Breast cancer and microcalcification

OBJECTIVE: Digital breast tomosynthesis (DBT) is a quasi-three-dimensional (3D) breast imaging modality that improves breast cancer screening and diagnosis because it reduces fibroglandular tissue overlap compared with 2D mammography. However, DBT suffers from noise and blur problems that can lower the detectability of subtle signs of cancers such as microcalcifications (MCs). Our goal is to improve the image quality of DBT in terms of image noise and MC conspicuity. APPROACH: We proposed a model-based deep convolutional neural network (deep CNN or DCNN) regularized reconstruction (MDR) for DBT...

Microcalcification (MC) is a valuable diagnostic indicator of breast cancer, and it is reported to be associated with increased tumor aggressiveness and poor prognosis. Nevertheless, the exact potential molecular mechanism is not completely understood. Here, we find that the mineralized invasive breast cancer (IBC) cells not only increased their proliferation and migration, but also showed the characteristic of doxorubicin resistance. The PI3K/AKT signaling pathway is associated with the generation of calcification in IBC, and it activates the transcription and translation of its downstream hypoxia-inducible factor 1α (HIF1α)...

[This retracts the article DOI: 10.1155/2021/6835963.].

BACKGROUND: Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammography. We developed and tested an AI model for localizing and characterizing microcalcifications. METHODS: Three expert radiologists annotated a dataset of mammograms using histology-based ground truth. The dataset was partitioned for training, validation, and testing...

BACKGROUND: The study was aimed at identifying how useful Computer-Aided Detection (CAD) could be in reducing false-negative reporting in mammography and early detection of breast cancer at an early stage as the best protection is early detection. MATERIALS AND METHODS: This retrospective study was conducted in a tertiary care setup of Atomic Energy Cancer Hospital, Nuclear Medicine, Oncology and Radiotherapy Institute (AECH-NORI), where 33 patients with suspicious findings on mammography and subsequent biopsy-proven malignancy were included...

BACKGROUND: Breast carcinoma (BC) threatens the physical and mental health of women worldwide, and early diagnosis is important for improving patient outcomes and ensuring successful treatment. PURPOSE: This research mainly aims to compare and analyze the value of molybdenum target X-ray and high-frequency color Doppler flow imaging (CDFI) in the early diagnosis of BC. METHODS: First, 102 patients with suspected early-stage BC (ESBC) admitted to Henan Provincial People's Hospital were examined by molybdenum target X-ray and CDFI...

PURPOSE: To describe in detail the special features of a previously unappreciated "classic invasive lobular carcinoma" which is confined to the terminal ductal lobular units (TDLUs) and differs considerably from the extensive classic invasive lobular carcinoma, and to suggest specific terminology. METHOD: All invasive breast cancer cases without associated microcalcifications diagnosed in our Institution with the histopathologic diagnosis of classic invasive lobular carcinoma during the years 1996-2019 (n = 560) formed the basis of this study...

PURPOSE: Recent research suggests that image quality degradation with reduced radiation exposure in mammography can be mitigated by postprocessing mammograms with denoising algorithms based on convolutional neural networks. Breast microcalcifications, along with extended soft-tissue lesions, are the primary breast cancer biomarkers in a clinical x-ray examination, with the former being more sensitive to quantum noise. We test one such publicly available denoising method to observe if an improvement in detection of small microcalcifications can be achieved when deep learning-based denoising is applied to half-dose phantom scans...

BACKGROUND AND OBJECTIVE: Computer-aided detection (CADe) of microcalcification clusters (MCs) in digital breast tomosynthesis (DBT) is crucial in the early diagnosis of breast cancer. Although convolutional neural network (CNN)-based detection models have achieved excellent performance in medical lesion detection, they are subject to some limitations in MC detection: 1) Most existing models employ the feature pyramid network (FPN) for multi-scale object detection; however, the rough feature sharing between adjacent layers in the FPN may limit the detection ability for small and low-contrast MCs; and 2) the MCs region only accounts for a small part of the annotation box, so the features extracted indiscriminately within the whole box may easily be affected by the background...

PURPOSE: This study investigated the relationship between breast ultrasound features and lump margin status in breast-conserving patients. METHODS: A single-institution database and medical records system were searched to identify patients who had undergone breast-conserving surgery between 2015 and 2022. Patients were divided into case and control groups based on their postoperative margin status, and different matching methods [case-control matching (CCM) and propensity score matching (PSM)] were used to match the cases and controls at a ratio of 1:1...

