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Objective: Breast cancer is one of the leading cancer causes among women worldwide. It can be classified as invasive ductal carcinoma (IDC) or metastatic cancer. Early detection of breast cancer is challenging due to the lack of early warning signs. Generally, a mammogram is recommended by specialists for screening. Existing approaches are not accurate enough for real‐time diagnostic applications and thus require better and smarter cancer diagnostic approaches. This study aims to develop a customized machine‐learning framework that will give more accurate predictions for IDC and metastasis cancer classification. Methods: This work proposes a convolutional neural network (CNN) model for classifying IDC and metastatic breast cancer. The study utilized a large‐scale dataset of microscopic histopathological images to automatically perceive a hierarchical manner of learning and understanding. Results: It is evident that using machine learning techniques significantly (15%–25%) boost the effectiveness of determining cancer vulnerability, malignancy, and demise. The results demonstrate an excellent performance ensuring an average of 95% accuracy in classifying metastatic cells against benign ones and 89% accuracy was obtained in terms of detecting IDC. Conclusions: The results suggest that the proposed model improves classification accuracy. Therefore, it could be applied effectively in classifying IDC and metastatic cancer in comparison to other state‐of‐the‐art models. [ABSTRACT FROM AUTHOR]

Invasive ductal carcinoma (IDC) is a common form of breast cancer that affects women. In traditional medical practice, physicians have to manually test and classify areas which are suspected to be cancerous. However, the literature strongly indicates that the manual segmentation process performed by medical practitioners is neither time efficient nor accurate, as it relies on their subjective judgment. This paper introduces a model called residual attention neural network breast cancer classification (RANN-BCC) to help medical practitioners in the cancer diagnostic process. RANN-BCC utilizes residual neural network (ResNet) as an expert-supportive method to aid medical practitioners in cancer diagnosis. The implementation of RANN-BCC can support the classification of whole slide imaging (WSI) into non-IDC and IDC without prior information about the presence of a cancerous lesion. The classification results demonstrate that the RANN-BCC model has achieved 92.45% accuracy, 0.98 recall, 0.91 precision, and 0.94 F-score which has outperformed other models such as CNN, AlexNet, Residual Neural Network 34 (ResNet34), and Feed-Forward Neural Network. The developed RANN-BCC model aims to help medical experts to classify IDC and non-IDC of breast cancer by learning the feature content of medical images. [ABSTRACT FROM AUTHOR]

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC. [ABSTRACT FROM AUTHOR]

Bacopa monnieri (L) Wettst, commonly known as Brahmi, stands as a medicinal plant integral to India's traditional medical system, Ayurveda, where it is recognized as a "medhya rasayana"—a botanical entity believed to enhance intellect and mental clarity. Its significant role in numerous Ayurvedic formulations designed to address conditions such as anxiety, memory loss, impaired cognition, and diminished concentration underscores its prominence. Beyond its application in cognitive health, Brahmi has historically been employed in Ayurvedic practices for the treatment of inflammatory diseases, including arthritis. In contemporary biomedical research, Bacopa monnieri can attenuate the release of pro-inflammatory cytokines TNF-α and IL-6 in animal models. However, there remains a paucity of information regarding Bacopa's potential as an anticancer agent, warranting further investigation in this domain. Based on previous findings with Brahmi (Bacopa monnieri), the current study aims to find out the role of Brahmi plant preparation (BPP) in immunomodulatory actions on IDC. Employing a specific BPP concentration, we conducted a comprehensive study using MTT assay, ELISA, DNA methylation analysis, Western blotting, ChIP, and mRNA profiling to assess BPP's immunomodulatory properties. Our research finding showed the role of BPP in augmenting the action of T helper 1 (TH1) cells which secreted interferon-γ (IFN-γ) which in turn activated cytotoxic T-lymphocytes (CTL) to kill the cells of IDC (*p < 0.05). Moreover, we found out that treatment with BPP not only increased the activities of tumor-suppressor genes (p53 and BRCA1) but also decreased the activities of oncogenes (Notch1 and DNAPKcs) in IDC (*p < 0.05). BPP had an immense significance in controlling the epigenetic dysregulation in IDC through the downregulation of Histone demethylation & Histone deacetylation and upregulation of Histone methylation and Histone acetylation (*p < 0.05). Our Chromatin immunoprecipitation (ChIP)-qPCR data showed BPP treatment increased percentage enrichment of STAT1 & BRCA1 (*p < 0.05) and decreased percentage enrichment of STAT3, STAT5 & NF ΚB (*p < 0.05) on both TBX21 and BRCA1 gene loci in IDC. In addition, BPP treatment reduced the hypermethylation of the BRCA1-associated-DNA, which is believed to be a major factor in IDC (*p < 0.05). BPP not only escalates the secretion of type 1 specific cytokines but also escalates tumor suppression and harmonizes various epigenetic regulators and transcription factors associated with Signal Transducer and Activator of Transcription (STAT) to evoke tumor protective immunity in IDC.. [ABSTRACT FROM AUTHOR]

Abstract Objective Breast cancer is one of the leading cancer causes among women worldwide. It can be classified as invasive ductal carcinoma (IDC) or metastatic cancer. Early detection of breast cancer is challenging due to the lack of early warning signs. Generally, a mammogram is recommended by specialists for screening. Existing approaches are not accurate enough for real‐time diagnostic applications and thus require better and smarter cancer diagnostic approaches. This study aims to develop a customized machine‐learning framework that will give more accurate predictions for IDC and metastasis cancer classification. Methods This work proposes a convolutional neural network (CNN) model for classifying IDC and metastatic breast cancer. The study utilized a large‐scale dataset of microscopic histopathological images to automatically perceive a hierarchical manner of learning and understanding. Results It is evident that using machine learning techniques significantly (15%–25%) boost the effectiveness of determining cancer vulnerability, malignancy, and demise. The results demonstrate an excellent performance ensuring an average of 95% accuracy in classifying metastatic cells against benign ones and 89% accuracy was obtained in terms of detecting IDC. Conclusions The results suggest that the proposed model improves classification accuracy. Therefore, it could be applied effectively in classifying IDC and metastatic cancer in comparison to other state‐of‐the‐art models.

