Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature

Abstract This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CE...

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Main Authors: Akila Anandarajah, Yongzhen Chen, Graham A. Colditz, Angela Hardi, Carolyn Stoll, Shu Jiang
Format: Article
Language:English
Published: BMC 2022-12-01
Series:Breast Cancer Research
Subjects:
Online Access:https://doi.org/10.1186/s13058-022-01600-5
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author Akila Anandarajah
Yongzhen Chen
Graham A. Colditz
Angela Hardi
Carolyn Stoll
Shu Jiang
author_facet Akila Anandarajah
Yongzhen Chen
Graham A. Colditz
Angela Hardi
Carolyn Stoll
Shu Jiang
author_sort Akila Anandarajah
collection DOAJ
description Abstract This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021 to extract published articles in English describing the relationship of parenchymal texture features with the risk of breast cancer. Twenty-eight articles published since 2016 were included in the final review. The identification of parenchymal texture features varied from using a predefined list to machine-driven identification. A reduction in the number of features chosen for subsequent analysis in relation to cancer incidence then varied across statistical approaches and machine learning methods. The variation in approach and number of features identified for inclusion in analysis precluded generating a quantitative summary or meta-analysis of the value of these features to improve predicting risk of future breast cancers. This updated overview of the state of the art revealed research gaps; based on these, we provide recommendations for future studies using parenchymal features for mammogram images to make use of accumulating image data, and external validation of prediction models that extend to 5 and 10 years to guide clinical risk management. Following these recommendations could enhance the applicability of models, helping improve risk classification and risk prediction for women to tailor screening and prevention strategies to the level of risk.
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spelling doaj.art-d0dd23eb3f1749b6bc2d06c5fcf874122023-01-01T12:30:35ZengBMCBreast Cancer Research1465-542X2022-12-0124111810.1186/s13058-022-01600-5Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literatureAkila Anandarajah0Yongzhen Chen1Graham A. Colditz2Angela Hardi3Carolyn Stoll4Shu Jiang5Division of Public Health Sciences, Department of Surgery, Washington University School of MedicineSaint Louis University School of MedicineDivision of Public Health Sciences, Department of Surgery, Washington University School of MedicineBernard Becker Medical Library, Washington University School of MedicineDivision of Public Health Sciences, Department of Surgery, Washington University School of MedicineDivision of Public Health Sciences, Department of Surgery, Washington University School of MedicineAbstract This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021 to extract published articles in English describing the relationship of parenchymal texture features with the risk of breast cancer. Twenty-eight articles published since 2016 were included in the final review. The identification of parenchymal texture features varied from using a predefined list to machine-driven identification. A reduction in the number of features chosen for subsequent analysis in relation to cancer incidence then varied across statistical approaches and machine learning methods. The variation in approach and number of features identified for inclusion in analysis precluded generating a quantitative summary or meta-analysis of the value of these features to improve predicting risk of future breast cancers. This updated overview of the state of the art revealed research gaps; based on these, we provide recommendations for future studies using parenchymal features for mammogram images to make use of accumulating image data, and external validation of prediction models that extend to 5 and 10 years to guide clinical risk management. Following these recommendations could enhance the applicability of models, helping improve risk classification and risk prediction for women to tailor screening and prevention strategies to the level of risk.https://doi.org/10.1186/s13058-022-01600-5Breast densityMammographyParenchymal patternsRisk predictionTexture
spellingShingle Akila Anandarajah
Yongzhen Chen
Graham A. Colditz
Angela Hardi
Carolyn Stoll
Shu Jiang
Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature
Breast Cancer Research
Breast density
Mammography
Parenchymal patterns
Risk prediction
Texture
title Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature
title_full Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature
title_fullStr Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature
title_full_unstemmed Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature
title_short Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature
title_sort studies of parenchymal texture added to mammographic breast density and risk of breast cancer a systematic review of the methods used in the literature
topic Breast density
Mammography
Parenchymal patterns
Risk prediction
Texture
url https://doi.org/10.1186/s13058-022-01600-5
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