Benign Breast Disease Research Articles

THE ROLE OF BREAST IMAGING MODALITIES IN THE DIAGNOSIS AND MANAGEMENT OF BENIGN BREAST DISEASES

Objective: Accurate diagnosis and management of benign breast diseases are crucial aspects of breast healthcare. Breast imaging modalities such as mammography, ultrasound, and magnetic resonance imaging (MRI) play a pivotal role in differentiating benign from malignant lesions and guiding appropriate management strategies. Methods: This retrospective study was conducted at [Institution Name] from January 2018 to December 2022. It involved a review of medical records, imaging results, and management outcomes of patients diagnosed with benign breast diseases. Imaging modalities included mammography, ultrasound, and MRI. The diagnostic accuracy of each modality was assessed by comparing imaging findings with histopathological results. Statistical analyses were performed using SPSS version 26.0. Results: A total of 200 patients were included, with a mean age of 45.3±12.6 y. Mammography showed a sensitivity of 85% and specificity of 78%, while ultrasound had a sensitivity of 92% and specificity of 84%. MRI exhibited the highest accuracy with a sensitivity of 95% and specificity of 90%. Combined imaging modalities achieved the highest diagnostic performance. Management strategies varied, with watchful waiting, medication, minimally invasive procedures, and surgical interventions employed based on the specific condition. Conclusion: Breast imaging modalities are indispensable in diagnosing and managing benign breast diseases. The integration of mammography, ultrasound, and MRI provides comprehensive diagnostic information, guiding optimal management strategies and improving patient outcomes. Future advancements in imaging technology promise to further enhance diagnostic capabilities.

Cystic Breast Disease: What to Do When It's Not So Cystic.

Cystic breast masses are a common entity encountered by breast radiologists. The imaging features of benign and malignant cystic masses may overlap, causing confusion and miscategorization with the potential to produce diagnostic delay and harm. This article provides a review of key differentiating imaging features that help guide appropriate mass characterization and treatment.

Diffusion weighted imaging as adjunct modality to distinguish benign and malignant breast lesions in resource constrained settings: A single institute experience

Objectives To establish the accuracy of the “targeted DWI/ADC sequence” as an adjunct to mammography and sonography for differentiating malignant and benign breast masses in an underdeveloped population, in correlation with histopathology. Materials and Methods The study population was predominantly rural and from underdeveloped regions. It included 108 female patients of various ages who presented with breast masses with equivocal diagnoses on mammography and sonography. These patients were unwilling to return for additional investigations. The targeted lesions were then further evaluated using diffusion weighted imaging (DWI)/apparent diffusion coefficient (ADC) maps and ADC values. The final diagnosis was later confirmed by histopathology examination. Results A total of 108 patients having 115 lesions were targeted based on mammography and sonography findings and subjected to DWI. The cut-off ADC value was established for these lesions to be 1.2 × 10–3 mm2/s through receiver operating characteristic curve analysis. This value exhibited a sensitivity of 98.7% and specificity of 91.9% in the present study. DWI overdiagnosed malignancy by 2.6%. Conclusion In the present study, the “targeted DWI/ADC sequence” has proven useful with a sensitivity of 98.7% and specificity of 91.9% using a cut-off value of 1.2 × 10–3 mm2/s. Targeted DWI/ADC in combination with mammography and sonography accurately identified all malignant lesions with overdiagnosis of malignancy in 2.6% of cases. In India, where the demographic is largely rural and underdeveloped, social and economic limitations, along with a lack of awareness, make adherence to ideal diagnostic protocols challenging. This ultimately results in losing the patient to follow-up and missing the cancer. This novel approach of targeted DWI/ADC sequence in combination with mammography and sonography is highly effective in such scenarios, enabling the identification of the likely nature of the disease during the same visit. This empowered healthcare professionals to counsel patients confidently and initiate early management.

Clinical utility of quantitative ultrasonography parameters combined with serum cancer antigen 15‑3, human epidermal growth factor receptor 2 and soluble E‑cadherin in diagnosing mass‑type breast cancer.

