Search

It is crucial to diagnose breast cancer early and accurately to optimize treatment. Presently, most deep learning models used for breast cancer detection cannot be used on mobile phones or low-power devices. This study intended to evaluate the capabilities of MobileNetV1 and MobileNetV2 and their fine-tuned models to differentiate malignant lesions from benign lesions in breast dynamic contrast-enhanced magnetic resonance images (DCE-MRI). [ABSTRACT FROM AUTHOR]

Purpose: Hyperprolactinaemia has been proposed to play a role in breast lesions pathophysiology. Thus far, controversial results have been reported for the relationship between hyperprolactinaemia and breast lesions. Moreover, the prevalence of hyperprolactinaemia in a population with breast lesions is scarcely reported. We aimed to investigate the prevalence of hyperprolactinaemia in Chinese premenopausal women with breast diseases, and explore the associations between hyperprolactinaemia with different clinical characteristics. Methods: This was a retrospective cross-sectional study performed in the department of breast surgery of Qilu hospital of Shandong University. Overall, 1,461 female patients who underwent the serum prolactin (PRL) level assay before breast surgery from January 2019 to December 2020 were included. Patients were divided into two groups: before and after menopause. Data were analyzed using SPSS 18.0 software. Results: The results showed an elevated PRL level in 376 of the 1,461 female patients with breast lesions (25.74%). Furthermore, the proportion of hyperprolactinemia among premenopausal patients with breast disease (35.75%, 340/951) was significantly higher than among postmenopausal patients with breast disease (7.06%, 36/510). In premenopausal patients, the proportion of patients with hyperprolactinaemia and the mean serum PRL level were significantly higher in those diagnosed with fibroepithelial tumours (FETs) and in younger patients (aged < 35 years) than in those with non-neoplastic lesions and in those aged ≥ 35 years (both p < 0.05). Especially, the prolactin level exhibited steady ascending tendency for positive correlation with FET. Conclusion: Hyperprolactinaemia is prevalent in Chinese premenopausal patients with breast diseases, especially in those with FETs, which implies a potential association, to some extent, between the PRL levels in various breast. [ABSTRACT FROM AUTHOR]

Background: Breast lesions are areas of abnormal breast tissue. It is estimated that 20% of women develop breast lesions. Breast lesions are either benign or malignant. Breast carcinomas are the most common cause of deaths in women accounting for 10.6% deaths in India, 6.9% deaths per year globally. Aims and Objectives: To study various histopathological patterns of breast lesions in women admitted in Government General Hospital. Materials and Methods: It is a prospective study in the department of pathology, Government General Hospital, Nizamabad, from December 2020 to July 2022. Grossing was done and details noted, tissue bits were processed and sections were stained with conventional H and E Staining. Results: Out of 70 cases of breast lesions, 55 (78.5%) are benign breast lesions and 15 (21.5%) are malignant breast lesions. Fibroadenoma is the most common breast lesion accounting for 33 cases, that is, 60 %, followed by fibrocystic diseases (21.8%). Infiltrating ductal carcinoma of No Special Type is the most common malignant breast lesion accounting for 10 cases, that is, 66.6%. Among invasive breast carcinomas, the majority of cases are Grade II (69%). Conclusion: Study of histopathological patterns of breast lesions plays an important role in diagnosis, treatment, and prognosis of breast lesions. This study highlighted incidence and pathological characteristics of a wide range of breast lesions. [ABSTRACT FROM AUTHOR]

Background: MRI has an essential role in breast imaging, along with mammography and ultrasonography. DCE- MRI is not 100% accurate in discriminating benign from malignant lesions. In attempt to improve the specificity of DCE-MRI, multiparametric MRI (mp-MRI) with additional functional parameters had been introduced. Objectives: To assess the added diagnostic value of MR spectroscopy in evaluation of suspicious breast lesions. Patients and methods: This prospective study included 60 females, their mean age was 42.1 ± 12 SD with 75 breast lesions categorized as BI-RADS 3 or BI-RADS 4 based on sonomamography. They were subjected to multiparametric breast MRI (T2WI, dynamic contrast-enhanced MR imaging, diffusion-weighted images, and MR spectroscopy). ROC-analysis was employed for comparison between the diagnostic accuracy of mp-MRI and mp-MRI combined with MRS to predict the malignant lesions using the histopathological results as a standard of reference. Results: 33 (55 %) patients had histopathologically diagnosed 43 (58%) benign breast lesions and 27 (45%) patients had 32 (42%) malignant lesions. Using mp-MRI (dynamic contrast-enhanced MR imaging, T2-weighted images and diffusion-weighted images) had 98% accuracy of with 97.8%, sensitivity and 98.6%, specificity in differentiating malignant from benign lesions. A higher diagnostic 99.2% accuracy was obtained from combined mp-MRI and MRS with 99.5% sensitivity, 98.6% specificity. Conclusion: Despite of its limitations, MRS is a promising functional MRI technique thus improves the diagnostic accuracy of MRI for characterization of suspicious breast lesions when combined to mp-MRI to avoid unnecessary biopsy.

Background: Breast cancer is the second cause of cancer death in women. Shear wave elastography (SWE) is an ultrasound (US) procedure that can improves the sensitivity and the specificity in the diagnosis of breast lesions. Objective: To evaluate the value of SWE to discriminate benign from malignant Breast Imaging-Reporting and Data System (BI-RADS) IV breast lesions. Materials and Methods: A cross sectional analytic study was done in the Radiology Department, Oncology Teaching Hospital, Baghdad Medical City, Baghdad, Iraq. The study period was one year (February 2020 to January 2021). The study included 42 female patients with suspicious breast lesions in the group BI-RAD 4 by mammography and US. Shear wave elastography was done for all patients. The final diagnosis of all breast lesions were done by fine needle aspiration cytology or true cut biopsy or excisional biopsy. Results: The final histological diagnosis showed that 23 (54.8%) of study patients were with benign breast lesions. There was a statistically significant association between the quality of SWE and histopathological diagnosis as the proportion of malignant breast lesions was significantly higher among the patients with score 5 (homogenous dark blue) images (85.7%, P= 0.004). Subjectts with malignant lesions had a significantly higher mean of E-mean SWV than those with benign lesions (133.8 versus 75.47 kPa, P = 0.001). The best cut point of E-mean SWV was 83 kPa (E-mean SWV > 83 kPa is predictive for malignant lesion of breast) with 89.5% sensitivity, 60.9% specificity, and 73.8% accuracy. Conclusion: SWE have a significant diagnostic value in differentiation of BI-RADS IV breast lesions into benign and malignant in both qualitative and quantitative patterns. The best cut off value in SWE is 83 KPa for E-mean.

Summary: Background: Breast cancer is the leading cause of cancer-related deaths in women. However, accurate diagnosis of breast cancer using medical images heavily relies on the experience of radiologists. This study aimed to develop an artificial intelligence model that diagnosed single-mass breast lesions on contrast-enhanced mammography (CEM) for assisting the diagnostic workflow. Methods: A total of 1912 women with single-mass breast lesions on CEM images before biopsy or surgery were included from June 2017 to October 2022 at three centres in China. Samples were divided into training and validation sets, internal testing set, pooled external testing set, and prospective testing set. A fully automated pipeline system (FAPS) using RefineNet and the Xception + Pyramid pooling module (PPM) was developed to perform the segmentation and classification of breast lesions. The performances of six radiologists and adjustments in Breast Imaging Reporting and Data System (BI-RADS) category 4 under the FAPS-assisted strategy were explored in pooled external and prospective testing sets. The segmentation performance was assessed using the Dice similarity coefficient (DSC), and the classification was assessed using heatmaps, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The radiologists’ reading time was recorded for comparison with the FAPS. This trial is registered with China Clinical Trial Registration Centre (ChiCTR2200063444). Findings: The FAPS-based segmentation task achieved DSCs of 0.888 ± 0.101, 0.820 ± 0.148 and 0.837 ± 0.132 in the internal, pooled external and prospective testing sets, respectively. For the classification task, the FAPS achieved AUCs of 0.947 (95% confidence interval [CI]: 0.916–0.978), 0.940 (95% [CI]: 0.894–0.987) and 0.891 (95% [CI]: 0.816–0.945). It outperformed radiologists in terms of classification efficiency based on single lesions (6 s vs 3 min). Moreover, the FAPS-assisted strategy improved the performance of radiologists. BI-RADS category 4 in 12.4% and 13.3% of patients was adjusted in two testing sets with the assistance of FAPS, which may play an important guiding role in the selection of clinical management strategies. Interpretation: The FAPS based on CEM demonstrated the potential for the segmentation and classification of breast lesions, and had good generalisation ability and clinical applicability. Funding: This study was supported by the Taishan Scholar Foundation of Shandong Province of China (tsqn202211378), National Natural Science Foundation of China (82001775), Natural Science Foundation of Shandong Province of China (ZR2021MH120), and Special Fund for Breast Disease Research of Shandong Medical Association (YXH2021ZX055).

