RSNA 2019

Abstract Archives of the RSNA, 2019


The Role of Magnetic Resonance Imaging in Predicting the Outcome of High-Intensity Focused Ultrasound Treatment of Adenomyosis

Monday, Dec. 2 12:45PM - 1:15PM Room: VI Community, Learning Center Station #2

FDA Discussions may include off-label uses.

Nguyen Minh Duc, MD, Ho Chi Minh, Vietnam (Presenter) Nothing to Disclose
Chandran Nadarajan, MD, Kota Bharu, Malaysia (Abstract Co-Author) Nothing to Disclose
Huynh Q. Huy Sr, MD, PhD, Ho Chi Minh, Vietnam (Abstract Co-Author) Nothing to Disclose
Rajiv Chopra, PhD, Dallas, TX (Abstract Co-Author) Stockholder, Profound Medical Corporation; Stockholder, Solenic Medical Inc
Bilgin Keserci, PhD, Kota Bharu, Malaysia (Abstract Co-Author) Nothing to Disclose

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To investigate the role of magnetic resonance imaging (MRI) in predicting the treatment outcome of high-intensity focused ultrasound (HIFU) ablation of adenomyosis defined as the immediate non-perfused volume (NPV) ratio.


A total of 50 women (40.3 6.0 years with a range of 30-56 years) with symptomatic adenomyosis underwent MRI-guided HIFU ablation. Multivariate linear regression analyses were carried out on multiple pre-treatment MRI parameters including (i) baseline anatomical features, (ii) T2 signal intensity (SI) and (iii) semiquantitative perfusion analysis. The ability of these parameters to predict the final NPV ratio was investigated. Generalized estimating equation (GEE) of all the significant screening MRI parameters acquired from the multivariate analyses were used to predict the immediate NPV ratio.


The results of multivariate analyses revealed that there were four statistically significant predictors (p < 0.05): abdominal subcutaneous fat thickness, T2 SI ratio of adenomyosis to myometrium, relative enhancement ratio of adenomyosis to myometrium, time to peak enhancement ratio of adenomyosis to myometrium were significant factors affecting NPV ratio. GEE analysis generated linear equation for predicting the immediate NPV ratio with four statistically significant predictors derived from multivariate analyses : y = 165.952 + 0.119x1 - 10.514x2 - 56.177x3 - 39.812x4, where x1 = abdominal subcutaneous fat thickness, x2 = T2 SI ratio of adenomyosis to myometrium, x3 = relative enhancement ratio of adenomyosis to myometrium, x4 = time to peak ratio of adenomyosis to myometrium. The Pearson test revealed strong correlation between the GEE predicted value with NPV ratio (rho = 0.783, p < 0.001)


The study suggests that the prediction of MRI-guided HIFU treatment of adenomyosis based on multivariate analyses and prediction model appears to be clinically possible.


Based on the prediction model introduced, the role of each significant MRI parameter in the screening phase must be considered to predict the treatment outcome of HIFU ablation of adenomyosis.

Printed on: 03/01/22