5,781 results match your criteria digital breast


Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis.

Lancet Digit Health 2022 Jul;4(7):e507-e519

Department of Diagnostic and Interventional Radiology and Neuroradiology, University-Hospital Essen, Essen, Germany.

Background: We propose a decision-referral approach for integrating artificial intelligence (AI) into the breast-cancer screening pathway, whereby the algorithm makes predictions on the basis of its quantification of uncertainty. Algorithmic assessments with high certainty are done automatically, whereas assessments with lower certainty are referred to the radiologist. This two-part AI system can triage normal mammography exams and provide post-hoc cancer detection to maintain a high degree of sensitivity. Read More

View Article and Full-Text PDF

Digital breast tomosynthesis-based peritumoral radiomics approaches in the differentiation of benign and malignant breast lesions.

Diagn Interv Radiol 2022 May;28(3):217-225

Department of Biomedical Engineering, China Medical University, Shenyang, China.

PURPOSE We aimed to evaluate digital breast tomosynthesis (DBT)-based radiomics in the differentiation of benign and malignant breast lesions in women. METHODS A total of 185 patients who underwent DBT scans were enrolled between December 2017 and June 2019. The features of handcrafted and deep learning-based radiomics were extracted from the tumoral and peritumoral regions with different radial dilation distances outside the tumor. Read More

View Article and Full-Text PDF

Improved Prediction of Survival Outcomes Using Residual Cancer Burden in Combination With Ki-67 in Breast Cancer Patients Underwent Neoadjuvant Chemotherapy.

Front Oncol 2022 7;12:903372. Epub 2022 Jun 7.

Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.

We developed a model for improving the prediction of survival outcome using postoperative Ki-67 value in combination with residual cancer burden (RCB) in patients with breast cancer (BC) who underwent neoadjuvant chemotherapy (NAC). We analyzed the data from BC patients who underwent NAC between 2010 and 2019 at Samsung Medical Center and developed our residual proliferative cancer burden (RPCB) model using semi-quantitative Ki-67 value and RCB class. The Cox proportional hazard model was used to develop our RPCB model according to disease free survival (DFS) and overall survival (OS). Read More

View Article and Full-Text PDF

Diagnostic Efficacy across Dense and Non-Dense Breasts during Digital Breast Tomosynthesis and Ultrasound Assessment for Recalled Women.

Diagnostics (Basel) 2022 Jun 16;12(6). Epub 2022 Jun 16.

Medical Image Optimisation and Perception Group, Discipline of Medical Imaging Science, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.

Background: To compare the diagnostic efficacy of digital breast tomosynthesis (DBT) and ultrasound across breast densities in women recalled for assessment.

Methods: A total of 482 women recalled for assessment from January 2017 to December 2019 were selected for the study. Women met the inclusion criteria if they had undergone DBT, ultrasound and had confirmed biopsy results. Read More

View Article and Full-Text PDF

The Early Detection of Breast Cancer Using Liquid Biopsies: Model Estimates of the Benefits, Harms, and Costs.

Cancers (Basel) 2022 Jun 15;14(12). Epub 2022 Jun 15.

Department of Public Health, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands.

Breast cancer screening is associated with harms, such as false-positives and overdiagnoses, and, thus, novel screen tests can be considered. Liquid biopsies have been proposed as a novel method for the early detection of cancer, but low cell-free DNA tumor fraction might pose a problem for the use in population screening. Using breast cancer microsimulation model MISCAN-Fadia, we estimated the outcomes of using liquid biopsies in breast cancer screening in women aged 50 to 74 in the United States. Read More

View Article and Full-Text PDF

The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI.

Tomography 2022 Jun 14;8(3):1552-1569. Epub 2022 Jun 14.

Department of Radiology, University of Iowa, 169 Newton Road, Iowa City, IA 52333, USA.

Radial acquisition with MOCCO reconstruction has been previously proposed for high spatial and temporal resolution breast DCE imaging. In this work, we characterize MOCCO across a wide range of temporal contrast enhancement in a digital reference object (DRO). Time-resolved radial data was simulated using a DRO with lesions in different PK parameters. Read More

View Article and Full-Text PDF

BM-Net: CNN-Based MobileNet-V3 and Bilinear Structure for Breast Cancer Detection in Whole Slide Images.

Bioengineering (Basel) 2022 Jun 20;9(6). Epub 2022 Jun 20.

The Institute of Technological Sciences, Wuhan University, Wuhan 430072, China.

Breast cancer is one of the most common types of cancer and is the leading cause of cancer-related death. Diagnosis of breast cancer is based on the evaluation of pathology slides. In the era of digital pathology, these slides can be converted into digital whole slide images (WSIs) for further analysis. Read More

View Article and Full-Text PDF

A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods.

Bioengineering (Basel) 2022 Jun 15;9(6). Epub 2022 Jun 15.