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Breast carcinoma is a sort of malignancy that begins in the breast. Breast malignancy cells generally structure a tumour that can routinely be seen on an x‐ray or felt like a lump. Despite advances in screening, treatment, and observation that have improved patient endurance rates, breast carcinoma is the most regularly analyzed malignant growth and the subsequent driving reason for malignancy mortality among ladies. Invasive ductal carcinoma is the most boundless breast malignant growth with about 80% of all analyzed cases. It has been found from numerous types of research that artificial intelligence has tremendous capabilities, which is why it is used in various sectors, especially in the healthcare domain. In the initial phase of the medical field, mammography is used for diagnosis, and finding cancer in the case of a dense breast is challenging. The evolution of deep learning and applying the same in the findings are helpful for earlier tracking and medication. The authors have tried to utilize the deep learning concepts for grading breast invasive ductal carcinoma using Transfer Learning in the present work. The authors have used five transfer learning approaches here, namely VGG16, VGG19, InceptionReNetV2, DenseNet121, and DenseNet201 with 50 epochs in the Google Colab platform which has a single 12GB NVIDIA Tesla K80 graphical processing unit (GPU) support that can be used up to 12 h continuously. The dataset used for this work can be openly accessed from http://databiox.com. The experimental results that the authors have received regarding the algorithm's accuracy are as follows: VGG16 with 92.5%, VGG19 with 89.77%, InceptionReNetV2 with 84.46%, DenseNet121 with 92.64%, DenseNet201 with 85.22%. From the experimental results, it is clear that the DenseNet121 gives the maximum accuracy in terms of cancer grading, whereas the InceptionReNetV2 has minimal accuracy. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis. Methods: Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA). Results: In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups. Conclusions: Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the main causes of death in women. When body tissues start behaves abnormally and the ratio of tissues growth becomes asymmetrical then this stage is called cancer. Invasive ductal carcinoma (IDC) is the early stage of breast cancer. The early detection and diagnosis of invasive ductal carcinoma is a significant step for the cure of IDC breast cancer. This paper presents a convolutional neural network (CNN) approach to detect and visualize the IDC tissues in breast on histological images dataset. The dataset consists of 90 thousand histopathological images containing two categories: Invasive Ductal Carcinoma positive (IDC+) and Invasive Ductal Carcinoma negative (IDC-). For the detection of this disease, we have proposed an ensemble learning-based deep learning model that consists of the multi-model structure having different internal configuration settings of CNN. As a result, the proposed method has significant progress as per present techniques in terms of accuracy as 92.7%. Therefore, the ensemble approach of multi-model CNN can provide the evolution of IDC at different stages, and this would help the pathologist in the cure of cancer. The experimented results show that the proposed ensemble-based approach of multi-model CNN generated the preeminent results with an accuracy of 92.7% as compared to the already existing techniques. [ABSTRACT FROM AUTHOR]

Breast cancer is a disease which we hear about a lot nowadays. It is one of the most widespread diseases. It affects both men and women all around the world. Research says that every year around 2000+ new cases of breast cancer for men and about 2,30,000 new cases for women. Diagnosis of this disease is crucial and its demand the faster treatment for the recover. Correct and early diagnosis of these disease can save the patient. Breast cancer detection is done with the help of mammograms, which are basically X-rays of the breasts. Detection is not easy due to different kinds of uncertainties identified in these mammograms. Machine Learning (ML) techniques can help for the early detection of breast cancer. This paper consists of these techniques which can help doctors for early detection and diagnosis of breast cancer which could greatly enhance the survival rate of patients. In this paper, Support Vector Machine (SVM) and Convolution Neural Network (CNN) model applied for the data set which contains both benign and malignant breast cancer images and generated confusion matrix for validating the result. We also performed a comparative analysis of Logistic regression, SVM, Naive Bays, Neural Networks, Decision tree, Adaboost and Random Forest. [ABSTRACT FROM AUTHOR]

We describe the case of a 65-year-old female with a history of left-sided ductal carcinoma in situ in 2008. Mammography in January 2020 demonstrated calcifications in the previously affected breast. Subsequent stereotactic biopsy results were benign. In the months that followed, the patient experienced breast changes but avoided returning to the facility as the COVID-19 pandemic worsened. In August of 2020, the patient returned for a repeat mammogram, which indicated 2 suspicious masses in the left breast. Further analysis through ultrasound-guided core biopsy ultimately led to a left mastectomy and lymph node biopsy, which were performed in September 2020. Pathology results revealed multifocal invasive ductal carcinoma stage IIB.

During the past few years, deep learning (DL) architectures are being employed in many potential areas such as object detection, face recognition, natural language processing, medical image analysis and other related applications. In these applications, DL has achieved remarkable results matching the performance of human experts. This paper presents a novel convolutional neural networks (CNN)-based approach for the detection of breast cancer in invasive ductal carcinoma tissue regions using whole slide images (WSI). It has been observed that breast cancer has been a leading cause of death among women. It also remains a striving task for pathologist to find the malignancy regions from WSI. In this research, we have implemented different CNN models which include VGG16, VGG19, Xception, Inception V3, MobileNetV2, ResNet50, and DenseNet. The experiments were performed on standard WSI slides data-set which include 163 patients of IDC. For performance evaluation, same data-set was divided into 113 and 49 images for training and testing, respectively. The testing was carried out separately over each model and the obtained results showed that our proposed CNN model achieved 83% accuracy which is better than the other models. [ABSTRACT FROM AUTHOR]

Abstract Background The aim of this study was to use texture analysis (TA) of breast magnetic resonance (MR) images to assist in differentiating estrogen receptor (ER) positive breast cancer molecular subtypes. Methods Twenty-seven patients with histopathologically proven invasive ductal breast cancer were selected in preliminary study. Tumors were classified into molecular subtypes: luminal A (ER-positive and/or progesterone receptor (PR)-positive, human epidermal growth factor receptor type 2 (HER2) -negative, proliferation marker Ki-67

