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MR-guided high-intensity focused ultrasound (MR-HIFU) is an effective method for treating symptomatic uterine fibroids, especially solitary lesions. The aim of our study was to compare the clinical and morphological outcomes of patients who underwent MR-HIFU due to solitary fibroid (SF) or multiple fibroids (MFs) in a prospective clinical trial. We prospectively included 21 consecutive patients with SF (10) and MF (11) eligible for MR-guided HIFU. The morphological data were assessed using mint Lesion™ for MRI. The clinical data were determined using the Uterine Fibroid Symptom and Quality of Life (UFS-QOL) questionnaire before and 6 months after treatment. Unpaired and paired Wilcoxon-test and t-tests were applied, and Pearson’s coefficient was used for correlation analysis. A p-value of 0.05 was considered statistically significant. The volume of treated fibroids significantly decreased in both the SF (mean baseline: 118.6 cm3; mean 6-month follow-up: 64.6 cm3) and MF (107.2 cm3; 55.1 cm3) groups. The UFS-QOL showed clinical symptoms significantly improved for patients in both the SF and MF groups regarding concern, activities, energy/mood, and control. The short-term outcome for the treatment of symptomatic fibroids in myomatous uterus by MR-guided HIFU is clinically similar to that of solitary fibroids.

Abstract Objective Fibroids are hormonally dependent uterine tumors. The literature on adiposity and fibroid prevalence is inconsistent. Previous work usually combined all those with a body mass index (BMI) ≥30 kg/m2 into a single category and relied on clinically diagnosed fibroids, which misclassifies the many women with undiagnosed fibroids. We used a prospective cohort design with periodic ultrasound screening to investigate associations between repeated measures of BMI and fibroid incidence and growth assessed at each follow-up ultrasound. Methods The Study of Environment, Lifestyle & Fibroids followed 1693 Black/African American women, ages 23 to 35 years from Detroit, Michigan, with ultrasound every 20 months for 5 years. Measured height and repeated weight measures were used to calculate BMI. Fibroid incidence was modeled using Cox models among those who were fibroid free at the enrollment ultrasound. Fibroid growth was estimated for individual fibroids matched across visits as the difference in log-volume between visits and was modeled using linear mixed models. All models used time-varying BMI and adjusted for time-varying covariates. Results Compared with BMI <25 kg/m2, those with BMI 30 to <35 kg/m2 had increased fibroid incidence (adjusted hazard ratio, 1.37; 95% CI, 0.96-1.94), those with BMI ≥40 kg/m2 had reduced incidence (adjusted hazard ratio, 0.61; 95% CI, 0.41-0.90). Fibroid growth had mostly small magnitude associations with BMI. Conclusion BMI has a nonlinear association with fibroid incidence, which could be driven by effects of BMI on inflammation and reproductive hormones. More detailed measures of visceral and subcutaneous adiposity and their effects on hormones, DNA damage, and cell death are needed.

Purpose Uterine fibroid is the most common benign tumor in female reproductive organs. In order to guide the treatment, it is crucial to detect the location, shape, and size of the tumor. This study proposed a deep learning approach based on attention mechanisms to segment uterine fibroids automatically on preoperative Magnetic Resonance (MR) images. Methods The proposed method is based on U‐Net architecture and integrates two attention mechanisms: channel attention of squeeze‐and‐excitation (SE) blocks with residual connections, spatial attention of pyramid pooling module (PPM). We did the ablation study to verify the performance of these two attention mechanisms module and compared DARU‐Net with other deep learning methods. All experiments were performed on a clinical dataset consisting of 150 cases collected from our hospital. Among them, 120 cases were used as the training set, and 30 cases are used as the test set. After preprocessing and data augmentation, we trained the network and tested it on the test dataset. We evaluated segmentation performance through the Dice similarity coefficient (DSC), precision, recall, and Jaccard index (JI). Results The average DSC, precision, recall, and JI of DARU‐Net reached 0.8066 ± 0.0956, 0.8233 ± 0.1255, 0.7913 ± 0.1304, and 0.6743 ± 0.1317. Compared with U‐Net and other deep learning methods, DARU‐Net was more accurate and stable. Conclusion This work proposed an optimized U‐Net with channel and spatial attention mechanisms to segment uterine fibroids on preoperative MR images. Results showed that DARU‐Net was able to accurately segment uterine fibroids from MR images.

