Advancing Breast Cancer Diagnosis through Breast Mass Images, Machine Learning, and Regression Models.

Breast cancer results from a disruption of certain cells in breast tissue that undergo uncontrolled growth and cell division. These cells most often accumulate and form a lump called a tumor, which may be benign (non-cancerous) or malignant (cancerous). Malignant tumors can spread quickly throughout the body, forming tumors in other areas, which is called metastasis. Standard screening techniques are insufficient in the case of metastasis; therefore, new and advanced techniques based on artificial intelligence (AI), machine learning, and regression models have been introduced, the primary aim of which is to automatically diagnose breast cancer through the use of advanced techniques, classifiers, and real images. Real fine-needle aspiration (FNA) images were collected from Wisconsin, and four classifiers were used, including three machine learning models and one regression model: the support vector machine (SVM), naive Bayes (NB), k-nearest neighbors (k-NN), and decision tree (DT)-C4.5. According to the accuracy, sensitivity, and specificity results, the SVM algorithm had the best performance; it was the most powerful computational classifier with a 97.13% accuracy and 97.5% specificity. It also had around a 96% sensitivity for the diagnosis of breast cancer, unlike the models used for comparison, thereby providing an exact diagnosis on the one hand and a clear classification between benign and malignant tumors on the other hand. As a future research prospect, more algorithms and combinations of features can be considered for the precise, rapid, and effective classification and diagnosis of breast cancer images for imperative decisions.

Ultrasound-based radiomics for the differential diagnosis of breast masses: A systematic review and meta-analysis.

OBJECTIVES: Ultrasound-based radiomics has demonstrated excellent diagnostic performance in differentiating benign and malignant breast masses. Given a few clinical studies on their diagnostic role, we conducted a meta-analysis of the potential effects of ultrasound-based radiomics for the differential diagnosis of breast masses, aiming to provide evidence-based medical basis for clinical research. MATERIALS AND METHODS: We searched Embase, Web of Science, Cochrane Library, and PubMed databases from inception through to February 2023. The methodological quality assessment of the included studies was performed according to Quality Assessment of Diagnostic Accuracy Studies checklist. A diagnostic test accuracy systematic review and meta-analysis was performed in accordance with PRISMA guidelines. Sensitivity, specificity, and area under curve delineating benign and malignant lesions were recorded. We also used sensitivity analysis and subgroup analysis to explore potential sources of heterogeneity. Deeks' funnel plots was used to examine the publication bias. RESULTS: A total of 11 studies were included in this meta-analysis. For the diagnosis of malignant breast masses worldwide, the overall mean rates of sensitivity and specificity of ultrasound-based radiomics were 0.90 (95% confidence interval [CI], 0.83-0.95) and 0.89 (95% CI, 0.82-0.94), respectively. The summary diagnostic odds ratio was 76 (95% CI, 26-219), and the area under the curve for the summary receiver operating characteristic curve was 0.95 (95% CI, 0.93-0.97). CONCLUSION: Ultrasound-based radiomics has the potential to improve diagnostic accuracy to discriminate between benign and malignant breast masses, and could reduce unnecessary biopsies.

Value of inversion imaging to diagnosis in differentiating malignant from benign breast masses.

BACKGROUND: We aimed to evaluate the added value of inversion imaging in differentiating between benign and malignant breast masses when combined with the Breast Imaging Reporting and Data System (BI-RADS). METHODS: A total of 364 patients with 367 breast masses (151 benign and 216 malignant) who underwent conventional ultrasound and inversion imaging prior to breast surgery were included. A 5-point inversion score (IS) scale was proposed based on the masses' internal echogenicity and distribution characteristics in the inversion images. The combination of IS and BI-RADS was compared with BI-RADS alone to evaluate the value of inversion imaging for breast mass diagnosis. The diagnostic performance of the BI-RADS and its combination with IS for breast masses were analyzed using area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: The IS for malignant breast masses (3.96 ± 0.77) was significantly higher than benign masses (2.58 ± 0.98) (P < 0.001). The sensitivity, specificity, accuracy, PPV, and NPV of BI-RADS were 86.1%, 81.5%, 84.2%, 86.9%, and 80.4%, respectively, and an AUC was 0.909. By compared with BI-RADS, 72 breast masses were downgraded from suspected malignancy to benign, and 6 masses were upgraded from benign to suspected malignancy. Thus, the specificity was increased from 81.5 to 84.8%, it allows 72 benign masses avoid biopsy. CONCLUSION: The combination of inversion imaging with BI-RADS can effectively improve the diagnostic efficacy of breast masses, and inversion imaging could help benign masses avoid biopsy.