Background: Medullary breast carcinoma (MBC) is a rare type of breast cancer. Our study aimed to compare the differences in clinical characteristics and prognosis between MBC and invasive ductal carcinoma (IDC), and to further develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in MBC patients., Methods: A total of 179,613 patients from the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2015, including 596 MBC patients, were analyzed using the Kaplan-Meier method and propensity score matching (PSM) to compare patients' OS and CSS. Cox proportional hazard regression model was used to determine independent prognostic factors for OS and CSS in MBC patients. Nomograms were constructed based on Cox regression analysis whereas receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the predictive accuracy., Results: There were significant differences in the clinical characteristics between MBC and IDC. According to the logrank test, MBC had better OS and CSS than IDC before and after PSM. Cox multivariate analysis showed that age, race, tumor size, lymph node (LN), and radiation therapy were independent prognostic factors for OS, whereas age, tumor size, American Joint Committee on Cancer (AJCC) stage, laterality, type of surgery, and chemotherapy were independent prognostic factors for CSS. Nomograms of OS and CSS were constructed based on independent prognostic factors., Conclusions: MBC had better OS and CSS than IDC. Nomograms based on clinicopathological features were sufficiently accurate in predicting the OS and CSS for MBC patients, which can effectively predict the survival risk of MBC patients and guide clinicians to provide more effective treatment measures., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-858/coif). The authors have no conflicts of interest to declare., (2024 Translational Cancer Research. All rights reserved.)

Background: Sclerosing adenosis (SA) is a common proliferative benign lesion without atypia in the breast that may mimic invasive ductal carcinoma (IDC) on medical imaging, leading to it often being misdiagnosed and mistreated. Consequently, the purpose of this study was to assess the diagnostic value of multimodal ultrasound imaging in distinguishing SA from IDC., Methods: Multimodal ultrasound imaging, including automated breast volume scan (ABVS), elasticity imaging (EI), and color Doppler flow imaging (CDFI), were performed on 120 consecutive patients comprising 122 breast lesions (54 SA, 68 IDC). All lesions were pathologically confirmed. Multimodal ultrasound imaging features were compared between the two groups. Binary logistic regression analysis based on ABVS, EI, and CDFI was conducted to formulate a logistic regression equation for differentiating SA from IDC. The diagnostic performances of ABVS, EI, CDFI, and their combination were compared by the receiver operating characteristic (ROC) curve analysis., Results: The sensitivity, specificity, and accuracy of ABVS, EI, CDFI, and their combination in differentiating SA from IDC were, respectively, 75.00%, 72.22%, and 73.77%; 86.76%, 72.22%, and 80.33%; 73.53%, 64.81%, and 69.67%; and 88.24%, 74.07%, and 81.97%. Combining multimodal ultrasound imaging yielded an area under the curve (AUC) of 0.895 (95% confidence interval: 0.827-0.943), which was higher than that of ABVS, EI, and CDFI, with AUC values of 0.736, 0.795, and 0.692, respectively, and the difference was statistically significant (ABVS vs. combined model, P<0.001; CDFI vs. combined model, P<0.001; EI vs. combined model, P<0.001). There was no significant difference in the diagnostic efficacy among the three imaging modalities (ABVS vs. EI, P=0.266; ABVS vs. CDFI, P=0.4671; EI vs. CDFI, P=0.051). Compared with those in IDC, the calcification (16.67% vs. 57.35%; P<0.001) and retraction phenomena in the coronal planes (18.52% vs. 57.35%; P<0.001) were less common in patients with SA, while circumscribed margin (38.89% vs. 5.88%; P<0.001), vascularity grade 0-I (64.81% vs. 26.47%; P<0.001), and elasticity scores 1-3 (72.22% vs. 13.24%; P<0.001) were more frequently found in patients with SA. Patients with SA were significantly younger than were patients with IDC (43±11 vs. 54±11 years; P<0.001), and the lesion size was smaller in patients with SA than in those with IDC (median size 1.0 cm; interquartile range (IQR), 0.9 cm vs. median size 1.3 cm; IQR, 1.3 cm; P<0.001)., Conclusions: The preliminary results suggested that multimodal ultrasound imaging can improve the diagnostic accuracy of SA and provide additional information for differential diagnosis of SA and IDC., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-524/coif). Y.L. reports that this study was supported by the Gusu Medical Talent of Suzhou City Program (grant No. GSWS2020009), the Translational Research Grant of NCRCH (grant No. 2020WSB06), and the Jiangsu Provincial Key Medical Discipline (grant No. JSDW202242). The other authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Aim: The study was carried out to determine the Immunohistochemical Correlation between the Expression of Vitamin D Receptor (VDR) and Triple Negative Invasive Ductal Carcinoma (IDC) tissues Materials and Method: Twenty two (22) cases of archived female breast Invasive Ductal Carcinoma tissue blocks that are Negative to ER, PR, and HER-2 (Triple Negative) were used. The tissue blocks were sectioned at not more than 2µm each. Haematoxylin and Eosin staining method and immunohistochemical staining technique using VDR antibodies were done and the results were correlated. Result and Discussion: The results show that there is a significant difference (P<0.05) found comparing the immunohistochemical expression of VDR with Triple Negative IDC tissues but strong positivity is shown in VDR positive IDC tissues. Conclusion: There is a statistically significant difference found in the expression of VDR with Triple negative IDC tissues; therefore VDR cannot be use as substitute in cases of triple negative IDC tissues but can be an additional antibody and of therapeutic target in breast cancer. [ABSTRACT FROM AUTHOR]

