scholarly journals Relationship Between Clustered Ring Nonmass Enhancement of Breast MRI and Prognostic Molecular Biomarkers in Breast Cancer

2022 ◽  
Author(s):  
Mei-Lin Wang ◽  
Yu-Pin Chang ◽  
Chuan-Han Chen ◽  
Ming-Cheng Liu ◽  
Chen-Hao Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Univariate Analysis ◽  
Breast Mri ◽  
Molecular Biomarkers ◽  
Response To Therapy ◽  
Biological Behavior ◽  
Pathology Report ◽  
Breast Lesions ◽  
Imaging Features ◽  
Expression Ratio

Abstract BackgroundClustered ring enhancement (CRE) of breast MRI is a lexicon of nonmass enhancement (NME) representing tendency of breast cancer and molecular biomarkers are predictors of response to therapy. The purpose of this study was to retrospectively determine the relationship between CRE NME and prognostic molecular biomarkers in breast cancer.MethodsRetrospective analysis of 58 breast lesions in 56 female patients between July 2013 and December 2018 was performed in our institution. Cases with MRI reporting NME in the text were collected via searching the report database. The patterns of enhancement including CRE on breast MRI were reviewed by a radiologist blinded to pathology report. The pathological results and expression of molecular biomarkers were collected. Univariate analysis was applied to evaluate the association between MRI NME imaging features, pathological and IHC stain findings.Results58 Breast lesions were pathologically proven breast carcinoma, and 31 lesions with CRE and 27 lesions without CRE on breast MRI. The expression of estrogen receptor (ER) (P=0.017) and progesterone receptor (PR) (P=0.017) was significantly lower in lesions with CRE compared with those without CRE. The expression of Ki-67 (≥ 25%) was significantly higher in lesions with CRE(P=0.046). The lesions with CRE have a lower expression ratio of ER (50.71 ± 45.39% vs. 74.26 ± 33.59%, p= 0.028).ConclusionOur results indicated that lesions with CRE may possess different features from those without CRE in molecular expression. They tend to bear a more aggressive biological behavior.

scholarly journals Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Dalia Abdelhady ◽  
Amany Abdelbary ◽  
Ahmed H. Afifi ◽  
Alaa-eldin Abdelhamid ◽  
Hebatallah H. M. Hassan
Keyword(s):  
Breast Cancer ◽  
Diffusion Tensor Imaging ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dce Mri ◽  
Additional Tool ◽  
Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

scholarly journals Value of Magnetic Resonance Imaging Features in Diagnosis and Treatment of Breast Cancer under Intelligent Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Shuang Liu ◽  
Min Tang ◽  
Shuqin Ruan ◽  
Feng Wei ◽  
Jiaxi Lu
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Breast Mri ◽  
Imaging Features ◽  
Mri Imaging ◽  
Resonance Imaging ◽  
Intelligent Algorithms ◽  
Mri Diagnosis ◽  
Diagnosis Model ◽  
Mri Image

This study was to analyze the clinical application value of magnetic resonance imaging (MRI) image features based on intelligent algorithms in the diagnosis and treatment of breast cancer and to provide an effective reference assessment for breast cancer diagnosis. The MRI diagnosis model (ACO-MRI) based on the ant colony algorithm (ACO) was proposed, which was compared with the diagnosis methods based on support vector machine (SVM) and proximity (KNN) algorithm, and the proposed algorithm was applied to MRI images to diagnose breast cancer. The results showed that the accuracy, sensitivity, and specificity of the ACO-MRI model were greater than those of the KNN and SVM algorithm. Moreover, the specificity was statistically considerable compared with the two algorithms of KNN and SVM ( P < 0.05 ). By comparing 1/5 number of ants and the average gray path of the ACO-MRI model under 1/8 number of ants, it was found that the average gray path value of 1/8 number of ants was greatly higher than the average gray path value of 1/5 number of ants ( P < 0.05 ). The differences in the overall distribution of breast MRI imaging features among Luminal A, Luminal B, HER-2 overexpression, and TN were compared. There were considerable differences in the overall distribution of the three breast MRI imaging features of the boundaries, morphology, and enhancement methods among the four groups ( P < 0.05 ). In short, MRI image based on the intelligent algorithm ACO-MRI diagnosis model can effectively improve the diagnosis effect of breast cancer. Its image feature boundaries, morphology, and enhancement methods had good imaging features in the diagnosis of breast cancer.