Contrast-enhanced ultrasonography (CEUS), a newly developed imaging technique, holds certain value in differentiating benign from malignant tumors. Additionally, serum tumor markers also exhibit significant clinical importance in the diagnosis and monitoring of malignant tumors. Reports have indicated abnormal expression of HER-2, CA153 and sE-cad in breast cancer. Early diagnosis of breast cancer facilitates early clinical intervention and enhances the overall quality of life for patients. Therefore, this study aims to explore the clinical value of quantitative CEUS parameters combined with serum levels of CA153, HER-2 and sE-cad in diagnosing mass-type breast cancer. In total, 49 patients with breast cancer (breast cancer group) and 56 patients with benign breast tumors (benign group) were selected as the study participants, while 50 healthy women served as the control group. Ultrasonography was performed on the patients in the breast cancer and benign groups using diagnostic color Doppler ultrasonography. The serum CA15-3, HER-2 and sE-cad levels in all three study groups were measured using a fully automated electrochemiluminescence immunoassay. Pearson's correlation test was used to analyze the correlation between the quantitative ultrasonography parameters and serum CA15-3, HER-2 and sE-cad levels. Logistic multivariate regression analysis was performed to analyze the independent risk factors, and a receiver operating characteristic curve was plotted to assess the diagnostic value of these factors. The peak intensity (PI), wash-in slope (WIS), gradient (Grad) and local mean transit time (mTTI), along with the CA15-3, HER-2 and sE-cad levels in the breast cancer group were significantly higher, and the time to peak (TTP) was significantly lower, compared with those values in the benign and control groups. CA15-3, HER-2 and sE-cad were negatively correlated with TTP in the breast cancer group (all P<0.05) and positively correlated with PI, WIS, Grad and mTTI (all P<0.05). The area under the curve (AUC) values for CA15-3, HER-2, sE-cad, PI, WIS, Grad, mTTI and TTP for the diagnosis of malignant breast cancer were 0.640, 0.730, 0.687, 0.683, 0.692, 0.737, 0.697 and 0.671, respectively. The AUC for the combined diagnosis was 0.919, with a sensitivity of 0.857 and a specificity of 0.911, outperforming each index alone for a single diagnosis. Logistic multivariate regression analysis revealed that HER-2, TTP, PI, WI and Grad were independent risk factors for malignant breast cancer. In conclusion, combining the quantitative ultrasonography parameters with the CA15-3, HER-2 and sE-cad levels facilitated the differential diagnosis of benign and malignant breast lesions, and may provide a reference for clinical treatment in the future.

Comparing the Diagnostic Performance of Ultrasound Elastography and Magnetic Resonance Imaging to Differentiate Benign and Malignant Breast Lesions: A Systematic Review and Meta-analysis.

The purpose of this systematic review and meta-analysis was comparing diagnostic performance of ultrasound elastography (UE), strain UE and shear wave elastography (SWE), with magnetic resonance imaging (MRI) in differentiating benign and malignant breast lesions. Literature search of MEDLINE, Web of Science, SCOPUS and Google Scholar was performed in June 2023. Included studies used Breast Imaging Reporting and Data System (BI-RADS) and histopathology as reference standard. A bivariate random-effects model was used to calculate sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios and area under the curve (AUC). Meta-regression subgroup analysis was performed. Nine studies and 536 lesions were included. Pooled sensitivity was not different between MRI vs UE [MRI: 94% (95% CI: 88.2%-96.9%) vs UE: 90% (95% CI: 84.7%-93.1%); P=0.153] but a difference was found for specificity [UE: 78% (95% CI: 66.3%-86.4%) vs MRI: 71.3% (95% CI: 52.1%-85%); P=0.0065]. Strain UE showed higher specificity and similar sensitivity to SWE [strain UE: 0.85 (95% CI: 0.71-0.93) vs SWE: 0.72 (95% 0.58-0.83); P=0.017 and strain UE: 0.87 (95% CI 0.79-0.93) vs SWE: 0.91 (95% CI 0.85-0.95); P=0.311, respectively]. AUC was similar between MRI vs UE [0.91 (95% CI 0.87-0.95) vs 0.92 (95% CI 0.88-0.95); P=0.452, respectively] as was DOR [MRI: 38.083 (95% CI: 12.401-116.957) vs UE: 30.395 (95% CI: 16.572-55.75); P>0.05]. Meta-regression analysis found no significant differences in the diagnostic accuracy between MRI, strain UE and SWE. Our results show that UE when compared to MRI has adequate performance in differentiating benign and malignant breast lesions.