Background: Diffusion tensor imaging (DTI) is a novel approach which uses extra gradients to quantify diffusion in several directions (at least six). The purpose of this research was to determine the role of diffusion tensor magnetic resonance imaging in breast lesion differentiation. Results: Apparent diffusion coefficient (ADC) values were significantly lower in malignant than benign lesions, with a cut-off value of 1.21 × 10−3 mm2/s, this gives a sensitivity of 88.46%, specificity 87.50% and accuracy 86.7%. Values of fractional anisotropy (FA) were higher significantly in malignant compared to benign lesions with a 0.15 cut-off value, has a 95.83% sensitivity, 96.15% specificity, and 95.6%, accuracy. Values of RA were significantly higher in malignant (0.180 ± 0.068) compared to benign lesions, with 0.13 cut-off value. Sensitivity, specificity, and accuracy were, respectively, 91.69%, 92.31%, and 90.2%. Values of λ1 were significantly lower in malignant (1.4 ± 0.453 × 10−3 mm2/s) than in benign (2.19 ± 0.659 × 10−3 mm2/s) lesions with a cut-off value of 1.71 × 10−3 mm2/s. Sensitivity and specificity were, respectively, 95.83 and 96.15%. The combined evaluation by (dynamic contrast enhancement) Sensitivity improved to 100% with DCE and DTI readings, while specificity remained at 95.6%. Conclusions: DTI breast imaging is a noninvasive procedure which demonstrated a high potential utility for cancer detection and serving as a standalone technique or in conjunction with DCE-MRI, the discriminating values of FA, λ1 and λ1–λ3 were high. Their measurements were strongly associated with identification breast malignancy and combined evaluation by DTI parameters and DCE-MRI DTI enhanced the sensitivity, lowered the rate of false-negatives, and completely improved the accuracy of breast lesions differential diagnosis. [ABSTRACT FROM AUTHOR]

Introduction: breast lumps account for a greater number of lesions in women attending surgical clinics in the developing world. Breast cancer which mostly presents as a breast lump is the leading cancer in Kenya, with an incidence of 12.5%. The study aims to describe the patterns of breast lesions in women presenting with palpable breast lumps in two major referral hospitals in Kenya. Methods: seven hundred and sixty-eight study participants with palpable lumps underwent fine needle aspiration cytology (FNAC). Sociodemographic data were captured using structured questionnaires. The FNAC materials were evaluated using the International Academy of Cytology Yokohama System (IACYS) and the lesions were classified into five-tier categories. Frequencies and percentages were used to summarize qualitative variables. Results: of 768 smears, 84.8% (n=651) were adequate for evaluation while 15.2% (n=117) were inadequate. Neoplastic lesions comprised 84.5% (n=550) and non-neoplastic 15.5% (n=101). Benign lesions accounted for 83.6% of the lesions followed by breast carcinoma (10.4%). Ductal carcinoma comprised 98.5% of cancerous lesions. The age group most affected with ductal carcinoma and suspicious lesions was 20-34 years (37.3% and 55.6% respectively). Fibroadenoma formed the bulk of the benign lesions identified (44.1%). Suspicious of malignancy was 4.1% (n=27). The age group with the most lesions (47.5%) was 20-34 years. Conclusion: a wide spectrum of breast lesions was established. Such include inflammatory, atypical, benign, suspicious of malignancy, and malignant lesions. Fibroadenoma was a common lesion diagnosed. The age group most affected by malignant lesions was 16-49 years, necessitating enhanced screening of women with breast lumps in our setups. [ABSTRACT FROM AUTHOR]

Copyright of Imaging Science & Photochemistry is the property of Imaging Science & Photochemistry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: To explore the ability of You Only Look Once version 5 (YOLOv5) to detect and classify breast lesions on dynamic contrast-enhanced MRI. Methods: Four YOLOv5 submodels were examined. A total of 2124 and 2226 images of benign and malignant lesions were obtained, respectively. Precision, recall rate and mean average precision were used to evaluate model performance. Results: The precision (0.916) and mean average precision _0.5 (0.894) of YOLOv5s were higher than those of YOLOv5m (0.832, 0.794), YOLOv5l (0.843, 0.803) and YOLOv5x (0.854, 0.821). In the validation set, YOLOv5s required 1.1 ms to detect lesions per image. Conclusion: YOLOv5s was the fastest and had the highest precision among the four YOLOv5 submodels for the detection and classification of breast lesions on dynamic contrast-enhanced MRI. It has a greater clinical application value. You Only Look Once version 5 (YOLOv5) is the latest YOLO series, which may be a useful tool for detecting and classifying breast lesions on dynamic contrast-enhanced MRI (DCE-MRI) and help clinicians make a rapid, accurate diagnosis and provide treatment. Data were retrospectively collected from a single-center study. The performances of the four submodels (YOLOv5s, YOLOv5m, YOLOv5l and YOLOv5x) were compared. The diagnostic performances of YOLOv5s were comparable with some convolutional neural network models for breast lesion identification in breast ultrasonography and mammography. This study may provide novel insights into the detection and classification of breast lesions on DCE-MRI. Thus, a sufficiently large series of data and high-quality DCE-MRIs are warranted. Owing to its applications in artificial intelligence-assisted imaging diagnosis, this method has promising prospects. [ABSTRACT FROM AUTHOR]

Background: Diffusion kurtosis imaging (DKI) is used to differentiate between benign and malignant breast lesions. DKI fits are performed either on voxel‐by‐voxel basis or using volume‐averaged signal. Purpose: Investigate and compare DKI parameters' diagnostic performance using voxel‐by‐voxel and volume‐averaged signal fit approach. Study type: Retrospective. Study population: A total of 104 patients, aged 24.1–86.4 years. Field Strength/Sequence: A 3 T Spin‐echo planar diffusion‐weighted sequence with b‐values: 50 s/mm2, 750 s/mm2, and 1500 s/mm2. Dynamic contrast enhanced (DCE) sequence. Assessment Lesions were manually segmented by M.P. under supervision of S.O. (2 and 5 years of experience in breast MRI). DKI fits were performed on voxel‐by‐voxel basis and with volume‐averaged signal. Diagnostic performance of DKI parameters DK (kurtosis corrected diffusion coefficient) and kurtosis K was compared between both approaches. Statistical Tests: Receiver operating characteristics analysis and area under the curve (AUC) values were computed. Wilcoxon rank sum and Students t‐test tested DKI parameters for significant (P <0.05) difference between benign and malignant lesions. DeLong test was used to test the DKI parameter performance for significant fit approach dependency. Correlation between parameters of the two approaches was determined by Pearson correlation coefficient. Results: DKI parameters were significantly different between benign and malignant lesions for both fit approaches. Median benign vs. malignant values for voxel‐by‐voxel and volume‐averaged approach were 2.00 vs. 1.28 (DK in μm2/msec), 2.03 vs. 1.26 (DK in μm2/msec), 0.54 vs. 0.90 (K), 0.55 vs. 0.99 (K). AUC for voxel‐by‐voxel and volume‐averaged fit were 0.9494 and 0.9508 (DK); 0.9175 and 0.9298 (K). For both, AUC did not differ significantly (P = 0.20). Correlation of values between the two approaches was very high (r = 0.99 for DK and r = 0.97 for K). Data Conclusion: Voxel‐by‐voxel and volume‐averaged signal fit approach are equally well suited for differentiating between benign and malignant breast lesions in DKI. Evidence Level 3 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Objective:In this prospective study, the diagnostic performance of the new version of superb microvascular imaging (SMI) in differentiating malignant from benign lesions was evaluated.Material and Methods:Ninety breast lesions were included. During color SMI examination, both free-hand region of interest (ROI) and box ROI were used. Vascular index (VI) values were obtained from the lesion using both types of ROI and from normal breast tissue via box ROI. VI values, monochrome SMI grading and histopathological results were compared. The efficacy of color SMI and monochrome SMI was investigated in differentiating between benign and malignant breast lesions.Results:The cut-off value, in the differentiation of benign and malignant lesions with color SMI was 0.50 for box ROI, while it was 0.30 for free-hand ROI. The specificity of VI values obtained with box ROI was higher than that of free-hand ROI when differentiating malignant lesions from benign. Comparison of VI values from a lesion and from normal breast tissue showed that VI values in malignant lesions were significantly higher (p

