Magnetic Resonance Imaging Parameters in Predicting the Treatment Outcome of High-intensity Focused Ultrasound Ablation of Uterine Fibroids With an Immediate Nonperfused Volume Ratio of at Least 90%

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

“…Despite the similar study design and prediction model between our previous [38] and present studies, it is worth to note that uterine fibroids and adenomyosis, two common gynecological benign tumours, have different histopathologic characteristics that generate different baseline, cellular and vascular features. In addition, in contrast with previous study [38], the present study assessed quantitative perfusion MRI features for investigating the potential predictors of the NPV ratio of at least 90%. Lastly, prospective studies with larger patient populations and longer follow-up periods are essential to confirm the validity of (i) the MRI features influencing an NPVr !90% in HIFU ablation of adenomyosis, (ii) the prediction model introduced in this retrospective study, and (iii) the safety and clinical efficacy of this approach.…”

“…Thus, it is not likely that a considerable overlap in the patient population affected our results. Furthermore, a recent retrospective study [38] demonstrated that the achievement of NPVr !90% in MRI-guided HIFU treatment of uterine fibroids using multivariate analyses and GEE prediction model. Despite the similar study design and prediction model between our previous [38] and present studies, it is worth to note that uterine fibroids and adenomyosis, two common gynecological benign tumours, have different histopathologic characteristics that generate different baseline, cellular and vascular features.…”

“…Furthermore, a recent retrospective study [38] demonstrated that the achievement of NPVr !90% in MRI-guided HIFU treatment of uterine fibroids using multivariate analyses and GEE prediction model. Despite the similar study design and prediction model between our previous [38] and present studies, it is worth to note that uterine fibroids and adenomyosis, two common gynecological benign tumours, have different histopathologic characteristics that generate different baseline, cellular and vascular features. In addition, in contrast with previous study [38], the present study assessed quantitative perfusion MRI features for investigating the potential predictors of the NPV ratio of at least 90%.…”

Clinical approach of perfusion-weighted imaging

“…Semiquantitative DCE PWI was simpler than quantitative DCE PWI by utilizing single multidynamic T1-weighted sequence with GBCE. Semi-quantitative DCE PWI was exploited to achieve parameters relative enhancement, maximal enhancement, maximal relative enhancement, T0, time to peak, wash-in rate, wash-out rate, brevity of enhancement and area under the curve as seen in Figure 2 [7][8][9].…”

“…Semi-quantitative DCE PWI was predominantly applied in perfusion assessment of breast tumor (FIGURE 3), liver tumor (FIGURE 4), bone tumor (FIGURE 5), prostate tumor and brain tumor [1][2][3][4][5][6][7][8][9].…”