scholarly journals BIRADS 4 breast lesions: comparison of contrast-enhanced spectral mammography and contrast-enhanced MRI

2019 ◽  
Vol 50 (1) ◽  
Author(s):  
Rabab Yasin ◽  
Enas Abd El Ghany
Keyword(s):  
Breast Cancer ◽  
Developing Countries ◽  
Statistical Significance ◽  
Breast Mri ◽  
Excision Biopsy ◽  
Breast Lesions ◽  
Common Cancer ◽  
Contrast Enhanced ◽  
Histopathological Result ◽  
Contrast Enhanced Mri

Abstract Background Breast cancer is the most common cancer in women worldwide. It is responsible for about 23% of cancer in females in both developed and developing countries [1]. We aimed to assess the accuracy of contrast-enhanced spectral mammography (CESM) versus contrast-enhanced breast MRI in the evaluation of BIRADS 4 breast lesions. Results Fifty patients were included in this study; there were 28 malignant cases and 22 benign cases; all cases were proved by histopathological result either by core biopsy or excision biopsy. CESM was found to have less sensitivity (94.1%) than MRI (100%) but CESM has higher specificity (100%) than MRI (95.5%). The accuracy of CESM was 96.4%, while the accuracy of MRI was 98.2% with no statistical significance (P value 0.827). Conclusion CESM can be used as a sensitive diagnostic tool in the detection and staging of breast cancer with higher specificity and less sensitivity as compared to contrast enhanced breast MRI.

Trastuzumab-reactive antibodies (TR-abs) in serum and trastuzumab (Tzb) benefit prediction in patients with HER2-overexpressing breast cancer.

2012 ◽  
Vol 30 (30_suppl) ◽  
pp. 77-77 ◽  
Author(s):  
Paula Raffin Pohlmann ◽  
Todd W. Miller ◽  
David L Blum ◽  
Dipti Pareh ◽  
Heping Yan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Transgenic Mice ◽  
Univariate Analysis ◽  
Metastatic Breast ◽  
Response To Therapy ◽  
Breast Cancer Cell Lines ◽  
Therapeutic Antibodies ◽  
Stage Iv Breast Cancer ◽  
Pharmacologically Active

77 Background: Trastuzumab (Tzb) is a humanized monoclonal antibody (MAb) approved for treatment of HER2-overexpressing breast cancer. Unfortunately not all patients benefit from it and lack of response cannot be predicted. We detected TR-abs in serum of mice and patients treated with Tzb. We hypothesized that TR-abs would associate with response to therapy. Methods: Direct/competition ELISA, dot blot, and mass spectrometry were used to detect and characterize TR-abs in sera from Tzb treated FVBMMTV/HER2transgenic mice, from hybridoma MAbs stemming from transgenic mice responding favorably to Tzb (992-18 mMAb), and in sera of 22 patients with metastatic breast cancer enrolled in a phase I clinical trial. WST-1 viability assay was used to assess biological activity of 992-18 on SKBR3 or BT474 human breast cancer cell lines. Results: From 12 mice bearing HER2-overexpressing tumors and treated with Tzb, 5 responded to therapy and 7 exhibited progressive disease (PD). All 5 responders had elevated TR-abs, whereas TR-abs were low/undetectable with PD (p=0.002; Mann-Whitney two-tailed). This was confirmed in a second cohort of 16 mice, in which TR-abs were undetectable prior to treatment, but gradually detected with Tzb therapy and tumor regression. TR-MAb 992-18 directly targeted also SKBR3 and BT474 in cell-based ELISAs and immunofluorescence assays. Treatment with 992-18 reduced BT474 and SKBR3 cell viability in comparison to isotype-matched control Ab (p<0.0001). In sera from patients with metastatic breast cancer, higher concentrations of TR-abs were significantly associated with lower risk of disease progression (p=0.023, Cox regression, univariate analysis). Conclusions: Low serum TR-abs are associated with poor response to Tzb in mice and with shorter progression free survival in women with HER2 overexpressing stage IV breast cancer. In addition, TR-abs (e.g. 992-18) produced in response to therapy may be pharmacologically active. Results support prospective evaluation of patients undergoing treatment with therapeutic antibodies to determine if this non-invasive immunoassay detecting anti-therapeutic antibodies would predict benefit to therapy.