Abstract Background Shear wave elastography can evaluate tissue stiffness. Previous studies showed that the elasticity characteristics of breast lesions were related to the components of extracellular matrix which was regulated by transforming growth factor beta 1(TGF-β1) directly or indirectly. However, the correlation of the expression level of TGF-β1, its signal molecules and elasticity characteristics of breast lesions have rarely been reported. The purpose of this study was to investigate the correlation between the expression level of TGF-β1, its signal molecules, and the elasticity characteristics of breast lesions. Methods 135 breast lesions in 130 patients were included. Elasticity parameters, including elasticity modulus, the elasticity ratio, the “stiff rim sign”, were recorded before biopsy and surgical excision. The expression levels of TGF-β1 and its signal molecules, including Smad2/3, Erk1/2, p38 mitogen-activated protein kinase (MAPK), c-Jun N-terminal kinase 2 (JNK2), phosphoinositide 3-kinase (PI3K), and protein kinase B (PKB/AKT) were detected by immunohistochemistry. The diagnostic performance of the expression level of those molecules and their correlation with the elasticity characteristics were analyzed. Results Elasticity parameters and the expression levels of TGF- β1 and its signal molecules of benign lesions were lower than those of malignant lesions (P

Abstract Background Breast cancer is considered the most serious lesion among different breast lesions. Mammography is the corner stone for screening for detection of breast cancer. It has been modified to digital mammography (DM) and then to digital breast tomosynthesis (DBT). Tomosynthesis is an emerging technique for diagnosis and screening of breast lesions. The aim of this study is to interrogate whether the addition of DBT to DM helps in better detection and characterization of different breast lesions. Methods This is a prospective study carried on 38 female patients according to our inclusion criteria. All patients were evaluated by using DM alone and thereafter with the addition of DBT to DM. Recall rate was calculated, and the imaging findings of each case were correlated with the final diagnosis and follow-up. Results DM identified 32 lesions while DBT with DM identified 37 lesions. On DM alone, 17 lesions were characterized as masses, 5 as focal asymmetry, 2 as architectural distortion, 7 as microcalcification and 1 as macrocalcification. With the addition of DBT, 27 lesions were characterized as masses, 1 as focal asymmetry, 1 as architectural distortion, 7 as microcalcification and 1 as macrocalcification. So, there were better detection and characterization of lesions with the addition of DBT than DM alone. The sensitivity, specificity, AUC, positive and negative predictive values were significantly higher with the addition of DBT to DM (100%, 90.5%, 0.952, 90% and 100%, respectively) than with DM (77.8%, 80.9%, 0.794, 77.8% and 80.9%, respectively) for all breast lesions. Conclusions The addition of DBT to DM helps in better detection and characterization of different breast lesions. This leads to early detection of breast cancer, improvement of the performance of radiologists and saving time by reduction of recall rate.

Background: This study aimed to explore whether collagen fiber features and collagen type I alpha 1 (COL1A1) are related to the stiffness of breast lesions and whether COL1A1 can predict axillary lymph node metastasis (LNM).Methods: Ninety-four patients with breast lesions were consecutively enrolled in the study. Amongst the 94 lesions, 30 were benign, and 64 were malignant (25 were accompanied by axillary lymph node metastasis). Ultrasound (US) and shear wave elastography (SWE) were performed for each breast lesion before surgery. Sirius red and immunohistochemical staining were used to examine the shape and arrangement of collagen fibers and COL1A1 expression in the included tissue samples. We analyzed the correlation between the staining results and SWE parameters and investigated the effectiveness of COL1A1 expression levels in predicting axillary LNM.Results: The optimal cut-off values for Emax, Emean, and Eratio for diagnosing the benign and malignant groups, were 58.70 kPa, 52.50 kPa, and 3.05, respectively. The optimal cutoff for predicting axillary LNM were 107.5 kPa, 85.15 kPa, and 3.90, respectively. Herein, the collagen fiber shape and arrangement features in breast lesions were classified into three categories. One-way analysis of variance (ANOVA) showed that Emax, Emean, and Eratio differed between categories 0, 1, and 2 (P < 0.05). Meanwhile, elasticity parameters were positively correlated with collagen categories and COL1A1 expression. The COL1A1 expression level > 0.145 was considered the cut-off value, and its efficacy in benign and malignant breast lesions was 0.808, with a sensitivity of 66% and a specificity of 90%. Furthermore, when the COL1A1 expression level > 0.150 was considered the cut-off, its efficacy in predicting axillary LNM was 0.796, with sensitivity and specificity of 96% and 59%, respectively.Conclusions: The collagen fiber features and expression levels of COL1A1 positively correlated with the elastic parameters of breast lesions. The expression of COL1A1 may help diagnose benign and malignant breast lesions and predict axillary LNM. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to compare the stiffness of different histological types of breast lesions by obtaining shear wave elastography (SWE) and apparent diffusion coefficient (ADC) values, and to determine the contribution of these two methods to the diagnosis. Materials and Methods: In total, 70 patients with biopsy-proven breast lesions were included in the study. The mean SWE values of breast lesions were recorded and ADC values of these lesions were calculated. Receiver operating characteristic (ROC) curve analyses and the diagnostic accuracies of SWE-ADC values were determined. Results: The mean SWE values were 45.47 ± 25.11 kPa and 3.51 ± 1.04 m/s in benign group, and 161.11 ± 219.34 kPa and 5.96 ± 1.06 m/s in malignant group, respectively. The mean ADC values were 1.38 ± 0.32 (×10–3 mm2/s) in benign group and 0.96 ± 0.22 (×10–3 mm2/s) in malignant group, respectively. When the diagnostic performances of both imaging modalities on mass stiffness are evaluated, statistically significant negative correlations were found between SWE lesion values and ADC lesion values. Conclusion: Evaluation of tissue elasticity has recently been used frequently in the diagnosis of breast diseases. SWE-ADC values, which are negatively correlated in the diagnosis of breast masses, may prove to be a powerful alternative diagnostic tool that can be used interchangeably, as appropriate. [ABSTRACT FROM AUTHOR]

This study aims to compare the Magnetic Resonance Imaging (MRI) and Shear Wave Elastography (SWE) data and investigate their contribution to diagnosis when both are individually used and combined. This study included the consent of 46 diagnostic biopsy patients after their breast MRI examination was performed. Mass appearance patients in the sonographic evaluation were SWE examined before the biopsy. In MR examination, lesion localization, size, contrast curves, contrast enhancement features, intensity in the fat-suppressed T2A sequence, Emean value in SWE examination, and histopathological results were examined. Individual and combined use of MRI and SWE findings were evaluated with histopathological results. The diagnosis consistency was compared according to the histopathological results of the malignant-benign defined lesions. Higher sensitivity in MRI; higher specificity and accuracy in SWE were acquired when both methods were compared. The accuracy of MRI improved when MRI use is combined with SWE. The combined use of SWE with MRI increases the diagnostic accuracy in breast lesion characterization. We observed that lesions showing a type 3 enhancement curve and iso-hypointense on the T2W sequence in breast MRI could be predicted to show a stiff elasticity pattern on SWE due to higher elastography values. [ABSTRACT FROM AUTHOR]

Abstract Background The aim of the study is to characterize the breast lesions on high-resolution Ultrasound and digital mammography to find the patterns and prevalence of different breast lesions in different age groups of our population. Results This prospective study was conducted at a breast care clinic of a tertiary care hospital from Jan 2018 to Dec 2019. Patients with breast-related complaints were enrolled. Patients under the 35 years of age were evaluated on High-Resolution Ultrasound (HR-USG) and those over 35 years of age on digital Mammography. Any lesion on digital mammography was characterized on HR-USG. Fine Needle Aspiration (FNAC) and Trucut biopsy was done where pathological correlation required. Data of all enrolled patients were recorded and analyzed. Patients with known cases of carcinoma breast on follow-up were excluded from the study. Total 6850 patients enrolled in our breast care clinic during study period. 5111 were above the age of 35 years while 1739 were under the age of 35 years. No lesion could be found in 3915 patients and were reported normal. 2935 patients were found to have different breast lesions. The frequency of different lesions was different in both age groups. The overall frequency of lesions was as malignancy 16.2%, benign lesions including Fibroadenoma, simple cysts, Lipoma and Galactocele 16%, inflammatory lesions including abscess 7.86% and Duct Ectasia 2.75%. Conclusions In developing countries where mass screening programs are deficient, Breast Care clinics in tertiary care hospitals have a noteworthy role in early detection of breast cancer and other breast lesions.

