Prediction of Clinical Outcome for High-Intensity Focused Ultrasound Ablation of Uterine Leiomyomas Using Multiparametric MRI Radiomics-Based Machine Leaning Model

Risk Factors and Prediction Nomogram of Local Regeneration After Ultrasound-Guided Microwave Ablation of Uterine Fibroids

STUDY OBJECTIVE

To explore the risk factors associated with local regeneration of the treated uterine fibroids (UFs) after microwave ablation (MWA) and to develop a nomogram model for predicting the risk of local regeneration.

DESIGN

Retrospective study.

SETTING

The Eighth Affiliated Hospital of Sun Yat-Sen University.

PATIENTS

Patients with UFs who underwent MWA at our hospital between October 2020 and April 2023 were included.

INTERVENTION

MWA was used for the treatment of UFs.

MEASUREMENTS AND MAIN RESULTS

A total of 47 patients with 68 fibroids were included into this study. Over a median follow-up of 13 months (interquartile range, 8-22 months), local regeneration occurred in 11 UFs. The clinical and imaging characteristics of these patients were recorded and compared. Risk factors for local regeneration were determined through univariate and multivariate Cox regression analysis. Multivariate analysis revealed that the fertility desires, larger size of UFs (≥95.3 cm3), and hyperenhancement of UFs on contrast-enhanced ultrasound were independent risk factors for local regeneration after MWA. A predictive nomogram was constructed to predict the local regeneration after MWA of UFs. The concordance index (C-index) (C-index, 0.924; internal validation C-index, 0.895) and the 1- and 2-year area under the curve values (0.962, 0.927) all indicated that the nomogram had good predictive performance. Calibration and decision curve analysis curves further confirmed the model's accuracy and clinical utility.

CONCLUSION

Fertility desires, larger size of UFs, and hyperenhancement on contrast-enhanced ultrasound were independent predictors of UFs local regeneration after MWA in our study. The nomogram constructed based on the abovementioned independent risk factors may help predict which UFs will develop local regeneration after MWA.

Predicting the Prognosis of HIFU Ablation of Uterine Fibroids Using a Deep Learning-Based 3D Super-Resolution DWI Radiomics Model: A Multicenter Study

RATIONALE AND OBJECTIVES

To assess the feasibility and efficacy of a deep learning-based three-dimensional (3D) super-resolution diffusion-weighted imaging (DWI) radiomics model in predicting the prognosis of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids.

METHODS

This retrospective study included 360 patients with uterine fibroids who received HIFU treatment, including Center A (training set: N = 240; internal testing set: N = 60) and Center B (external testing set: N = 60) and were classified as having a favorable or unfavorable prognosis based on the postoperative non-perfusion volume ratio. A deep transfer learning approach was used to construct super-resolution DWI (SR-DWI) based on conventional high-resolution DWI (HR-DWI), and 1198 radiomics features were extracted from manually segmented regions of interest in both image types. Following data preprocessing and feature selection, radiomics models were constructed for HR-DWI and SR-DWI using Support Vector Machine (SVM), Random Forest (RF), and Light Gradient Boosting Machine (LightGBM) algorithms, with performance evaluated using area under the curve (AUC) and decision curves.

RESULT

All DWI radiomics models demonstrated superior AUC in predicting HIFU ablated uterine fibroids prognosis compared to expert radiologists (AUC: 0.706, 95% CI: 0.647-0.748). When utilizing different machine learning algorithms, the HR-DWI model achieved AUC values of 0.805 (95% CI: 0.679-0.931) with SVM, 0.797 (95% CI: 0.672-0.921) with RF, and 0.770 (95% CI: 0.631-0.908) with LightGBM. Meanwhile, the SR-DWI model outperformed the HR-DWI model (P < 0.05) across all algorithms, with AUC values of 0.868 (95% CI: 0.775-0.960) with SVM, 0.824 (95% CI: 0.715-0.934) with RF, and 0.821 (95% CI: 0.709-0.933) with LightGBM. And decision curve analysis further confirmed the good clinical value of the models.

CONCLUSION

Deep learning-based 3D SR-DWI radiomics model demonstrated favorable feasibility and effectiveness in predicting the prognosis of HIFU ablated uterine fibroids, which was superior to HR-DWI model and assessment by expert radiologists.

The Predictive Effect of Quantitative Analysis of Signal Intensity Heterogeneity on T2-Weighted MR Images for High-intensity Focused Ultrasound Treatment of Uterine Fibroids

RATIONALE AND OBJECTIVES

To investigate whether the quantitative index of signal intensity (SI) heterogeneity on T2-weighted (T2W) magnetic resonance images can predict the difficulty and efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine fibroids.

MATERIALS AND METHODS

The standard deviation (SD) of T2W image (T2WI) SI was used to quantify SI heterogeneity. The correlation between SD and the non-perfused volume ratio (NPVR) in 575 patients undergoing HIFU treatment was retrospectively analyzed, and the efficacy of SD in predicting NPVR was discussed. Three classifications were made based on the SD, and the ablation difficulty and ablation effect of different grades were compared. A total of 65 cases from another center were used as an external validation set to verify the classification performance of SD.