Background: Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) have distinct clinical, pathologic, and genomic characteristics. The objective of the current study was to compare the relative impact of adjuvant chemotherapy on the survival of patients with ILC versus those with IDC.Methods: Women with estrogen receptor (ER)-positive, human epidermal growth factor receptor 1 (HER2) -negative, stage I/II IDC and ILC who received endocrine therapy were identified from the 2000 to 2014 California Cancer Registry. Patient, tumor, and treatment characteristics were collected. Ten-year overall survival (OS) was estimated using the Kaplan-Meier method and Cox proportional-hazards modeling.Results: In total, 32,997 women with IDC and 4638 with ILC were identified. The receipt of chemotherapy significantly decreased during the study for both subtypes. For patients with IDC, the 10-year OS rate was 95% among those who received endocrine therapy alone versus 93% (P < .01) among those who received endocrine therapy plus chemotherapy. For patients with ILC, the 10-year OS rate was 94% among those who received endocrine therapy alone versus 92% (P < .01) among those who received endocrine therapy plus chemotherapy. After adjusting for patient and treatment factors, adjuvant chemotherapy was significantly associated with a decreased 10-year hazard of death for patients with IDC (hazard ratio, 0.83; 95% confidence interval, 0.74-0.92). In contrast, adjuvant chemotherapy was not independently associated with the adjusted 10-year hazard of death for patients with ILC (hazard ratio, 1.14; 95% confidence interval, 0.90-1.46).Conclusions: Adjuvant chemotherapy was not associated with improved OS for patients with ER-positive, HER2-negative, stage I/II ILC. Avoidance of ineffective chemotherapy will markedly reduce the adverse effects and economic burden of breast cancer treatment for a large proportion of patients with breast cancer. Cancer 2017;123:3015-21. © 2017 American Cancer Society. [ABSTRACT FROM AUTHOR]

Background: Diffusion Weighted Imaging with Back-ground Suppression is a new technique which uses the same concept of diffusion weighted imaging yet has the privilege of back-ground suppression and acquisition at a wider range of b-values hence increasing sensitivity and specificity. Objective: to determine the accuracy of DWIBS MR imaging in comparison to the DEC MR imaging in characterizing suspicious mammography lesions. Patients and Methods: twenty patients were included in the study, all with suspicious breast lesions from Ain-Shams University mammography clinic. A cross-sectional study was held where all the patients under-went MRI breast protocol which included DCE and DWIBS sequences. The MRI of all the patients was read by two expert radiologists blinded to each other's opinion. Biopsy was then done for histopathological correlation. The results were statistically analyzed. Results: seventy percent of the patients included in our study had malignant lesions and 30% had benign lesions. Both DWIBS and DCE showed comparable efficacy of 90% and 95% respectively. Conclusion: DWIBS can be used as an adjunct to DCE breast MRI improving its sensitivity and specificity. It can as well be used instead of DCE sequences in cases of renal impairment. [ABSTRACT FROM AUTHOR]

Aim To better characterize spindle cell metaplastic carcinoma ( SpCMC) of breast, a rare variant of breast cancer that has been classified under the broad rubric of metaplastic carcinoma. Methods We presented herein 19 cases of metaplastic breast carcinoma with dominant spindle cell component. All cases were clinically of breast origin, showed more than 80% spindle morphology, 10 cases exhibited pure spindled morphology, 8 contained invasive ductal carcinoma ( IDC) and 1 presented with ductal carcinoma in situ elements. Results Immunohistochemical studies showed evidence suggesting myoepithelial and epithelial differentiation as exhibited by immunoreactivity for at least one myoepithelial and epithelial markers in all pure spindle cell components. IDC group showed 21.7% of axillary lymph nodes metastasis rate, whereas the axillary lymph node metastasis rate of the SpCMC group was 1.3%, significantly lower than that of the IDC group ( P < 0.001). Immunohistochemical staining of IDC exhibited higher degrees of positivity for ER, PR and Her2 (90, 60 and 30%, respectively) when compared with the SpCMC group, which showed a positive degree of 5.2, 5.2 and 10.5% for ER, PR and Her2, respectively ( P < 0.001). Conclusion Based on this series, SpCMC is a rare variant of metaplastic breast carcinoma with the distinct histopathological and immunohistochemical features. The biological behaviors of SpCMC, like axillary lymph node status, were quite different from that of IDC, suggesting that it may act as an independent pathologic subtype. Immunohistochemical analysis of a panel of epithelial and myoepithelial markers could contribute to the pathologic diagnosis of SpCMC. [ABSTRACT FROM AUTHOR]

Introduction: Benign Phyllodes Tumours (PTs) are rare fibroepithelial neoplasms that resemble fibroadenoma. But unlike fibroadenoma, benign PT can recur and both stromal & epithelial components can progress to malignancy. Contrary to earlier belief that benign PT is a stromal neoplasm and possibly arises from fibroadenoma, more recent molecular studies have suggested that both stroma and epithelium can become neoplastic. Sometimes, benign PT can occur synchronously with fibroadenoma. Here histomorphologic analysis of eleven cases of benign PT are presented including some unusual features. Materials and Methods: Eleven cases of benign PT diagnosed between Dec 2014 and Jan 2016 in the Department of Pathology were studied. The demographic and clinicopathological features were analysed. Results: The most common age group affected was 20-30 years (range: 13-45). Clinical features included pain, lump and bleeding from nipple. The tumour size varied from 2.5-18 cm in diameter. H&E stained sections showed secondary changes (haemorrhage, myxoid, change, cystic degeneration), epithelial hyperplasia (8), squamous & columnar metaplasia (1), benign tubular adenoma like areas (1), Ductal Carcinoma In Situ (DCIS) (1), Invasive Ductal Carcinoma (IDC) (1), Pseudoangiomatous Stromal Hyperplasia (PASH) (1), histologic infarction (2), tumour necrosis (1) and synchronous fibroadenoma (1). Unusual histologic features included atypical ductal hyperplasia, DCIS, IDC, synchronous fibroadenoma and tubular adenoma like areas arising within benign PT. Conclusion: This study shows a spectrum of hyperplastic, metaplastic, dysplastic, benign, in-situ-malignancy and even invasive ductal malignancy occurring in benign PT. Therefore adequate and extensive sampling is recommended for accurate diagnosis.

