scholarly journals Association of the imaging characteristics of desmoplasia on digital breast tomosynthesis and the Ki-67 proliferation index in invasive breast cancer

2021 ◽  
Vol 62 (1) ◽  
pp. 59-67
Author(s):  
Kristina Samaržija ◽  
Zoran Jurjević
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Digital Breast Tomosynthesis ◽  
Proliferation Index ◽  
Ki 67 ◽  
Breast Tomosynthesis ◽  
Imaging Characteristics

scholarly journals Is Digital Breast Tomosynthesis Superior to Digital Mammography? A Preclinical Evaluation of Tumor Histopathological Markers Using Digital Breast Tomosynthesis

2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Aysegul Altunkeser ◽  
Zeynep Fatma Arslan ◽  
Mehmet Ali Eryilmaz ◽  
Muslu Kazım Korez ◽  
Zeynep Bayramoğlu
Keyword(s):  
Breast Cancer ◽  
Triple Negative ◽  
Mass Density ◽  
Digital Breast Tomosynthesis ◽  
Molecular Classification ◽  
Architectural Distortion ◽  
Ki 67 ◽  
Breast Tomosynthesis ◽  
Skin Changes ◽  
The Relationship

Background: Digital mammography (DM) and digital breast tomosynthesis (DBT) are important radiological modalities, which increase the survival of breast cancer patients. Breast cancer is a morphologically heterogeneous disease with various histopathological parameters and multiple receptors in its biological profile. Objectives: This study aimed to analyze the morphological features of invasive breast cancer on DM and DBT, to investigate the contribution of DBT to DM, to examine the association of DBT findings with pathological molecular subtypes, Bloom-Richardson grade, and Ki-67 index, and to determine the effect of breast parenchyma density on the relationship between DBT findings and hormone receptors. Patients and Methods: A total of 36 patients with malignant lesions were evaluated in this study. According to the American College of Radiology (ACR) classification, the lesion features were divided into subgroups based on DM and DBT, and the findings were compared. The relationships between DBT findings and the hormone receptor status, molecular classification, and Bloom-Richardson grade were also investigated, and the effect of density on these relationships was assessed. Results: The mean age of the patients (n = 36) was 53 years. Based on the comparison of DM and DBT findings, spiculated margins, mass density, architectural distortion, and microcalcifications were significantly more frequent in DBT. Lesions with indistinct margins on DM were observed as mass lesions with spiculated margins on DBT (P < 0.001). Regarding the relationship between DBT findings and hormone receptor status and Ki-67 proliferation index, in PR-positive patients, an irregular tumor shape was more common (89.7%). In PR-negative patients, skin changes and nipple retraction were more frequently seen (P = 0.03 for skin changes, and P = 0.049 for nipple retraction). Regarding the association between Bloom-Richardson grade and DBT findings, tumors with a higher grade were more likely to be associated with a high tumor density (P = 0.032). Also, considering the relationship between molecular classification and DBT findings, skin changes and nipple retraction were significantly more frequent in triple-negative masses compared to other subtypes (P = 0.011 for skin changes and P = 0.016 for nipple retraction). Conclusions: DBT is superior to DM, as it reveals the lesion margins, density, and architectural distortion more accurately. The majority of PR-positive tumors were irregular, while most PR-negative cases were round. The mass density also increased as the tumor grade increased. Skin change and nipple retraction were frequently seen in triple-negative tumors compared to other subtypes. Therefore, DBT is a promising diagnostic tool for showing molecular subtypes in dense breasts.

Centromere 17 Copy Number Alteration: Negative Prognostic Factor in Invasive Breast Cancer?

2012 ◽  
Vol 136 (9) ◽  
pp. 993-1000 ◽  
Author(s):  
Stella Petroni ◽  
Teresa Addati ◽  
Eliseo Mattioli ◽  
Maria Angela Caponio ◽  
Carmela Quero ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Copy Number ◽  
Growth Factor Receptor ◽  
Copy Number Gain ◽  
Chromosome 17 ◽  
Proliferation Index ◽  
Fish Analysis ◽  
Breast Cancers ◽  
Ki 67