Uterine fibroids (UFs) are common tumors in women of reproductive age. It is imperative to comprehend UFs’ associated risk factors to facilitate early detection and prevention. Simple relying on surgical/pharmacological treatment of advanced disease is not only highly expensive, but it also deprives patients of good quality of life (QOL). Unfortunately, even if the disease is discovered early, no medical intervention is traditionally initiated until the disease burden becomes high, and only then is surgical intervention performed. Furthermore, after myomectomy, the recurrence rate of UFs is extremely high with the need for additional surgeries and other interventions. This confused approach is invasive and extremely costly with an overall negative impact on women’s health. Secondary prevention is the management of early disease to slow down its progression or even halt it completely. The current approach of watchful observation for early disease is considered a major missed opportunity in the literature. The aim of this article is to present an approach named the ESCAPE (Evidence-Based Approach for Secondary Prevention) of UF management. It comprises simple, inexpensive, and safe steps that can arrest the development of UFs, promote overall reproductive health, decrease the number of unnecessary surgeries, and save billions of health care systems’ dollars worldwide.

Background/Objectives: One of the common gynecological issues that can have a major effect on women’s reproductive health and quality of life is uterine fibroids (UFs). For personalized treatment planning and a reduction in long-term consequences, early fibroid prognosis and recurrence prediction are essential. In this context, prognosis refers to anticipated symptom progression and treatment response, while recurrence prediction estimates the likelihood of regrowth after interventions such as myomectomy, uterine artery embolization (UAE), or new fibroid formation during follow-up. Conventional techniques for predicting the prognosis and recurrence of UFs depend on imaging, clinical evaluations, and statistical models; nevertheless, they frequently have limited accuracy and are subjective. Methods: Therefore, we introduce FibroidX, which utilizes vision transformers and self-attention processes to improve forecast accuracy, automate feature extraction, and offer customized risk evaluations to overcome these obstacles. Prognosis encompasses overall disease progression, symptom severity, and response to therapy, whereas recurrence prediction focuses on post-treatment regrowth or new fibroid formation. Results: The dataset comprises 1990 ultrasound images split into training-test sets (80-20). With an accuracy of 98.4%, the suggested model outperformed baseline models like Model A (92.3%) and Model B (94.1%), exhibiting exceptional performance. A significant percentage of accurately anticipated cases was ensured by the precision and recall values, which were 97.8% and 96.9%, respectively. The model’s balanced precision-recall trade-off is highlighted by its F1-score of 97.3%, and its exceptional class distinction is confirmed by its AUC-ROC score of 0.99. Conclusions: The model was suitable for real-time applications, with an average inference time of 0.02 s per sample. The proposed method showed its effectiveness and reliability in prediction tasks. It achieved a 15% increase in accuracy and a 12% reduction in the false positive rate compared to traditional machine learning techniques.