Objective: сomparative assessment of the diagnostic efficiency of magnetic resonance imaging (MRI) and contrastenhanced ultrasound examination in the primary diagnosis of breast cancer based on propensity score matching.Materials and methods. From 2017 to 2018 on the basis of the National Medical Research Center of Oncology named after N.N. Petrov 176 women with various complaints of breast diseases were examined using MRI, which was carried out on a Magnetom Aera (Siemens) and Signa Excite HD (GE) apparatus with a magnetic field strength of 1.5 T and special surface breast coil. From 2018 to 2019 on the basis of the National Medical Research Center of Oncology named after N.N. Petrov 277 women with various complaints of breast diseases were examined using multiparametric ultrasonography (US) consisting of gray-scale US, color Doppler US, strain US, and contrast enhanced US, performed on a Hitachi Hi Vision Ascendus ultrasound scanner using a linear transducer in the frequency range 5–13 MHz. To verify the lesions, the patients underwent histological or cytological examination. The results of ultrasound examination, histological and cytological conclusions were entered into the database containing 453 diagnostic records: 277 were obtained using the multiparametric US and 176 – using the MRI method. To solve the problem, the propensity score matching algorithm was used: building a model, calculating conditional probabilities, balancing, checking the balance quality, evaluating efficiency. The main and auxiliary characteristics of the methods of MRI and contrast-enhanced ultrasound before and after the selection of pairs are given in the work.Conclusion. The proposed algorithm is implemented in the R language. The results of the program are that both diagnostic methods showed excellent results, 95 % confidence intervals almost completely overlap, from which a preliminary conclusion should be made that these methods are equivalent in efficiency in the primary diagnosis of breast cancer.

No literature is available on the benign versus malignant breast lesion ratio in trans women (male sex assigned at birth, female gender identity). As hormone treatment in trans women results in breast tissue histologically comparable with cis (non-trans) women, breast pathology may be expected. Previously, an increased breast cancer risk compared with cis men have been observed. We aimed to investigate the frequency and outcomes of breast biopsies in trans women. Therefore, we retrospectively examined the medical files of 2616 trans women. To gain data on breast lesions, we linked our cohort to a national pathology database. In this study we found that 126 people (5%) had one or more breast biopsies (n = 139). Of these, 21 trans women had a breast biopsy before the start of hormone treatment, and 53 after the start of hormone treatment. Breast biopsies were performed predominantly because of abnormalities during physical examination (37%, n = 51/139 biopsies), or because of capsular formation or contraction (28%, n = 16/57 biopsies) in trans women with breast implants. The most common breast lesions after the start of hormone treatment were fibroadenomas (n = 20), breast cancer (n = 6), fibrosis (n = 5), cysts (n = 4), and infections (n = 4). The benign versus malignant breast biopsy ratio was 88:12, which is comparable to the ratio in cis women (90:10). This study shows breast lesions in a limited number of trans women. Since the indications and outcomes of biopsies in trans women were similar to those in cis women, it seems reasonable to follow breast care guidelines as developed for cis women.

Aim:To reduce operator dependency and achieve greater accuracy, the computer-aided diagnosis (CAD) systems are becoming a useful tool for detecting noninvasively and determining tissue characterization in medical images. We aimed to suggest a CAD system in discriminating between benign and malignant breast masses.Methods:The dataset was composed of 105 randomly breast magnetic resonance imaging (MRI) including biopsy-proven breast lesions (53 malignant, 52 benign). The expectation-maximization (EM) algorithm was used for image segmentation. 2D-discrete wavelet transform was applied to each region of interests (ROIs). After that, intensity-based statistical and texture matrix-based features were extracted from each of the 105 ROIs. Random Forest algorithm was used for feature selection. The final set of features, by random selection base, splatted into two sets as 80% training set (84 MRI) and 20% test set (21 MRI). Three classification algorithms are such that decision tree (DT, C4.5), naive bayes (NB), and linear discriminant analysis (LDA) were used. The accuracy rates of algorithms were compared.Results:C4.5 algorithm classified 20 patients correctly with a success rate of 95.24%. Only one patient was misclassified. The NB classified 19 patients correctly with a success rate of 90.48%. The LDA Algorithm classified 18 patients correctly with a success rate of 85.71%.Conclusion:The CAD equipped with the EM segmentation and C4.5 DT classification was successfully distinguished as benign and malignant breast tumor on MRI.

Background: Ultrasonography is the main examination method for breast diseases. Ultrasound imaging is currently relied upon by doctors to form statements of characteristics and locations of lesions, which severely limits the completeness and effectiveness of ultrasound image information. Moreover, analyzing ultrasonography requires experienced ultrasound doctors, which are not common in hospitals. Thus, this work proposes a 3D-based breast ultrasound system, which can automatically diagnose ultrasound images of the breasts and generate a representative 3D breast lesion model through typical ultrasonography. Methods: In this system, we use a weighted ensemble method to combine three different neural networks and explore different combinations of the neural networks. On this basis, a breast locator was designed to measure and transform the spatial position of lesions. The breast ultrasound software generates a 3D visualization report through the selection and geometric transformation of the nodular model. Results: The ensemble neural network improved in all metrics compared with the classical neural network (DenseNet, AlexNet, GoogLeNet, etc.). It proved that the ensemble neural network proposed in this work can be used for intelligent diagnosis of breast ultrasound images. For 3D visualization, magnetic resonance imaging (MRI) scans were performed to achieve their 3D reconstructions. By comparing two types of visualized results (MRI and our 3D model), we determined that models generated by the 3D-based breast ultrasound system have similar nodule characteristics and spatial relationships with the MRI. Conclusions: In summary, this system implements automatic diagnosis of ultrasound images and presents lesions through 3D models, which can obtain complete and accurate ultrasound image information. Thus, it has clinical potential. [ABSTRACT FROM AUTHOR]

While T2 hyperintense masses on breast MRI are often benign, there are several malignant etiologies that can also be T2 hyperintense. Delineation between benign and malignant entities is important for the accurate interpretation of breast MRI. Common benign T2 hyperintense masses include cysts, fibroadenomas, and lymph nodes. Malignant processes that are T2 hyperintense include metastatic lymph nodes, mucinous breast carcinomas, papillary breast carcinomas, and breast cancers with central necrosis. Evaluation of the morphology and enhancement pattern of a T2 hyperintense mass can help to differentiate a benign process from a malignant one. This educational review will present both benign and malignant causes of T2 hyperintense masses on breast MRI and review common imaging findings and pertinent imaging characteristics that can be used to help accurately identify benign entities while also recognizing suspicious lesions that require additional evaluation. [ABSTRACT FROM AUTHOR]

Background: The mammary glands are prone to various lesions, either benign or malignant, many of benign types that can mature to malignant if untreated. The breast glandular structure can undergo changes from puberty to pregnancy and menopause due to hormonal effects, so the type of lesion occurrence among women varies depending on the age. Objectives: This study aimed to identify if there is an association between age and BIRADS classification and/ or association between age and type of lesions. Methodology: One hundred women from the city of Kirkuk participated in this study; they underwent mammography screening for detecting breast lesions. The relationship between age and mammography screening classification has been analyzed. Results: There is a significant association between age and BIRADS, and the age over 40 year was more frequent in most scores of BIRADS classification. In addition the number of patients with breast lesions in both BIRADS-3 and BIRADS-4 increased significantly with age. On the other hand, there is no significant association between age and types of breast lesion. Conclusion: There is significant association between age and BIRADS. [ABSTRACT FROM AUTHOR]

Background and Aim This study aimed to evaluate the role of diffusion-weighted imaging (DWI) and apparent diffusion coefficient in diagnosis of the breast lesions. Patients and methods This study included 100 patients referred to the Radiology Department of Al-Azhar Assiut University Hospital from February 2018 to May 2020 for DWI MRI examination with a provisional diagnosis of breast lesions. All patients were recruited after meeting the inclusion criteria. They underwent clinical examination, mammography, ultrasonography, and contrast-enhanced MRI with DWI. Results Our study included 100 cases. The combined MRI protocol of dynamic contrast-enhanced (DCE)-MRI and DWI was true positive in 60 and true negative in 30 patients. The combined MRI protocol of DCE-MRI and DWI provided a sensitivity of 92%, a specificity of 90%, a positive predictive value of 95.8%, a negative predictive value of 81.8% and accuracy of 91.43%. In this study, the addition of DWI to standard DCE-MRI provided a 10% increase in the specificity of breast MRI, with a 4% decrease in the sensitivity. Conclusion DWI is a short unenhanced scan and had the highest specificity compared with other imaging modalities, as it reduced the false-positive results. It should be added to conventional breast MRI to increase the sensitivity and specificity of MRI.