Multivariable Models Based on Baseline Imaging Features and Clinicopathological Characteristics to Predict Breast Pathologic Response after Neoadjuvant Chemotherapy in Patients with Breast Cancer

Breast Care ◽  
2021 ◽  
Author(s):  
Peixian Chen ◽  
Chuan Wang ◽  
Ruiliang Lu ◽  
Ruilin Pan ◽  
Lewei Zhu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Prediction Models ◽  
Univariate Analysis ◽  
Pathologic Complete Response ◽  
Clinicopathological Characteristics ◽  
Her2 Status ◽  
Imaging Features ◽  
Multivariate Models ◽  
Multivariable Models

Abstract Introduction Currently, the accurate evaluation and prediction of response to neoadjuvant chemotherapy (NAC) remains a great challenge. We developed several multivariate models based on baseline imaging features and clinicopathological characteristics to predict the breast pathologic complete response (pCR). Methods We retrospectively collected clinicopathological and imaging data of patients who received NAC and subsequent surgery for breast cancer at our hospital from 2014 June till 2020 September. We used mammography, ultrasound and magnetic resonance imaging (MRI) to investigate the breast tumors at baseline. Results A total of 308 patients were included and 111 patients achieved pCR. The HER2 status and Ki-67 index were significant factors for pCR on univariate analysis and in all multivariate models. Among the prediction models in this study, the ultrasound-MRI model performed the best, producing an area under curve of 0.801 (95%CI=0.749-0.852), a sensitivity of 0.797 and a specificity of 0.676. Conclusion Among the multivariable models constructed in this study, the ultrasound plus MRI model performed the best in predicting the probability of pCR after NAC. Further validation is required before it is generalized.

scholarly journals Clinico-radio-pathological Features and Biological Behavior of Breast Cancer in Young Indian Women: A Prospective Study

2021 ◽  
Author(s):  
Rashmi Sudhir ◽  
Kamala Sannapareddy ◽  
Alekya Potlapalli ◽  
Vidhatri Penmetsa
Keyword(s):  
Breast Cancer ◽  
Brca Mutation ◽  
Biological Behavior ◽  
P Value ◽  
Imaging Method ◽  
Imaging Features ◽  
High Grade ◽  
Pathological Features ◽  
Detection Rates ◽  
Indian Women

Abstract Aims The aim of the study is to evaluate the characteristic imaging features of breast cancer on mammogram, ultrasound, and magnetic resonance imaging (MRI) in women less than 40 years of age and to assess the degree of correlation between clinico-radio-pathological features and biological behavior. Methods and Materials A prospective observational study on consecutive women under 40 years of age evaluated with ultrasound of breast, digital mammogram, or contrast-enhanced breast MRI, diagnosed with breast cancer on histopathology and molecular analysis done at our center between January and December 2019 were included. Patient demographics, clinical presentation, family history, BRCA mutation status, imaging, pathological findings, and molecular status were determined. Results Out of 2,470 women diagnosed with breast cancer, 354 (14.3%) were less than 40 years of age who were included in this study. Mammography showed positive findings in 85%, ultrasonography in 94.3%, and MRI in 96.4% of women. Majority of the women (69.6%) presented in the late stage (Stage III and IV) with high-grade carcinoma in 39.5% and triple-negative breast cancer (TNBC) in 45.7%. Tumors with human epidermal growth factor-2neu expression were associated with the presence of microcalcifications (p-value = 0.006), and TNBC with circumscribed margins or BI-RADS 3/4a category on imaging (p-value = 0.007) and high-grade invasive carcinoma compared with others (p-value <0.0001). Conclusion The incidence of breast cancer in Indian women less than 40 years of age is relatively high as compared with the West. The detection of breast cancer in young women remains challenging due to dense breast tissue, lower incidence rate, and lack of regular breast screening. While ultrasound is the recommended imaging method for evaluation of breast under the age of 40 years, we found a better characterization of lesions and higher cancer detection rates when they were also evaluated with mammography and MRI.

