Breast fibroadenomas: a review in the light of current literature

Application of MRI-based tumor heterogeneity analysis for identification and pathologic staging of breast phyllodes tumors

OBJECTIVE

To explore the application value of MRI-based imaging histology and deep learning model in the identification and classification of breast phyllodes tumors.

METHODS

Seventy-seven patients diagnosed as breast phyllodes tumors and fibroadenomas by pathological examination were retrospectively analyzed, and traditional radiomics features, subregion radiomics features, and deep learning features were extracted from MRI images, respectively. The features were screened and modeled using variance selection method, statistical test, random forest importance ranking method, Spearman correlation analysis, least absolute shrinkage and selection operator (LASSO). The efficacy of each model was assessed using the subject operating characteristic (ROC) curve, The DeLong test was used to assess the differences in the AUC values of the different models, and the clinical benefit of each model was assessed using the decision curve (DCA), and the predictive accuracy of the model was assessed using the calibration curve (CCA).

RESULTS

Among the constructed models for classification of breast phyllodes tumors, the fusion model (AUC: 0.97) had the best diagnostic efficacy and highest clinical benefit. The traditional radiomics model (AUC: 0.81) had better diagnostic efficacy compared with subregion radiomics model (AUC: 0.70). De-Long test, there is a statistical difference between the fusion model traditional radiomics model, and subregion radiomics model in the training group. Among the models constructed to distinguish phyllodes tumors from fibroadenomas in the breast, the TDT_CIDL model (AUC: 0.974) had the best predictive efficacy and the highest clinical benefit. De-Long test, the TDT_CI combination model was statistically different from the remaining five models in the training group.

CONCLUSION

Traditional radiomics models, subregion radiomics models and deep learning models based on MRI sequences can help to differentiate benign from junctional phyllodes tumors, phyllodes tumors from fibroadenomas, and provide personalized treatment for patients.

Identification of differentiating sonographic features between fibroadenomas and malignant tumors of the breast mimicking fibroadenomas: 10-year experience in 421 histologically verified cases

Ultrasound is a highly effective imaging tool for assessing abnormalities within the breast. However, especially the identification of malignant tumors of the breast mimicking fibroadenomas (MTMF) by means of breast ultrasound can be challenging. This study aimed to identify reliable imaging characteristics of MTMF.This retrospective study was approved by the local ethics review board. After screening 623 patients, 421 cases with histologically verified fibroadenomas and MTMF between 2011 and 2021 were included. Sonographic features were compared to histopathological results and an algorithm-based quantitative ranking of predictors contributing most to the correct classification of malignant tumors was conducted.A total of 363 benign, 18 intermediate, and 40 malignant lesions were analyzed. Algorithm-based quantitative ranking showed that the most predictive features indicating malignancy were a hyperechoic rim (gain ratio merit 0.135 ± 0.004), an irregular border (0.057 ± 0.002), perilesional stiffening (0.054 ± 0.002), pectoral contact (0.051 ± 0.003), an irregular shape (0.029 ± 0.001), and irregular vasculature (0.027 ± 0.002).Ultrasound findings for fibroadenomas vary, making identification of MTMF challenging. Features such as indistinct margins and increased perilesional echogenicity are predictors for malignancy and should be considered during sonographic evaluation of fibroadenomas and MTMF.

Development of a nomogram for predicting malignancy in BI-RADS 4 breast lesions using contrast-enhanced ultrasound and shear wave elastography parameters

This study aimed to develop a Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression (LR) model using quantitative imaging features from Shear Wave Elastography (SWE) and Contrast-Enhanced Ultrasound (CEUS) to assess the malignancy risk of BI-RADS 4 breast lesions (BLs). The features predictive of malignancy in the LASSO analysis were used to construct a nomogram. Female patients (n = 111) with BI-RADS 4 BLs detected via routine ultrasound at Ma'anshan People's Hospital underwent SWE, CEUS, and histopathological examinations were enrolled in this study. The histopathological results served as the gold standard. A time-intensity curve (TIC) was used to analyze the peak intensity (PI), area under the curve (AUC), and other CEUS parameters. The Young's modulus was used for the SWE analysis. Bootstrap sampling was used to validate the nomogram. The performance of the model was evaluated using calibration curves, receiver operator characteristics curve (ROC) analysis, and decision curve analysis (DCA). The histopathological analysis revealed 35 malignant and 76 benign BLs. The multivariate LR analysis identified PI (odds ratio [OR] = 5.788, p < 0.05), AUC (OR = 6.920, p < 0.05), and SWE_Max (OR = 10.802, p < 0.05) as predictive of malignancy. The nomogram based on these features demonstrated an AUC of 0.875 (95% CI 0.805-0.945), sensitivity of 88.6%, specificity of 68.4%, good calibration, and excellent clinical utility. The nomogram could be used to improve the classification of BI-RADS 4 BLs and hence reduce the need for invasive biopsies to confirm malignancy.

