Article
Radiology, Nuclear Medicine & Medical Imaging
Chunyan Yi, Yuxing Tang, Rushan Ouyang, Yanbo Zhang, Zhenjie Cao, Zhicheng Yang, Shibin Wu, Mei Han, Jing Xiao, Peng Chang, Jie Ma
Summary: The study investigated the value of an artificial intelligence system in assisting radiologists to improve the assessment accuracy of BI-RADS 0 cases in mammograms. The AI system was found to effectively reduce unnecessary follow-ups, decrease benign biopsy rates, and not miss highly malignant tumors.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Huanhuan Liu, Yanhong Chen, Yuzhen Zhang, Lijun Wang, Ran Luo, Haoting Wu, Chenqing Wu, Huiling Zhang, Weixiong Tan, Hongkun Yin, Dengbin Wang
Summary: The combined deep learning model based on full-field digital mammography improves the prediction of malignancy in BI-RADS 4 microcalcifications, assisting junior radiologists to achieve better performance and optimize clinical decision-making.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Thomas Dratsch, Xue Chen, Mohammad Rezazade Mehrizi, Roman Kloeckner, Aline Maehringer-Kunz, Michael Puesken, Bettina Baessler, Stephanie Sauer, David Maintz, Daniel Pinto dos Santos
Summary: This study aims to determine the impact of automation bias on radiologists with different levels of experience when reading mammograms with the aid of an artificial intelligence (AI) system. The study found that both inexperienced and experienced radiologists are prone to automation bias when using AI-based systems for mammography reading.
Article
Chemistry, Analytical
Kuen-Jang Tsai, Mei-Chun Chou, Hao-Ming Li, Shin-Tso Liu, Jung-Hsiu Hsu, Wei-Cheng Yeh, Chao-Ming Hung, Cheng-Yu Yeh, Shaw-Hwa Hwang
Summary: Breast cancer has the highest incidence rate globally, but early-stage treatment is cost effective. Screening mammography is acknowledged as a reliable method for early diagnosis. The Taiwanese government recommends bi-yearly screening for women aged 45-69 without symptoms. To assist radiologists with mammographic interpretation, a deep neural network model was developed and trained using Taiwanese mammograms. This model achieved high accuracy and sensitivity, making it potentially more effective for breast cancer screening in Asian women with dense breasts.
Article
Radiology, Nuclear Medicine & Medical Imaging
Clarisse Florence de Vries, Samantha Colosimo, Moragh Boyle, Gerald Lip, Lesley Anderson, Roger Staff, iCAIRD Radiology Collaboration
Summary: This study surveyed breast screening readers in the UK on their views of incorporating Artificial Intelligence (AI) technology into breast screening mammography. The results showed that readers supported AI as a partial replacement for human readers and preferred a graphical indication of the suspected tumor area as the AI representation option. National guidelines and independent prospective studies were considered crucial evidence prior to implementing AI.
INSIGHTS INTO IMAGING
(2022)
Article
Biology
Zahra Assari, Ali Mahloojifar, Nasrin Ahmadinejad
Summary: This paper presents a novel bimodal GoogLeNet-based CAD system that combines mammographic and sonographic images for solid breast mass classification. The system achieves promising results in terms of various performance metrics and has the potential to improve breast cancer diagnostic performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Raphael Sexauer, Patryk Hejduk, Karol Borkowski, Carlotta Ruppert, Thomas Weikert, Sophie Dellas, Noemi Schmidt
Summary: This study aimed to develop and adapt two deep convolutional neural networks (DCNN) for automatic breast density classification on synthetic 2D tomosynthesis reconstructions. The DCNN showed accurate and observer-independent classification of breast density based on the ACR BI-RADS system.
EUROPEAN RADIOLOGY
(2023)
Review
Engineering, Biomedical
Fei Lin, Hang Sun, Lu Han, Jing Li, Nan Bao, Hong Li, Jing Chen, Shi Zhou, Tao Yu
Summary: An intelligent BI-RADS grading prediction method was proposed in this study, which extracted features and employed a two-layer classifier integration for fine grading prediction, achieving high AUC values on both the testing set and DDSM dataset, significantly outperforming doctors' diagnosis.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2022)
Article
Multidisciplinary Sciences
Mingnan Lin, Size Wu
Summary: The purpose of this study was to investigate the positive predictive value of ultrasound classification of non-mass breast lesions (NMLs) following the breast imaging reporting and data system (BI-RADS), and to enhance understanding of NMLs. The results showed that stratifying the malignancy risk of breast NMLs using the BI-RADS has the potential to improve sensitivity and positive predictive value, but malignant NMLs are underestimated in terms of malignancy likelihood, while benign NMLs are overestimated. The solution may be to separate NMLs from breast masses and use different malignancy risk stratification protocols.
