparametric MRI (bpMRI)-based nomogram for distinguishing malignant or potentially malignant uterine smooth muscle tumors from atypical benign leiomyomas.
MATERIALS AND METHODS: In this retrospective study, patients who underwent MRI for atypical uterine masses from January 2012 to January 2023 and subsequently underwent surgery were identified. MRI was performed using 1.5 Tesla or 3 Tesla scanners, including T2-weighted, diffusion-weighted sequences, and ADC maps. Two experienced radiologists evaluated lesions for qualitative features (i.e., T1/ T2 signal intensity, margins, presence of haemorrhage, DWI restriction) and quantitative mean ADC values. Histopathology served as the reference standard. Logistic regression identified significant predictors of malignancy, which were incorporated into a point-based nomogram. Receiver Operating Characteristic (ROC) analysis assessed model performance; interobserver agreement was evaluated using Cohen's kappa.
RESULTS: Eighty-nine lesions from 77 patients (median age, 45.6 years) were included. Malignant and potentially malignant lesions were 26 (30%), and 63 (70%) were benign. On multivariate analysis, irregular margins, hyperintense T2 signal, hyperintense DWI signal, and low ADC values (≤ 0.998 × 10⁻3 mm2/s) were independent predictors of malignancy. These were incorporated into the point-based nomogram. Patients scoring ≥ 132 on the nomogram were classified as likely malignant. The derived nomogram model demonstrated high accuracy (AUC = 0.975; 95% Confidence Interval (CI): 0.91-0.99), with 96.1% sensitivity and 93.6% specificity. Interobserver agreement ranged from substantial to excellent (κ = 0.72-0.89).
CONCLUSION: A biparametric MRI-based nomogram using reproducible, contrast-free imaging features can help accurately differentiate malignant from benign uterine smooth muscle tumors. This tool may guide preoperative management, particularly when CE-MRI is unavailable or contraindicated.
MATERIALS AND METHODS: In this retrospective study, patients who underwent MRI for atypical uterine masses from January 2012 to January 2023 and subsequently underwent surgery were identified. MRI was performed using 1.5 Tesla or 3 Tesla scanners, including T2-weighted, diffusion-weighted sequences, and ADC maps. Two experienced radiologists evaluated lesions for qualitative features (i.e., T1/ T2 signal intensity, margins, presence of haemorrhage, DWI restriction) and quantitative mean ADC values. Histopathology served as the reference standard. Logistic regression identified significant predictors of malignancy, which were incorporated into a point-based nomogram. Receiver Operating Characteristic (ROC) analysis assessed model performance; interobserver agreement was evaluated using Cohen's kappa.
RESULTS: Eighty-nine lesions from 77 patients (median age, 45.6 years) were included. Malignant and potentially malignant lesions were 26 (30%), and 63 (70%) were benign. On multivariate analysis, irregular margins, hyperintense T2 signal, hyperintense DWI signal, and low ADC values (≤ 0.998 × 10⁻3 mm2/s) were independent predictors of malignancy. These were incorporated into the point-based nomogram. Patients scoring ≥ 132 on the nomogram were classified as likely malignant. The derived nomogram model demonstrated high accuracy (AUC = 0.975; 95% Confidence Interval (CI): 0.91-0.99), with 96.1% sensitivity and 93.6% specificity. Interobserver agreement ranged from substantial to excellent (κ = 0.72-0.89).
CONCLUSION: A biparametric MRI-based nomogram using reproducible, contrast-free imaging features can help accurately differentiate malignant from benign uterine smooth muscle tumors. This tool may guide preoperative management, particularly when CE-MRI is unavailable or contraindicated.