School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA.

Objective: Radiomics and deep transfer learning are two popular technologies used to develop computer-aided detection and diagnosis (CAD) schemes of medical images. This study aims to investigate and to compare the advantages and the potential limitations of applying these two technologies in developing CAD schemes.

Methods: A relatively large and diverse retrospective dataset including 3000 digital mammograms was assembled in which 1496 images depicted malignant lesions and 1504 images depicted benign lesions. Read More

View Article and Full-Text PDF

A Narrative Review on the Collection and Use of Electronic Patient-Reported Outcomes in Cancer Survivorship Care with Emphasis on Symptom Monitoring.

Curr Oncol 2022 Jun 17;29(6):4370-4385. Epub 2022 Jun 17.

Department of Research and Development, Netherlands Comprehensive Cancer Organization (IKNL), 3511 DT Utrecht, The Netherlands.

Electronic patient-reported outcome (ePRO) applications promise great added value for improving symptom management and health-related quality of life. The aim of this narrative review is to describe the collection and use of ePROs for cancer survivorship care, with an emphasis on ePRO-symptom monitoring. It offers many different perspectives from research settings, while current implementation in routine care is ongoing. Read More

View Article and Full-Text PDF

Axillary vascular malformation visualized on mammogram: A case report.

Radiol Case Rep 2022 Sep 15;17(9):2902-2905. Epub 2022 Jun 15.

Integrated Breast Care Centre, All India Institute of Medical Sciences, Rishikesh, 249203, India.

Chest wall lesions can mimic masses on mammograms and can cause diagnostic difficulty in interpretation. Here, we report a case of an axillary and retro-pectoral vascular malformation visualized on mammography in a 67-year-old patient presenting with fullness in the right axilla and right supraclavicular region. Mammography, ultrasonography (US), and computed tomography (CT) angiography of the patient were done to make the final diagnosis. Read More

View Article and Full-Text PDF
September 2022

Regulation of Baby Food Marketing in Thailand: A NetCode analysis.

Public Health Nutr 2022 Jun 23:1-34. Epub 2022 Jun 23.

National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT, Australia.

Objective: To report on the prevalence of different types of breast-milk substitutes (BMS) marketing and the compliance of such marketing with the "Control of Marketing of Infant and Young Child Food Act 2017" (The Act) and the "International Code of Marketing of Breastmilk Substitutes (WHO Code)" in Thailand.

Design: Cross-sectional quantitative study, guided by the WHO/UNICEF NetCode Periodic Assessment Protocol.

Setting: Health facilities and retail outlets in Bangkok, Thai media. Read More

View Article and Full-Text PDF

Breast Cancer Physical Activity Mobile Intervention: Early Findings From a User Experience and Acceptability Mixed Methods Study.

JMIR Form Res 2022 Jun 22;6(6):e32354. Epub 2022 Jun 22.

Adhera Health, Inc, Palo Alto, CA, United States.

Background: Physical activity (PA) is the most well-established lifestyle factor associated with breast cancer (BC) survival. Even women with advanced BC may benefit from moderate PA. However, most BC symptoms and treatment side effects are barriers to PA. Read More

View Article and Full-Text PDF

Sister, Give Me Your Hand: a Qualitative Focus Group Study on Beliefs and Barriers to Mammography Screening in Black Women During the COVID-19 Era.

J Racial Ethn Health Disparities 2022 Jun 22. Epub 2022 Jun 22.

MD Anderson Cancer Center at Cooper, Camden, NJ, USA.

Aims/purpose: To evaluate current day challenges and beliefs about breast cancer screening for Black women in two diverse northeast communities in the midst of the COVID-19 pandemic.

Background: Breast cancer is the second leading cause of cancer-related death in women in the USA. Although Black women are less likely to be diagnosed with breast cancer, they suffer a higher mortality. Read More

View Article and Full-Text PDF

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.

Mod Pathol 2022 Jun 21. Epub 2022 Jun 21.

Lester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. Read More

View Article and Full-Text PDF

Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammograms.

Biomed Phys Eng Express 2022 Jun 21. Epub 2022 Jun 21.

Niigata University Graduate School of Health Sciences, 2-746, Asahimachi-dori, Chuo-ku, Niigata, Niigata, 951-8518, JAPAN.

This study investigates the equivalence or compatibility between U-Net and visual segmentations of fibroglandular tissue regions by mammography experts for calculating the breast density and mean glandular dose (MGD). A total of 703 mediolateral oblique-view mammograms were used for segmentation. Two region types were set as the ground truth (determined visually): (1) one type included only the region where fibroglandular tissue was identifiable (called the 'dense region'); (2) the other type included the region where the fibroglandular tissue may have existed in the past, provided that apparent adipose-only parts, such as the retromammary space, are excluded (the 'diffuse region'). Read More

View Article and Full-Text PDF

A Convolutional Neural Network Based on Ultrasound Images of Primary Breast Masses: Prediction of Lymph-Node Metastasis in Collaboration With Classification of Benign and Malignant Tumors.