A nomogram based on multiparametric magnetic resonance imaging improves the diagnostic performance of breast lesions diagnosed as BI-RADS category 4: A comparative study with the Kaiser score.

To construct a nomogram combining Kaiser score (KS), synthetic MRI (syMRI) parameters, apparent diffusion coefficient (ADC), and clinical features to distinguish benign and malignant breast lesions better. From December 2022 to February 2024, a retrospective cohort of 168 patients with breast lesions diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 by ultrasound and/or mammography was included. The research population was divided into the training set (n=117) and the validation set (n=51) by random sampling with a ratio of 7:3. Breast lesions' KS, ADC, relaxation time of syMRI, and clinical and imaging features were statistically analyzed and compared between malignant and benign groups. Two experienced radiologists independently assigned KS, and measured quantitative values of ADC and parameters of syMRI, and the intraclass correlation coefficient (ICC) was calculated. Independent predictors were identified by univariable and multivariable logistic regression analysis. Then, a nomogram was established, and its performance was evaluated by the area under the curve (AUC), calibration curve, and decision curve. There were 168 lesions (118 malignant and 50 benign) in 168 female patients confirmed by histopathology. The interobserver agreement for each quantitative parameter was excellent. Older patient (OR=1.091, 95% confidence interval [CI]: 1.017-1.170, P=0.014), higher lesions' KS (OR=288.431, 95% CI: 34.930-2381.654, P<0.001), lower ADC (OR=0.077, 95% CI: 0.011-0.558, P=0.011), and lower T2 relaxation time (OR=0.918, 95% CI: 0.868-0.972, P=0.003) were independent predictors of breast malignancies and utilized to establish the nomogram. The accuracy of KS, ADC, T2, and patient age in predicting malignant breast lesions was 88.89%, 79.48%, 82.05%, and 58.97%, respectively. No significant differences in AUCs of KS, ADC and T2 were observed in distinguishing benign from malignant breast lesions. The nomogram yielded higher AUCs of 0.968 (0.934-0.996) and 0.959 (0.863-0.995) in training and validation sets than KS, ADC, T2, and patient age (p<0.05). Although there were no significant differences among the AUCs of KS, ADC, and T2, the constructed nomogram incorporating these parameters significantly improves diagnostic performance for distinguishing benign and malignant BI-RADS 4 breast lesions. Future external validation is needed in practical applications.

Time-dependent diffusion MRI and kinetic heterogeneity as potential imaging biomarkers for diagnosing suspicious breast lesions with 3.0-T breast MRI.

This study aimed to evaluate the diagnostic efficacy of time-dependent diffusion magnetic resonance imaging (td-dMRI) and dynamic contrast-enhanced MRI (DCE-MRI)-based kinetic heterogeneity in differentiating suspicious breast lesions (categorised as Breast Imaging Reporting and Data System 4 or 5). This prospective study included 51 females with suspicious breast lesions who underwent preoperative breast MRI, including DCE-MRI and td-dMRI. Six kinetic parameters, namely peak, persistent, plateau, washout component, predominant curve type, and heterogeneity, were extracted from the DCE series using MATLAB and SPM software. The td-dMRI data were analysed using the JOINT model to obtain five microstructural parameters and apparent diffusion coefficient at 50ms (ADC50ms). Chi-square or Fisher's exact test and the Mann-Whitney U test were used to compare these parameters between benign and malignant breast lesions. Univariate and multivariate logistic regression analyses with forward stepwise covariate selection were performed to identify significant clinical and radiologic variables. Differential diagnostic performance was evaluated using receiver operating characteristic curves and logistic regression analyses. For td-dMRI-derived parameters, the values of fin and cellularity were significantly higher in malignant breast lesions compared to benign lesions (P=0.001 and P<0.001, respectively), while ADC50ms was significantly lower in malignant lesions (P=0.001). In the kinetic heterogeneity analysis, the washout component was higher in malignant lesions compared to benign lesions (P=0.003). When combining significant td-dMRI and kinetic heterogeneity parameters, the area under the curve (AUC) value was 0.875, with an accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 82.69%, 86.11%, 75.00%, 88.57%, and 70.59%, respectively. Notably, margin and kinetic pattern emerged as independent predictors of malignant breast lesions (P=0.019 and 0.006, respectively). Furthermore, incorporating these two clinical-radiologic characteristics further enhanced diagnostic accuracy, yielding an AUC of 0.969, with accuracy, sensitivity, specificity, PPV, and NPV improving to 90.38%, 86.11%, 100%, 100%, and 76.19%, respectively. Kinetic heterogeneity- and td-dMRI-derived parameters are potentially non-invasive biomarkers for distinguishing suspicious breast lesions.

