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For: Astley SM, Harkness EF, Sergeant JC, Warwick J, Stavrinos P, Warren R, Wilson M, Beetles U, Gadde S, Lim Y, Jain A, Bundred S, Barr N, Reece V, Brentnall AR, Cuzick J, Howell T, Evans DG. A comparison of five methods of measuring mammographic density: a case-control study. Breast Cancer Res 2018;20:10. [PMID: 29402289 DOI: 10.1186/s13058-018-0932-z] [Cited by in Crossref: 38] [Cited by in F6Publishing: 31] [Article Influence: 9.5] [Reference Citation Analysis]
Number Citing Articles
1 Lian J, Li K. A Review of Breast Density Implications and Breast Cancer Screening. Clinical Breast Cancer 2020;20:283-90. [DOI: 10.1016/j.clbc.2020.03.004] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
2 Wang C, Brentnall AR, Mainprize J, Yaffe M, Cuzick J, Harvey JA. External validation of a mammographic texture marker for breast cancer risk in a case-control study. J Med Imaging (Bellingham) 2020;7:014003. [PMID: 32064299 DOI: 10.1117/1.JMI.7.1.014003] [Reference Citation Analysis]
3 Porembka JH, Ma J, Le-Petross HT. Breast density, MR imaging biomarkers, and breast cancer risk. Breast J 2020;26:1535-42. [PMID: 32654416 DOI: 10.1111/tbj.13965] [Reference Citation Analysis]
4 Burnside ES, Warren LM, Myles J, Wilkinson LS, Wallis MG, Patel M, Smith RA, Young KC, Massat NJ, Duffy SW. Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case-control study. Br J Cancer 2021. [PMID: 34168297 DOI: 10.1038/s41416-021-01466-y] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
5 Gennaro G, Bigolaro S, Hill ML, Stramare R, Caumo F. Accuracy of mammography dosimetry in the era of the European Directive 2013/59/Euratom transposition. Eur J Radiol 2020;127:108986. [PMID: 32298958 DOI: 10.1016/j.ejrad.2020.108986] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
6 Wang C, Brentnall AR, Cuzick J, Harkness EF, Evans DG, Astley S. Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds. Breast Cancer Res 2018;20:49. [PMID: 29884207 DOI: 10.1186/s13058-018-0979-x] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 1.5] [Reference Citation Analysis]
7 Albeshan SM, Hossain SZ, Mackey MG, Peat JK, Al Tahan FM, Brennan PC. Preliminary investigation of mammographic density among women in Riyadh: association with breast cancer risk factors and implications for screening practices. Clin Imaging 2019;54:138-47. [PMID: 30639525 DOI: 10.1016/j.clinimag.2019.01.002] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
8 van Leeuwen KG, de Rooij M, Schalekamp S, van Ginneken B, Rutten MJCM. How does artificial intelligence in radiology improve efficiency and health outcomes? Pediatr Radiol 2021. [PMID: 34117522 DOI: 10.1007/s00247-021-05114-8] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Youk JH, Gweon HM, Son EJ, Eun NL, Kim JA. Fully automated measurements of volumetric breast density adapted for BIRADS 5th edition: a comparison with visual assessment. Acta Radiol 2021;62:1148-54. [PMID: 32910685 DOI: 10.1177/0284185120956309] [Reference Citation Analysis]
10 Geras KJ, Mann RM, Moy L. Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives. Radiology 2019;293:246-59. [PMID: 31549948 DOI: 10.1148/radiol.2019182627] [Cited by in Crossref: 56] [Cited by in F6Publishing: 42] [Article Influence: 18.7] [Reference Citation Analysis]
11 Destounis SV, Santacroce A, Arieno A. Update on Breast Density, Risk Estimation, and Supplemental Screening. American Journal of Roentgenology 2020;214:296-305. [DOI: 10.2214/ajr.19.21994] [Cited by in Crossref: 13] [Cited by in F6Publishing: 1] [Article Influence: 6.5] [Reference Citation Analysis]
12 Ionescu GV, Fergie M, Berks M, Harkness EF, Hulleman J, Brentnall AR, Cuzick J, Evans DG, Astley SM. Prediction of reader estimates of mammographic density using convolutional neural networks. J Med Imaging (Bellingham) 2019;6:031405. [PMID: 30746393 DOI: 10.1117/1.JMI.6.3.031405] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 3.7] [Reference Citation Analysis]
