[Diffusion-weighted magnetic resonance imaging instead of contrast-enhanced imaging for evaluating immediate therapeutic efficacy of high-intensity focused ultrasound ablation of adenomyosis].
Diffusion-weighted MRI can replace contrast-enhanced MRI for assessing immediate therapeutic efficacy of high-intensity focused ultrasound ablation for adenomyosis, showing good consistency in necrotic volume measurements and reliability.
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This retrospective study evaluated whether diffusion-weighted MRI (DWI) can replace contrast-enhanced MRI for assessing immediate ablation efficacy after high-intensity focused ultrasound (HIFU) in 29 patients with adenomyosis, with MRI performed pre-treatment and within 24 hours post-treatment. Two independent observers classified ablation lesions on DWI into three morphological types and assessed inter- and intra-observer agreement using kappa statistics; they also measured necrotic area volumes for lesion types 2 and 3 and compared DWI-derived volumes with those from contrast-enhanced images using Bland–Altman plots. DWI lesion morphology showed good agreement (kappa up to 0.933), and DWI volume measurements demonstrated good concordance and reliability versus contrast-enhanced measurements, though small type 1 lesions were sometimes not measurable on DWI. The paper does not explicitly discuss limitations beyond the practical finding that smaller, less effective ablation lesions may be difficult to measure on DWI, and it used DWI only for types 2 and 3 volume comparisons. This paper is centrally about adenomyosis—using DWI instead of contrast-enhanced imaging to evaluate immediate HIFU ablation outcomes.
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Cites (3)
- Minimally invasive treatment of adenomyosis 2018
- Ultrasound-guided high intensity focused ultrasound for the treatment of gynaecological diseases: A review of safety and efficacy 2015
- Magnetic resonance imaging features influencing high-intensity focused ultrasound ablation of adenomyosis with a nonperfused volume ratio of ≥90% as a measure of clinical treatment success: retrospective multivariate analysis 2018
References (15)
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