The value of radiomics model based on ultrasound image features in the differentiation between minimal breast cancer and small benign breast masses.

BACKGROUND: Female breast cancer has surpassed lung cancer as the most common cancer, and is also the main cause of cancer death for women worldwide. Breast cancer <1 cm showed excellent survival rate. However, the diagnosis of minimal breast cancer (MBC) is challenging. OBJECTIVE: The purpose of our research is to develop and validate an radiomics model based on ultrasound images for early recognition of MBC. METHODS: 302 breast masses with a diameter of <10 mm were retrospectively studied, including 159 benign and 143 malignant breast masses. The radiomics features were extracted from the gray-scale ultrasound image of the largest face of each breast mass. The maximum relevance minimum reduncancy and recursive feature elimination methods were used to screen. Finally, 10 features with the most discriminating value were selected for modeling. The random forest was used to establish the prediction model, and the rad-score of each mass was calculated. In order to evaluate the effectiveness of the model, we calculated and compared the area under the curve (AUC) value, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the model and three groups with different experience in predicting small breast masses, and drew calibration curves and decision curves to test the stability and consistency of the model. RESULTS: When we selected 10 radiomics features to calculate the rad-score, the prediction efficiency was the best, the AUC values for the training set and testing set were 0.840 and 0.793, which was significantly better than the insufficient experience group (AUC = 0.673), slightly better than the moderate experience group (AUC = 0.768), and was inferior to the experienced group (AUC = 0.877). The calibration curve and decision curve also showed that the radiomics model had satisfied stability and clinical application value. CONCLUSION: The radiomics model based on ultrasound image features has a satisfied predictive ability for small breast masses, and is expected to become a potential tool for the diagnosis of MBC, and it is a zero cost (in terms of patient participation and imaging time).

Stiffness in breast masses with posterior acoustic shadowing: significance of ultrasound real time shear wave elastography.

BACKGROUND: To assess the stiffness of benign breast masses in ultrasound images with posterior acoustic shadowing (PAS) and malignant lesions, and explore the significance of differential diagnosis using ultrasound real time shear wave elastography. MATERIAL AND METHODS: All 117 mammary masses (98 patients) with PAS were assessed by using routine ultrasound examination, and elastic modulus values were obtained with the real time shear wave elastography mode. All breast lesions were confirmed by surgery or biopsy. The significance of differences in ultrasound elastography values between breast benign and malignant masses with posterior acoustic shadowing was assessed, and the ROC curves of elasticity modulus values were analyzed. RESULTS: Among the 117 masses, 72 were benign and 45 were malignant. The two types of breast masses showed significant differences in size, margin, internal echo, calcification, and blood flow characteristics (P < 0.05), although the difference in orientation was not significant (P > 0.05). Emean, Emax and Esd obtained with real time shear wave elastography showed statistically significant differences between benign masses with posterior acoustic shadowing and breast cancer (P < 0.05), while Emin showed no significant difference between them (P = 0.633). Ultrasound real time shear wave elastography showed higher sensitivity and specificity than conventional ultrasound. CONCLUSIONS: Benign and malignant breast masses with PAS show different ultrasound manifestations. Real time shear wave elastography can facilitate the differential diagnosis and treatment planning for these breast masses.

Efficient System for Delimitation of Benign and Malignant Breast Masses.

In this study, a high-performing scheme is introduced to delimit benign and malignant masses in breast ultrasound images. The proposal is built upon by the Nonlocal Means filter for image quality improvement, an Intuitionistic Fuzzy C-Means local clustering algorithm for superpixel generation with high adherence to the edges, and the DBSCAN algorithm for the global clustering of those superpixels in order to delimit masses' regions. The empirical study was performed using two datasets, both with benign and malignant breast tumors. The quantitative results with respect to the BUSI dataset were JSC≥0.907, DM≥0.913, HD≥7.025, and MCR≤6.431 for benign masses and JSC≥0.897, DM≥0.900, HD≥8.666, and MCR≤8.016 for malignant ones, while the MID dataset resulted in JSC≥0.890, DM≥0.905, HD≥8.370, and MCR≤7.241 along with JSC≥0.881, DM≥0.898, HD≥8.865, and MCR≤7.808 for benign and malignant masses, respectively. These numerical results revealed that our proposal outperformed all the evaluated comparative state-of-the-art methods in mass delimitation. This is confirmed by the visual results since the segmented regions had a better edge delimitation.