Clinical efficacy and safety of ultrasound-guided high-intensity focused ultrasound for breast fibroadenoma: a systematic review and meta-analysis

OBJECTIVE

The purpose of this systematic review and meta-analysis was to assess the clinical efficacy and safety of ultrasound (US)-guided high intensity focused ultrasound (HIFU) in the treatment of breast fibroadenoma in different studies.

METHODS

Studies evaluating the efficacy and safety of US-guided HIFU in the treatment of histologically-proven FA with follow-up outcomes of more than 3 months were searched through MEDLINE/PubMed databases. Volume reduction rate (VRR) and side effects were extracted and compared for further analysis.

RESULTS

Of 29 identified articles, 10 studies involving 385 women and more than 545 FAs met the inclusion criteria. The mean VRR at 6 months and 12 months after HIFU was 52.00% and 72.00%. In terms of intraoperative safety, nine studies reported mild to moderate pain, with an average visual analogue scale (VAS) score ranging from 1.60 to 7.10. The most common postoperative side effect associated with HIFU was subcutaneous ecchymosis and less frequent were pain, erythema, and skin pigmentation, most of which disappeared within weeks. No serious side effects were observed.

CONCLUSION

S-guided HIFU is an effective and safe noninvasive treatment for breast FA that does not cause serious side effects. Further studies are needed to explore crucial influencing factors of VRR.

MS-CFNet: a multi-scale clinical studying-based and feature extraction-guided network for breast fibroadenoma segmentation in ultrasonography

Segmenting breast tumors in ultrasonography is challenging due to the low image quality and presence of artifacts. Radiologists' studying and diagnosis skills are integrated with artificial intelligence to establish a clinical learning-based deep learning network in order to robustly extract and delineate features of breast fibroadenoma. The spatial local feature contrast (SLFC) module captures overall tumor contours, while the channel recursive gated attention (CRGA) module enhances edge perception through high-dimensional information interaction. Additionally, full-scale feature fusion and enhanced deep supervision are applied to improve model stability and performance. To achieve smoother boundaries, we introduce a new loss function (cosh-smooth) that penalizes and finely tunes tumor edges. Our dataset comprises 1016 clinical ultrasound images of breast fibroadenoma with labeled masks, alongside a publicly available dataset of 246 ones. Segmentation performance is evaluated using the Dice similarity coefficient (DSC) and mean intersection over union (MIOU). Extensive experiments demonstrate that our proposed MS-CFNet outperforms state-of-the-art methods. Compared to TransUNet as a baseline model, MS-CFNet improves by 1.47% in DSC and 2.56% in MIOU. The promising result of MS-CFNet is attributed to the integration of radiologists' clinical diagnosis procedure and the bionic mindset, enhancing the network's ability to recognize and segment breast fibroadenomas effectively.

Efficacy and safety of vacuum-assisted excision (VAE) of fibroadenomas: experience in a tertiary centre

PURPOSE

To evaluate the technical success and efficacy rates of US-guided percutaneous vacuum-assisted excision (VAE) of breast fibroadenomas, also assessing procedural complications and long-term patient satisfaction rates.

MATERIALS AND METHODS

The institutional database of a tertiary breast cancer referral centre was retrospectively reviewed to retrieve all women with fibroadenomas who underwent US-guided VAE between May 2011 and September 2019. We subsequently included in this study all fibroadenomas with a maximum diameter of 3 cm at US and an available histological confirmation obtained by core-needle biopsy before VAE. Immediately after VAE, technical success (defined as the correct VAE execution) and the occurrence of procedural complications were evaluated. Imaging follow-up (US ± mammography) after 6, 12, 24 and 36 months was performed to evaluate technical efficacy (defined as the absence of fibroadenoma recurrence at 6-month follow-up). Long-term patient satisfaction was evaluated with telephonic interviews in October 2022.

RESULTS

We retrospectively included 108 women (median age 46 years) with 110 fibroadenomas diagnosed at core-needle biopsy with a median lesion size at US of 12 mm. Technical success was obtained in 110/110 VAEs (100%). Minor procedural complications (haematomas) occurred in 7/110 VAEs (6%), whereas 8/110 patients had a fibroadenoma recurrence at 6-month follow-up, resulting in a 93% technical efficacy (102/110 VAEs). All patients available for telephonic follow-up (104/104, 100%) reported high satisfaction with VAE results.