Article
Radiology, Nuclear Medicine & Medical Imaging
Gisella Gennaro, Letizia Povolo, Sara Del Genio, Lina Ciampani, Chiara Fasoli, Paolo Carlevaris, Maria Petrioli, Tiziana Masiero, Federico Maggetto, Francesca Caumo
Summary: This study aims to improve the individual performance of breast radiographers by using automated software to assess the correctness of breast positioning and compression. The results showed that active use of the software tool significantly increased the quality of breast positioning and compression, indicating the potential to improve screening outcomes.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Xiaocui Rong, Yihe Kang, Jing Xue, Pengyin Han, Zhigang Li, Guang Yang, Gaofeng Shi
Summary: This study investigated the diagnostic performance of contrast-enhanced mammography (CEM) combined with the Kaiser score (KS) in digital breast tomosynthesis (DBT) BI-RADS 4A lesions, aiming to reduce unnecessary breast biopsies. The results showed that the combination of CEM and KS had a higher accuracy and specificity in diagnosis.
EUROPEAN RADIOLOGY
(2022)
Article
Medicine, General & Internal
Rania Mostafa Hassan, Yassir Edrees Almalki, Mohammad Abd Alkhalik Basha, Sharifa Khalid Alduraibi, Mervat Aboualkheir, Ziyad A. Almushayti, Asim S. Aldhilan, Sameh Abdelaziz Aly, Asmaa A. Alshamy
Summary: This study aimed to evaluate the impact of combining digital mammography (DM) with digital breast tomosynthesis (DBT) on the BI-RADS categorization of equivocal breast lesions. The results showed that compared to DM, DBT can improve the diagnostic accuracy of breast lesions and decrease the number of lesions classified as BI-RADS 4 and 3.
Review
Radiology, Nuclear Medicine & Medical Imaging
Constance De Margerie-Mellon, Jean-Baptiste Debry, Axelle Dupont, Caroline Cuvier, Sylvie Giacchetti, Luis Teixeira, Marc Espie, Cedric de Bazelaire
Summary: There is only fair agreement between community practices and MTB reviews for BI-RADS classification of nonpalpable breast lesions. However, MTB review improves diagnostic performances of breast imaging and patient management by identifying additional high-risk and malignant lesions compared to community practices.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Ziting Xu, Yue Lin, Jiekun Huo, Yang Gao, Jiayin Lu, Yu Liang, Lian Li, Zhouyue Jiang, Lingli Du, Ting Lang, Ge Wen, Yingjia Li
Summary: Developing a bimodal nomogram can reduce unnecessary breast biopsies, improve diagnostic accuracy for breast cancer, and minimize missed diagnoses.
EUROPEAN RADIOLOGY
(2023)
Article
Medicine, General & Internal
Kristina Klaric, Andrej Sribar, Anuska Budisavljevic, Loredana Labinac, Petra Valkovic Zujic
Summary: This study aimed to evaluate contrast-enhanced mammography (CEM) and compare breast lesions on CEM and breast magnetic resonance imaging (MRI) using 5 features. The study found no significant differences in KS results between CEM and breast MRI. The KS flowchart is useful for evaluating breast lesions on CEM.
Article
Biology
Marzieh K. Golmakani, Rebecca A. Hubbard, Diana L. Miglioretti
Summary: Screening tests are important for early disease detection, but may lead to negative consequences such as false positive results. Research suggests that the cumulative risk of multiple false positive results during multiple rounds of screening is high, potentially impacting patient participation.
Article
Oncology
Shailesh Advani, Linn Abraham, Diana S. M. Buist, Karla Kerlikowske, Diana L. Miglioretti, Brian L. Sprague, Louise M. Henderson, Tracy Onega, John T. Schousboe, Joshua Demb, Dongyu Zhang, Louise C. Walter, Christoph Lee, Dejana Braithwaite, Ellen S. O'Meara
Summary: This study investigated the impact of age and comorbidity on biopsy rates and findings among older women. The results showed that biopsy rates decreased with age and increased with comorbidity. Core and surgical biopsy rates only increased in the age group of 66-74. The yield of invasive breast cancer increased with age for all biopsy types, irrespective of comorbidity.