Application of S-detect combined with virtual touch imaging quantification in ultrasound for diagnosis of breast mass. / S-detectè”åˆå£°è§¦è¯Šç»„ç»‡æˆåƒå®šé‡åœ¨ä¹³è ºè‚¿å—è¶ å£°è¯Šæ–­ä¸­çš„åº”ç”¨.

OBJECTIVES: Ultrasound is a safe and timely diagnosis method commonly used for breast lesion, however it depends on the operator to a certain degree. As an emerging technology, artificial intelligence can be combined with ultrasound in depth to improve the intelligence and precision of ultrasound diagnosis and avoid diagnostic errors caused by subjectivity of radiologists. This paper aims to investigate the value of artificial intelligence S-detect system combined with virtual touch imaging quantification (VTIQ) technique in the differential diagnosis of benign and malignant breast masses by conventional ultrasound (CUS). respectively, and AUCs for them were 0.74, 0.86, 0.79, and 0.94, respectively. The diagnostic accuracy of CUS+S-detect was higher than that of CUS (P<0.05). The diagnostic accuracy of CUS+S-detect was higher than that of CUS (P<0.05). The diagnostic specificity of CUS+VTIQ was higher than that of CUS (P<0.05). The diagnostic accuracy and AUC of CUS+S-detect+VTIQ were higher than those of S-detect or VTIQ applied to CUS alone (P<0.05). The sensitivities of CUS for senior radiologists, CUS for junior radiologists, CUS+S-detect+VTIQ for senior radiologists, and CUS+S-detect+VTIQ for junior radiologists were 60.00%, 80.00%, 72.73%, and 90.00%, respectively, when diagnosing benign and malignant breast masses in 50 randomly selected cases. The specificities for them was 66.67%, 76.67%, 80.00%, and 81.25%, respectively. The accuracies for them was 64.00%, 78.00%, 80.00%, and 88.00%, respectively. The AUCs for them were 0.63, 0.78, 0.88, and 0.80, respectively. Compared with the CUS for junior radiologists, the CUS+S-detect+VTIQ for junior radiologists had higher sensitivity, specificity, and accuracy (all P<0.05). The consistency of the combined application of S-detect and VTIQ for diagnosing breast masses at 2 different times was good among junior radiologists (Kappa=0.800). METHODS: CUS, S-detects, and VTIQ were used to differentially diagnose benign and malignant breast masses in 108 cases, and the final pathological results were referred to as the gold standard for classifying breast masses. The diagnostic efficacy were evaluated and compared, among the 3 methods and among S-detect applied to CUS (CUS+S-detect), VTIQ applied to CUS (CUS+VTIQ), and S-detect combined with VTIQ applied to CUS (CUS+S-detect+VTIQ). Fifty cases were acquired randomly from the collected breast masses, and 2 radiologists with different years of experience (2 and 8 years) used S-detect combined with VTIQ for the ultrasonic differential diagnosis of benign and malignant breast masses. RESULTS: The differences in sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC) of the 3 diagnostic methods of CUS, S-detect, and VTIQ were not statistically significant (all P>0.05). The sensitivities of CUS, CUS+Sdetect, CUS+VTIQ, and CUS+S-detect+VTIQ were 78.57%, 92.86%, 69.05%, and 95.24%, respectively, the specificities for them were 69.70%, 78.79%, 87.88%, and 92.42%, respectively, the accuracies for them were 73.15%, 84.26%, 80.56%, and 93.52%. CONCLUSIONS: S-detect combined with VTIQ when applied to CUS can overcome the shortcomings of separate applications and complement each other, especially for junior radiologists, and can more effectively improve the diagnostic efficacy of ultrasound for benign and malignant breast masses.

Management of Pediatric Breast Masses: A Multi-institutional Retrospective Cohort Study.