13 Harkness EF, Astley SM, Evans D. Risk-based breast cancer screening strategies in women. Best Practice & Research Clinical Obstetrics & Gynaecology 2020;65:3-17. [DOI: 10.1016/j.bpobgyn.2019.11.005] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 5.5] [Reference Citation Analysis]
14 Balleyguier C, Arfi-rouche J, Boyer B, Gauthier E, Helin V, Loshkajian A, Ragusa S, Delaloge S. A new automated method to evaluate 2D mammographic breast density according to BI-RADS® Atlas Fifth Edition recommendations. Eur Radiol 2019;29:3830-8. [DOI: 10.1007/s00330-019-06016-y] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.7] [Reference Citation Analysis]
15 Janan F, Brady M. RICE: A method for quantitative mammographic image enhancement. Med Image Anal 2021;71:102043. [PMID: 33813287 DOI: 10.1016/j.media.2021.102043] [Reference Citation Analysis]
16 Archer M, Dasari P, Evdokiou A, Ingman WV. Biological Mechanisms and Therapeutic Opportunities in Mammographic Density and Breast Cancer Risk. Cancers (Basel) 2021;13:5391. [PMID: 34771552 DOI: 10.3390/cancers13215391] [Reference Citation Analysis]
17 Cheasley D, Devereux L, Hughes S, Nickson C, Procopio P, Lee G, Li N, Pridmore V, Elder K, Bruce Mann G, Kader T, Rowley SM, Fox SB, Byrne D, Saunders H, Fujihara KM, Lim B, Gorringe KL, Campbell IG. The TP53 mutation rate differs in breast cancers that arise in women with high or low mammographic density. NPJ Breast Cancer 2020;6:34. [PMID: 32802943 DOI: 10.1038/s41523-020-00176-7] [Reference Citation Analysis]
18 Brand JS, Humphreys K, Li J, Karlsson R, Hall P, Czene K. Common genetic variation and novel loci associated with volumetric mammographic density. Breast Cancer Res 2018;20:30. [PMID: 29665850 DOI: 10.1186/s13058-018-0954-6] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 2.3] [Reference Citation Analysis]
19 Giorgi Rossi P, Djuric O, Hélin V, Astley S, Mantellini P, Nitrosi A, Harkness EF, Gauthier E, Puliti D, Balleyguier C, Baron C, Gilbert FJ, Grivegnée A, Pattacini P, Michiels S, Delaloge S. Validation of a new fully automated software for 2D digital mammographic breast density evaluation in predicting breast cancer risk. Sci Rep 2021;11:19884. [PMID: 34615978 DOI: 10.1038/s41598-021-99433-3] [Reference Citation Analysis]
20 Atakpa EC, Brentnall AR, Astley S, Cuzick J, Evans DG, Warren RML, Howell A, Harvie M. The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study. Cancers (Basel) 2021;13:3245. [PMID: 34209579 DOI: 10.3390/cancers13133245] [Reference Citation Analysis]
21 Fowler EE, Smallwood A, Khan N, Miltich C, Drukteinis J, Sellers TA, Heine J. Calibrated Breast Density Measurements. Acad Radiol 2019;26:1181-90. [PMID: 30545682 DOI: 10.1016/j.acra.2018.10.009] [Reference Citation Analysis]
22 Saffari N, Rashwan HA, Abdel-Nasser M, Kumar Singh V, Arenas M, Mangina E, Herrera B, Puig D. Fully Automated Breast Density Segmentation and Classification Using Deep Learning. Diagnostics (Basel). 2020;10. [PMID: 33238512 DOI: 10.3390/diagnostics10110988] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
23 Evans DG, van Veen EM, Howell A, Astley S. Heritability of mammographic breast density. Quant Imaging Med Surg 2020;10:2387-91. [PMID: 33269237 DOI: 10.21037/qims-2020-20] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
24 Arieno A, Chan A, Destounis SV. A Review of the Role of Augmented Intelligence in Breast Imaging: From Automated Breast Density Assessment to Risk Stratification. American Journal of Roentgenology 2019;212:259-70. [DOI: 10.2214/ajr.18.20391] [Cited by in Crossref: 12] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
25 Oh H, Rice MS, Warner ET, Bertrand KA, Fowler EE, Eliassen AH, Rosner BA, Heine JJ, Tamimi RM. Early-Life and Adult Anthropometrics in Relation to Mammographic Image Intensity Variation in the Nurses' Health Studies. Cancer Epidemiol Biomarkers Prev 2020;29:343-51. [PMID: 31826913 DOI: 10.1158/1055-9965.EPI-19-0832] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Article Influence: 2.3] [Reference Citation Analysis]