Predictive Model for Hematoma Formation Following Ultrasound-Guided Excision of Benign Breast Lesions

Predictive Model for Hematoma Formation Following Ultrasound-Guided Excision of Benign Breast Lesions

Changes in Breast Cancer Risk Associated with Benign Breast Disease from 1967 to 2013.

Benign breast disease (BBD) increases breast cancer (BC) risk progressively for women diagnosed with non-proliferative (NP) change, proliferative disease without atypia (PDWA), and atypical hyperplasia (AH). Leveraging data from 18,704 women in the Mayo BBD Cohort (1967-2013), we evaluated temporal trends in BBD diagnoses and how they have influenced associated BC risk over four decades. BC risk trends associated with BBD were evaluated using standardized incidence ratios (SIRs) and age-period-cohort modeling across four eras-pre-mammogram (1967-1981), pre-core needle biopsy (CNB) (1982-1992), transition to CNB (1993-2001), and CNB era (2002-2013). With a median follow-up of 15.8 years, 9.9% of women were diagnosed with BC (invasive and/or DCIS). From the pre-mammogram era to the CNB era, we observed a significant increase in BC risk, rising from an SIR of 1.61 to 1.99. The proportion of proliferative BBD diagnoses (PDWA or AH) increased markedly over time (28.1% to 49.7%), as did the proportion of DCIS events (11% to 28%; chi-square p < .001). Within specific BBD categories, the risk of invasive BC increased modestly. While absolute risk of BC within BBD categories remained stable, the relative risk of BC after BBD increased over time due to notable increases in higher risk BBD lesions, specifically PDWA and AH. These findings illustrate how evolving screening practices have changed the risk profile of BBD and should inform management strategies for patients with BBD in modern clinical settings.

Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions

This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.We created a model called CLDLR that utilizes clinical parameters and DLR to diagnose both BBL and MBL through grayscale ultrasound images. In order to assess the practicality of the CLDLR model, two rounds of evaluations were conducted by radiologists. The CLDLR model demonstrates the highest diagnostic performance in predicting benign and malignant BI-RADS 4 lesions, with areas under the receiver operating characteristic curve (AUC) of 0.988 (95% confidence interval : 0.949, 0.985) in the training cohort and 0.888 (95% confidence interval : 0.829, 0.947) in the testing cohort.The CLDLR model outperformed the diagnoses made by the three radiologists in the initial assessment of the testing cohorts. By utilizing AI scores from the CLDLR model and heatmaps from the DLR model, the diagnostic performance of all radiologists was further enhanced in the testing cohorts. Our study presents a noninvasive imaging biomarker for the prediction of benign and malignant BI-RADS 4 lesions. By comparing the results from two rounds of assessment, our AI-assisted diagnostic tool demonstrates practical value for radiologists with varying levels of experience.