BACKGROUND: The objective of our study was to describe the workup, management, and outcomes of pediatric patients with breast masses undergoing operative intervention. MATERIALS AND METHODS: A retrospective cohort study was conducted of girls 10-21 y of age who underwent surgery for a breast mass across 11 children's hospitals from 2011 to 2016. Demographic and clinical characteristics were summarized. RESULTS: Four hundred and fifty-three female patients with a median age of 16 y (IQR: 3) underwent surgery for a breast mass during the study period. The most common preoperative imaging was breast ultrasound (95%); 28% reported the Breast Imaging Reporting and Data System (BI-RADS) classification. Preoperative core biopsy was performed in 12%. All patients underwent lumpectomy, most commonly due to mass size (45%) or growth (29%). The median maximum dimension of a mass on preoperative ultrasound was 2.8 cm (IQR: 1.9). Most operations were performed by pediatric surgeons (65%) and breast surgeons (25%). The most frequent pathology was fibroadenoma (75%); 3% were phyllodes. BI-RADS scoring ≥4 on breast ultrasound had a sensitivity of 0% and a negative predictive value of 93% for identifying phyllodes tumors. CONCLUSIONS: Most pediatric breast masses are self-identified and benign. BI-RADS classification based on ultrasound was not consistently assigned and had little clinical utility for identifying phyllodes.

ACR BI-RADS Category 3 Lesions in Women Younger Than 30: Follow-up Outcomes and Factors Associated With Biopsy.

OBJECTIVE: Investigate imaging follow-up patterns and assessment of malignancy rate of BI-RADS 3 lesions in women younger than 30 years. METHODS: We retrospectively reviewed consecutive studies between January 1, 2013 and January 1, 2015 with BI-RADS 3 assessment in women <30 years. Lesion size, follow-up rate, and biopsy rate were recorded. Completion of 24-month imaging follow-up or biopsy determined the endpoint. Statistical analysis of follow-up rates and biopsy timing was performed. RESULTS: Of 2525 BI-RADS 3 lesions, 278 were identified in 215 women <30 years. Fifty-two (24%) women underwent a biopsy which was more frequently done at patient request than for lesion growth [33 (63.4%) versus 19 (36.5%), P <.01]. The odds of having biopsy upfront was significantly higher in lesions >2 cm in diameter (OR: 4.4 [95% CI 2.1-9.4], P <.01). The malignancy rate in our cohort was 0% (95% CI 0-1.7%). Of the 188 women expected for follow-up imaging, 58 (30%) were lost to follow-up, while 103 (55%) had 6-month follow-up, 74 (39%) 12-month follow-up, and 56 (30%) 24-month follow-up. CONCLUSIONS: BI-RADS 3 lesions identified in our cohort had high biopsy rates and low compliance with no cancers. Our findings suggest that probable fibroadenomas in young women may only warrant abbreviated short-term follow-up at 6-months.

Comparison of the Diagnostic Performance of Power Doppler Ultrasound and a New Microvascular Doppler Ultrasound Technique (AngioPLUS) for Differentiating Benign and Malignant Breast Masses.

This study was performed to compare the diagnostic performance of power Doppler ultrasound (US) and a new microvascular Doppler US technique (AngioPLUS; SuperSonic Imagine, Aix-en-Provence, France) for differentiating benign and malignant breast masses. Power Doppler US and AngioPLUS findings were available in 124 breast masses with confirmed pathologic results (benign, 80 [64.5%]; malignant, 44 [35.5%]). The diagnostic performance of each tool was calculated to distinguish benign from malignant masses using a receiver operating characteristic curve analysis and compared. The area under the curve showed that AngioPLUS was superior to power Doppler US in differentiating benign from malignant breast masses, but the difference was not statistically significant.

[The value of ultrasound classification in BI-RADS category 4 of breast complex cystic masses].