Due to the complex tissue structure of the breast, breast ultrasound (BUS) images exhibit the characteristics of low-contrast, lesion boundary blurring. Therefore, accurately automatic detection of ultrasound breast lesions is an important challenge for a computer-aided diagnosis system. Although previous saliency detection methods have been applied to detect breast lesions, they do not take full advantages of the prior knowledge of breast lesions. Here, to further accurately detect the breast lesions, a novel saliency detection method is proposed for BUS images, which seamlessly incorporates multiple priors into a hybrid architecture. To reduce the speckle noise and enhance the contrast, the BUS images are preprocessed by the methods of median filtering and a proposed adaptive thresholding. Also, to reveal the differences of benign and malignant lesions, a heat map based on the boundary of the breast lesions is established. Extensive experiments indicate that the proposed saliency detection method achieves an excellent performance of 0.925 accuracy, 0.871 sensitivity, 0.889 dice, and 0.912 F-measure on breast lesions detection in the BUS images, which is superior to the saliency detection models with a single prior. The boundary heat maps of the lesions also visually reflect the differences between benign and malignant lesions, which may potentially be used for automated computer diagnosis to assist radiologists in detection and identification of breast lesions. [ABSTRACT FROM AUTHOR]

Background: Stratification of breast lesions for appropriate management is achieved through an integration of clinical examination, imaging, and fine needle aspiration biopsy (FNAB). The current study aimed to evaluate the combined effectiveness of the widely used Breast Imaging‐Reporting and Data System (BI‐RADS) with the recently proposed International Academy of Cytology (IAC) Yokohama System for Reporting Breast Fine Needle Aspiration Biopsy Cytopathology. Methods: A retrospective analysis was done on all breast FNABs from 2016 through 2020. The cases were categorised according to the IAC Yokohama System. Histopathological correlation of the BI‐RADS and IAC Yokohama System was performed. The rate of malignancy (ROM) for each category of the BI‐RADS and IAC Yokohama System was calculated. Results: The ROM values for categories I to V were 38%, 0.6%, 21.9%, 100%, and 97%, respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of FNAB with category III assumed as malignant were 98.9%, 85%, 76.1%, 99.3%, and 89.5%, respectively. With category III assumed as benign, these indices were 90.8%, 98.9%, 97.5%, 95.7%, and 96.2%, respectively. The sensitivity, specificity, PPV, NPV and accuracy of BI‐RADS were 91.5%, 81.9%, 72%, 95%, and 85.1%, respectively. Conclusions: FNAB is still an indispensable test in the evaluation of breast lesions. The utilisation of the IAC Yokohama reporting system for breast cytology in conjunction with ACR BI‐RADS aids in better stratification of lesions. [ABSTRACT FROM AUTHOR]

Aims: Although evaluation of nuclear morphology is important for the diagnosis and categorisation of breast lesions, the criteria used to assess nuclear atypia rely upon the subjective evaluation of several features that may result in inter‐ and intraobserver variation. This study aims to refine the definitions of cytonuclear features in various breast lesions. Methods and results: ImageJ was used to assess the nuclear morphological features including nuclear diameter, axis length, perimeter, area, circularity and roundness in 160 breast lesions comprising ductal carcinoma in situ (DCIS), invasive breast carcinoma of no special type (IBC‐NST), tubular carcinoma, usual ductal hyperplasia (UDH), columnar cell change (CCC) and flat epithelial atypia (FEA). Reference cells included normal epithelial cells, red blood cells (RBCs) and lymphocytes. Reference cells showed size differences not only between normal epithelial cells and RBCs but also between RBCs in varied‐sized blood vessels. Nottingham grade nuclear pleomorphism scores 1 and 3 cut‐offs in IBC‐NST, compared to normal epithelial cells, were < ×1.2 and > ×1.4 that of mean maximum Feret's diameter and < ×1.6 and > ×2.4 that of mean nuclear area, respectively. Nuclear morphometrics were significantly different in low‐grade IBC‐NST versus tubular carcinoma, low‐grade DCIS versus UDH and CCC versus FEA. No differences in the nuclear features between grade‐matched DCIS and IBC‐NST were identified. Conclusion: This study provides a guide for the assessment of nuclear atypia in breast lesions, refines the comparison with reference cells and highlights the potential diagnostic value of image analysis tools in the era of digital pathology. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To investigate the added value of contrast-enhanced ultrasound (CEUS) and superb microvascular imaging (SMI) to the conventional ultrasound (US) in the diagnosis of breast lesions. METHODS: PubMed, EMBASE, Web of Science, Chinese national knowledge infrastructure databases, Chinese biomedical literature databases, and Wanfang were searched for relevant studies from November 2015 to November 2021. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Studies (QUADAS) tool. Meta-Disc version 1.4 was used to calculate sensitivity (SEN), specificity (SPE), positive likelihood ratio (LR+), negative likelihood ratio (LR–), area under curve (AUC), and diagnostic odds ratio (DOR). Meta-regression analysis was performed using STATA 16.0 software to compare the diagnostic accuracy of the two techniques. RESULTS: In the five studies included, 530 patients were eligible for this meta-analysis. For SMI, the pooled SEN and SPE were 0.75 (95% confidence interval [CI]: 0.69–0.91) and 0.88 (95% CI: 0.83–0.91), respectively, LR+ was 5.75 (95% CI: 4.26–7.78), LR– was 0.29 (95% CI: 0.23–0.36), DOR was 21.42 (95% CI, 13.61–33.73), and AUC was 0.8871. For CEUS, the pooled SEN and SPE were 0.87 (95% CI: 0.82–0.91) and 0.86 (95% CI: 0.82–0.89), respectively, LR+ was 5.92 (95% CI: 4.21–8.33), LR– was 0.16 (95% CI: 0.11–0.25), DOR was 38.27 (95% CI: 18.73–78.17), and AUC was 0.9210. CONCLUSIONS: Adding CEUS and (or) SMI to conventional US could improve its diagnostic performance in differentiating benign from malignant solid breast lesions. [ABSTRACT FROM AUTHOR]

Objective　To evaluate the diagnostic value of high-frequency ultrasound-guided guide wire localization of breast mass in patients with breast lesions. Methods　Ninety patients with suspected breast mass lesions in Yunnan Hospital of Traditional Chinese Medicine from May 2020 to August 2021 were selected as subjects by random sampling method. After admission，the patients received high-frequency ultrasound-guided guide wire localization diagnosis of breast mass， and the pathological tissue examination results were used as the "gold standard". The diagnostic value of high-frequency ultrasound-guided guide wire localization of breast mass in patients with breast lesions was calculated and analyzed. Results　All 90 patients with suspected breast mass lesions had complete pathological results. The results showed that 61 patients had benign lesions. 29 cases were malignant lesions. There was no significant difference in the detection rate of ultrasound-guided guide wire localization in fibroadenoma，breast adenosis，intraductal papilloma，invasive ductal carcinoma and invasive lobular carcinoma compared with pathological examination （ P > 0.05）. 57 cases of patients with benign breast lesions were diagnosed by ultrasonic-guided guide wire localization of benign breast masses，and the coincidence rate with gold standard diagnosis was 86.67%[（53+25） /90]，the difference was statistically significant （ P < 0.05）. The diagnostic sensitivity and specificity were 86.89% （53/61） and 86.21% （25/29）. Ultrasound guided guide wire localization of benign breast mass was confirmed in 27 cases of breast malignant lesions，and the coincidence rate with gold standard diagnosis was 88.89%[（57+23） /90] （ P < 0.05）. The diagnostic sensitivity and specificity were 79.31% （23/29） and 93.44% （57/61） respectively. Conclusion　High frequency ultrasound-guided guide wire localization of breast mass for patients with breast lesions can obtain a high diagnostic rate， high diagnostic sensitivity and specificity，which can guide clinical diagnosis and treatment，and is worthy of promotion and application. [ABSTRACT FROM AUTHOR]