The Role of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Benign and Malignant Breast Lesions: A Comprehensive Review

Background: Breast magnetic resonance imaging (MRI) has emerged as a vital tool for detecting and characterizing breast lesions, particularly in differentiating benign from malignant tumors. This review explores the role of diffusion-weighted imaging (DWI) in breast MRI, highlighting its advantages over conventional imaging techniques. Methods: A systematic literature search was conducted across multiple databases, including PubMed and Scopus, to gather studies assessing DWI's sensitivity and specificity in breast cancer detection. Results: The findings indicate that DWI provides high diagnostic accuracy, with a pooled sensitivity of 86.5% and specificity of 83.5%, comparable to dynamic contrast-enhanced MRI (DCE-MRI). Notably, utilizing apparent diffusion coefficient (ADC) thresholds can minimize unnecessary biopsies without compromising sensitivity. However, challenges remain in achieving standardization in DWI protocols, particularly regarding b-value selection and imaging techniques, which impact ADC accuracy. Advanced methodologies such as intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) have shown promise in enhancing diagnostic capabilities by providing deeper insights into tissue microstructure. Conclusions: This review underscores the importance of ongoing standardization efforts and collaboration among institutions to improve the reliability and applicability of DWI in clinical settings. In conclusion, DWI represents a transformative approach to breast cancer management, allowing for enhanced differentiation of lesions while reducing the need for invasive procedures. Further research and standardization are essential to optimize its use in routine clinical practice.

DWI in the Differentiation of Malignant and Benign Breast Lesions Presenting with Non-Mass Enhancement on CE-MRI.

This study aimed to investigate whether the apparent diffusion coefficient (ADC) maps values of breast lesions presenting as non-mass enhancement (NME) on MRI could predict benign or malignant pathohistological findings. This retrospective single-center study included 136 female patients with NME and corresponding ultrasound correlate and a subsequent ultrasound-guided core needle biopsy. The patients were subdivided into benign or malignant subgroups based on pathology reports, which served as the gold standard. Blinded to the pathological results, two radiologists independently measured the ADC values of the depicted NME using punctate, 10 mm and whole tumor regions of interest (ROIs) wherever applicable. The mean of all measurements was also analyzed and compared with the pathologic subdivision. The sensitivity of whole tumor ROI in detecting benign NME is 91% compared to 74% for 10 mm ROI and 78% for punctate ROI. No significant differences in ADC values were observed when comparing fatty breast tissue and dense breast tissue. There were differences in ADC values between benign and malignant findings using all types of measurements, where the whole tumor ROI was the most sensitive.

The benefits of contrast-enhanced ultrasound in the differential diagnosis of suspicious breast lesions.

Contrast-enhanced ultrasound (CEUS) shows potential for the differential diagnosis of breast lesions in general, but its effectiveness remains unclear for the differential diagnosis of lesions highly suspicious for breast cancers. This study aimed to evaluate the diagnostic value of CEUS in differentiating pathological subtypes of suspicious breast lesions defined as category 4 of US-BI-RADS. The dataset of 150 breast lesions was prospectively collected from 150 patients who underwent routine ultrasound and CEUS examination and were highly suspected of having breast cancers. All lesions were pathologically confirmed by US-guided needle biopsy and surgery. The qualitative features and the quantitative parameters of CEUS of these breast lesions were analyzed. The CEUS and biopsy examinations were performed after informed consent. In the qualitative features, crab clam-like enhancement, the presence of more than two enhanced vessels within lesions, and surrounding enriched vessels inserting into lesions were able to differentiate atypical fibroadenomas (FIB) and mass-like non-puerperal mastitis (NPM) from invasive ductal carcinomas (IDC) and ductal carcinomas in situ (DCIS) (p < 0.05). The enlarged scope, irregular shape, and perfusion deficiency were valuable to the differential diagnosis of FIB from the others (p < 0.05). In the four quantitative parameters of CEUS, only the peak intensity (IMAX) contributed to the differential diagnosis between malignant and benign tumors (p < 0.05, ROCAUC: 0.61, sensitivity: 60.4% and specificity: 65.9%, accuracy: 62.1%). However, IMAX did not show any difference in the paired comparison of IDC, DCIS, FIB, and NPM (p > 0.05). The logistic regression analysis results showed that heterogeneous perfusion, crab clam-like enhancement, and partial_ IMAX were independent risk factors for benign and malignant breast lesions (p < 0.05). The area under a receiver operating characteristic of the integrated model was 0.89. In the diagnosis of benign and malignant pathological subtypes of breast lesions, independent risk factors and integrated models had no statistical significance in the diagnosis of IDC and DCISs, FIB, and NPM (p > 0.05). Some qualitative risk features of CEUS can distinguish malignant breast lesions from NPM and atypical FIB with a high score of US-BI-RADS, aiding physicians to reduce the misdiagnosis of suspicious breast lesions in clinical practice.