Objective: To analyze the feature of breast complex cystic masses and to classify it at ultrasonography (US), which applied to the Breast Imaging Reporting and Data System (BI-RADS) categories 4a to 4c with pathological results as the golden standards. Methods: The ultrasonographic data and clinical features of 78 patients with complex cystic masses confirmed by pathology in Cancer Hospital from July 2014 to June 2017 were retrospectively reviewed. The complex cystic breast masses were divided into four classes on the basis of their US features: type 1 [thick wall and (or) thick septa (> 0.5 mm)], type 2 (one or more intra-cystic masses), type 3 (mixed cystic and solid components with cystic components more than 50%) and type 4 (mixed cystic and solid components with solid components more than 50%). Positive values (PPVs) were calculated for each type. Multiple linear regression analysis was used to analyze the ultrasonographic features of the masses (lesion size, margins, blood flow resistance index, calcification, and axillary lymph nodes, etc.) with malignant correlation. Results: There were 81 lesions in 78 patients. Among the 81 masses based on US appearance, 14 (17.3%) were classified as type Ⅰ, 18 (22.2%) as type Ⅱ, 18 (22.2%) as type Ⅲ, and 31 (38.3%) as type Ⅳ. The positive predictive values of the malignant lesions of type Ⅰ, type Ⅱ, Ⅲ and Ⅳ were 7.1%, 16.7%, 61.1% and 48.3%, respectively (P=0.040). In all the 81 masses, 14 were BI-RADS categories 4a, 18 were BI-RADS categories 4b and 49 were BI-RADS categories 4c. Masses with maximum diameter equal to or larger than 2.0 cm, unclear margins, RI≥0.7 and presence of abnormal axillary nodes assessment had a high probability of malignancy (P=0.030, 0.038, <0.001 and 0.025, respectively). Conclusion: Ultrasound typing is helpful for differentiating benign and malignant breast complex cysts and classifying BI-AIDS 4a to 4c, thus providing clearer treatment for clinical practice.

Is clinical breast examination important for breast cancer detection?

BACKGROUND: Screening clinical breast examination (cbe) is controversial; the use of cbe is declining not only as a screening tool, but also as a diagnostic tool. In the present study, we aimed to assess the value of cbe in breast cancer detection in a tertiary care centre for breast diseases. METHODS: This retrospective study of all breast cancers diagnosed between July 1999 and December 2010 at our centre categorized cases according to the mean of detection (cbe, mammography, or both). A cbe was considered "abnormal" in the presence of a mass, nipple discharge, skin or nipple retraction, edema, erythema, peau d'orange, or ulcers. RESULTS: During the study period, a complete dataset was available for 6333 treated primary breast cancers. Cancer types were ductal carcinoma in situ (15.3%), invasive ductal carcinoma (75.7%), invasive lobular carcinoma (9.0%), or others (2.2%). Of the 6333 cancers, 36.5% (n = 2312) were detected by mammography alone, 54.8% (n = 3470) by mammography and cbe, and 8.7% (n = 551) by physician-performed cbe alone (or 5.3% if considering ultrasonography). Invasive tumours diagnosed by cbe alone were more often triple-negative, her2-positive, node-positive, and larger than those diagnosed by mammography alone (p < 0.05). CONCLUSIONS: A significant number of cancers would have been missed if cbe had not been performed. Compared with cancers detected by mammography alone, those detected by cbe had more aggressive features. Clinical breast examination is a very low-cost test that could improve the detection of breast cancer and could prompt breast ultrasonography in the case of a negative mammogram.

Biopsy versus conservative management of sonographically benign-appearing solid breast masses in adolescents.

OBJECTIVES: To determine whether the size of palpable solid breast masses in adolescents at initial sonography and their growth at follow-up sonography could be used to decide between conservative management and tissue biopsy. METHODS: This retrospective study included 37 adolescent female patients with 45 palpable benign-appearing solid breast masses on initial sonography. They were grouped as follows: group I, masses undergoing follow-up sonography with subsequent biopsy (n = 9); group II, masses undergoing biopsy without follow-up sonography (n = 13); and group III, masses undergoing follow-up sonography without biopsy (n = 23). The largest dimension, volume, volume change per month, and change in the sonographic appearance were analyzed to predict the need for biopsy. A combination of a largest dimension greater than 3 cm and volume change per month greater than 16% was used to assess the need for biopsy. Sonograms of 22 masses were correlated with histopathologic diagnoses. RESULTS: None of the masses that underwent follow-up sonography showed changes in their sonographic appearance. All masses that underwent biopsy were benign on histopathologic analysis. There was no significant difference in the largest dimension among the groups at initial sonography or between groups I and III at follow-up sonography. The volume change was smaller for fibroadenomas (n = 7; mean, 22.67%) than benign phyllodes tumors (n = 2; mean, 45.30%) in group I, but the difference was not significant (P = .384). However, the volume change for groups I and III showed a significant difference (P = .026). Neither size greater than 3 cm nor volume change greater than 16% predicted pathologic outcomes. CONCLUSIONS: If the combined criteria for assessing benignity of palpable breast masses had been used, biopsy could have been reduced by 89% in group I and deemed not necessary in 96% of group III breast masses.

