Articles tagged with Mammography
A USC-led team has found indications for an early breast cancer detection method using high-definition liquid biopsies. The test detected multiple cancer biomarkers, including 'oncosomes,' in the blood samples of most early-stage breast cancer patients.
A study found that trained radiographers perform as well as radiologists in key areas of double reading mammograms, improving cancer detection rates. The results suggest that focused training and experience are key factors in reader performance, not just medical degree or broad radiology education.
Researchers found lower stages of breast cancer in women aged 40-49 compared to those aged 50-59, with a significant decrease in stage 4 cases. This suggests that early detection through regular mammograms can lead to better health outcomes and survival rates.
A study published in JAMA Oncology found significant disparities in breast biopsy delays among non-white women, with Black women experiencing the longest delays. Structural racism within healthcare facilities and screening site-specific factors contribute to these disparities.
A study of 45,000 women found significant racial and ethnic disparities in the time it takes to receive a biopsy after an abnormal screening mammogram result. Factors such as individual characteristics, neighborhood socioeconomic status, and healthcare access were also associated with delays in biopsies.
A prospective study compared CEM and MRI for NAT response assessment in patients with breast cancer. CEM yielded comparable assessments of lesion size and RECIST categories as MRI, but with lower sensitivity for pathologic complete response. Delayed CEM acquisition detected residual ductal carcinoma in situ (DCIS).
A study published in Cancer Epidemiology, Biomarkers & Prevention found that diagnostic mammogram accuracy differed across racial and ethnic groups. Asian/Pacific Islander women were more likely to receive false-positive reports, while non-Hispanic Black women were more likely to receive false-negative reports.
A multi-institutional study found that diagnostic mammography outcomes vary across racial and ethnic groups, with higher accuracy in non-Hispanic white women and lower accuracy in Hispanic women. The study suggests that imaging facility and concurrent use of breast ultrasound or MRI may contribute to some disparities.
A new study published in JAMA found that digital breast tomosynthesis (DBT) may reduce the chance of an advanced cancer diagnosis for women with the densest breasts and highest risk, but not all women. DBT had additional advantages for women with specific risk profiles, including a higher rate of detection of small invasive breast canc...
A study published in AJR found that COVID-19 mRNA vaccination-induced axillary lymphadenopathy resolves after a mean of 97 days. Longer resolution times were observed with Moderna vaccination, receipt of second doses, and thicker cortical thickness at presentation.
The QUSTom project aims to develop a new medical imaging modality using ultrasound and supercomputing, improving breast cancer diagnosis and potentially replacing mammograms. The technology will offer superior image quality and better tumor monitoring, while being completely safe for patients.
Dr. Gary J. Whitman, MD of the University of Texas MD Anderson Cancer Center, has been appointed as the 122nd President of the American Roentgen Ray Society (ARRS). He succeeds Jonathan Kruskal, MD, PhD, and will serve for the next year.
A new study suggests that while breast density knowledge may be increasing due to existing state laws, there is still room for improvement. The study found that most women with non-dense breasts did not correctly know their own density, and that lower education was associated with a lower chance of accurately knowing one's own density.
Researchers found a steady decline in annual mammography use by breast cancer survivors between 2009 and 2016, with the largest decrease seen among younger patients. The study highlights the importance of reinforcing the significance of annual mammograms for breast cancer survivors.
Researchers have discovered 23 proteins in breast milk that could indicate breast cancer, paving the way for a potential blood test. The study's findings, if confirmed, may enable earlier diagnosis and improve survival rates.
A study published in JAMA Network Open found that half of all women will experience at least one false positive mammogram over a decade of annual breast cancer screening with 3D mammography. The risk of false positives is lower for women screened every other year, and non-dense breasts also show a lower false positive risk.
New research suggests that routine mammograms can provide key insights into a woman's risk of cardiovascular disease. The study found that detection of breast arterial calcifications on mammograms was associated with a higher risk of heart disease and stroke in postmenopausal women.
The Cancer Prevention & Research Institute of Texas has awarded a grant extension to Dr. Rakhshanda Rahman, allowing her to provide no-cost mammograms and Pap smears to underinsured and uninsured women in the Permian Basin. The program aims to address high cervical cancer incidence and mortality rates in West Texas.
A modeling study suggests that breast cancer overdiagnosis may occur in about 15% of screen-detected cases, rather than the estimated 30%. This could spare around 25,000 women unnecessary treatment. Researchers used data from the Breast Cancer Surveillance Consortium to estimate the rate of overdiagnosis.
A new editorial cautions against the unchecked use of AI in mammography due to past errors like false-positive tests and over-treatment. The authors propose safeguards to ensure improved patient outcomes, including tying Medicare reimbursement to performance metrics.
