In breast imaging, there is an unrelenting increase in the demand for breast imaging services, partly explained by continuous expanding imaging indications in breast diagnosis and treatment. As the human workforce providing these services is not growing at the same rate, the implementation of artificial intelligence (AI) in breast imaging has gained significant momentum to maximize workflow efficiency and increase productivity while concurrently improving diagnostic accuracy and patient outcomes. Thus far, the implementation of AI in breast imaging is at the most advanced stage with mammography and digital breast tomosynthesis techniques, followed by ultrasound, whereas the implementation of AI in breast magnetic resonance imaging (MRI) is not moving along as rapidly due to the complexity of MRI examinations and fewer available dataset. Nevertheless, there is persisting interest in AI-enhanced breast MRI applications, even as the use of and indications of breast MRI continue to expand. This review presents an overview of the basic concepts of AI imaging analysis and subsequently reviews the use cases for AI-enhanced MRI interpretation, that is, breast MRI triaging and lesion detection, lesion classification, prediction of treatment response, risk assessment, and image quality. Finally, it provides an outlook on the barriers and facilitators for the adoption of AI in breast MRI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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http://dx.doi.org/10.1002/jmri.29358 | DOI Listing |
Acad Radiol
January 2025
Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve. Campus de Gambelas, Edifício 2, 8005-139 Faro, Portugal (A.F.G., D.J., C.T., D.J., A.M., H.L.); Algarve Biomedical Center Research Institute (ABC-RI), Universidade do Algarve. Campus de Gambelas, Edifício 2, 8005-139 Faro, Portugal (A.M., E.P., H.L.).
Objective: The purpose of this systematic review and meta-analysis was comparing diagnostic performance of ultrasound elastography (UE), strain UE and shear wave elastography (SWE), with magnetic resonance imaging (MRI) in differentiating benign and malignant breast lesions.
Methods: Literature search of MEDLINE, Web of Science, SCOPUS and Google Scholar was performed in June 2023. Included studies used Breast Imaging Reporting and Data System (BI-RADS) and histopathology as reference standard.
JCO Clin Cancer Inform
January 2025
SimBioSys Inc, Chicago, IL.
Purpose: Perfusion modeling presents significant opportunities for imaging biomarker development in breast cancer but has historically been held back by the need for data beyond the clinical standard of care (SoC) and uncertainty in the interpretability of results. We aimed to design a perfusion model applicable to breast cancer SoC dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) series with results stable to low temporal resolution imaging, comparable with published results using full-resolution DCE-MRI, and correlative with orthogonal imaging modalities indicative of biophysical markers.
Methods: Subsampled high-temporal-resolution DCE-MRI series were run through our perfusion model and resulting fits were compared for consistency.
JAMA Netw Open
January 2025
City of Hope National Medical Center, Duarte, California.
Importance: Enhanced breast cancer screening with magnetic resonance imaging (MRI) is recommended to women with elevated risk of breast cancer, yet uptake of screening remains unclear after genetic testing.
Objective: To evaluate uptake of MRI after genetic results disclosure and counseling.
Design, Setting, And Participants: This multicenter cohort study was conducted at the University of Southern California Norris Cancer Hospital, the Los Angeles General Medical Center, and the Stanford University Cancer Institute.
Neurology
January 2025
Department of Neurosurgery, Lenox Hill Hospital, Zucker School of Medicine at Hofstra/Northwell, New York, NY; and.
Background And Objectives: This systematic review aims to synthesize the current literature on the association between chemotherapy (CTX) and chemotherapy-related cognitive impairment (CRCI) with functional and structural brain alterations in patients with noncentral nervous system cancers.
Methods: A comprehensive search of the PubMed/MEDLINE, Web of Science, and Embase databases was conducted, and results were reported following preferred reporting items for systematic review and meta-analyses guidelines. Data on study design, comparison cohort characteristics, patient demographics, cancer type, CTX agents, neuroimaging methods, structural and functional connectivity (FC) changes, and cognitive/psychological assessments in adult patients were extracted and reported.
Brain Imaging Behav
January 2025
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Physical exercise is a promising intervention to improve brain white matter integrity. In the PAM study, exercise intervention effects on white matter integrity were investigated in breast cancer patients. Chemotherapy-treated breast cancer patients with cognitive problems were randomized 2-4 years post-diagnosis to an exercise (n = 91) or control group (n = 90).
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