Abstract Background Fine needle aspiration cytology is a simple, relatively accurate, non-invasive, and cost-effective method of diagnosing most breast pathologies. To date, there is no sufficient data depicting the distribution of breast lesions detected by fine needle aspiration cytology in our healthcare setting. The aim of this study was to elucidate the general distribution of breast lesions diagnosed by cytology test at Eritrean National Health Laboratory. Methods This retrospective study was carried out on 905 symptomatic patients between the years 2013 and 2017 at Eritrean National Health Laboratory. Diagnosis was made by fine needle aspiration cytology in patients with palpable breast lump and in some patients direct smear was prepared from a nipple discharge. Statistical analysis was carried out using Statistical Package for the Social Sciences version 23. Results A total of 905 patients were included in the study, of whom 871 (96.24%) were females. The age range of patients was from 13 to 93 years with mean and standard deviation of 33 ± 14.9 years. Breast lump, occurring in 892 (98.56%), was the most frequent presenting symptom. Fibroadenoma and fibrocystic breast lesions were the most prevalent lesions accounting for approximately 40% and 15%, respectively. Malignant breast lesions were seen predominantly in females above the age of 40 years with the highest frequency observed in the age range between 51 and 60 years. Pearson Chi-squared test showed significant association between patients’ age above 40 years and the risk of having a malignant breast lesion (p

Abstract Objectives IL17 is a critical pro-inflammatory cytokine that is involved in inflammation, multidrug resistance and growth persistence pathways in cancer. This study is aiming at studying the expression of IL17 and hormonal receptors expression in benign and malignant breast lesions using immunohistochemical staining methods. Results A total of 137 cases of breast lesions were studied, 97 (70.8%) were malignant and 40 (29.2%) were benign cases. Age range for malignant and benign cases were between 26 and 80 years [mean age 50 ± 2 years], and 20 to 70 years [mean age 41 ± 4 years], respectively, Odds ratio = 2.3 [1.78–1.99, 95% CI]. The majority of the histopathological diagnosis of the benign and malignant lesions were 21 (15.3%) fibro-adenomas and 87 (63.5%) invasive ductal carcinoma, respectively. Expression of IL17 and age were insignificantly negatively correlated for both groups; benign cases [r = − 0.054, P value 0.742] and malignant cases [r = − 0.080, P value 0.444]. IL17 expression was showing insignificant association with age group, P value 0.065. IL17 expression showed a statistical significance based on the different histopathological diagnosis, P value 0.035. Expression levels of estrogen, progesterone, and human epidermal receptors were showing insignificant difference among IL17 expression categories, P values 0.678, 0.623, and 0.361, respectively.

Abstract Background The majority of breast lesions in women under 25 years are being benign. Imaging is important for diagnosis and selecting patients for further procedures. Although malignancy is rare in this group of patients, suspected lesions must be biopsied. Imaging is very important in the selection of patients for radiological intervention. Understanding of the clinical, pathologic, and imaging features allows the radiologist to guide proper management of these patients. The aim of this study was to determine the frequency of different breast lesions in symptomatic women under 25 years and the value of radiological imaging in the diagnosis. Results This was a retrospective study; a total number of 250 cases with breast lumps under 25 years of age were registered in the PACKS of our institution in the period from January 01, 2017 to December 31, 2018. Two hundred three cases coped with our inclusion criteria that include available histopathological results either by biopsy or after surgery based on their referring physicians decision. Our exclusion criteria were those cases (47) with definite BIRADS 2 lesions with no available pathology reports. Ultrasonography was done to all patients (203 cases) and MRI was performed to 26 cases. All cases were histologically verified; their findings were reviewed and compared to radiological findings. A total of 203 symptomatic breast lesions were received at the radiological department in women under 25 years; there were 115 (56.7%) benign, 85 (41.9%) cystic, and 3 (1.5%) malignant lumps. The commonest benign lesion was fibroadenoma (104 cases, 51.2%) and all the malignant lesions were invasive ductal carcinoma (IDC) (3 cases, 1.47%). The p value is > 0.05, so there were no differences between examination using the ultrasonography and the MRI imaging compared to histopathological results. Conclusions Most breast lesions in young women are benign. Ultrasonography is an essential first imaging modality in the diagnosis of women under 25 years with breast lesions.

It is crucial to diagnose breast cancer early and accurately to optimize treatment. Presently, most deep learning models used for breast cancer detection cannot be used on mobile phones or low-power devices. This study intended to evaluate the capabilities of MobileNetV1 and MobileNetV2 and their fine-tuned models to differentiate malignant lesions from benign lesions in breast dynamic contrast-enhanced magnetic resonance images (DCE-MRI).

Introduction: A breast lesion is an unusual development in the breast tissue that typically appears as a lump or swelling. It encompasses a wide range of disorders, from benign to malignant, posing significant health challenges globally., Methods: The study was a retrospective study conducted at King Fahad Specialist Hospital (KFSH), Buraidah, Qassim region in Saudi Arabia between March 10, 2017, and April 2, 2024. Data was cleaned, coded, and analyzed using SPSS version 27., Results: The results revealed that most (639 (79.7%)) patients had symptomatic clinical presentations, with breast lump (470 (73.5%)) being the main presenting symptom. The majority (565 (70.4%)) of the patients presented malignant conditions, while 237 (29.6%) presented benign conditions. Of the patients who presented benign conditions, more than half (131 (55.3%)) were fibroadenoma benign lesions. Stage IIB cancer was the most common, constituting 192 (33.9%) of the patients. No complications were reported in the majority (480 (85.0%))., Conclusion: The study revealed a considerably high prevalence of malignant conditions among patients. Fibroadenoma was the most common breast lesion type, followed by intra-ductal papilloma and benign phyllodes. Age and BMI were found to be the risk factors that predicted the development of breast cancers. Knowledge and awareness of the prevalence, risk factors, and treatment of breast illnesses, as well as early screening and diagnosis, promote better patient outcomes and healthcare delivery., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. Regional Research Ethics Committee of Qassim Province issued approval 607/45/13634. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Alsalamah et al.)

Purpose: We aimed to investigate the diagnostic feasibility of an adjusted diffusion-weighted imaging (DWI) lexicon using multiple b values to assess breast lesions according to DWI-based breast imaging reporting and data system (BI-RADS)., Methods: This Institutional Review Board (IRB)-approved prospective study included 127 patients with suspected breast cancer. Breast MRI was performed using a 3T scanner. Breast DW images were acquired using five b-values of 0, 200, 800, 1000, and 1500 s/mm 2 (5b-value DWI) on 3T MRI. Two readers independently assessed lesion characteristics and normal breast tissue using DWI alone (5b-value DWI and 2b-value DWI with b = 0 and 800 s/mm 2 ) according to DWI-based BI-RADS and in combination with the standard dynamic contrast-enhanced images (combined MRI). Interobserver and intermethod agreements were assessed using kappa statistics. The specificity and sensitivity of lesion classification were evaluated., Results: Ninety-five breast lesions (39 malignant and 56 benign) were evaluated. Interobserver agreement for lesion assessment on 5b-value DWI was very good (k ≥ 0.82) for DWI-based BI-RADS categories, lesion type, and mass characteristics; good (k = 0.75) in breast composition; and moderate (k ≥ 0.44) in background parenchymal signal (BPS) and non-mass distribution. Intermethod agreement between assessments performed using either 5b-value DWI or combined MRI was good-to-moderate (k = 0.52-0.67) for lesion type; moderate (k = 0.49-0.59) for DWI-based BI-RADS category and mass characteristics; and fair (k = 0.25-0.40) for mass shape, BPS, and breast composition. The sensitivity and positive predictive values (PPVs) for 5b-value DWI were 79.5%, 84.6% and 60.8%, 61.1% for each reader, respectively; 74.4%, 74.4% and 63.0%, 61.7% for 2b-value DWI; and 97.4%, 97.4% and 73.1%, 76.0% for combined MRI. The specificity and negative predictive values (NPVs) were 64.3%, 62.5% and 81.8%, 85.4% for 5b-value DWI; 69.6%, 67.9% and 79.6%, 79.2% for 2b-value DWI; and 75.0%, 78.6% and 97.7%, 97.8% for combined MRI., Conclusion: Good observer agreement was observed in the 5b-value DWI. The 5b-value DWI based on multiple b-values might have the potential to complement the 2b-value DWI; however, their diagnostic performance tended to be inferior to that of combined MRI for the characterization of breast tumors.