RESULTS

The SD of SI was negatively correlated with NPVR (r = -0.460, p < 0.001). The predictive efficiency of SD for the ablation effect was higher than that of the scaled signal intensity (0.767 vs. 0.701, p = 0.006). Univariate and multivariate logistic regression analyses showed that SD was an independent predictor of ablation effect. Based on SD, the three classifications were divided into SD I: SD < 101.0, SD II: 101.0 ≤ SD < 138.7, and SD III: SD≥ 138.7. The treatment time, sonication time, treatment intensity, and total energy of SD I were lower than those of SD II and III (p < 0.05).

CONCLUSION

The heterogeneity of T2WI SI of uterine fibroids is negatively correlated with NPVR. The SD of SI can be used to predict the ablation difficulty and ablation effect of HIFU.

Predicting the efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine leiomyomas based on DTI indicators and imaging features

PURPOSE

To predict the efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine leiomyomas based on diffusion tensor imaging (DTI) indicators and imaging features.

METHODS

Sixty-two patients with 85 uterine leiomyomas were consecutively enrolled in this retrospective study and underwent DTI scanning before HIFU treatment. Based on whether the non-perfused volume ratio (NPVR) was greater than 70%, all patients were assigned to sufficient ablation (NPVR ≥ 70%) or insufficient ablation (NPVR < 70%) groups. The selected DTI indicators and imaging features were incorporated to construct a combined model. The predictive performance of DTI indicators and the combined model were assessed using receiver operating characteristic (ROC) curves.

RESULTS

There were 42 leiomyomas in the sufficient ablation group (NPVR ≥ 70%) and 43 leiomyomas in the insufficient ablation group (NPVR < 70%). The fractional anisotropy (FA) and relative anisotropy (RA) values were higher in the sufficient ablation group than in the insufficient ablation group (p < 0.05). Conversely, the volume ratio (VR) and mean diffusivity (MD) values were lower in the sufficient ablation group than those in the insufficient ablation group (p < 0.05). Notably, the combined model composed of the RA and enhancement degree values had high predictive efficiency, with an AUC of 0.915. The combined model demonstrated higher predictive performance than FA and MD alone (p = 0.032 and p < 0.001, respectively) but showed no significant improvement compared with RA and VR (p > 0.05).

CONCLUSION

DTI indicators, especially the combined model incorporating DTI indicators and imaging features, can be a promising imaging tool to assist clinicians in predicting HIFU efficacy for uterine leiomyomas.

Prediction of high-intensity focused ultrasound (HIFU)-induced lesion size using the echo amplitude from the focus in tissue

In the realm of high-intensity focused ultrasound (HIFU) therapy, the precise prediction of lesion size during treatment planning remains a challenge, primarily due to the difficulty in quantitatively assessing energy deposition at the target site and the acoustic properties of the tissue through which the ultrasound wave propagates. This study investigates the hypothesis that the echo amplitude originating from the focus is indicative of acoustic attenuation and is directly related to the resultant lesion size. Echoes from multi-layered tissues, specifically porcine tenderloin and bovine livers, with varying fat thickness from 0 mm to 35 mm were collected using a focused ultrasound (FUS) transducer operated at a low power output and short duration. Subsequent to HIFU treatment under clinical conditions, the resulting lesion areas in the ex vivo tissues were meticulously quantified. A novel treatment strategy that prioritizes treatment spots based on descending echo amplitudes was proposed and compared with the conventional raster scan approach. Our findings reveal a consistent trend of decreasing echo amplitudes and HIFU-induced lesion areas with the increasing fat thickness. For porcine tenderloin, the values decreased from 2541.7 ± 641.9 mV and 94.4 ± 17.9 mm2 to 385(342.5) mV and 24.9 ± 18.7 mm2, and for bovine liver, from 1406(1202.5) mV and 94.4 ± 17.9 mm2 to 502.1 ± 225.7 mV and 9.4 ± 6.3 mm2, respectively, as the fat thickness increases from 0 mm to 35 mm. Significant correlations were identified between preoperative echo amplitudes and the HIFU-induced lesion areas (R = 0.833 and 0.784 for the porcine tenderloin and bovine liver, respectively). These correlations underscore the potential for an accurate and dependable prediction of treatment outcomes. Employing the proposed treatment strategy, the ex vivo experiment yielded larger lesion areas in bovine liver at a penetration depth of 8 cm compared to the conventional approach (58.84 ± 17.16 mm2 vs. 44.28 ± 15.37 mm2, p < 0.05). The preoperative echo amplitude from the FUS transducer is shown to be a reflective measure of acoustic attenuation within the wave propagation window and is closely correlated with the induced lesion areas. The proposed treatment strategy demonstrated enhanced efficiency in ex vivo settings, affirming the feasibility and accuracy of predicting HIFU-induced lesion size based on echo amplitude.