Evaluation of functional magnetic resonance APT and DKI imaging for breast cancer

ObjectiveThis study aimed to compare the performance of amide proton transfer–weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in differentiating benign from malignant breast lesions, evaluate molecular subtypes of breast cancer, and determine the diagnostic efficacy of the quantitative magnetic resonance imaging (qMRI) parameters in differentiating benign from malignant breast diseases.MethodsThe study included 168 women who underwent breast APTWI and DKI at Yunnan Cancer Hospital between December 2022 and July 2023. The APT signal intensity (SI), apparent kurtosis coefficient (Kapp), non-Gaussian diffusion coefficient (Dapp), and apparent diffusion coefficient (ADC) values were measured before surgery. The differences in the aforementioned qMRI parameters in molecular subtypes of breast cancer were analyzed using one-way analysis of variance. The efficacy of each quantitative parameter in differentiating benign from malignant breast diseases was evaluated using the receiver-operating characteristic curve.ResultsSignificant differences in qMRI parameters were noted between benign and malignant breast lesions. The Kapp (P < .0001) and APT (P < .05) values were higher for malignant tumors than for benign lesions. Conversely, the ADC (P < .0001) and Dapp (P < .0001) values were lower for malignant tumors than for benign lesions. The diagnostic performance was assessed using the area under the curve (AUC) for various parameter combinations. The AUC of Kapp was 0.871, Dapp was 0.872, APT SI was 0.643, DKI + APT was 0.893, DKI + ADC was 0.936, APT + ADC was 0.925, and DKI + APT + ADC was 0.933. Additionally, ADC values (P = .01) demonstrated superior diagnostic performance compared to Kapp (P = .03), Dapp (P = .03), and APT values (P = .06) in distinguishing between different molecular subtypes of breast cancer.ConclusionsAPTWI distinguished benign from malignant breast disease and enhanced the utility of diffusion-weighted MRI. However, it was not superior to DKI and DWI in identifying the molecular subtypes of breast cancer.

Expression Patterns of ER, PR, Her2/neu, and Ki67 in Sudanese Breast Cancer Patients

Background: Tumor markers are crucial indicators for breast cancer treatment and follow-up. Thus, this study attempted to explore the expression patterns of ER, PR, Her2/neu, and Ki67 in Sudanese breast cancer patients. Methodology: This study was a retrospective descriptive analysis conducted in El-Obeid city, Sudan. Records of 190 patients were obtained, including 110 with malignant lesions and 79 with benign breast lesions, from two histopathology laboratories. Results: Approximately 37% of patients were ER/PR positive, whereas 31% of cases tested for ER, PR, and Her2/neu were classified as triple negative. Ki-67 expression exhibited significant variability among breast lesions. Invasive ductal carcinoma (IDC) exhibited the highest expression of estrogen receptors (ER) at 59%, followed by progesterone receptors (PR) at 56%, and HER2 positivity at 53.8%. Conclusion: Breast cancer cases in Sudan are prevalent, characterized by ER/PR positivity, triple-negative status, and elevated Ki-67 expression. The predominant histological type of breast cancer is invasive ductal carcinoma. Women under the age of 45 exhibit a higher susceptibility to breast cancer. A significant number of patients exhibit advanced stages of the disease. Sudan advocates for the prevention and early detection of breast cancer.

Breast hamartomas associated with epithelial atypia and malignancy: are there specific clinical, radiological or pathological features that identify at risk patients?