Breast imaging reporting and data system for sonography: Positive and negative predictive values of sonographic features in Kumasi, Ghana.

BACKGROUND: Breast cancer is the most common female cancer globally. The method of choice for screening and diagnosing breast cancer is mammography, which is not widely available in Ghana as compared to ultrasonography. This study aimed to evaluate the sonographic features of solid breast lesions using the new sonographic Breast Imaging- Reporting and Data System (BI-RADS-US) lexicon for malignancy with histopathology as the gold standard. METHODS: This was a prospective quantitative study that sonographically scanned female patients with breast masses and consecutively selected cases recommended for core biopsy from May 2018 to May 2021. Sixty (60) solid breast masses were described using the sonographic BI-RADS lexicon features. Lesion description and biopsy results from histopathology were compared and analyzed using Pearson's Chi-square test. Odds ratios, sensitivity, specificity, and predictive values were also calculated. Statistical significance level was set at p ≤ 0.05. RESULTS: Irregular shape (p < 0.0001), spiculated mass margins (p < 0.0001), and not parallel mass orientation (p= 0.0007) were more commonly associated with malignant masses. The sensitivity of breast ultrasound for malignancy was 93.9 % and the specificity was 55.6 % with an overall accuracy rate of 76.6 %. The negative predictive value was 88.7 % and the positive predictive value was 72.1 %. Descriptors like irregular shape, non-parallel orientation, angular and spiculated margins, echogenic halo, and markedly hypoechoic internal content, demonstrated higher odds ratios for malignancy. CONCLUSIONS: This study adds valuable insights to the diagnosis of breast cancer using the sonographic BI-RADS lexicon features. The results demonstrate that specific sonographic descriptors can effectively differentiate between benign and malignant breast masses.

Contrast-Enhanced Ultrasound in the Evaluation of Complex Cystic and Solid Breast Masses-A Feasibility Study.

OBJECTIVE: Complex cystic and solid breast mass (CCSBM) is a radiological diagnosis based on grayscale B-mode sonographic features. Because of potential for malignancy, biopsy is typically recommended. We examined the feasibility of contrast-enhanced US (CEUS) as a tool to identify benign CCSBMs. METHODS: This Institutional Review Board-approved prospective observational study performed targeted CEUS of 14 CCSBMs that were subsequently biopsied. CEUS images were independently reviewed by two readers blinded to other sonographic features, noting presence or absence of enhancement and time to perceived optimal enhancement. Interobserver agreement for presence or absence of enhancement was analyzed using Cohen's kappa coefficient. From retrospective review of initial diagnostic US examinations, descriptive CCSBM sizes, subtypes, and Doppler information were recorded. Histopathologies were categorized as benign, benign with upgrade potential (BWUP), and malignant. Measures of diagnostic accuracy and 95% CIs were calculated for CEUS enhancement. RESULTS: Of 14 CCSBMs, 12 were nonmalignant (9 benign, 3 BWUP) and 2 were malignant. There was perfect interobserver agreement (Cohen's kappa 1.00) between the 2 readers for CEUS enhancement. CEUS was 100% sensitive, 25% specific, with an area under the receiver operating characteristic curve (AUROC) of 0.625 (95% CI, 0.50-0.75) in differentiating nonmalignant from malignant lesions. It was 100% sensitive, 33.3% specific, with an AUROC of 0.667 (95% CI, 0.50-0.85) in differentiating benign from surgically significant (BWUP and malignant) CCSBMs. CONCLUSION: This small feasibility study highlighted the potential of CEUS as a safe noninvasive tool to identify the proportion of CCSBMs that are benign and can avoid tissue biopsy.

Adenoma of the Nipple: A Case Report.