Context.—Chromosome 17 polysomy has been identified in 5% to 50% of invasive breast cancers; even though a relationship with human epidermal growth factor receptor 2 (HER2/neu) status has been reported, other studies have shown that coincident centromere 17 (Cep17) amplification may be the cause of an overestimation of chromosome 17 polysomy in fluorescence in situ hybridization (FISH) testing. Objective.—To evaluate polysomy/amplification of Cep17 in invasive breast cancer with relation to proliferative activity (Ki-67), estrogen receptor, progesterone receptor, and HER2/neu status, in an attempt to identify a subgroup of patients with a worse prognosis. Design.—A total of 647 cases of invasive ductal breast cancer were collected and subjected to FISH analysis for HER2/neu gene and centromere 17 alteration, HercepTest for HER2/neu protein expression, and routine immunohistochemistry for Ki-67 and hormone receptor status. Results.—Copy number gain of Cep17 was observed in 27.3% of cases. Within this group, HER2/neu gene amplification was detected in 14.1% of cases, whereas HER2/neu expression was scored 3+ in 20.1% of cases; about half of the HER2/neu overexpressing cases (9.8%) did not show amplification by FISH. Moreover, 69% of polysomic cases showed high Ki-67 index. Conclusions.—(1) Centromere 17–altered cases are frequently HER2/neu overexpressing but not amplified, resulting in HercepTest/FISH disagreement; (2) HER2/neu amplification is seen at a higher incidence in cases without Cep17 copy number alterations, which are therefore not necessarily due to chromosome 17 disorder; (3) proliferation index is significantly higher in aneusomic tumors. These data suggest that the presence of Cep17 alterations could identify a subset of breast cancers with more aggressive biological and clinical behavior, which may show nonresponsiveness to conventional therapy independently of HER2/neu amplification status.

scholarly journals Breast cancer Ki-67 expression prediction by digital breast tomosynthesis radiomics features

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Alberto Stefano Tagliafico ◽  
Bianca Bignotti ◽  
Federica Rossi ◽  
Joao Matos ◽  
Massimo Calabrese ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Digital Breast Tomosynthesis ◽  
Ki 67 ◽  
Breast Tomosynthesis

scholarly journals Correlation between Ki-67 proliferation index in invasive breast cancer and molecular signatures: EndoPredict and MammaPrint

2021 ◽  
Author(s):  
J. Eduardo Amezcua-Gálvez ◽  
Carlos A. Lopez-Garcia ◽  
Villarreal-Garza Cynthia ◽  
Lopez-Rivera Victor ◽  
Canavati-Marcos Mauricio ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Invasive Breast Cancer ◽  
Histological Grade ◽  
Area Under The Curve ◽  
Molecular Signature ◽  
Proliferation Index ◽  
Molecular Signatures ◽  
Ki 67

Abstract Background: The need to identify patients with hormone receptor-positive (HR+) early invasive breast cancer (EIBC) who could benefit from adjuvant chemotherapy has been enhanced with the development of molecular signature tests. However, due to their high cost and limited availability alternative low-cost prognostic and predictive tests are used in clinical practice. Here, we sought to evaluate the performance of the proliferation marker Ki-67 to identify these patients and explore its association with molecular signatures and risk stratification markers. Methods: From our prospectively maintained multicenter breast cancer registry, we identified EIBC HR+ patients tested with EndoPredict or MammaPrint and Ki-67 as part of their routine workup. Patients were categorized into two groups: Group 1 (2016-2018) was evaluated using EndoPredict and Group 2 (2011 to 2018) with MammaPrint. A ≥20% Ki67 cutoff was utilized for identify high proliferative EIBC and a receiver-operative curve area under the curve (AUC) and kappa concordance were utilized to evaluate the performance of Ki-67 compared to molecular signature tests. Results: In the EndoPredict group, 54/96 patients were considered high-risk by EPclin. 57/96 patients had a Ki-67 ≥20%. However, there was no significant overall concordance between them (59.37%, κ = 0.168, p=0.09). In the MammaPrint group, 21/70 patients were considered high-risk. Ki67 ≥20% was present in 36 patients with a significant overall concordance (67.14%, κ 0.35, p<0.001). Additionally, Ki-67 was associated with the Nottingham histological grade (NHG) in both groups. Conclusion: There is a fair concordance between Ki-67 and MammaPrint risk stratification of HR + EIBC and no concordance with EndoPredict molecular signature. Cost-effectiveness analysis of these tests in developing countries are needed, until then, the use of Ki-67 seems reasonable to aid clinical decision.