Background: Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis., Methods: Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA)., Results: In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups., Conclusions: Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yang, Zuo, Lin, Zhou, Wen, Zhang, Xiao, Jiang, Fujita, Gao and Fu.)

Introduction: Benign Phyllodes Tumours (PTs) are rare fibroepithelial neoplasms that resemble fibroadenoma. But unlike fibroadenoma, benign PT can recur and both stromal & epithelial components can progress to malignancy. Contrary to earlier belief that benign PT is a stromal neoplasm and possibly arises from fibroadenoma, more recent molecular studies have suggested that both stroma and epithelium can become neoplastic. Sometimes, benign PT can occur synchronously with fibroadenoma. Here histomorphologic analysis of eleven cases of benign PT are presented including some unusual features. Materials and Methods: Eleven cases of benign PT diagnosed between Dec 2014 and Jan 2016 in the Department of Pathology were studied. The demographic and clinicopathological features were analysed. Results: The most common age group affected was 20-30 years (range: 13-45). Clinical features included pain, lump and bleeding from nipple. The tumour size varied from 2.5-18 cm in diameter. H&E stained sections showed secondary changes (haemorrhage, myxoid, change, cystic degeneration), epithelial hyperplasia (8), squamous & columnar metaplasia (1), benign tubular adenoma like areas (1), Ductal Carcinoma In Situ (DCIS) (1), Invasive Ductal Carcinoma (IDC) (1), Pseudoangiomatous Stromal Hyperplasia (PASH) (1), histologic infarction (2), tumour necrosis (1) and synchronous fibroadenoma (1). Unusual histologic features included atypical ductal hyperplasia, DCIS, IDC, synchronous fibroadenoma and tubular adenoma like areas arising within benign PT. Conclusion: This study shows a spectrum of hyperplastic, metaplastic, dysplastic, benign, in-situ-malignancy and even invasive ductal malignancy occurring in benign PT. Therefore adequate and extensive sampling is recommended for accurate diagnosis. [ABSTRACT FROM AUTHOR]

Background: In this retrospective analysis, the clinicopathological features and pattern of metastatic spread of invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed ductal/lobular carcinoma (MDLC), together with the type and outcome of surgical intervention, were comparatively evaluated. Methods: A total of 633 breast cancer patients with histopathological subtype IDC, ILC or MDLC were included in the study. The mean age was 52.6 ± 12.7 years. Follow-up period ranged between 0 and 33 (median 6.0) years. The groups were compared with respect to age, tumor size, nodal involvement, stage, hormonal therapy, multicentricity, multifocality, bilaterality, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2)/neu, p53, and Ki67 expression, disease-free survival (DFS) and overall survival (OS) rates, and surgical approach. Results: The distribution of patients was as follows: IDC 508 (80.3 %), ILC 78 (12.3 %), MDLC 47 (7.4 %). Among the parameters evaluated, statistically significant differences were observed in mean tumor size (IDC 2.5 ± 1.98 cm, ILC 3.0 ± 1.8 cm, MDLC 3.2 ± 2.4 cm), advanced T stage (T3 + T4) at diagnosis (IDC 14.7 %, ILC 21.4 %, MDLC 25.6 %), N stage (N0 was dominant in IDC and ILC; N3 was dominant in MDLC), tumor-node-metastasis (TNM) stage (stage II was dominant in IDC and ILC; stage III was dominant in MDLC), HER2/neu expression (IDC 23.8 %, ILC 11.8 %, MDLC 21.4 %), and frequency of bone metastasis (IDC 14.3 %, ILC 17.9 %, MDLC 25.5 %). Conclusions: MDLC-type tumors have different histopathological characteristics and are often diagnosed at advanced stage. However, their survival outcomes do not vary significantly from ILC and IDC. [ABSTRACT FROM AUTHOR]

Aim of the study: Expression of oestrogen and progesterone receptors is a very powerful and useful predictor. Because the response rate to hormonal treatment in breast cancer is associated with the presence of oestrogen and progesterone receptors, assessment of the receptor expression profile allows for prediction of breast cancer response to hormonal treatment. The aim of this study was to assess whether the expression of receptors for oestrogen (ER) and progesterone (PR) in the tumour tissue of patients with invasive breast cancer correlated with tumour histological type, histological grade of malignancy, tumour size, and lymph node status. Material and methods: Materials consisted of histological preparations derived from patients treated for invasive breast cancer. Evaluations were conducted with histopathological and immunohistochemical methods using suitable antibodies. Results: Among 231 cases of breast cancer 18 invasive lobular carcinomas (ILC) and 213 invasive ductal carcinomas (IDC) were diagnosed. Taking the histological type of tumour into account, oestrogen receptor-positive reaction was observed in 74.2% of IDC and 77.8% of ILC, and the positive response to PR was observed in 67.1% of IDC and 61.1% of ILC. Considering the histological grade, ER- in the largest percentage (72%) was observed in second-grade (G2) invasive carcinomas. Similarly, PR expression (75%) was found in the largest percentage in second-grade (G2) carcinomas. Based on our own studies and data from literature, it appears that the ER (+) status is an indicator of good prognosis, because it points to a less aggressive cancer, in which overall survival and disease-free time is longer in comparison with ER (-) tumours. Conclusions: Determination of ER status may, therefore, have significant clinical value and is widely used in routine pathological diagnostics. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to contribute to the standardization of the numeric positive enhancement integral (PEI) values in breast parenchyma, ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) and to evaluate the significance of the difference in PEI values between IDC and parenchyma, DCIS and parenchyma and IDC and DCIS. Materials and Methods: In the prospective trial, we analyzed the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of 60 consecutive patients with histologically confirmed unilateral DCIS (n =30) and IDC (n =30) and defined the PEI values (range; mean±SD) for the lesions and the breast parenchyma. Tumor-to-non-tumor (T/NT) ratios were calculated for DCIS and IDC and compared. PEI color maps (PEICM) were created. The differences in PEI values between IDC and parenchyma and between DCIS and parenchyma were tested according to t-test. Analysis of variance (ANOVA) was used to test the differences between the mean PEI values of parenchyma, DCIS and IDC. Results: IDC showed highly statistically different PEI numeric values compared to breast parenchyma (748.7±32.2 vs. 74.6±17.0; p <0.0001). The same applied to the differences in the group of patients with DCIS (428.0±25.0 vs. 66.0±10.6; p <0.0001). The difference between IDC, DCIS and parenchyma were also considered highly statistically significant (p <0.0001) and so were the T/NT ratios for IDC and DCIS (10.1±2.4 vs. 6.6±1.4; p <0.0001). Conclusions: PEI numeric values may contribute to differentiation between invasive and in situ breast carcinoma. [ABSTRACT FROM AUTHOR]