26 Mann RM, Athanasiou A, Baltzer PAT, Camps-Herrero J, Clauser P, Fallenberg EM, Forrai G, Fuchsjäger MH, Helbich TH, Killburn-Toppin F, Lesaru M, Panizza P, Pediconi F, Pijnappel RM, Pinker K, Sardanelli F, Sella T, Thomassin-Naggara I, Zackrisson S, Gilbert FJ, Kuhl CK; European Society of Breast Imaging (EUSOBI). Breast cancer screening in women with extremely dense breasts recommendations of the European Society of Breast Imaging (EUSOBI). Eur Radiol 2022. [PMID: 35258677 DOI: 10.1007/s00330-022-08617-6] [Reference Citation Analysis]
27 Warner ET, Rice MS, Zeleznik OA, Fowler EE, Murthy D, Vachon CM, Bertrand KA, Rosner BA, Heine J, Tamimi RM. Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study. NPJ Breast Cancer 2021;7:68. [PMID: 34059687 DOI: 10.1038/s41523-021-00272-2] [Reference Citation Analysis]
28 Grimm LJ. Radiomics: A Primer for Breast Radiologists. Journal of Breast Imaging 2021;3:276-87. [DOI: 10.1093/jbi/wbab014] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
29 Kanbayti IH, Rae WID, McEntee MF, Al-Foheidi M, Ashour S, Turson SA, Ekpo EU. Is mammographic density a marker of breast cancer phenotypes? Cancer Causes Control 2020;31:749-65. [PMID: 32410205 DOI: 10.1007/s10552-020-01316-x] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
30 Brentnall AR, Warren R, Harkness EF, Astley SM, Wiseman J, Fox J, Fox L, Eriksson M, Hall P, Cuzick J, Evans DG, Howell A. Mammographic density change in a cohort of premenopausal women receiving tamoxifen for breast cancer prevention over 5 years. Breast Cancer Res 2020;22:101. [PMID: 32993747 DOI: 10.1186/s13058-020-01340-4] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
31 Tan M, Mariapun S, Yip CH, Ng KH, Teo SH. A novel method of determining breast cancer risk using parenchymal textural analysis of mammography images on an Asian cohort. Phys Med Biol 2019;64:035016. [PMID: 30577031 DOI: 10.1088/1361-6560/aafabd] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
32 Yu X, Zhou Q, Wang S, Zhang Y. A systematic survey of deep learning in breast cancer. Int J Intell Syst 2022;37:152-216. [DOI: 10.1002/int.22622] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
33 Abdolell M, Payne JI, Caines J, Tsuruda K, Barnes PJ, Talbot PJ, Tong O, Brown P, Rivers-Bowerman M, Iles S. Assessing breast cancer risk within the general screening population: developing a breast cancer risk model to identify higher risk women at mammographic screening. Eur Radiol 2020;30:5417-26. [PMID: 32358648 DOI: 10.1007/s00330-020-06901-x] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
34 Henze Bancroft LC, Strigel RM, Macdonald EB, Longhurst C, Johnson J, Hernando D, Reeder SB. Proton density water fraction as a reproducible MR-based measurement of breast density. Magn Reson Med 2021. [PMID: 34775638 DOI: 10.1002/mrm.29076] [Reference Citation Analysis]
35 Jo HM, Lee EH, Ko K, Kang BJ, Cha JH, Yi A, Jung HK, Jun JK; Alliance for Breast Cancer Screening in Korea (ABCS-K). Prevalence of Women with Dense Breasts in Korea: Results from a Nationwide Cross-sectional Study. Cancer Res Treat 2019;51:1295-301. [PMID: 30699499 DOI: 10.4143/crt.2018.297] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 2.7] [Reference Citation Analysis]
36 Kim S, Park B. Association between changes in mammographic density category and the risk of breast cancer: A nationwide cohort study in East-Asian women. Int J Cancer 2021;148:2674-84. [PMID: 33368233 DOI: 10.1002/ijc.33455] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Duric N, Sak M, Fan S, Pfeiffer RM, Littrup PJ, Simon MS, Gorski DH, Ali H, Purrington KS, Brem RF, Sherman ME, Gierach GL. Using Whole Breast Ultrasound Tomography to Improve Breast Cancer Risk Assessment: A Novel Risk Factor Based on the Quantitative Tissue Property of Sound Speed. J Clin Med 2020;9:E367. [PMID: 32013177 DOI: 10.3390/jcm9020367] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]