CONCLUSION

US-guided VAE is a safe and effective procedure for the excision of fibroadenomas, representing a viable alternative to surgery, with a low complication rate and high patient satisfaction.

Prevalence, Impact, and Diagnostic Challenges of Benign Breast Disease: A Narrative Review

Benign breast diseases, which are commonly seen in clinical practice, have various clinical presentations and implications, as well as management strategies. This article describes common benign breast lesions, presentations of these lesions, and typical radiographic and histologic findings. Also included in this review are the most recent data and guideline-based recommendations for the management of benign breast diseases at diagnosis, including surgical referral, medical management, and ongoing surveillance.

Focused ultrasound ablation surgery for multiple breast fibroadenomas: pathological and follow-up results

OBJECTIVE

To investigate the histopathological findings and follow-up outcome of focused ultrasound ablation surgery (FUAS) treatment of multiple fibroadenomas (FA).

METHODS

A total of 20 patients with 101 multiple FAs were enrolled. After one session FUAS ablation, 21 lesions (≥15.0 mm) were surgically removed within one week for histopathological analysis, including 2, 3, 5-triphenyltetrazolium chloride (TTC) staining, H&E staining, nicotinamide adenine dinucleotide (NADH) -flavretin enzyme staining, Transmission electron microscope (TEM) and scanning electron microscope (SEM). The remaining 80 lesions were followed up at 3, 6 and 12 months after treatment.

RESULTS

All ablation procedures were performed successfully. Pathologic findings showed that irreversible damage of FA was confirmed. TTC, H&E and NADH staining and TEM/SEM demonstrated tumor cell death and tumor structural destruction at the gross, cellular, and subcellular levels, respectively. The median shrinkage rate at 12 months post-FUAS was 66.4 (43.6, 89.5) %.

CONCLUSION

Histopathological analysis for FAs after FUAS treatment proved that FUAS could effectively induce irreversible coagulative necrosis of FA, and the tumor volume would gradually shrink in follow-up. FUAS was safe and effective to treat multiple FAs with good cosmesis.Key pointsThis study was the first study of detailed histopathological analysis for FAs after FUAS treatment.FUAS can effectively induce irreversible coagulative necrosis of fibroadenoma cells.FUAS ablation of multiple fibroadenomas is safe and effective.

Evaluating the learning curve of high intensity focus ultrasound for breast fibroadenoma by CUSUM analysis: a multi-center study

OBJECTIVE

To explore the learning curve of high intensity focus ultrasound (HIFU) treatment for breast fibroadenoma.

METHODS

A database of 110 patients with 255 breast fibroadenomas who underwent HIFU treatment at two different clinical centers (Center 1 and 2) were retrospectively analyzed. The learning curves of HIFU treatment for breast fibroadenoma were drawn by CUSUM analysis in two centers, respectively. According to the inflection point of the learning curves, the treatment was divided into two groups: initial phase and consolidation phase. HIFU treatment parameters were compared between two groups. The effectiveness and safety results were also evaluated.

RESULTS

The inflection points of the learning curves were the 60^th treatment in Center 1 and the 65^th treatment in Center 2. The screening time, treatment time, sonication time and hyperechoic scale change time were significantly shorter in consolidation phase than those in initial phase of the two centers (p < 0.05). There were no differences in non-perfused volume (NPV) ratio and energy effect factor (EEF) between the two groups in Center 1, while in Center 2, these above-mentioned results in consolidation phase led to a greater improvement than those in initial phase. There was no difference of Visual Analogue Scale (VAS) scores and no adverse event observed in both centers.

CONCLUSION

HIFU treatment for breast fibroadenoma was effective and safe. The learning curve of HIFU treatment for breast fibroadenoma can be completed after treating 60-65 tumors without increasing the safety risk.

Imaging of fibroadenoma: Be careful with imaging follow-up

The present letter to the editor is related to the study titled, “Preoperational diagnosis and management of breast ductal carcinoma in situ arising within fibroadenoma: Two case reports.” Fibroadenoma is the most common benign mass lesion in young females. Based on this study showing that malignancy can develop on fibroadenomas, we want to emphasize that careful sonographic follow-up of fibroadenomas should be done and that each lesion should be followed carefully and separately in cases with multiple fibroadenomas. Additionally, we want to emphasize the critical role of sonographic examination in diagnosing fibroadenoma, the importance of correctly defining benign and malignant sonographic findings, and which lesions should be followed up sonographically and which lesions should be evaluated histopathologically.