Which Modality Should Be Integrated to Increase the Diagnostic Efficiency of BI-RADS 0, 3, and 4 Lesions? Ultrasonography or Digital Breast Tomosynthesis?

Background: Digital mammography (DM) is one of the most common and effective radiological methods for breast cancer screening and detection. A dense fibroglandular breast tissue can lead to false negative results by superimposing on the lesion margins. Therefore, adjunctive imaging methods, such as digital breast tomosynthesis (DBT) and ultrasonography (US), are needed to increase mammographic sensitivity. Objectives: This study aimed to examine the contribution of US and DBT to DM in different patient groups (patients group of BI-RADS 0 and 3-4 lesions, patients with dense breast parenchyma, patients with non-dense breast parenchyma).. Whether US and DBT can upgrade or downgrade the BI-RADS category of uncertain lesions detected on DM was also investigated. Patients and Methods: Forty-six patients, who were classified as BI-RADS categories 0, 3, and 4 in DM, according to DBT and US findings, were included in the study. DM followed by DBT was performed for the patients, and the BI-RADS classification system was applied. Subsequently, the patients were evaluated sonographically, and the BI-RADS system was applied according to the US results. Each BI-RADS category was compared with the histopathological and multimodality follow-up results. The diagnostic performance of all modalities was also examined alone and in combination. Results: The sensitivity and specificity of DM alone was 42% and 87%, respectively. DBT detected the lesions with 92% sensitivity and 68% specificity. The modality with the highest sensitivity for the detection of malignant lesions was US (100%). Besides, the specificity of DBT was significantly high for dense breasts (P < 0.001). There was no significant difference in terms of the diagnostic accuracy of US measurements between dense and non-dense breasts. For indeterminate lesions, the integration of DBT and US to DM increased the diagnostic accuracy. Conclusion: The contribution of DBT is more valuable than US in patients with dense breast parenchyma.

Intraparenchymal Breast Leiomyoma and Atypical Leiomyoma

Introduction: Intraparenchymal breast leiomyoma is a rare lesion of breast. The diagnostic criteria to differentiate benign and borderline breast leiomyoma was not yet clear. No atypical leiomyoma of breast parenchyma has been reported. Case series presentation: We described one case of leiomyoma and one case of bilateral atypical leiomyoma in breast parenchyma. The morphological features that lead to the diagnosis of atypical leiomyoma include invasive growth pattern, mild nuclear atypia and mitotic figures up to 3mitoses/10HPF. Conclusion Due to the limited experience, cases presented as atypical intraparenchymal breast leiomyoma should be closely followed.

AI-enhanced simultaneous multiparametric 18F-FDG PET/MRI for accurate breast cancer diagnosis

Purpose To assess whether a radiomics and machine learning (ML) model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI can discriminate between benign and malignant breast lesions. Methods A population of 102 patients with 120 breast lesions (101 malignant and 19 benign) detected on ultrasound and/or mammography was prospectively enrolled. All patients underwent hybrid 18F-FDG PET/MRI for diagnostic purposes. Quantitative parameters were extracted from DCE (MTT, VD, PF), DW (mean ADC of breast lesions and contralateral breast parenchyma), PET (SUVmax, SUVmean, and SUVminimum of breast lesions, as well as SUVmean of the contralateral breast parenchyma), and T2-weighted images. Radiomics features were extracted from DCE, T2-weighted, ADC, and PET images. Different diagnostic models were developed using a fine Gaussian support vector machine algorithm which explored different combinations of quantitative parameters and radiomics features to obtain the highest accuracy in discriminating between benign and malignant breast lesions using fivefold cross-validation. The performance of the best radiomics and ML model was compared with that of expert reader review using McNemar’s test. Results Eight radiomics models were developed. The integrated model combining MTT and ADC with radiomics features extracted from PET and ADC images obtained the highest accuracy for breast cancer diagnosis (AUC 0.983), although its accuracy was not significantly higher than that of expert reader review (AUC 0.868) (p = 0.508). Conclusion A radiomics and ML model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI images can accurately discriminate between benign and malignant breast lesions.

Contrast-enhanced spectral mammography: successful initial clinical institute experience

Background Contrast-enhanced spectral mammography (CESM) is a relatively newly developed advanced application with modification of digital mammography by the use of a contrast agent, but still has little known efficacy among Egyptian patients. Our aim in this study is to share our initial experience in evaluating symptomatic patients with different ACR breast parenchyma especially in dense breast parenchyma as it is always challenging in diagnosis. Results CESM in this study gave a sensitivity of 92% and specificity of 85% in characterization of benign and malignant lesions. For postoperative cases, sensitivity was 85% and specificity was 60%. For chemotherapy cases, sensitivity was 85% and specificity was 76%. Contrast uptake was noted in 68% of masses. Cavitary benign lesions were noted in 22.1% of cases. Multifocal and multicentric carcinomas were detected in 39.7% of pathologically proved malignant masses. Statistical analysis revealed sensitivity, specificity, and accuracy of 82.9%, 76.5%, and 81.0% for conventional mammograms as compared to 92.7%, 82.4%, and 89.7% for CESM respectively. Conclusion CESM is a promising technique that can enhance the specificity of conventional mammograms. It is an easy, simple, and rapid contrast-based procedure, especially for characterization of lesions in dense breast parenchyma. It performs proper diagnosis for high-risk patients and follow-up response to different lines of management.