Purpose: This study investigated the breast lesion conspicuity and apparent diffusion coefficient (ADC) reliability for three different diffusion-weighted imaging (DWI) protocols: spatiotemporal encoding (SPEN), single-shot echo-planar imaging (SS-EPI), and readout segmentation of long variable echo-trains (RESOLVE)., Methods: Sixty-five women suspected of having breast tumors were included in this study, with 44 lesions (36 malignant, 8 benign) analyzed further. Breast MRI was performed on a 3 Tesla (3T) system (MAGNETOM Prisma, Siemens) equipped with a dedicated 18-channel breast array coil for a phantom and patients. Three DWI protocols-SPEN, SS-EPI, and RESOLVE-were used. SS-EPI was acquired with an in-plane resolution of 2 × 2 mm 2 , a slice thickness of 3 mm, and b-values of 0 and 1000 s/mm 2 . SPEN had a higher in-plane resolution of 1 × 1 mm 2 , a slice thickness of 1.5 mm, and b-values of 0, 850, and 1500 s/mm 2 . RESOLVE was acquired with an in-plane resolution of 1 × 1 mm 2 , a slice thickness of 1.5 mm, and b-values of 0 and 850 s/mm 2 . Lesion conspicuity and ADC values were evaluated., Results: The average lesion conspicuity scores were significantly higher for RESOLVE (3.54 ± 0.65) than for SPEN (3.07 ± 0.91) or SS-EPI (2.48 ± 0.78) (P < 0.01). The SPEN score was significantly higher than the SS-EPI score (P < 0.01). Phantom measurements indicated marginally lower ADC values for SPEN compared to SS-EPI and RESOLVE across all concentrations. The results revealed that SPEN (b = 0, 850, 1500 sec/mm 2 ) yielded significantly lower ADC values compared to SPEN (b = 0, 850 sec/mm 2 ) in malignant lesions (P < 0.01), with no significant difference observed between SPEN (b = 0, 850 sec/mm 2 ), SS-EPI, and RESOLVE. For benign lesions, no significant difference in ADC values was found between SPEN (b = 0, 850 sec/mm 2 ), SPEN (b = 0, 850, 1500 sec/mm 2 ), SS-EPI, and RESOLVE., Conclusion: RESOLVE provided the highest lesion conspicuity, and ADC values in breast lesions were not significantly different among sequences ranging b values 850-1000 sec/mm 2 . SPEN with higher b-values (0, 850, 1500 vs. 0, 850 sec/mm 2 ) yielded significantly lower ADC values in malignant lesions, highlighting the importance of b-value selection in ADC quantification.

Objective: This study is focused on ultrasound multimodality examination, which refers to the combined use of three ultrasound examination modalities, ultrasound (US), acoustic radiation force impulse (ARFI) imaging, and contrast-enhanced ultrasound (CEUS). The purpose of this study is to analyze the value of applying ultrasound multimodality examination in the differential diagnosis of benign and malignant breast non-mass-like lesions (NMLs)., Methods: Cases of breast NMLs were analyzed retrospectively, and the nature of all the lesions was verified by pathological examination. Based on the gray-scale ultrasound image characteristics, the cases were classified into types Ⅰ to Ⅴ, and type Ⅰ and type Ⅱ were further classified into 4 subtypes, Ⅰa, Ⅰb, Ⅱa, and Ⅱb, according to whether there was also calcification, and the proportion of malignant cases in each subtype was statistically analyzed. Logistic regression models of US, US+ARFI, US+CEUS, and US+ARFI+CEUS for the diagnosis of malignant cases were established, ROC curves were drawn, the area under the curve (AUC) was calculated, and comparisons were made accordingly. The detection rate of malignant NMLs without calcification (atypical malignant NMLs) by the combination examination of US, ARFI, and CEUS was analyzed., Results: A total of 407 cases were included in the study. All subjects were female, aged 22 to 81 years, with the average age being (47.0±11.0) years. There were 220 benign cases and 187 malignant cases. Ranked from the highest to the lowest, the malignancy proportion of the different types was Ⅰb>Ⅱb>Ⅲ>Ⅴ>Ⅰa>Ⅱa>Ⅳ. The malignant proportion of the low echo area with calcification was significantly higher than that of the lesions without calcification. The AUC (95% confidence interval [CI]) for diagnosing malignant cases with the logistic regression models of US, US+ARFI, US+CEUS, and US+ARFI+CEUS were 0.895 (0.862-0.927), 0.908 (0.878-0.937), 0.921 (0.893-0.948), and 0.927 (0.902-0.952), respectively. Comparison of the AUC of the 4 regression models showed significant differences ( P <0.001). The detection rate of US for NMLs without calcification was 80.7%. When US was used in combination with ARFI and CEUS, 86.4% of the malignant NMLs lesions without calcification could be detected if the lesion CEUS score was 4 or 5 points or if shear-wave velocity (SWV)≥4.28 m/s., Conclusion: Breast NMLs with calcification show high risks of malignancy, and a pathological examination is always recommended for a conclusive diagnosis. Ultrasound multimodality examination can improve the diagnostic accuracy of breast NML without calcification., Competing Interests: 利益冲突　所有作者均声明不存在利益冲突, (© 2024《四川大学学报（医学版）》编辑部 版权所有Copyright ©2024 Editorial Office of Journal of Sichuan University (Medical Sciences).)

Objective: In this prospective study, the diagnostic performance of the new version of superb microvascular imaging (SMI) in differentiating malignant from benign lesions was evaluated. Material and Methods: Ninety breast lesions were included. During color SMI examination, both free-hand region of interest (ROI) and box ROI were used. Vascular index (VI) values were obtained from the lesion using both types of ROI and from normal breast tissue via box ROI. VI values, monochrome SMI grading and histopathological results were compared. The efficacy of color SMI and monochrome SMI was investigated in differentiating between benign and malignant breast lesions. Results: The cut-off value, in the differentiation of benign and malignant lesions with color SMI was 0.50 for box ROI, while it was 0.30 for free-hand ROI. The specificity of VI values obtained with box ROI was higher than that of free-hand ROI when differentiating malignant lesions from benign. Comparison of VI values from a lesion and from normal breast tissue showed that VI values in malignant lesions were significantly higher (p<0.05). The VI values of benign lesions and VI values of normal breast tissue were similar. There was a statistically significant relationship between monochrome SMI grading and the malignancy or benign status of the lesion (p<0.001). Conclusion: Drawing the lesion circumference free-hand using a free-shape ROI did not enhance the sensitivity and specificity. Contrary to popular belief, a more easy and practical measurement method may be more suitable for SMI examination. It is hoped that this will be one of the earliest studies to assess the clinical performance of the latest version of SMI. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the second cause of cancer death in women. Shear wave elastography (SWE) is an ultrasound (US) procedure that can improves the sensitivity and the specificity in the diagnosis of breast lesions. Objectives: To evaluate the value of SWE to discriminate benign from malignant Breast Imaging-Reporting and Data System (BI-RADS) IV breast lesions. Materials and methods: A cross sectional analytic study was done in the Radiology Department, Oncology Teaching Hospital, Baghdad Medical City, Baghdad, Iraq. The study period was one year (February 2020 to January 2021). The study included 42 female patients with suspicious breast lesions in the group BI-RAD 4 by mammography and US. Shear wave elastography was done for all patients. The final diagnosis of all breast lesions were done by fine needle aspiration cytology or true cut biopsy or excisional biopsy. Results: The final histological diagnosis showed that 23 (54.8%) of study patients were with benign breast lesions. There was a statistically significant association between the quality of SWE and histopathological diagnosis as the proportion of malignant breast lesions was significantly higher among the patients with score 5 (homogenous dark blue) images (85.7%, P= 0.004). Subjectts with malignant lesions had a significantly higher mean of E-mean SWV than those with benign lesions (133.8 versus 75.47 kPa, P = 0.001). The best cut point of E-mean SWV was 83 kPa (E-mean SWV > 83 kPa is predictive for malignant lesion of breast) with 89.5% sensitivity, 60.9% specificity, and 73.8% accuracy. Conclusion: SWE have a significant diagnostic value in differentiation of BI-RADS IV breast lesions into benign and malignant in both qualitative and quantitative patterns. The best cut off value in SWE is 83 KPa for E-mean. [ABSTRACT FROM AUTHOR]