Objective To evaluate implementation of a patient decision aid for symptomatic uterine fibroid management to improve shared decision-making at five clinical settings across the United States. Methods We used a type 3 hybrid effectiveness-implementation stepped-wedge design and the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) planning and evaluation framework. We conducted clinician training, monthly reach tracking with feedback to site clinical leads, patient and clinician surveys, and visit audio-recordings. Implementation strategies included assessment of organizational readiness for shared decision-making, synchronous clinician training, audit and feedback of decision aid reach, and access to multiple decision aid formats. Outcomes and analyses included patient-level reach, clinician-level adoption, and associations of patient-reported decision aid exposure (as treated) and setting-level implementation (intention-to-treat) with patient-reported (collaboRATE measure) and observed (OPTION-5 measure) shared decision-making. We also designed and assessed setting-level plans for sustainability and other factors impacting sustained decision aid use. Results The decision aid was adopted by 72 of the 74 eligible gynecologists (97%) and reached 2553 patients across five settings. CollaboRATE scores improved among patients who reported receiving the decision aid (as-treated analysis, 69% vs. 59%; OR 1.6, 95% CI 1.16–2.27). CollaboRATE scores remained consistent before and after setting-level decision aid implementation (intention-to-treat analysis, 64% vs. 63%; OR 0.86, 95% CI 0.61–1.22). Participants would prefer to receive a decision aid at multiple time points (91.9% before the visit, 90.7% during the visit, 86.5% after the visit). Shared decision-making experiences did not improve when comparing pre vs. post-implementation collaboRATE scores across included settings (intention-to-treat, 64% vs. 63%; OR 0.86, 95% CI 0.61–1.22). Conclusion When patients with symptomatic uterine fibroids are given decision aids, they report higher shared decision-making scores. However, the differences we observed between the as-treated and intention-to-treat results suggest that unaddressed implementation challenges continue to limit the extent to which patients receive decision aids and likely hinder their overall impact. Future efforts to implement decision aids should explore enhancing their integration into clinical workflows and standard operating procedures, supported by organizational incentives that prioritize shared decision-making. Trial registration ClinicalTrials.gov NCT03985449; registered 6 June 2019.

Digital variance angiography (DVA), a recently developed image processing technology, provides a higher contrast-to-noise ratio (CNR) and better image quality during lower limb interventions than digital subtraction angiography (DSA). Our aim was to investigate whether the quality reserve of DVA can also be observed in uterine fibroid embolization (UFE). In this retrospective observational study, the CNR and image quality of DSA and DVA images from 56 patients (mean ± standard deviation age: 44.2 ± 5.3 years) who underwent UFE at our institution were assessed. For the visual evaluation of the same image pairs, the visibility of large vessels, small vessels, tissue blush, and background noise was compared by three experienced readers using a four-grade Likert scale. Data were analyzed using the Wilcoxon signed-rank test or the one-sample Wilcoxon test. DVA provided significantly higher CNR than DSA (the median CNR /CNR was 1.96). In the visual comparison of DVA and DSA images, Likert scores did not significantly differ from zero (equal quality level) in any evaluated categories. The median (interquartile range) values were 0.00 (1.00) for large vessels, -0.33 (1.33) for small vessels, 0.00 (0.67) for tissue blush, and 0.00 (0.75) for background noise. Although the visual image quality of DSA and DVA was identical, DVA provided a twofold CNR in UFE, indicating a significant quality advantage for this technology. The observed quality reserve may allow for dose management (reduction of applied radiation dose and/or contrast media), enhancing the safety of UFE for both patients and personnel.

Background/Objectives: Transcervical fibroid ablation (TFA) is an incisionless method to treat symptomatic uterine fibroids. While safety regarding future pregnancy remains to be established, TFA does not preclude the possibility of pregnancy, and a previous 36-patient case series of post-TFA pregnancies reported normal outcomes. That prior series did not include postmarket cases in the United States, as the Sonata® System was initially cleared and used in Europe. This is a substantive update of known pregnancies with the Sonata System since June 2011, and includes pregnancies in Europe, Mexico, and the US. Methods: TFA was carried out under both clinical trial and postmarket use to treat symptomatic uterine fibroids. All post-TFA pregnancies reported by physicians with their patient’s consent were included. Results: 89 pregnancies and 55 deliveries have occurred among 72 women treated with the Sonata System. This includes 8 women who conceived more than once after TFA. Completed pregnancies (n = 62 women) include 19 vaginal deliveries, 35 Cesarean sections, 5 therapeutic abortions, 1 ectopic pregnancy, and 1 delivery by an unknown route. Ten pregnancies are ongoing. Mean birthweight was 3276.7 ± 587.3 g. Ten women experienced 18 first-trimester spontaneous abortions (SAbs), with 10 of the 18 SAbs (55.6%) occurring between two patients with a history of recurrent abortion. The SAb rate was 22.8%, inclusive of these two patients, and 10.1% if they were excluded as outliers. There were no instances of uterine rupture, placenta accreta spectrum, or stillbirth. Conclusions: This case series, the largest to date for any hyperthermic ablation modality, suggests that TFA with the Sonata System could be a feasible, safe treatment option regarding eventual pregnancy in women with symptomatic uterine fibroids.