Front Physiol 2022 2;13:882648. Epub 2022 Jun 2.

Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

A convolutional neural network (CNN) can perform well in either of two independent tasks [classification and axillary lymph-node metastasis (ALNM) prediction] based on breast ultrasound (US) images. This study is aimed to investigate the feasibility of performing the two tasks simultaneously. We developed a multi-task CNN model based on a self-built dataset containing 5911 breast US images from 2131 patients. Read More

View Article and Full-Text PDF

Data of real-world reference scores for EORTC QLQ-C30 and QLQ-BR23 at baseline in women with early breast cancer and other breast diseases.

Data Brief 2022 Aug 3;43:108347. Epub 2022 Jun 3.

Department of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.

Patient-reported outcomes are information about health status and health-related quality of life collected directly from patients. The data in this publication contain the first assessment of patient-reported outcomes (PROs) from real-life measurements in the breast cancer center at Charité - Universitätsmedizin Berlin between November 2016 and March 2021. At baseline (before the start of treatment), 1727 ambulatory patients with early breast cancer, ductal carcinoma (DCIS), fibroadenoma, and other breast diseases were registered in the digital PRO-system as part of clinical routine. Read More

View Article and Full-Text PDF

Design and implementation of an Internet-Based cancer risk assessment tool: Use over 10 years.

Cancer Med 2022 Jun 19. Epub 2022 Jun 19.

Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Background: Prevention and early intervention can improve survival and quality of life across all cancers. Patient understanding of risk factors and associated actionable lifestyle changes and screening programs is not well understood by clinicians METHODS: An Internet-based tool, Reduce My Risk, was created in 2009 and made available on oncolink.org. Read More

View Article and Full-Text PDF

Systemic Sclerosis-Specific Antibodies: Novel and Classical Biomarkers.

Clin Rev Allergy Immunol 2022 Jun 18. Epub 2022 Jun 18.

Rheumatology and Clinical Immunology Unit, ASST Spedali Civili, piazzale Spedali Civili 1, Brescia, 25123, Italy.

Disease-specific autoantibodies are considered the most important biomarkers for systemic sclerosis (SSc), due to their ability to stratify patients with different severity and prognosis. Anti-nuclear antibodies (ANA), occurring in subjects with isolated Raynuad's phenomenon, are considered the strongest independent predictors of definite SSc and digital microvascular damage, as observed by nailfold videocapillaroscopy. ANA are present in more than 90% of SSc, but ANA negativity does not exclude SSc diagnosis: a little rate of SSc ANA negative exists and shows a distinct subtype of disease, with less vasculopathy, but more frequent lower gastrointestinal involvement and severe disease course. Read More

View Article and Full-Text PDF

Can Contrast-Enhanced Spectral Mammography (CESM) Reduce Benign Breast Biopsy?

Breast J 2022 24;2022:7087408. Epub 2022 Mar 24.

Tan Tock Seng Hospital, 11 Jln Tan Tock Seng, Singapore.

Objectives: To evaluate the potential of contrast-enhanced spectral mammography (CESM) in reducing benign breast biopsy rate, thereby improving resource utilization. To explore its potential as a value-adding modality in the management of BI-RADS 4/5 lesions.

Materials And Methods: This was a prospective study conducted between July 2016 and September 2018. Read More

View Article and Full-Text PDF

Reply to T. Ménard.

JCO Precis Oncol 2022 Jun;6:e2200188

Nahed Jalloul, PhD, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ; Shridar Ganesan, MD, PhD, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, Department of Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ; Judy E. Garber, MD, Division of Cancer Genetics and Prevention, Dana-Farber Cancer Institute, Boston, MA, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; and Hossein Khiabanian, PhD, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ.

View Article and Full-Text PDF

Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations.

Eur Radiol 2022 Jun 15. Epub 2022 Jun 15.

Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.

Objectives: Artificial intelligence (AI) has shown promising results when used on retrospective data from mammographic screening. However, few studies have explored the possible consequences of different strategies for combining AI and radiologists in screen-reading.

Methods: A total of 122,969 digital screening examinations performed between 2009 and 2018 in BreastScreen Norway were retrospectively processed by an AI system, which scored the examinations from 1 to 10; 1 indicated low suspicion of malignancy and 10 high suspicion. Read More

View Article and Full-Text PDF

Comparison of Outcomes for One-View Asymmetries Recalled From Digital Breast Tomosynthesis Versus Full-Field Digital Mammography Screening Examinations.

AJR Am J Roentgenol 2022 Jun 15. Epub 2022 Jun 15.

Johns Hopkins Medicine.