An interpretable MRI-based radiomics model predicting the prognosis of high-intensity focused ultrasound ablation of uterine fibroids

BACKGROUND

Accurate preoperative assessment of the efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine fibroids is essential for good treatment results. The aim of this study was to develop robust radiomics models for predicting the prognosis of HIFU-treated uterine fibroids and to explain the internal predictive process of the model using Shapley additive explanations (SHAP).

METHODS

This retrospective study included 300 patients with uterine fibroids who received HIFU and were classified as having a favorable or unfavorable prognosis based on the postoperative nonperfusion volume ratio. Patients were divided into a training set (N = 240) and a test set (N = 60). The 1295 radiomics features were extracted from T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) scans. After data preprocessing and feature filtering, radiomics models were constructed by extreme gradient boosting and light gradient boosting machine (LightGBM), and the optimal performance was obtained by Bayesian optimization. Finally, the SHAP approach was used to explain the internal prediction process.

RESULTS

The models constructed using LightGBM had the best performance, and the AUCs of the T2WI and CE-T1WI models were 87.2 (95% CI = 87.1-87.5) and 84.8 (95% CI = 84.6-85.7), respectively. The use of SHAP technology can help physicians understand the impact of radiomic features on the predicted outcomes of the model from a global and individual perspective.

CONCLUSION

Multiparametric radiomic models have shown their robustness in predicting HIFU prognosis. Radiomic features can be a potential source of biomarkers to support preoperative assessment of HIFU treatment and improve the understanding of uterine fibroid heterogeneity.

CLINICAL RELEVANCE STATEMENT

An interpretable radiomics model can help clinicians to effectively predict the prognosis of HIFU treatment for uterine fibroids. The heterogeneity of fibroids can be characterized by various radiomics features and the application of SHAP can be used to visually explain the prediction process of radiomics models.

Development and validation of a combined model based on dual-sequence MRI radiomics for predicting the efficacy of high-intensity focused ultrasound ablation for hysteromyoma

OBJECTIVES

To determine the value of dual-sequence magnetic resonance imaging (MRI)-based radiomics in predicting the efficacy of high-intensity focused ultrasound (HIFU) ablation for hysteromyoma.

METHODS

A total of 142 patients with 172 hysteromyomas (95 hysteromyomas from the sufficient ablation group, and 77 hysteromyomas from the insufficient ablation group) were enrolled in the study. The clinical-radiological model was constructed with independent clinical-radiological risk factors, the radiomics model was constructed based on the optimal radiomics features of hysteromyoma from dual sequences, and the two groups of features were incorporated to construct the combined model. A fivefold cross validation procedure was adopted to validate these models. A nomogram was constructed, applying the combined model in the training cohort. The models were assessed with receiver operating characteristic (ROC) curves and integrated discrimination improvement (IDI). An independent test cohort comprising 40 patients was used to evaluate the performance of the optimal model.

RESULTS

Among the three models, the average areas under the ROC curves (AUC) of the radiomics model and combined model were 0.803 (95% confidence interval (CI): 0.726-0.881) and 0.841 (95% CI: 0.772-0.909), which were better than the clinical-radiological model in the training cohort. The IDI showed that the combined model had the best prediction accuracy. The combined model also showed good discrimination in both the validation cohort (AUC = 0.834) and the independent test cohort (AUC = 0.801).

CONCLUSION

The combined model based on the dual-sequence MRI radiomics is the most promising tool from our study to assist clinicians in predicting HIFU ablation efficacy.

Transvaginal natural orifice endoscopic surgery for myomectomy: Can it be a conventional surgery?

INTRODUCTION

As a new minimally invasive surgery, transvaginal natural orifice transluminal endoscopic surgery (vNOTES) has been proved to be suitable for the treatment of a variety of gynecological benign diseases. However, compared with other minimally invasive surgeries that have been widely used, such as conventional multiport laparoscopy and transumbilical laparoendoscopic single-site surgery (LESS), their advantages and disadvantages and how to choose are still unknown. The purpose of our study is to compare the advantages and disadvantages of the three minimally invasive surgeries in myomectomy and to provide theoretical basis for the wider development of vNOTES surgery.

MATERIAL AND METHODS

This retrospective study included 282 patients at our hospital who underwent laparoscopic myomectomy from May 2021 to March 2022. Based on the surgical approach, patients were classified into multiport, transumbilical LESS, and vNOTES groups. The patients' demographic characteristics and follow-up data were collected during the perioperative period and at 1 month postoperatively.

RESULTS

Among the three procedures, vNOTES had the shortest anal exhaust time but also the highest postoperative infection rate. Multiple linear regression analysis showed that the operative time increased by 3.5 min for each 1 cm increase in myoma, and intraoperative bleeding increased by approximately 12 ml. The average duration of single pores increased by 25 min compared to that of multiports, and the operative duration increased by 10.48 min for each degree of adhesion.

CONCLUSIONS

For gynecologists who have mastered vNOTES, this procedure has the same efficacy and safety as the two existing minimally invasive surgeries in myomectomy, but it shows obvious advantages in postoperative recovery.