JOURNAL OF GERIATRIC ONCOLOGY
(2022)
Article
Public, Environmental & Occupational Health
Jose Gomez-Castro, Diego Cerecero-Garcia, Heleen Vermandere, Sergio Bautista-Arredondo
Summary: This study examined the impact of COVID-19 lockdown on sexual behavior and PrEP use among MSM in Mexico. The results showed a decrease in sexual partners and PrEP use during the lockdown. Younger age, lower perceived risk of COVID-19, and condom use in the last sexual encounter were associated with a higher likelihood of continuing PrEP use.
Review
Health Policy & Services
M. A. Colchero, R. Gomez, S. Bautista-Arredondo
Summary: The systematic review of impact evaluations of Seguro Popular (SP) found mixed evidence on its effectiveness in terms of financial protection, healthcare utilization, morbidity, and mortality. Roughly half of the outcomes studied showed positive effects, while the rest showed null results.
HEALTH RESEARCH POLICY AND SYSTEMS
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Thao-Quyen H. Ho, Michael C. S. Bissell, Christoph I. Lee, Janie M. Lee, Brian L. Sprague, Anna N. A. Tosteson, Karen J. Wernli, Louise M. Henderson, Karla Kerlikowske, Diana L. Miglioretti
Summary: The purpose of this study was to develop a prioritization strategy for scheduling immediate screening mammographic interpretation and possible diagnostic evaluation. Classification trees were used to identify combinations of clinical history, screening modality, and facility characteristics that grouped screening mammograms by recall rate. The results showed that prioritizing women with baseline mammograms or >5 years since prior mammogram for immediate interpretation and possible diagnostic evaluation could considerably reduce the number of women needing to return for diagnostic imaging at another visit.
JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY
(2023)
Article
Oncology
Yu-Ru Su, Diana S. M. Buist, Janie M. Lee, Laura Ichikawa, Diana L. Miglioretti, Erin J. Aiello Bowles, Karen J. Wernli, Karla Kerlikowske, Anna Tosteson, Kathryn P. Lowry, Louise M. Henderson, Brian L. Sprague, Rebecca A. Hubbard
Summary: This study compared the predictive performance of statistical and machine learning models in predicting surveillance mammography outcomes in breast cancer patients, and found that regularized regression models performed the best.
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
(2023)
Article
Immunology
Valdilea G. Veloso, Carlos F. Caceres, Brenda Hoagland, Ronaldo Moreira, Hamid Vega-Ramirez, Kelika A. Konda, Iuri C. Leite, Sergio Bautista-Arredondo, Marcus Vinicius de Lacerda, Jose Valdez Madruga, Alessandro Farias, Josue N. Lima, Ronaldo Zonta, Lilian Lauria, Cesar Vidal Osco Tamayo, Hector Javier Salvatierra Flores, Yovanna Margot Cabrera Santa Cruz, Ricardo Martin Moreno Aguayo, Marcelo Cunha, Julio Moreira, Alessandra Ramos Makkeda, Steven Diaz, Juan Guanira, Heleen Vermandere, Marcos Benedetti, Heather L. Ingold, M. Cristina Pimenta, Thiago S. Torres, Beatriz Grinsztejn
Summary: This study assessed the feasibility of same-day oral PrEP delivery in Brazil, Mexico, and Peru. The results showed that gay, bisexual, and other cisgender men who have sex with men (MSM) and transgender women have the highest HIV burden in Latin America, but PrEP implementation is inadequate. Social and structural determinants of HIV vulnerability need to be addressed to achieve the benefits of PrEP.
Article
Health Care Sciences & Services
Marjorie Opuni, Jorge Eduardo Sanchez-Morales, Jose Luis Figueroa, Andrea Salas-Ortiz, Louis Masankha Banda, Alice Olawo, Spy Munthali, Julius Korir, Meghan DiCarlo, Sergio Bautista-Arredondo
Summary: This study estimated the unit costs of HIV services delivered to key populations in the LINKAGES program in Kenya and Malawi. The results showed that when considering non-clinical services and program management costs, the costs of HIV services for key populations can be significantly higher.