Breast Imaging

2018 ◽  
Keyword(s):  
Breast Cancer ◽  
Breast Imaging ◽  
Medical Physics ◽  
Breast Mri ◽  
Imaging Features ◽  
Comprehensive Overview ◽  
Multiple Imaging ◽  
Breast Cancer Epidemiology ◽  
Management Recommendations ◽  
Basic Medical

This textbook provides a comprehensive overview of breast imaging, a subspecialty of radiology dedicated to breast cancer screening, diagnosis, and treatment management. Overview chapters provide the fundamentals of breast cancer epidemiology, pathophysiology, screening, staging, and treatment, in addition to the fundamentals of mammography, tomosynthesis, breast ultrasound, and breast MRI. The basic medical physics relevant to breast imaging are covered, as are the basics of imaging quality control. The remaining chapters are organized by individual imaging findings, with review of key imaging features, imaging protocols, pitfalls, differential diagnoses, and management recommendations. Each type of breast imaging-guided interventional procedures are covered in dedicated chapters. This efficient textbook is heavily weighted towards providing multiple imaging examples with short summaries and bullet points, providing an easy, effective overview of the subspecialty for radiologists both in training and in practice.

scholarly journals Chronic Lymphocytic Leukemia Involving the Breast Parenchyma, Mimicker of Invasive Breast Cancer: Differentiation on Breast MRI

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Vandana Dialani ◽  
Kalpana Mani ◽  
Nicole B. Johnson
Keyword(s):  
Breast Cancer ◽  
Chronic Lymphocytic Leukemia ◽  
Invasive Ductal Carcinoma ◽  
Invasive Breast Cancer ◽  
Ductal Carcinoma ◽  
Breast Mri ◽  
Collision Tumor ◽  
Lymphocytic Leukemia ◽  
Imaging Features ◽  
Breast Parenchyma

Leukemic involvement of the breast is rare, particularly involvement by chronic lymphocytic leukemia (CLL). While concurrent invasive ductal carcinoma and CLL manifesting as a collision tumor in the breast is extremely rare, this association (CLL and carcinoma) has been described in other organs. We report here a case of a 58-year-old woman with concurrent invasive ductal carcinoma and CLL and describe the imaging features of CLL, particularly the differentiation on MRI.

scholarly journals Unusual Male Breast Lesions

2021 ◽  
Vol 11 ◽  
pp. 21
Author(s):  
Shaza AlSharif ◽  
Khalid Misfer Alshamrani ◽  
Anabel Scaranelo ◽  
Nuha Khoumais ◽  
Ahmad Subahi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Male Breast Cancer ◽  
Diagnostic Algorithm ◽  
Breast Tumors ◽  
Male Breast ◽  
Breast Lesions ◽  
Imaging Features ◽  
Breast Masses ◽  
Female Breast ◽  
Primary Male

Most of male breast masses are benign with gynecomastia being the most common entity encountered. Primary male breast cancer accounts for less than 1% of the total number of breast cancer. Male breast can be affected by a variety of conditions affecting the female breast with less frequency due to the lack of hormonal influence and consequent glandular sub-development. Imaging features of male breast masses are quite similar to the female breast. Therefore, using the knowledge of the female breast and applying it may help in the diagnosis and management of male breast abnormalities. In this article, we aim to review a variety of unusual male breast masses. We discuss the demographics of male breast tumors, describe the diagnostic algorithm for evaluating male breast masses, and review the imaging features of rare breast masses and mimickers of male breast cancer.

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