Abstract: Aim of the work: To evaluate the value of real-time ultrasound elastography (RTE) in differentiating benign from malignant breast masses. Materials and methods: This study included, whether palpable or non-palpable, 145 sonographically proven breast masses in 121 patients, imaged by conventional B-mode US, color-flow Doppler US and RTE with histopathological analysis considered as the golden standard reference. Results: Lesions were differentiated into benign and malignant by conventional B-mode US (79; 45.5% and 66; 54.5%, respectively), RTE (80; 55.2% and 65; 44.8% respectively), and histopathology (82; 56.6% and 63; 43.4%, respectively). The mean difference in the mass size was significant between B-mode US and RTE in malignant masses (P =0.002), while not significant among benign masses (P =0.153). The B-mode US depicted sensitivity of 92.06%, specificity of 90.24%, PPV of 87.88%, NPV of 93.67% and accuracy of 91.03%, while the RTE showed sensitivity of 98.41%, specificity of 96.34%, PPV of 95.38%, NPV of 98.75% and accuracy of 97.24%. Conclusion: Combined use of RTE can complement conventional B-mode US with improving its diagnostic performance in differentiating breast lesions with subsequent reduction in the rate of unnecessary biopsies in benign lesions. [Copyright &y& Elsevier]

Abstract: Introduction: One-Step Nucleic acid Amplification (OSNA) is a molecular biological assay of cytokeratin-19 (a breast epithelial marker) mRNA. It can be employed intra-operatively for detection of lymph node metastases in breast carcinoma. Patients with positive sentinel nodes may proceed to axillary lymph node dissection (ALND) level I or higher dependent upon the OSNA quantitative result, during the same surgical procedure, avoiding a second operation and eliminating the technical difficulties possibly associated with delayed ALND. Aims: Our Breast Unit was the first in the UK to implement this novel technique in routine practice. This study reviews our first 44-month data following introduction of OSNA “live” on whole sentinel nodes following an extensive validation study (Snook et al.).9 Methods: Data was collected prospectively from the period of introduction 01/12/2008 to 30/08/2012. All patients eligible for sentinel node biopsy were offered OSNA and operations were performed by five consultant breast surgeons. On detection of macro-metastasis a level II/III and for a micro-metastasis a level I ALND was performed. Results: A total of 859 patients (1709 sentinel lymph nodes) were analysed. All except one were females. The majority underwent wide local excision (73.4%, n = 631) or mastectomy 25% (n = 215) and 1.6% (13) underwent SLN biopsy alone. IDC was seen in 79% (n = 680) of the patients and 53.5% (n = 460) had grade II tumours. One-third (30.8%, n = 265) had positive sentinel nodes and had further axillary surgery at the time of SLN biopsy. Of these, 47% (n = 125/265) had macro-metastases, 38% (n = 101/265) had micro-metastases and 14.7% (n = 39/265) had “positive but inhibited” results. Positive non-sentinel lymph nodes (NSLN) were seen in 35% (44/125) of those with macro-metastases; 17.8% (18/101) of the patients with micro-metastases and 10.2% (4/39) of the “positive but inhibited” group. Conclusion: In our series over a third of our patients had positive lymph nodes detected with OSNA allowing them to proceed directly to axillary surgery at the same operation. This technique eliminates the need for a second operation in sentinel lymph node positive patients and avoids the anxiety waiting for histological results. [Copyright &y& Elsevier]

Abstract: Breast cancer is the most common cancer and the second leading cause of cancer death among women of all races and Hispanic origin populations in the United States. In the present study, we reported that the survival time of the breast cancer patients is influenced by the expression level of mdig, a previously identified lung cancer-associated oncogene encoding a JmjC-domain protein. By checking the expression levels of mRNA and protein of mdig through both RT-PCR and immunohistochemistry in samples from 204 patients, we noticed that about 30% of breast cancer samples showed increased expression of mdig. Correlation of the mdig expression levels with the survival time of the breast cancer patients indicated a clear inverse relationship between mdig expression and patient survival, including poorer overall survival, distant metastasis free survival, relapse free survival, and post-progression survival. Taken together, these data suggest that an increased expression of mdig is an important prognostic factor for poorer survival time of the breast cancer patients. [Copyright &y& Elsevier]

Abstract: FGFs, in a complex with their receptors (FGFRs) and heparan sulfate (HS), are responsible for a range of cellular functions, from embryogenesis to metabolism. Both germ line and somatic FGFR mutations are known to play a role in a range of diseases, most notably craniosynestosis dysplasias, dwarfism and cancer. Because of the ability of FGFR signalling to induce cell proliferation, migration and survival, FGFRs are readily co-opted by cancer cells. Mutations in, and amplifications of, these receptors are found in a range of cancers with some of the most striking clinical findings relating to their contribution to pathogenesis and progression of female cancers. Here, we outline the molecular mechanisms of FGFR signalling and discuss the role of this pathway in women's cancers, focusing on breast, endometrial, ovarian and cervical carcinomas, and their associated preclinical and clinical data. We also address the rationale for therapeutic intervention and the need for FGFR-targeted therapy to selectively target cancer cells in view of the fundamental roles of FGF signalling in normal physiology. [Copyright &y& Elsevier]