Breast hamartomas are rarely associated with epithelial atypia or malignancy. Since the introduction of digital mammography in the UK from 2008, hamartoma detection has increased. The aim of this study was to identify if there are characteristic clinical, radiological or histological features that distinguish hamartomas with intralesional atypia/malignancy (complex hamartomas, CH) or ipsilateral/contralateral atypia/malignancy (non-CH) from those without atypia/malignancy at diagnosis (other benign hamartomas, BH). We performed a retrospective single-institution review of 450 hamartomas reported between 2010 and 2023. Anonymised H&E sections and imaging of CH and non-CH were reviewed to identify distinguishing features. 13,441 benign breast lesions were biopsied/resected between 2010 and 2023 including 450 hamartomas (3.3%), 19 of which (4.2%) were associated with atypia or malignancy. 14 were analysed further (7 CH; 7 non-CH). The mean age of CH plus non-CH patients was significantly higher than patients with BH (47.5 vs. 40.6years; p = 0.03). The mean size of CH was greater than non-CH (32.1mm vs.17.6mm; p = 0.06). There was a statistically significantly higher incidence of atypical/malignant lobular lesions (ALH/LCIS/ILC) in CH vs. non-CH (42.9% vs 0%; p = 0.05). MRI was performed in 2 CH and 3 non-CH; in all 5 the associated malignancy was detected. There was no significant difference between the CH and non-CH group in ultrasound/mammographic features, other hamartoma histological features or other associated benign breast changes. Ultrasound/mammogram are not sufficiently sensitive to identify hamartomas with associated atypia/malignancy. Certain hamartoma features may preferentially be associated with atypia/malignancy and which merit further radiological and/or detailed histological investigation.

Diagnostic accuracy of ultrasonography and mammography of breast lesions

Introduction: Breast cancer is the most common malignant tumors in women, with over one million cases diagnosed globally each year, resulting in approximately 410,000 deaths. Early detection and treatment significantly reduce the risk of mortality. Ultrasound and mammography are widely used non-invasive, cost-effective imaging techniques for early breast cancer diagnosis. This study aims to identify the characteristics of breast lesions on ultrasound and mammography and correlate them with histological findings. Method: This was a retrospective study conducted in Patan Hospital, with the data set from January 2019 to December 2022. All patient’s data were collected regarding findings of ultrasound, mammography, BIRADS from radiological department and correlated with histopathological diagnosis. All findings were compared for the sensitivity and specificity of mammography with ultrasonography in diagnosing breast lesions. Result: A total of 137 cases were found to have histopathology diagnosed benign and malignant breast lesions. Ultrasonography showed 91.58% sensitivity, 57.14% specificity, 82.86% positive predictive value, 75.00% negative predictive value, and 81.02% diagnostic accuracy. Mammography exhibited 92.63% sensitivity, 61.90% specificity, 84.62% positive predictive value, 78.79% negative predictive value, and 83.62% diagnostic accuracy. When combining mammography and ultrasonography, the results showed 93.63% sensitivity, 42.86% specificity, 78.76% positive predictive value, 75% negative predictive value, and 78.10% diagnostic accuracy. Conclusion: Ultrasound and mammography are both highly sensitive in detecting benign and malignant breast lesions. While mammography has a slightly higher overall accuracy in diagnosis, it is recommended to complement ultrasonography with mammography for a more comprehensive detection of breast lesions.

Fibrocystic Breast Changes: Imaging and Pathological Correlational Study of a Sample in The Kurdistan Region of Iraq

Background and objectives: Fibrocystic changes of the breast are the most common breast changes observed globally. The study aimed to assess these changes using ultrasound and correlate the imaging findings with histopathological changes to determine accuracy. Methods: A prospective cross-sectional study included 240 women who were diagnosed with fibrocystic breasts between January 2022 and July 2023 at a specialized medical center in Duhok city. Ultrasound was performed to evaluate changes in the breast. Imaging results were classified according to the guidelines of the American College of Radiology's Breast Imaging Reporting and Data System. Women with moderate imaging findings underwent ultrasound guided needle aspiration. The samples obtained were sent for cytological and histopathological evaluation. A correlation was conducted between the results of both of these modalities. Results: The age group most affected was 29-49 years. Bilateral breast involvement was the most prevalent, accounting for 78% of the cases. 74% of the affected women complained of cyclical mastalgia. Ultrasound findings mainly show simple cysts, clustered cysts, and duct ectasia, accounting for 29%, 30%, and 15% respectively. BI-RAD 2, followed by 3, and then 4A were the most common imaging categories. Simple cyst (36%), ducts with apocrine metaplasia (23%), and epithelial hyperplasia without atypia (18%) were the most commonly observed histopathological findings. Statistically significant accuracy was observed regarding the imaging and cytological correlations in BI-RAD 3and 4A. Conclusion: A strong correlation was observed between the ultrasound findings of breast fibrocystic changes and the histopathological evaluation.