Nipple adenomas are rare, benign breast lesions that present similarly to breast malignancies, often manifesting with unilateral bloody discharge, a palpable mass, and/or nipple distortion. Imaging techniques have limited specificity in distinguishing nipple adenomas from malignancy; therefore, clinicians must rely on histologic and immunohistochemistry evaluation. Here, we highlight the case of a 69-year-old woman with bilateral nipple adenomas presenting as an enlarging nipple mass with chronic nipple discharge. Complete lesion resection with clear margins stands as the primary route of management and complete avoidance of re-occurrence. However, partial excision with nipple preservation has been reported to be successful in selected cases.

Breast hydatid cyst mimicking fibroadenoma and malignancy: A case report.

Echinococcus granulosis is known as the cause of hydatid cyst disease. It is often seen in many regions of the world, and can cause serious health problems. This parasite can invade tissues in all parts of the body and produce hydatid cysts, although it has been mainly observed in the liver and the lungs. Breast hydatid cysts are encountered rarely. After physical examination, radiological and serological tests are performed on patients with breast hydatid disease. These examinations are helpful for an early diagnosis, but they are insufficient to make a definitive diagnosis, which can only be made according to the results of histopathological examinations. We had a primary diagnosis of either fibroadenoma or malignancy in the breast during the preoperative period of the present case. A precise diagnosis could only be made by histopathological examinations in the postoperative period.

The Correlation of Sonographic and Histopathologic Findings in the Diagnosis of Palpable Breast Masses in Zaria.

Introduction: Presently, histology is the gold standard in definite diagnosis of breast masses. Ultrasound is a relatively cheap, non-invasive, and non-ionizing imaging modality which is widely available in most hospitals. An assessment of its accuracy in diagnosing breast masses is necessary to minimize unwarranted biopsies. Aim and Objectives: This study aims to correlate the ultrasonographic and histopathologic findings in the diagnosis of patients with palpable breast masses. Materials and Methods: This was a cross-sectional hospital-based study, which involved 100 consecutive patients who presented with palpable breast masses in Zaria. This was carried out for a period of 7 months (November 2016-June 2017). They had a clinical breast examination to identify the mass, which was then imaged and biopsied via ultrasound-guided fine needle aspiration cytology. Results: The generated data were analysed using SPSS version 23.0 (Chicago, IL, USA). There were more benign masses (63%) than malignant masses (29%). On correlating the final diagnosis of ultrasound to that of histology, it was found to have a sensitivity of 89%; specificity of 94%; positive predictive value of 89%; negative predictive value of 94%; and accuracy of 92%. Conclusion: This study shows that there was a correlation between ultrasound and histology findings in differentiating between benign and malignant masses. This proves that ultrasound has a significant role to play in evaluating and diagnosing clinically palpable breast masses.

Borderline Phyllodes Tumor in a Child.

Phyllodes tumor (PT) is considered a rare fibroepithelial tumor. Very few series have been reported in children and adolescents. Based on histopathological features, it can be classified as benign, borderline, or malignant, with the latter having a more aggressive clinical behavior. We report the case of a 10-year-old female who began with an asymptomatic mobile right breast mass. An initial fine needle biopsy (FNB) concluded fibroadenoma (FA). Months later, the mass kept growing, with the appearance of pain and nipple discharge. Benign PT was demonstrated in a new biopsy. A total mastectomy was performed. The post-surgical histopathological examination was compatible with a borderline PT. The patient is now symptom-free and with no signs of relapse. Not all breast masses in the pediatric or adolescent age bracket are FA. Attention is warranted when the clinical behavior does not follow the usual outline. PT has to be considered as a possible diagnosis and treated accordingly.

Breast development and disorders in children and adolescents.

Breast masses are infrequently encountered in pediatric and adolescent populations. Most breast masses in children are benign entities arising from embryological defects which can be managed once breast development is complete. Diagnostic and management dilemmas arise when fibroepithelial lesions of the breast are seen in clinical practice. Differentiation between a fibroadenoma and a phyllodes tumor is important to guide management. Breast cancer in children under 18 years of age is extremely rare and invasive diagnostic testing and aggressive management is only recommended when clinical suspicion of malignancy is very high. Patient and caregiver counseling plays an important role in the management of these diseases. While adult-onset breast diseases have been studied very closely, there is a dearth of literature on pediatric breast anomalies. This review aims to provide a scoping overview of the available literature on benign, fibroepithelial, and malignant lesions of the breast in pediatric and adolescent populations to help guide physicians and surgeons with decision-making regarding the diagnosis and management of pediatric breast diseases.