Abstract: Background: The aim of this study was to evaluate the significance of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) for speculating the malignant level and prognostic value of operable breast cancers. Methods: Of 578 consecutive patients with primary invasive breast cancer who underwent curative surgery between 2005 and 2010, 311 patients (53.8%) who received FDG-PET/CT before initial therapy were examined. Results: Receiver operating characteristics (ROC) curve analysis showed the cutoff value of the maximum standardized uptake value (SUVmax) to predict cancer recurrence was 3.8 in all patients and 8.6 in patients with the triple-negative subtype, respectively. In all patients, 3-year DFS rates were 98.8% for patients with a tumor of SUVmax ≤ 3.8 and 91.6% for patients with a tumor of SUVmax > 3.8 (p < 0.001). High value of SUVmax was significantly associated with large tumor size (p < 0.001), lymph node metastasis (p = 0.040), high nuclear grade (p < 0.001), lymphovascular invasion (p = 0.032), negative hormone receptor status (p < 0.001), and positive HER2 status (p = 0.014). Based on the results of multivariate Cox analysis in all patients, high SUVmax (p = 0.001) and negative hormone receptor status (p = 0.005) were significantly associated with poor prognosis. In patients with triple-negative subtype, 3-year DFS rates were 90.9% for patients with a tumor of SUVmax ≤ 8.6 and 42.9% for patients with a tumor of SUVmax > 8.6 (p = 0.002), and high SUVmax was the only significant independent prognostic factor (p = 0.047). Conclusion: FDG-PET/CT is useful for predicting malignant behavior and prognosis in patients with operable breast cancer, especially the triple-negative subtype. [Copyright &y& Elsevier]

Abstract: Background: Male breast cancer (MBC) is rare. Molecular subtype has been utilized widely in female breast cancer. But the relationship between subtype and prognosis in MBC patients is still unknown. We aim to study the impact of molecular subtype on the prognosis of MBC. Methods: We identified MBC cases from 1990 to 2011 retrospectively; molecular subtype was assigned by immunohistochemistry. We compared overall survival in different subtypes by Kaplan–Meier method and COX proportional hazard regression model. Results: 68 patients with MBC were included in analysis with 115 months of a median follow-up time. Comparing to non-luminal A (subtypes of Luminal B, HER2 over-express and Basal-like) group, patients with luminal A had a lower recurrent rate and better overall survival (10-year survival rate was 78.0% vs 67.0%, mean survival time 197.46 ± 12.22 months vs 146.51 ± 16.88 months, p < 0.05). Conclusion: Molecular subtype may have prognosis-predicting value for MBC. [Copyright &y& Elsevier]

Abstract: Background: In order to reduce the probability of later clinical involvement of the axilla and at establishing a sound basis for adjuvant treatment planning axillary dissection is an important operative procedure. So, partial axillary dissection has been applied to decrease the morbidity and postoperative axillary complications. Aim of the work was to study the reliability of partial axillary lymph node dissection in patients with breast carcinoma with clinically negative axilla. Methods: Eighteen patients underwent modified radical mastectomy, while the other two patients who were fulfilling the criteria for conservative breast surgery underwent lumpectomy. All patients did complete axillary lymph nodes dissection. Intraoperative leveling of the axilla was performed and level I axillary lymph nodes were identified according to their relation to pectoralis minor muscle; then they were subjected to intraoperative pathological examination by frozen section examination followed by complete axillary clearance. Then post operative histopathological examination of the tumor and all lymph nodes was done. Results: By intraoperative pathological examination; five patients (25%) were found positive for malignant invasion, while 15 patients (75%) were pathologically free. While paraffin section showed six patients (30%) with malignant invasion, and 14 patients (70%) were pathologically free. There was a false negative rate of 5% in level I axillary lymph nodes by intraoperative pathological examination which was positive for metastasis by paraffin section that revealed microinvasion in one lymph node out of 8 in level I. Only two cases out of 20 were found positive for metastasis in level II and III. Conclusion: Partial axillary lymph node dissection is a minimally invasive, feasible and sufficient technique that can predict the axillary lymph node status. [Copyright &y& Elsevier]

Abstract: Objectives: To investigate the expression profile of miR-1258 and heparanase (HPSE) in breast cancer and to assess their clinicopathological significance. Design and methods: The expression levels of miR-1258 and HPSE were analyzed in normal, benign and malignant breast tissues. Their serum levels were evaluated in healthy women and in patients with benign and malignant breast disease. We studied the correlation between the expression of miR-1258 and HPSE and the clinical features presented by the patients. Results: MiR-1258 was down-regulated and HPSE was up-regulated in breast cancer, with a significant inverse correlation. A reduced miR-1258 expression and an elevated HPSE expression were associated with the lymph node status, late clinical stages, a short overall survival and a short relapse-free survival. In frozen fresh tissue samples, the miR-1258 levels in breast cancer with lymph node metastasis were significantly lower than that of breast cancer without lymph node metastasis and benign disease (BD). In contrast, the HPSE levels in breast cancer with lymph node metastasis were the highest. In serum samples, the miR-1258 levels in metastatic breast cancer (M1) were lower than that of primary breast cancer (M0) and BD. However, serum HPSE levels of M1 patients were significantly higher than that of M0 patients and BD patients. Conclusions: MiR-1258 may play an important role in breast cancer development and progression by regulating the expression of HPSE, and they might be potential prognostic biomarkers for breast cancer. [Copyright &y& Elsevier]

