[1] |
Wilson GM, Dinh P, Pathmanathan N, et al. Ductal carcinoma in situ: molecular changes accompanying disease progression[J]. J Mammary Gland Biol Neoplasia, 2022, 27(1): 101-131. DOI: 10.1007/s10911-022-09517-7.
|
[2] |
Giaquinto AN, Sung H, Miller KD, et al. Breast cancer statistics, 2022[J]. CA Cancer J Clin, 2022, 72(6): 524-541. DOI: 10.3322/caac.21754.
|
[3] |
Salvatorelli L, Puzzo L, Vecchio GM, et al. Ductal carcinoma in situ of the breast: an update with emphasis on radiological and morphological features as predictive prognostic factors[J]. Cancers (Basel), 2020, 12(3): 609. DOI: 10.3390/cancers12030609.
|
[4] |
Grimm LJ, Rahbar H, Abdelmalak M, et al. Ductal carcinoma in situ: state-of-the-art review[J]. Radiology, 2022, 302(2): 246-255. DOI: 10.1148/radiol.211839.
|
[5] |
D'Orsi CJ. Imaging for the diagnosis and management of ductal carcinoma in situ[J]. J Natl Cancer Inst Monogr, 2010, 2010(41): 214-217. DOI: 10.1093/jncimonographs/lgq037.
|
[6] |
Kim G, Mikhael PG, Oseni TO, et al. Ductal carcinoma in situ on digital mammography versus digital breast tomosynthesis: rates and predictors of pathologic upgrade[J]. Eur Radiol, 2020, 30(11): 6089-6098. DOI: 10.1007/s00330-020-07021-2.
|
[7] |
Chou SS, Romanoff J, Lehman CD, et al. Preoperative breast MRI for newly diagnosed ductal carcinoma in situ: imaging features and performance in a multicenter setting (ECOG-ACRIN E4112 trial)[J]. Radiology, 2021, 301(1): 66-77. DOI: 10.1148/radiol.2021204743.
|
[8] |
Bragg A, Candelaria R, Adrada B, et al. Imaging of noncalcified ductal carcinoma in situ[J]. J Clin Imaging Sci, 2021, 11: 34. DOI: 10.25259/JCIS_48_2021.
pmid: 34221643
|
[9] |
Shehata M, Grimm L, Ballantyne N, et al. Ductal carcinoma in situ: current concepts in biology, imaging, and treatment[J]. J Breast Imaging, 2019, 1(3): 166-176. DOI: 10.1093/jbi/wbz039.
pmid: 31538141
|
[10] |
Amornsiripanitch N, Lam DL, Rahbar H. Advances in breast MRI in the setting of ductal carcinoma in situ[J]. Semin Roentgenol, 2018, 53(4): 261-269. DOI: 10.1053/j.ro.2018.08.006.
pmid: 30449344
|
[11] |
Oda G, Nakagawa T, Ogawa A, et al. Predictors for upstaging of ductal carcinoma in situ (DCIS) to invasive carcinoma in non-mass-type DCIS[J]. Mol Clin Oncol, 2020, 13(1): 67-72. DOI: 10.3892/mco.2020.2036.
|
[12] |
Greenwood HI, Wilmes LJ, Kelil T, et al. Role of breast MRI in the evaluation and detection of DCIS: opportunities and challenges[J]. J Magn Reson Imaging, 2020, 52(3): 697-709. DOI: 10.1002/jmri.26985.
pmid: 31746088
|
[13] |
van Seijen M, Lips EH, Thompson AM, et al. Ductal carcinoma in situ: to treat or not to treat, that is the question[J]. Br J Cancer, 2019, 121(4): 285-292. DOI: 10.1038/s41416-019-0478-6.
|
[14] |
Schmitz RSJM, Wilthagen EA, van Duijnhoven F, et al. Prediction models and decision aids for women with ductal carcinoma in situ: a systematic literature review[J]. Cancers (Basel), 2022, 14(13): 3259. DOI: 10.3390/cancers14133259.
|
[15] |
Moon HJ, Kim EK, Kim MJ, et al. Comparison of clinical and pathologic characteristics of ductal carcinoma in situ detected on mammography versus ultrasound only in asymptomatic patients[J]. Ultrasound Med Biol, 2019, 45(1): 68-77. DOI: 10.1016/j.ultrasmedbio.2018.09.003.
pmid: 30322671
|
[16] |
Brennan ME, Turner RM, Ciatto S, et al. Ductal carcinoma in situ at core-needle biopsy: meta-analysis of underestimation and predictors of invasive breast cancer[J]. Radiology, 2011, 260(1): 119-128. DOI: 10.1148/radiol.11102368.
pmid: 21493791
|
[17] |
Nicosia L, Bozzini AC, Penco S, et al. A model to predict upsta-ging to invasive carcinoma in patients preoperatively diagnosed with low-grade ductal carcinoma in situ of the breast[J]. Cancers (Basel), 2022, 14(2): 370. DOI: 10.3390/cancers14020370.
|
[18] |
Chong A, Weinstein SP, McDonald ES, et al. Digital breast tomosynthesis: concepts and clinical practice[J]. Radiology, 2019, 292(1): 1-14. DOI: 10.1148/radiol.2019180760.
pmid: 31084476
|
[19] |
范文文, 欧阳汉, 周纯武, 等. 数字乳腺断层成像与磁共振成像对乳腺肿瘤的诊断价值[J]. 放射学实践, 2020, 35(3): 360-364. DOI: 10.13609/j.cnki.1000-0313.2020.03.020.
|
[20] |
杨彩仙, 赵宏光, 刘慧, 等. 乳腺癌数字化X线三维断层摄影肿块边缘征象及其与病理学指标的相关性[J]. 肿瘤研究与临床, 2019, 31(1): 16-21. DOI: 10.3760/cma.j.issn.1006-9801.2019.01.004.
|
[21] |
Park KW, Kim SW, Han H, et al. Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer[J]. NPJ Breast Cancer, 2022, 8(1): 8. DOI: 10.1038/s41523-021-00364-z.
pmid: 35031626
|
[22] |
Shi B, Grimm LJ, Mazurowski MA, et al. Prediction of occult invasive disease in ductal carcinoma in situ using deep learning features[J]. J Am Coll Radiol, 2018, 15(3 Pt B): 527-534. DOI: 10.1016/j.jacr.2017.11.036.
pmid: 29398498
|
[23] |
Zhu Z, Harowicz M, Zhang J, et al. Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ[J]. Comput Biol Med, 2019, 115: 103498. DOI: 10.1016/j.compbiomed.2019.103498.
|
[24] |
Hou R, Grimm LJ, Mazurowski MA, et al. Prediction of upstaging in ductal carcinoma in situ based on mammographic radiomic features[J]. Radiology, 2022, 303(1): 54-62. DOI: 10.1148/radiol.210407.
|
[25] |
Lee HJ, Park JH, Nguyen AT, et al. Prediction of the histologic upgrade of ductal carcinoma in situ using a combined radiomics and machine learning approach based on breast dynamic contrast-enhanced magnetic resonance imaging[J]. Front Oncol, 2022, 12: 1032809. DOI: 10.3389/fonc.2022.1032809.
|