BMC HEALTH SERVICES RESEARCH
(2023)
Article
Oncology
Brian L. Sprague, Laura Ichikawa, Joanna Eavey, Kathryn P. Lowry, Garth Rauscher, Ellen S. O'Meara, Diana L. Miglioretti, Shuai Chen, Janie M. Lee, Natasha K. Stout, Jeanne S. Mandelblatt, Nila Alsheik, Sally D. Herschorn, Hannah Perry, Donald L. Weaver, Karla Kerlikowske
Summary: There are no consensus guidelines for supplemental breast cancer screening with whole-breast ultrasound. This study evaluated the risk of mammography screening failures among women undergoing ultrasound screening compared to mammography alone. The results showed that a clinically significant proportion of women undergoing mammography alone were at high mammography screening failure risk.
Article
Public, Environmental & Occupational Health
Charlotte C. Gard, Jane Lange, Diana L. Miglioretti, Ellen S. O'Meara, Christoph Lee, Ruth Etzioni
Summary: This study examines the risk of breast cancer onset based on race/ethnicity and finds that Asian and Hispanic women have lower risks than non-Hispanic Black and White women.
JOURNAL OF MEDICAL SCREENING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Brian L. Sprague, Rebecca Yates Coley, Kathryn P. Lowry, Karla Kerlikowske, Louise M. Henderson, Yu-Ru Su, Christoph I. Lee, Tracy Onega, Erin J. A. Bowles, Sally D. Herschorn, Roberta M. diFlorio-Alexander, Diana L. Miglioretti
Summary: This study aimed to evaluate breast cancer screening outcomes with digital breast tomosynthesis (DBT) versus digital mammography (DM) on successive screening rounds. The study found that DBT had lower recall rates and higher cancer detection rates compared with DM. Additionally, DBT had significantly higher cancer detection rates than DM in the third round and above.
Article
Radiology, Nuclear Medicine & Medical Imaging
Christoph I. Lee, Linn Abraham, Diana L. Miglioretti, Tracy Onega, Karla Kerlikowske, Janie M. Lee, Brian L. Sprague, Anna N. A. Tosteson, Garth H. Rauscher, Erin J. A. Bowles, Roberta M. diFlorio-Alexander, Louise M. Henderson
Summary: This study aimed to establish performance benchmarks for digital breast tomosynthesis (DBT) screening and evaluate performance trends over time in U.S. community practice. The results showed that most radiologists achieved acceptable performance ranges for screening performance metrics with DBT.
Article
Radiology, Nuclear Medicine & Medical Imaging
Vignesh A. Arasu, Laurel A. Habel, Ninah S. Achacoso, Diana S. M. Buist, Jason B. Cord, Laura J. Esserman, Nola M. Hylton, M. Maria Glymour, John Kornak, Lawrence H. Kushi, Donald A. Lewis, Vincent X. Liu, Caitlin M. Lydon, Diana L. Miglioretti, Daniel A. Navarro, Albert Pu, Li Shen, Weiva Sieh, Hyo-Chun Yoon, Catherine Lee
Summary: By comparing selected mammography artificial intelligence algorithms and the Breast Cancer Surveillance Consortium risk model, it was found that AI algorithms performed better in predicting 5-year risk, and combining the two could further improve prediction accuracy.
Article
Medicine, General & Internal
Brian L. Sprague, Shuai Chen, Diana L. Miglioretti, Charlotte C. Gard, Jeffrey A. Tice, Rebecca A. Hubbard, Erin J. Aiello Bowles, Peter A. Kaufman, Karla Kerlikowske
Summary: This study developed a 6-year risk prediction model for screen-detected DCIS based on mammography screening interval and women's risk factors. The findings showed that annual mammography screening was associated with a higher risk of screen-detected DCIS compared to biennial or triennial screening within a 6-year period.
Article
Clinical Neurology
Ronald P. Lesser, W. R. S. Webber, Diana L. Miglioretti
Summary: We previously found that cognitive tasks can affect the efficacy of afterdischarge termination in patients undergoing cortical stimulation, and that diffuse wavelet cross-coherence changes on electrocorticography are associated with termination efficacy. In this study, we report wavelet cross-coherence findings during different time segments of trials during which afterdischarges ended.
CLINICAL NEUROPHYSIOLOGY
(2023)