BACKGROUND: Microcalcifications persist even if a patient with breast cancer achieves pathologic complete response (pCR) as confirmed by surgery after neoadjuvant treatment (NAT). In practice, surgeons tend to remove all the microcalcifications. This study aimed to explore the correlation between changes in the extent of microcalcification after NAT and pathological tumor response and compare the accuracy of mammography (MG) and magnetic resonance imaging (MRI) in predicting the size of residual tumors...

BACKGROUND: Breast microcalcifications (MCs) are considered to be a robust marker of breast cancer. A machine learning model can provide breast cancer diagnosis based on properties of individual MCs - if their characteristics are captured at high resolution and in 3D. PURPOSE: The main purpose of the study was to explore the impact of image resolution (8 µm, 16 µm, 32 µm, 64 µm) when diagnosing breast cancer using radiomics features extracted from individual high resolution 3D micro-CT MC images...

OBJECTIVES: The goal of this study was to assess the clinicopathological and ultrasound (US) features of breast cancer for predicting the risk of axillary lymph node metastasis. METHODS: Patients with breast cancer were included in this retrospective, moncentric, observational study. Their preoperative ultrasound features, clinical data, laboratory results and postoperative pathologic results and immunophenotyping were collected. The association of these factors of breast cancer with axillary lymph node metastasis was evaluated by univariate and multivariate analysis...

OBJECTIVE: To investigate the diagnostic value of ultrasound for patients with axillary lymph node-negative breast cancer (ALNNBC). METHODS: A retrospective analysis was performed on the clinical data of 204 breast cancer patients who were admitted by Quanzhou First Hospital Affiliated to Fujian Medical University between October 2020 and May 2022. According to the results of axillary lymph node (ALN) examination, the patients were assigned to a positive group(n=102) and a negative group(n=102)...

We perform MRI of the breast as a first pass technique. We successfully established 10-minute-protocols (including T2 images) with a fixed dosage of 5 ml 1 M CM. A high spatial resolution of 526 × 526, better 672 × 672 or maximum (1.024 × 1.024, MIO MRI) is vital to achieve best results. We use fixation tools to avoid motion artifacts. Motion correction algorithms can, however, often eliminate such artifacts when they are present. In initial breast MRI exams, morphologic features are the most important criteria for lesion evaluation...

PURPOSE: Analysis of the morphology of lesions classified into the BI-RADS 4 category and assessment of the possibility of downgrade the BI-RADS category in those that did not show enhancement on recombinant contrast-enhanced mammography (CEM) images. METHOD: The retrospective, single-center study included 528 patients who underwent a core needle biopsy performed from January 2017 to November 2022 due to a breast lesion classified as BI-RADS 4 on CEM. Patients' electronic records and imaging examinations were reviewed...

Mineral particles that form in soft tissues in association with disease conditions are heterogeneous in their composition and physiochemical properties. Hence, it is challenging to study the effect of mineral type on disease progression in a high-throughput and realistic manner. For example, most early breast precancer lesions, termed ductal carcinoma in situ (DCIS), contain microcalcifications (MCs), calcium-containing pathological minerals. The most common type of MCs is calcium phosphate crystals, mainly carbonated apatite; it is associated with either benign or malignant lesions...

Introduction: Identifying the HER2 status of breast cancer patients is important for treatment options. Previous studies have shown that ultrasound features are closely related to the subtype of breast cancer. Methods: In this study, we used features of conventional ultrasound and ultrasound elastography to predict HER2 status. Results and Discussion: The performance of model (AUROC) with features of conventional ultrasound and ultrasound elastography is higher than that of the model with features of conventional ultrasound (0...

The clinical applications of the volography algorithm and concomitant refraction-corrected reflection algorithm as described in Chap. 10 are discussed here. Comparisons with an H&E stained image, discussion of glandular tissue visibility, related biomarkers, segmentation accuracy and capabilities, microcalcification and cyst detection and analysis, and various VGA and clinical studies show the unique capabilities of the method. The accuracy of the fibroglandular segmentation and its relevance to breast density in imaging is mentioned...

RATIONALE AND OBJECTIVES: Information evaluating the efficacy of 2D synthesized mammography (2Ds) reconstructions in microcalcification detection is limited. This study used stereotactic biopsy data for microcalcifications to evaluate the stepwise implementation of 2Ds in screening mammography. The study aim was to identify whether 2Ds + digital breast tomosynthesis (DBT) is non-inferior to 2D digital mammography (2DM) + 2Ds + DBT, 2DM + DBT, and 2DM in identifying microcalcifications undergoing further diagnostic imaging and stereotactic biopsy...