Background: Shear wave elastography can evaluate tissue stiffness. Previous studies showed that the elasticity characteristics of breast lesions were related to the components of extracellular matrix which was regulated by transforming growth factor beta 1(TGF-β1) directly or indirectly. However, the correlation of the expression level of TGF-β1, its signal molecules and elasticity characteristics of breast lesions have rarely been reported. The purpose of this study was to investigate the correlation between the expression level of TGF-β1, its signal molecules, and the elasticity characteristics of breast lesions.Methods: 135 breast lesions in 130 patients were included. Elasticity parameters, including elasticity modulus, the elasticity ratio, the "stiff rim sign", were recorded before biopsy and surgical excision. The expression levels of TGF-β1 and its signal molecules, including Smad2/3, Erk1/2, p38 mitogen-activated protein kinase (MAPK), c-Jun N-terminal kinase 2 (JNK2), phosphoinositide 3-kinase (PI3K), and protein kinase B (PKB/AKT) were detected by immunohistochemistry. The diagnostic performance of the expression level of those molecules and their correlation with the elasticity characteristics were analyzed.Results: Elasticity parameters and the expression levels of TGF- β1 and its signal molecules of benign lesions were lower than those of malignant lesions (P<0.0001). The expression levels of TGF- β1 and its signal molecules were correlated with elasticity parameters. The expression levels of TGF- β1 and its signal molecules in lesions with "stiff rim sign" were higher than those without "stiff rim sign" (P<0.05). And the expression levels of Smad2/3, Erk1/2, p38 MAPK, JNK2, PI3K and AKT were correlated with that of TGF- β1. The area under the curve for receiver operator characteristic curve of TGF-β1 and its signal molecules in the differentiation of malignant and benign breast lesions ranged from 0.920-0.960.Conclusions: The expression levels of TGF-β1, its signal molecules of breast lesions showed good diagnostic performance and were correlated with the elasticity parameters. The expression levels of signal molecules were correlated with that of TGF- β1, which speculated that TGF- β1 might play an important role in the regulation of breast lesion elasticity parameters and multiple signal molecule expressions. [ABSTRACT FROM AUTHOR]

Background: Histological diagnosis is crucial to the management of breast diseases. It determines the kind of disease, the treatment modalities, and the outcome of management. Our department receives breast biopsies from the northern sector of Ghana constituting over 50% of the Ghanaian population. This study aimed at elucidating the pattern of disease and associated traditional prognostic indices of breast cases in our department over a period of 9 years. Methods: Information on the demographic characteristics and the histological diagnoses made on all breast cases received and processed in the department were accessed and entered into an Excel spreadsheet. Slides were reviewed and IHC was done on suitable cases. Descriptive statistics were generated using IMB-SPSS version 23. Results: A total of 4276 breast cases were received by the department within the study period, with 97.6% being female. Age ranged (female/male) from 10 to 98/13 to 102 years, with mean ages of 38.2 years (SD ± 16.7) and 41.15 years (SD ± 21.6), respectively. Cases were evenly distributed in both left and right breasts and 4.3% were bilateral. Inflammatory conditions were seen in 7.5% of cases. The most diagnosed benign tumor was fibroadenoma (54%), followed by fibrocystic change (8.1%). Gynecomastia was diagnosed in 66.3% of males. Malignant cases were 38.6%, with invasive carcinoma NST being the most frequent (87.5%). Histological grades were I = 9.4%, II = 41.6%, and III = 49%. Molecular subtypes were luminal A (19.8%), luminal B (9.9%), Her2 (16%), and TNBC (54.3%). Conclusion: Our findings show an increase in breast cancer cases compared to previous studies in our center, suggesting increased awareness and improved diagnosis. However, this increase is consistent with most studies in sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is considered the most serious lesion among different breast lesions. Mammography is the corner stone for screening for detection of breast cancer. It has been modified to digital mammography (DM) and then to digital breast tomosynthesis (DBT). Tomosynthesis is an emerging technique for diagnosis and screening of breast lesions. The aim of this study is to interrogate whether the addition of DBT to DM helps in better detection and characterization of different breast lesions. Methods: This is a prospective study carried on 38 female patients according to our inclusion criteria. All patients were evaluated by using DM alone and thereafter with the addition of DBT to DM. Recall rate was calculated, and the imaging findings of each case were correlated with the final diagnosis and follow-up. Results: DM identified 32 lesions while DBT with DM identified 37 lesions. On DM alone, 17 lesions were characterized as masses, 5 as focal asymmetry, 2 as architectural distortion, 7 as microcalcification and 1 as macrocalcification. With the addition of DBT, 27 lesions were characterized as masses, 1 as focal asymmetry, 1 as architectural distortion, 7 as microcalcification and 1 as macrocalcification. So, there were better detection and characterization of lesions with the addition of DBT than DM alone. The sensitivity, specificity, AUC, positive and negative predictive values were significantly higher with the addition of DBT to DM (100%, 90.5%, 0.952, 90% and 100%, respectively) than with DM (77.8%, 80.9%, 0.794, 77.8% and 80.9%, respectively) for all breast lesions. Conclusions: The addition of DBT to DM helps in better detection and characterization of different breast lesions. This leads to early detection of breast cancer, improvement of the performance of radiologists and saving time by reduction of recall rate. [ABSTRACT FROM AUTHOR]

Spindle cell lesions of the breast (BSCLs) are uncommon and encompass a wide spectrum of entities, ranging from benign reactive lesions to high-grade malignancies. The wide spectrum of differential diagnoses and significant overlap of clinicopathological features of BSCLs can cause diagnostic difficulties. An accurate diagnosis is crucial for guiding the clinical management. A BSCL can generally be classified as low grade/bland looking or high grade/malignant looking proliferations. Immunohistochemistry and/or other ancillary studies are usually necessary to differentiate morphologically challenging spindle cell lesion cases. This review focuses on the histological features and differential diagnoses of common spindle cell lesions of the breast.

Objective: To investigate the diagnostic value of digital breast tomosynthesis (DBT) combined with breast ultrasonography (BUS) in dense breast lesions. Methods: The imaging data of 149 patients with dense breast lesions with complete pathological findings who were admitted to our hospital from June 2018 to April 2019 were retrospectively analyzed, and the detection rates of DBT and BUS of two inspection methods were compared. The pathological results were taken as the gold standard, the diagnostic efficiency of DBT, BUS and DBT combined BUS were analyzed. Results: The detection rate of BUS in benign lesions (97.87%) was higher than DBT (89.36%), the difference was statistically significant (x²=5.697, P＜0.05). The detection rates of DBT and BUS for malignant lesions were 98.44% and 95.31%, respectively, and the differences were not statistically significant (x²=1.032, P>0.05). The sensitivity of DBT in diagnosis of dense breast lesions was 90.61%, the specificity was 93.55%, the accuracy rate was 91.77%. The sensitivity of BUS in diagnosis of dense breast lesions was 78.13%, the specificity was 89.36%, the accuracy rate was 84.81%. The sensitivity of DBT combined with BUS in diagnosis of dense breast lesions was 95.31%, the specificity was 95.74%, the accuracy rate was 95.57%. The area under the receiver operating characteristic curve (ROC) of DBT combined with BUS for diagnosis of dense breast lesions was 0.977, which was slightly higher than that of DBT (0.951), and significantly higher than that of BUS (0.885). Conclusion: The detection rate of BUS for benign lesions is significantly higher than that of DBT, and the diagnosis efficiency of DBT for dense breast lesions is higher than that of BUS, the combined application of the two methods can improve the detection rate and diagnostic efficiency of lesions. [ABSTRACT FROM AUTHOR]

Background: The aim of the study is to characterize the breast lesions on high-resolution Ultrasound and digital mammography to find the patterns and prevalence of different breast lesions in different age groups of our population. Results: This prospective study was conducted at a breast care clinic of a tertiary care hospital from Jan 2018 to Dec 2019. Patients with breast-related complaints were enrolled. Patients under the 35 years of age were evaluated on High-Resolution Ultrasound (HR-USG) and those over 35 years of age on digital Mammography. Any lesion on digital mammography was characterized on HR-USG. Fine Needle Aspiration (FNAC) and Trucut biopsy was done where pathological correlation required. Data of all enrolled patients were recorded and analyzed. Patients with known cases of carcinoma breast on follow-up were excluded from the study. Total 6850 patients enrolled in our breast care clinic during study period. 5111 were above the age of 35 years while 1739 were under the age of 35 years. No lesion could be found in 3915 patients and were reported normal. 2935 patients were found to have different breast lesions. The frequency of different lesions was different in both age groups. The overall frequency of lesions was as malignancy 16.2%, benign lesions including Fibroadenoma, simple cysts, Lipoma and Galactocele 16%, inflammatory lesions including abscess 7.86% and Duct Ectasia 2.75%. Conclusions: In developing countries where mass screening programs are deficient, Breast Care clinics in tertiary care hospitals have a noteworthy role in early detection of breast cancer and other breast lesions. [ABSTRACT FROM AUTHOR]