Superomedial Reduction Mammoplasty Affects Patients’ Ability to Breastfeed in a Distinct Manner: A Multicenter Study of 303 Patients

Background Breast reduction using the superomedial technique can relieve symptoms related to breast hypertrophy; however, as the lateral and inferior portion of the breast parenchyma is removed and displaced, reduction mammoplasty may lead to an impaired ability to breastfeed. Objectives To assess the patient's ability to breastfeed after superomedial reduction mammoplasty. Methods This was a cross-sectional study including patients treated with superomedial reduction mammoplasty between January 2009 and December 2018 at two tertiary hospitals in Denmark. Patients were stratified into two cohorts, depending on whether they had childbirth before or after their reduction mammoplasty. Patients were sent specific questionnaires regarding maternity, breastfeeding before and after reduction mammoplasty, nipple sensitivity, and current demographic information. Operative details were retrieved from electronic medical records. Results We identified 303 patients eligible for this study (37 patients giving birth after and 266 before reduction mammoplasty). Fewer patients were able to breastfeed exclusively for the recommended six months after reduction mammoplasty (2/37 = 5.41%) compared to before (92/266 = 34.59%, p&lt;0.05). Also, fewer patients were able to breastfeed at all after reduction mammoplasty (18/37 = 48.64%) compared to before mammoplasty (241/266 = 90.60%, p&lt;0.001). Patients unable to breastfeed after reduction mammoplasty had less nipple sensitivity and more breast tissue excised (p&lt;0.05). Conclusions Superomedial reduction mammoplasty seems to impair the patient's ability to breastfeed exclusively for the recommended 6 months. Patients of childbearing age considering reduction mammoplasty should be made aware that reduction mammoplasty reduces their breastfeeding capacity.

Relation Between Post-Augmentation Parenchymal Atrophy and Local Tissue Pressure

Background Breast parenchyma interacts dynamically with an inserted implant, which may lead to local atrophy and sensory involvement, changes in vascular tissue and lactation, besides volume reduction over time. The inversely proportional relationship between pressure and volume cannot be stated with certainty, that is, the larger implants having more local pressure would lead to compression, thus leading to atrophy of parenchyma more intensely when compared with smaller implants. The objective of this study was to assess and list breast parenchyma volume changes with different pressure levels due to silicone implants of several sizes. Objectives To list the pressure exerted by silicone implants and the atrophy caused in the breast tissue. Methods Thirty-six women were placed in 3 groups (n=12) and subjected to augmentation mammoplasty in the subglandular plane. The measurement of pressure in millimeters of mercury was done with help of molds with the same base and projection of implants introduced posteriorly. The magnetic resonance imaging was done in all participants in the pre-operative period and at 6 and 12 months after surgery. Results Twelve months after breast implant insertion, the groups had a significant glandular volume reduction (mean 12.97% in the right breast and 12.42% in the left breast). There is a statistically significant difference in the proportions of volume reduction and the pressure levels measured. Conclusions A reduction in breast volume was verified. This reduction is also related to the level of pressure exerted on the implant.

AI-enhanced Synchronized Multiparametric 18F-FDG PET/MRI for Accurate Breast Cancer Diagnosis

Purpose: to assess whether a radiomics and machine learning (ML) model combining quantitative parameters and radiomics features extracted from synchronized multiparametric 18F-FDG PET/MRI images can differentiate benign and malignant breast lesions.Methods: 102 consecutive patients with 120 BI-RADS 0, 4 and 5 breast lesions (101 malignant, 19 benign) detected by ultrasound and/or mammography were prospectively enrolled and underwent hybrid 18F-FDG PET/MRI for diagnostic purposes. Quantitative parameters and radiomics features were extracted from dynamic contrast-enhanced (MTT, VD, PF), diffusion (ADCmean of breast lesions and contralateral breast parenchyma), PET (SUVmax, mean and minimum of breast lesions, SUVmean of uni- and contralateral breast parenchyma) and T2-w images. Different diagnostic models were developed using a fine gaussian support vector machine algorithm and exploring different combinations of quantitative parameters and radiomics features to obtain the highest accuracy in discriminating benign from malignant breast lesions using a 5-fold cross validation. The performance of the best radiomics and ML model was compared with that of expert readers review physician using the McNemar test.Results: Eight radiomics models were developed. The integrated model combining MTT and ADC with radiomics features extracted from PET and ADC images obtained the highest accuracy for breast cancer diagnosis (AUC 0.983) and was higher (AUC 0.868) yet not significant to expert readers review (p=0.508).Conclusion: A radiomics and ML model combining quantitative parameters and radiomics features extracted from synchronized multiparametric 18F-FDG PET/MRI images can accurately discriminate benign from malignant breast lesions.

Giant epidermal inclusion cyst with infection arising within the breast parenchyma: a case report

Epidermal inclusion cysts (EICs) of the breast develop in the deep breast parenchyma, and they are very rare. Only about 10 cases have been reported in the English-language literature to date. In this report, we present a rare case of a giant EIC with infection arising within the deep breast parenchyma. Unlike a typical EIC of the breast, the EIC in the present case was a cystic and solid lesion containing a large amount of liquid within the cyst and popcorn-like calcification in the wall. In this report, we describe the contrast-enhanced spectral mammography (CESM), ultrasonography, and computed tomography findings and provide a reference for the diagnosis of EICs. To the best of our knowledge, this is the first report of the CESM findings of an EIC. Our case illustrates that CESM has excellent performance similar to that of magnetic resonance imaging and is much more effective than conventional digital mammography. Additionally, our case indicates that precise correlation of CESM with ultrasonography findings contributes to the diagnosis of EICs. This rare case with multiple imaging findings will increase the awareness of EICs in the breast parenchyma.