The role of T1 perfusion-based classification in predicting the outcome of magnetic resonance-guided high-intensity focused ultrasound treatment of adenomyosis

Abstract

Objective: To assess the relationship between magnetic resonance (MR) T1 perfusion-based classification and the outcome of MR-guided high intensity focused ultrasound treatment of adenomyosis, defined as nonperfused volume (NPV) ratio.

Methods: The adenomyosis of 31 women was classified into group A (time–signal intensity [SI] curve of adenomyosis lower than that of the myometrium) and group B (time–SI curve of adenomyosis equal to or higher than that of the myometrium) on the basis of time–SI curves on dynamic contrast enhanced (DCE) MR images acquired at screening. NPV ratios immediately after treatment and adenomyosis volume reduction ratios and symptom severity scores (SSS) at the six-month follow-up were retrospectively assessed. Univariate and multivariate analysis of pretreatment parameters conducted to assess independent factors impacting on immediate NPV ratio. All adverse effects were recorded.

Results: The immediate NPV ratios in groups A and B were 89.2 ± 6.7% and 42.4 ± 19.0%, respectively. At the six-month follow-up, the adenomyosis volume reduction ratios in groups A and B were 0.27 ± 0.8 and 0.04 ± 0.1, respectively, with corresponding improvements of 0.7 ± 0.18 and 0.26 ± 0.25, respectively, in the mean transformed SSS. Univariate and multivariate analysis revealed that only T1 perfusion-based classification as an independent factor associated with the outcome of MR-guided high intensity focused ultrasound treatment. No serious adverse effects were reported.

Conclusions: Our novel classification method introduced in this study might be clinically beneficial in classifying adenomyosis for predicting the immediate outcome of MR-guided high intensity focused ultrasound treatment.

Keywords:

• Adenomyosis
• myometrium
• T1 perfusion
• magnetic resonance imaging
• high intensity focused ultrasound

Disclosure statement

One author (Bilgin Keserci) is an employee of Philips Healthcare; however other author (Nguyen Minh DUC) in control of the study data and data analysis are not employees of Philips Healthcare and has no conflict of interest to declare. The authors alone are responsible for the content and writing of the paper.