A predictive model combining conventional and contrast-enhanced ultrasound for predicting complete microwave ablation of uterine fibroids: a multi-centre study
Year: 2026
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: To develop a pre-percutaneous microwave ablation (PMWA) model combining conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) for predicting non-perfused volume ratio (NPVR) ≥ 80% in patients with uterine fibroids. METHODS: This multicentre, retrospective study enrolled 276 patients with pathologically confirmed uterine fibroids (training/validation = 140/136). CUS features (maximum diameter, pre-operative volume, location, echo), CEUS parameters (maximum intensity: IMAX), and ablation parameters (energy, time, energy per unit volume [EPV], and time per unit volume [TPV]) were analysed. Multivariate logistic regression identified predictors, and model performance was assessed using the area under the receiver operating characteristic curve (AUC) and clinical decision curve analysis. RESULTS: Multivariate analysis identified four independent predictors: maximum diameter (odds ratio [OR] = 0.47, p < 0.001), IMAX (OR = 0.34, p = 0.013), energy (OR = 1.01, p = 0.002), and TPV (OR = 0.69, p < 0.001). The prediction model performed well in both the training (AUC = 0.79, 95% confidence interval [CI] = 0.71-0.87) and validation (AUC = 0.70, 95%CI = 0.61-0.79) datasets. P values for the Hosmer-Lemeshow test were 0.263 and 0.980, respectively, and the Brier Score was 0.184. CONCLUSION: This study established a prediction model based on CUS features, CEUS perfusion parameters, and ablation parameters to evaluate the efficacy of PMWA for uterine fibroids; NPVR ≥ 80% can be predicted using the nomogram. This model enables accurate prediction of the efficacy of PMWA for uterine fibroids, providing profound guidance for pre-operative assessment and intraoperative management in clinical practice and facilitating personalised, precision treatment.
Source: Abdominal Radiology
Language: English
Subfield: Obstetrics and Gynecology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,790
Award: G5711506276
OpenAlex ID: W7130513847
