Automated Breast Density Assessment in MRI using Deep Learning and Radiomics: Strategies for Reducing Inter-observer Variability

Review Medicine, General & Internal

Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions

Clayton R. Taylor et al.

Summary: Efforts to use computers for breast cancer detection have been made for over 20 years, but traditional computer-aided detection has shown minimal improvement. However, recent advancements in AI and machine learning have started to yield better results. While there are over 20 FDA-approved AI applications for breast imaging, their adoption and usage are still low. Breast imaging offers various opportunities and challenges for AI development, including decision support and risk assessment, among others.

DIAGNOSTICS (2023)

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Article Health Care Sciences & Services

Breast Density Evaluation According to BI-RADS 5th Edition on Digital Breast Tomosynthesis: AI Automated Assessment Versus Human Visual Assessment

Daniele Ugo Tari et al.

Summary: This study aimed to compare the concordance of automatic breast density classification with visual assessment. The results showed that the categorization proposed by the Quantra software had good agreement with radiological evaluations, although it did not completely reflect the visual assessment. Therefore, clinical decisions regarding supplemental screening should be based on the radiologist's subjective judgement of masking effect rather than solely relying on the data produced by the Quantra software.

JOURNAL OF PERSONALIZED MEDICINE (2023)

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Article Radiology, Nuclear Medicine & Medical Imaging

Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks

Raphael Sexauer et al.

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)

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Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

Anna Landsmann et al.

Summary: This study investigated the use of texture analysis features to distinguish breast density in spiral photon-counting breast CT images, highlighting skewness and grey-level nonuniformity as strongly correlated with breast density. Multinomial logistic regression analysis showed an overall accuracy of 80% for breast density assessment, suggesting texture analysis of PC-BCT images as a potential observer-independent tool for breast density evaluation.

EUROPEAN RADIOLOGY EXPERIMENTAL (2022)

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Review Oncology

Harnessing multimodal data integration to advance precision oncology

Kevin M. Boehm et al.

Summary: Advancements in quantitative biomarker development have accelerated insights for cancer patients, but integrated approaches across modalities remain underdeveloped. To succeed, efforts in data engineering, computational methods for heterogeneous data analysis, and instantiation of synergistic data models in biomedical research are necessary.

NATURE REVIEWS CANCER (2022)

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Review Radiology, Nuclear Medicine & Medical Imaging

Update on Breast Density, Risk Estimation, and Supplemental Screening

Stamatia Destounis et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2020)

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Automated Breast Density Assessment in MRI using Deep Learning and Radiomics: Strategies for Reducing Inter-observer Variability

相关参考文献

Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions

Breast Density Evaluation According to BI-RADS 5th Edition on Digital Breast Tomosynthesis: AI Automated Assessment Versus Human Visual Assessment

Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

Harnessing multimodal data integration to advance precision oncology

Update on Breast Density, Risk Estimation, and Supplemental Screening

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