New studies from Michigan Medicine researchers aim to remove financial barriers for patients who receive abnormal test results, enabling them to complete the diagnostic process. The findings suggest that removing cost barriers could save lives by increasing screening uptake, particularly among women and underserved populations.
A retrospective study found that the upgrade rate of architectural distortion on digital breast tomosynthesis (DBT) to malignancy was 10.2% for radial scars without atypia and 28.2% for those with atypia. Imaging surveillance is considered an alternative to surgery for these cases.
Researchers at Duke University developed an artificial intelligence platform that analyzes potentially cancerous lesions in mammography scans. The algorithm is interpretable, showing physicians how it came to its conclusions, making it more trustworthy and useful for training students and aiding physicians in sparsely populated regions.
A prospective study found that ultrasound alone adequately completed the diagnostic evaluation of 71.2% of noncalcified lesions, diagnosed 92.1% of cancers, and yielded a sensitivity of 94.9%. Radiologists should consider performing ultrasound first for digital breast tomosynthesis-recalled noncalcified masses.
A study found that rural women are less likely to get screened for colorectal cancer compared to urban counterparts, despite similar breast cancer screening rates. The disparity may be attributed to limited access to testing and financial constraints, highlighting the need for targeted public health interventions.
Researchers simulated an attack that falsified mammogram images, fooling both AI breast cancer diagnosis models and human radiologist experts. The study highlights the need to develop ways to make AI models more robust to adversarial attacks, which could lead to incorrect cancer diagnoses.
A study found that racial disparities in mammography screening worsened after COVID-19 closures, with non-white patients facing reduced access to facilities. Early interventions aimed at expanding access to these facilities helped to recover late recovery volumes for patients of races other than white.
A new diagnostic tool for breast cancer uses a low-voltage electrical current to detect changes in lymphatic interstitial fluid, showing 70% effectiveness in predicting cancer presence. The device can be used repeatedly on women of any age, providing an additional diagnostic option for younger patients and those with dense breast tissue.
A modeling study found that annual mammography screening beyond age 75 may provide little to no benefit in terms of lives saved, while increasing costs and potential harms from overdiagnosis. Biennial screening up to age 80 is more cost-effective but yields a small number of deaths averted.
Women with dense breast tissue are at increased risk of developing breast cancer, which can be masked by mammograms. Mayo Clinic expert Suneela Vegunta recommends supplemental screening to diagnose additional cancers; however, consensus-based guidelines and randomized controlled studies are needed.
Breast cancer deaths can be reduced by 57% in Black women if they start mammography screening every other year at age 40. This approach is consistent with the US Preventive Services Task Force's guidance for biennial mammography.
A Loma Linda University Health research study found that mammogram cancellations increased during the early months of the COVID-19 pandemic before decreasing to pre-pandemic levels. The study's findings could help breast cancer surgeons prepare for a potential surge of patients presenting with more advanced stages of breast cancer.
A new AI system developed by NYU and NYU Abu Dhabi researchers achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. The system helps decrease false-positive findings and requested biopsies while maintaining sensitivity.
Individualized breast cancer risk estimates led to a significant increase in annual mammography rates among women at high risk. The study found that nearly all Hispanic or Black women who received personalized risk assessments used mammography more frequently, with rates rising from 37% to 51%.
A new paradigm in breast cancer screening has been established with immediate-read screenings during the pandemic. This approach reduces racial and ethnic disparities in same-day diagnostic imaging, while speeding up diagnoses.
A single-center retrospective study found that AI-CAD reduced recall rates and improved accuracy compared to digital mammography (DM) and DBT. The study showed lower recall rates and higher accuracy for DM with AI-CAD, indicating a practical addition to lowering false-positive findings.
A national study found a strong rebound in breast cancer screening rates despite COVID-19 pandemic challenges, but significant disparities and missed appointments persist. The study highlights the need for targeted interventions to overcome barriers to healthcare utilization during the pandemic.
Researchers recommend a risk-based algorithm that maximizes cancer detection by considering clinical indication, breast symptoms, and age. The approach successfully detects high-risk individuals, accounting for 55% of cancers despite limited mammograms.
Screenings for breast cancer and colon cancer dropped dramatically during the pandemic but returned to near-normal levels by July 2020. Researchers analyzed insurance claims from over 6 million Americans and found that mammography rates among women aged 45-64 declined by 96% in March and April 2020.
Nearly 500 breast cancer centers in US have different starting ages for mammography, with some recommending 40-50 years old and others 35-39 years old. The study highlights the need for standardization to ensure optimal screening guidelines.