Objective To evaluate the impact of fibroid size on maternal and neonatal outcomes, determine whether a dose–response pattern exists across size categories (< 5 cm, 5–10 cm, > 10 cm), and identify a threshold at which pregnancy risk increases significantly. Methods This retrospective cohort study included 651 pregnant women with sonographically confirmed uterine fibroids. Participants were stratified into three groups based on the maximum diameter of the largest fibroid: <5 cm, 5–10 cm, and > 10 cm. Outcomes assessed included preterm birth, PPROM, malpresentation, caesarean delivery, postpartum haemorrhage (PPH), fetal growth restriction (FGR), NICU admission, miscarriage, surgical outcomes such as operative time and blood loss, and a composite adverse perinatal outcome (CAPO). Logistic regression analysis was performed to identify variables independently associated with CAPO. Results Adverse events rose stepwise with fibroid size. Preterm birth occurred in 12.3%, 24.1% and 36.1% of the size groups ( p  < 0.001); PPROM in 2.5%, 10.6% and 13.9% ( p  < 0.001); malpresentation in 13.3%, 28.6% and 47.2% ( p  < 0.001). Caesarean deliveries were 56.6%, 67.3% and 92.1%, while PPH rose from 1.3 to 30.6% (both p  < 0.001). Operative blood loss and time likewise increased with diameter. Neonatally, mean birthweight declined (3150 g, 2995 g, 2870 g; p  = 0.003); NICU admission rose from 13.5 to 34.1% ( p  < 0.001), and CAPO from 14.8 to 35.1% ( p  < 0.001). Multivariate analysis showed that fibroids > 5 cm independently predicted CAPO (aOR: 1.84 for 5–10 cm; 3.78 for > 10 cm), while maternal age, parity, IVF were not significant. Descriptive subgroup analysis revealed longer operative times and greater blood loss in women with multiple, cervical, or combined-type fibroids. Conclusion Fibroid diameter emerged as a key determinant of obstetric and neonatal risk. Lesions > 5 cm, particularly > 10 cm, were associated with markedly increased rates of maternal haemorrhage, preterm birth, and neonatal morbidity. Such pregnancies should be managed as high-risk, with enhanced antenatal surveillance and individualized delivery planning.

Background and Objectives: Hormonal replacement therapy (HRT) is effective in treating many debilitating symptoms of menopause. However, its use in women with uterine fibroids is widely debated, based on the susceptibility of these tumors to sexual steroids. This review aims to ascertain the effects of HRT on leiomyomas development and growth in postmenopausal women. Materials and Methods: Electronic databases (i.e., MEDLINE, Scopus, ClinicalTrials.gov, EMBASE, Sciencedirect, the Cochrane Library at the CENTRAL Register of Controlled Trials, Scielo) were searched from January 1990 until May 2019. All English-written studies evaluating the impact of various HRT regimens on uterine leiomyomas were selected. Results: Seventeen papers, considering a total of 1122 participants, were included. Fifteen of these were prospective trials, of which nine were randomized controlled trials. The remaining two works were a retrospective observational trial and a retrospective case series respectively. Five studies evaluated the effects of tibolone, also comparing it with various estrogen/progestin combinations, while two were about raloxifene. Thirteen studies compared different combinations of estrogens/progestins, the most common being transdermal estrogens (used in nine studies) and medroxyprogesterone acetate at different doses (used in 10 studies). Conclusions: For women with uterine fibroids, the choice of the most appropriate HRT regimen is crucial to avoid leiomyomas growth and the symptoms possibly related to it. Available data are conflicting, but suggest that uterine fibroids might be influenced by HRT, without representing an absolute contraindication to hormonal replacement therapy. Women with uterine fibroids subjected to HRT should be periodically examined and hormonal treatment should be discontinued if leiomyomas appear to increase in size. Moreover, the minimal effective dose of progestin should be employed.