Diagnostic performance of simultaneous multislice diffusion-weighted imaging in differentiating breast lesions: a systematic review and meta-analysis.

To investigate the diagnostic performance of simultaneous multislice diffusion-weighted imaging (SMS-DWI) in differentiating malignant and benign breast lesions, and compare it with conventional single shot and readout segmented echo planar imaging without the SMS technique. The literature search was performed in PubMed, Embase, and Web of Science to identify comparative studies reporting the diagnostic performance of SMS-DWI and conventional DWI in patients with breast lesions. Histopathological analysis was used as a reference standard for malignant breast lesions. The methodological quality was evaluated using QUADAS-2 scale. The summary sensitivity, summary specificity, and area under the curve (AUC) of the summarized receiver operating characteristic curve were calculated and compared between SMS-DWI and conventional DWI using a bivariate random-effects model. Heterogeneity was explored with meta-regression and subgroup analyses. Six studies with 626 patients and 649 breast lesions (benign: 222, malignant: 427) were included. The summary sensitivity, summary specificity, and AUC for SMS-DWI were 0.89 (95% CI: 0.78-0.95), 0.94 (95% CI: 0.81-0.98), and 0.96 (95% CI: 0.94-0.98), respectively, and those for conventional DWI were 0.90 (0.95 CI: 0.84-0.94), 0.87 (95% CI: 0.80-0.92), and 0.94 (95% CI: 0.92-0.96), respectively. The diagnostic performance was not significantly different between SMS-DWI and conventional DWI (P = .337). SMS-DWI has high diagnostic performance in differentiating breast lesions, which is not significantly different from the conventional DWI. There is no significant difference between SMS-DWI and conventional DWI in differentiating breast lesions, suggesting SMS-DWI may be a potential alternative to conventional DWI in breast imaging.

A head-to-head comparison of breast lesion's conspicuity at contrast-enhanced mammography and contrast-enhanced MRI.

Lesion conspicuity, the relative enhancement of a lesion compared to surrounding tissue, is a new descriptor in the ACR BI-RADS 2022 CEM supplement. We compared lesion conspicuity in contrast-enhanced mammography (CEM) and contrast-enhanced MRI (CE-MRI) in patients with suspicious breast lesions. IRB-approved retrospective study; three blinded readers rated 462 indeterminate or suspicious breast lesions in 388 patients (54.2 ± 11 years; range 30-90) who underwent CEM and CE-MRI from 2018 to 2022. Each lesion's conspicuity was scored from 1 to 5, with 5 indicating excellent conspicuity. Visual grading characteristics (VGC) analysis and area under the curve (AUC) were used for comparison, with sub-analyses for benign and malignant lesions. VGC analysis showed a significant AUC of 0.670 to 0.723 (p < 0.001) favouring CE-MRI. No lesion enhancement (score 1) was observed in 16.2% of CE-MRI and 44.7% of CEM. Excellent conspicuity was seen in 29.6% of CE-MRI and 11.9% of CEM. Sub-analysis showed higher conspicuity on CE-MRI for both malignant (AUC 0.665 to 0.732, p < 0.001) and benign lesions (AUC 0.734 to 0.798, p < 0.001). CE-MRI showed higher lesion conspicuity compared to CEM both for non-mass lesions (0.656) and for mass lesions 0.605. CE-MRI shows significantly higher conspicuity for benign and malignant breast lesions compared to CEM, especially for benign lesions. The low conspicuity of benign lesions on CEM may help reduce false positives in clinical practice. Question Lesion conspicuity is a new descriptor for lesion enhancement according to the new CEM lexicon. Data correlating lesion conspicuity with malignancy likelihood are limited. Findings Lesion conspicuity is higher for contrast-enhanced-MRI than for contrast-enhanced mammography (CEM) for all lesions but significantly better for benign lesions. Clinical relevance The low conspicuity of benign lesions on CEM may reduce false-positive results, making it a valuable tool in breast cancer screening.