Recall rates are lower for digital breast tomosynthesis (DBT) than full-field digital mammography (FFDM). This difference could have important implications with respect to one-view asymmetries given that missed cancers are often visible on one view. To compare outcomes of one-view asymmetries recalled from DBT versus FFDM screening mammography, and to determine predictors of malignancy among recalled asymmetries. Read More

View Article and Full-Text PDF

Response-based molecular subtyping-emergence of the third generation of breast cancer subtypes.

Cancer Cell 2022 Jun;40(6):592-594

German Breast Group and University of Frankfurt, Frankfurt, Germany.

The therapeutic landscape of breast cancer is becoming increasingly complex. In this issue of Cancer Cell, Wolf et al. present a breast cancer classification scheme that allows for better prediction of treatment response and can be continuously adapted to guide prioritization of new treatments. Read More

View Article and Full-Text PDF

Digital Breast Tomosynthesis and Detection of Interval Invasive and Advanced Breast Cancers.

JAMA 2022 06;327(22):2198-2200

Department of Radiology, Duke University School of Medicine, Durham, North Carolina.

View Article and Full-Text PDF

Association of Screening With Digital Breast Tomosynthesis vs Digital Mammography With Risk of Interval Invasive and Advanced Breast Cancer.

JAMA 2022 06;327(22):2220-2230

Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle.

Importance: Digital breast tomosynthesis (DBT) was developed with the expectation of improving cancer detection in women with dense breasts. Studies are needed to evaluate interval invasive and advanced breast cancer rates, intermediary outcomes related to breast cancer mortality, by breast density and breast cancer risk.

Objective: To evaluate whether DBT screening is associated with a lower likelihood of interval invasive cancer and advanced breast cancer compared with digital mammography by extent of breast density and breast cancer risk. Read More

View Article and Full-Text PDF

Automatic Segmentation of Calcification Areas in Digital Breast Images.

Biomed Res Int 2022 3;2022:2525433. Epub 2022 Jun 3.

Accounting and Financial Management, School of Management Studies, University of Khartoum, Sudan.

In this study, the authors hope to demonstrate that when mammography is combined with intelligent segmentation techniques, it can become more effective in diagnosing breast abnormalities and aiding in the early detection of breast cancer. In conjunction with intelligent segmentation techniques, mammography can be made more effective in diagnosing breast abnormalities and aiding in the early diagnosis of breast cancer, hence increasing its overall effectiveness. The methodology, which includes some concepts of digital imaging and machine learning techniques, will be described in the following section after a review of the literature on breast cancer (categories, prevention involving the environment and lifestyle, diagnosis, and tracking of the disease) has been completed (neural networks and random forests). Read More

View Article and Full-Text PDF

Change in the Use of Fractionation in Radiotherapy Used for Early Breast Cancer at the Start of the COVID-19 Pandemic: A Population-Based Cohort Study of Older Women in England and Wales.

Clin Oncol (R Coll Radiol) 2022 May 31. Epub 2022 May 31.

Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, UK; Clinical Effectiveness Unit, The Royal College of Surgeons of England, London, UK.

Aims: Adjuvant radiotherapy is recommended for most patients with early breast cancer (EBC) receiving breast-conserving surgery and those at moderate/high risk of recurrence treated by mastectomy. During the first wave of COVID-19 in England and Wales, there was rapid dissemination of randomised controlled trial-based evidence showing non-inferiority for five-fraction ultra-hypofractionated radiotherapy (HFRT) regimens compared with standard moderate-HFRT, with guidance recommending the use of five-fraction HFRT for eligible patients. We evaluated the uptake of this recommendation in clinical practice as part of the National Audit of Breast Cancer in Older Patients (NABCOP). Read More

View Article and Full-Text PDF

Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies.

Sci Rep 2022 Jun 11;12(1):9690. Epub 2022 Jun 11.

Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, ON, Canada.

Complete pathological response (pCR) to neoadjuvant chemotherapy (NAC) is a prognostic factor for breast cancer (BC) patients and is correlated with improved survival. However, pCR rates are variable to standard NAC, depending on BC subtype. This study investigates quantitative digital histopathology coupled with machine learning (ML) to predict NAC response a priori. Read More

View Article and Full-Text PDF

Deep learning-based transcription factor activity for stratification of breast cancer patients.

Biochim Biophys Acta Gene Regul Mech 2022 Jun 8;1865(6):194838. Epub 2022 Jun 8.

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China. Electronic address:

Transcription factors directly bind to DNA and regulate the expression of the gene, causing epigenetic modification of the DNA. They often mediate epigenetic parameters of transcriptional and posttranscriptional mechanisms, and their expression activities can be used to characterize genomic aberrations in cancer cell. In this study, the activity profile of transcription factors inferred by VIPER algorithm. Read More

View Article and Full-Text PDF