A study of over half a million Swedish women found that attending consecutive mammography screens reduces fatal breast cancer incidence by 50% and mortality by 22-33%. Repeated attendance confers greater protection than single-screen attendance, highlighting the importance of regular screening.
A large study of over half a million women found that skipping even one scheduled mammography screening before a breast cancer diagnosis significantly increases the risk of dying from the cancer. Regular participation in all scheduled screens confers the greatest reduction in risk of dying from breast cancer.
Research reveals women of minority races and ethnicities with less education and income have lower access to 3D mammography, a technology that improves breast cancer detection. Despite FDA approval for over a decade, the technology's benefits are not equally shared across sub-populations.
A mammography screening strategy based on a baseline breast density measure at age 40 is the most effective and cost-effective way to reduce breast cancer mortality. The study suggests that this approach can lead to a significant reduction in breast cancer mortality, but also increases the number of mammograms performed and false posit...
A nationwide panel developed guidelines recommending discontinuing routine mammograms for survivors with a life expectancy under five years. Guidelines also suggest stopping screening for those with a 5-10-year life expectancy, and continuing annual or biennial mammography when life expectancy exceeds 10 years.
A new machine learning algorithm named Mirai estimates breast cancer risk in women more accurately than current models, identifying 41.5% of patients at risk within 5 years. The model was effective across various races and ethnicities, supporting its potential to inform screening guidelines for diverse populations.
A pilot study at Massachusetts General Hospital found that inpatient mammograms can be effective in increasing breast cancer screening rates among low-income women. The study identified 21 women who were eligible for an inpatient mammogram and successfully completed the test, with 35% having never had a mammogram before.
A new study suggests that Dense Breast Notifications (DBNs) have achieved partial success in informing women about their breast density, with higher rates of notification and discussions with providers in states with mandated DBN laws. However, the study also found disparities in knowledge and awareness among women of different race/et...
Researchers developed two new mammogram-based measures of risk, combining them to predict breast cancer risk more effectively than known genetic and breast density factors. The new measures could improve screening, reduce mortality, and make it less stressful for women.
A new study by MIT scholars suggests that mammogram screening may be more effective for targeted testing, rather than age-based recommendations. Women who start getting mammograms at age 40 are found to be healthier and less likely to have cancer, making targeting higher-risk groups a potential solution.
A study published in Radiology found that digital breast tomosynthesis (DBT) improved cancer detection and reduced false negative rates compared to digital mammography. DBT also showed advantages in imaging women with dense breasts, leading to lower recall rates and more effective cancer screening.
A new deep learning model predicts breast cancer risk with greater accuracy, leveraging subtle imaging biomarkers in mammograms. The model outperforms traditional risk assessment models, providing more accurate and cost-effective care for patients.
A study published in Radiology found that digital breast tomosynthesis (DBT) with synthetic mammography improved cancer detection rates compared to traditional digital mammography. The technique reduced radiation exposure and detected a higher proportion of early-stage cancers, particularly among women with dense breasts.
A new 'fast' MRI test has been shown to detect breast cancers that 3-D mammograms may miss in women with dense breasts. The test, which is an abbreviated version of traditional breast MRI, detected 27 cancers per 1,000 women screened.
A study aims to identify geographic and racial disparities in mammography screening rates among Black and Hispanic women. The research will inform targeted interventions to improve access to screening and reduce mortality from breast cancer.
Spanish-speaking women are less likely to receive screening mammograms due to language barriers. Women with limited English proficiency had 27% lower rates of mammogram screenings, according to the study. This disparity affects approximately 450,000 eligible women in the US.
Researchers at Karolinska Institutet have found that one AI algorithm is as accurate as the average radiologist in identifying breast cancer from mammograms. The study compared three AI algorithms and showed significant differences between them, with one outperforming others and rivaling human detection accuracy.
A new study found that digital breast tomosynthesis (DBT) outperforms digital mammography in detecting cancers and reducing recalls. However, women with extremely dense breasts do not experience the same level of benefit from DBT. Most women with dense breasts saw an increase in cancer detection rates with DBT.
A systematic review and meta-analysis found that digital mammography did not improve health outcomes for women screened with the technology. The study analyzed 24 studies and found a small increase in cancer detection rates, but this was largely due to more detection of non-invasive DCIS and no significant difference in invasive cancer...
A new study published in Radiology found that women with probably benign breast lesions (BI-RADS 3) should have six-month follow-up imaging surveillance. The study showed that 1.9% of these women were diagnosed with cancer within six months, with a higher risk of malignancy than those downgraded to BI-RADS 1 or 2.