Primary breast invasive ductal carcinoma coexisting with ductal carcinoma in situ (IDC-DCIS) is characterized by lower proliferation rate and metastatic propensity than size-matched pure IDC. IDC-DCIS is also more often ER-positive, PR-positive and/or HER2-positive. This analysis aims to clarify whether the presence of coexisting DCIS in IDC affects tumor aggressiveness in various biological subtypes of breast cancer, respectively. Tumor data obtained from 1,355 consecutive female patients undergoing upfront surgery for primary breast cancer were analyzed retrospectively; 196 patients with pure DCIS were excluded. Based on evidence that immunohistochemistry (IHC) provides a reasonable approximation of molecular phenotypes, the tumor samples were divided into 4 groups: (1) luminal A (ER and/or PR-positive, HER2-negative, Ki67 ≤ 12), (2) luminal B (ER and/or PR-positive, HER2-negative, Ki67 > 12), (3) HER2 (HER2-positive) and (4) basal-like (triple-negative) disease. Ki67 expression and nodal involvement of IDC with or without DCIS in these groups were compared. The number of patients with luminal A, luminal B, HER2 and basal-like breast cancer were 396, 265, 258 and 117, respectively. Ki-67 was lower in IDC-DCIS than in size-adjusted pure IDC of both luminal A and luminal B subtypes ( P = 0.15 and <0.005, respectively). In HER2 or basal-like tumors, there were no significant difference between pure IDC and IDC-DCIS. The presence of coexisting DCIS in IDC predicts lower biological aggressiveness in luminal cancers but not in the conventionally more aggressive HER2-positive and triple-negative subtypes. [ABSTRACT FROM AUTHOR]

A nondestructive method employing Fourier transform infrared (FTIR) microspectroscopy coupled with attenuated total reflectance (ATR) objective for the analysis of histopathological specimens is described. Malignant breast tissue specimens have been analyzed to demonstrate the hypothesis that chemical changes taking place in biological tissue can be reliably and reproducibly identified. This study is the first report to elucidate clear spectral differences between different ductal carcinoma in situ (DCIS) grades. Sixty individual cases of breast carcinoma including DCIS and invasive ductal carcinoma (IDC) and seven cases of normal breast tissues were studied using the FTIR-ATR spectroscopic technique. FTIR analysis of tissue sections has provided distinct spectra that can be used to distinguish between the nuclear grades of DCIS and IDC of the breast. It was concluded that FTIR could objectively and reproducibly discriminate between DCIS and IDC grades without sample destruction. In the future, applications of FTIR approaches should become feasible in the nondestructive express classification of grades and diagnosis of breast carcinoma. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: This novel study aims to investigate texture parameters in distinguishing healthy breast tissue and breast cancer in breast magnetic resonance imaging (MRI). A specific aim was to identify possible differences in the texture characteristics of histological types (lobular and ductal) of invasive breast cancer and to determine the value of these differences for computer-assisted lesion classification. Materials and Methods: Twenty patients (mean age 50.6 ± SD 10.6; range 37–70 years), with histopathologically proven invasive breast cancer (10 lobular and 10 ductal) were included in this preliminary study. The median MRI lesion size was 25 mm (range, 7–60 mm). The selected T1-weighted precontrast, post-contrast, and subtracted images were analyzed and classified with texture analysis (TA) software MaZda and additional statistical tests were used for testing the parameters separability. Results: All classification methods employed were able to differentiate between cancer and healthy breast tissue and also invasive lobular and ductal carcinoma with classification accuracy varying between 80% and 100%, depending on the used imaging series and the type of region of interest. We found several parameters to be significantly different between the regions of interest studied. The co-occurrence matrix based parameters proved to be superior to other texture parameters used. Conclusions: The results of this study indicate that MRI TA differentiates breast cancer from normal tissue and may be able to distinguish between two histological types of breast cancer providing more accurate characterization of breast lesions thereby offering a new tool for radiological analysis of breast MRI. [Copyright &y& Elsevier]

Our report describes a 66-yr-old man who underwent surgical resection of the pancreas twice within a period of 3 yr for primary and recurrent intraductal papillary mucinous tumors (IPMTs). During the second operation, a minute invasive ductal carcinoma (IDC) was accidentally discovered in the resected specimen of the residual pancreas. The similarity and continuity between this IDC and recurrent IPMT were not recognized histologically. A solid tumor was found in the hepatoduodenal ligament 3 mo after the second operation. We performed a third operation, performing laparotomy and intra-operative radiotherapy, but could not extirpate the tumor. A biopsy specimen obtained from the tumor during this third operation revealed adenocarcinoma, and the patient later died because of tumor progression. We immunohistochemically analyzed the expression of HER-2/neu, Smad4, p16, p21, p53, mucin immunophenotypes and the Ki-67 labeling index in this series of pancreatic-duct neoplasias. Overexpression of HER-2/neu and loss of Smad4 were detected in the minute IDC, which was very different from the immunohistochemical features of both the primary and recurrent IPMTs. The IDC also showed a MUC1-positive/MUC2-negative phenotype. Therefore, we suggest that de novo IDC may occur in IPMT patients, especially those with multiple tumor recurrence. The present case may be helpful in understanding the pathogenesis of pancreatic duct lesions. [ABSTRACT FROM AUTHOR]

Background: Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting., Methods: We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MK T ), anisotropic mean kurtosis (MK A ), isotropic mean kurtosis (MK I ), macroscopic fractional anisotropy (FA), and microscopic fractional anisotropy (µFA) were estimated. The parameter differences were compared between IDC and normal fibroglandular breast tissue (FGBT), as well as the association between the diffusion parameters and histopathologic items., Results: The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 vs. 1.34±0.29, P<0.001); however, MK T , MK A , MK I , FA, and µFA were significantly higher (P<0.005). Among all the diffusion parameters, MK I was positively correlated with the tumor size on both MRI and pathological specimen (r s =0.38, P<0.05 vs. r s =0.54, P<0.01), whereas MK T had a positive correlation with the tumor size in the pathological specimen only (r s =0.47, P<0.02). In addition, the lymph node (LN) metastasis group had significantly higher MK T , MK A , and µFA compared to the metastasis negative group (P<0.05)., Conclusions: Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/qims-21-870). JL and SMG are employees of GE Healthcare. However, GE Healthcare has no role in the design of the study, data analyses, or data interpretation. The other authors have no conflicts of interest to declare., (2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.)