Strategic Aspects of NPY-Based Monoclonal Antibodies for Diagnosis and Treatment of Breast Cancer

2020 ◽  
Vol 21 (11) ◽  
pp. 1097-1102
Author(s):  
Drashti Desai ◽  
Pravin Shende
Keyword(s):  
Breast Cancer ◽  
Monoclonal Antibodies ◽  
Diagnosis And Treatment ◽  
Detection Methods ◽  
Active Immunotherapy ◽  
Immune Checkpoints ◽  
Proliferation Index ◽  
Protein Fusion ◽  
Ki 67 ◽  
Cost Efficient

: Immunotherapy emerges as a treatment strategy for breast cancer marker, diagnosis and treatment. In this review, monoclonal antibodies (mAbs)-based passive and peptide vaccines as active immunotherapy approaches like activation of B-cells and T-cells are studied. Passive immunotherapy is mAbs-based therapy effective against tumor cells, which acts by targeting HER2, IGF 1R, VEGF, BCSC and immune checkpoints. Neuropeptide Y (NPY) and GPCR are the areas of interest to target BC metastases for on-targeting therapeutic action. Neuropeptide S (NPS) or NPS receptor 1, acts as a biomarker for Neuroendocrine tumors (NET), mostly characterized by synaptophysin and chromogranin-A expression or Ki-67 proliferation index. The protein fusion technologies arise as a promising avenue in plant expression systems for increased recombinant Ab accumulation and cost-efficient purification. Recently, mAbs-based immunotherapy effectiveness is appreciated as a novel therapeutic combination of chemotherapy and immunotherapy to reduce the side effects and improve therapeutic responsiveness. Synthetic drug resistance will be overcome by mAbs-based therapy through several clinical trials and detection methods need to be optimized for accuracy and precision. Pharmacokinetic attributes need to be accessed for preferred receptor-agonist activity without ligand accumulation.

scholarly journals Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study

2021 ◽  
Author(s):  
Suzanne L. van Winkel ◽  
Alejandro Rodríguez-Ruiz ◽  
Linda Appelman ◽  
Albert Gubern-Mérida ◽  
Nico Karssemeijer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Detection ◽  
Support System ◽  
Reading Time ◽  
Digital Breast Tomosynthesis ◽  
Breast Tomosynthesis ◽  
Screening Programs ◽  
The Impact

Abstract Objectives Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is increasingly implemented in breast cancer screening. However, the large volume of images increases the risk of reading errors and reading time. This study aims to investigate whether the accuracy of breast radiologists reading wide-angle DBT increases with the aid of an artificial intelligence (AI) support system. Also, the impact on reading time was assessed and the stand-alone performance of the AI system in the detection of malignancies was compared to the average radiologist. Methods A multi-reader multi-case study was performed with 240 bilateral DBT exams (71 breasts with cancer lesions, 70 breasts with benign findings, 339 normal breasts). Exams were interpreted by 18 radiologists, with and without AI support, providing cancer suspicion scores per breast. Using AI support, radiologists were shown examination-based and region-based cancer likelihood scores. Area under the receiver operating characteristic curve (AUC) and reading time per exam were compared between reading conditions using mixed-models analysis of variance. Results On average, the AUC was higher using AI support (0.863 vs 0.833; p = 0.0025). Using AI support, reading time per DBT exam was reduced (p < 0.001) from 41 (95% CI = 39–42 s) to 36 s (95% CI = 35– 37 s). The AUC of the stand-alone AI system was non-inferior to the AUC of the average radiologist (+0.007, p = 0.8115). Conclusions Radiologists improved their cancer detection and reduced reading time when evaluating DBT examinations using an AI reading support system. Key Points • Radiologists improved their cancer detection accuracy in digital breast tomosynthesis (DBT) when using an AI system for support, while simultaneously reducing reading time. • The stand-alone breast cancer detection performance of an AI system is non-inferior to the average performance of radiologists for reading digital breast tomosynthesis exams. • The use of an AI support system could make advanced and more reliable imaging techniques more accessible and could allow for more cost-effective breast screening programs with DBT.

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