The mammographic density of a mass is a significant predictor of breast cancer

Radiology

Volumn 258, Issue 2, 2011, Pages 417-425

  Woods, Ryan W ^a,d   Sisney, Gale S ^a   Salkowski, Lonie R ^a   Shinki, Kazuhiko ^c   Lin, Yunzhi ^b   Burnside, Elizabeth S ^a  

^a UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^b University of Wisconsin   (United States)

^c WAYNE STATE UNIVERSITY   (United States)

^d JOHNS HOPKINS HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; BREAST BIOPSY; BREAST CANCER; CONTROLLED STUDY; DIAGNOSTIC IMAGING; ECHOGRAPHY; FEMALE; HUMAN; HUMAN TISSUE; MAJOR CLINICAL STUDY; MAMMOGRAPHY; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTIVE VALUE; PRIORITY JOURNAL; PROSPECTIVE STUDY; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY;

BIOPSY; BREAST NEOPLASMS; CHI-SQUARE DISTRIBUTION; DIAGNOSIS, DIFFERENTIAL; FEMALE; HUMANS; LOGISTIC MODELS; MAMMOGRAPHY; PROSPECTIVE STUDIES; RETROSPECTIVE STUDIES;

EID: 79952354871     PISSN: 00338419     EISSN: 15271315     Source Type: Journal    
DOI: 10.1148/radiol.10100328     Document Type: Article

References (27)

1. Kopans D. Breast imaging. 3rd ed. Philadelphia, Pa: Lippincott-Raven, 2007.
2. Poplack SP, Carney PA, Weiss JE, Titus-Ernstoff L, Goodrich ME, Tosteson AN. Screening mammography: costs and use of screening-related services. Radiology 2005; 234(1):79-85. (Pubitemid 39658372)
3. Baker JA, Kornguth PJ, Floyd CE Jr. Breast Imaging Reporting and Data System standardized mammography lexicon: observer variability in lesion description. AJR Am J Roentgenol 1996;166(4):773-778.
4. D'Orsi CJ. The American College of Radiology mammography lexicon: an initial attempt to standardize terminology. AJR Am J Roentgenol 1996;166(4):779-780.
5. American College of Radiology. Breast Imaging Reporting and Data System (BI-RADS). 4th ed. Reston, Va : American College of Radiology, 2003.
6. Lacquement MA, Mitchell D, Hollingsworth AB. Positive predictive value of the Breast Imaging Reporting and Data System. J Am Coll Surg 1999;189(1):34-40. (Pubitemid 29307740)
7. Lazarus E, Mainiero MB, Schepps B, Koelliker SL, Livingston LS. BI-RADS lexicon for US and mammography: interobserver variability and positive predictive value. Radiology 2006;239(2):385-391.
8. Liberman L, Abramson AF, Squires FB, Glassman JR, Morris EA, Dershaw DD. The Breast Imaging Reporting and Data System: positive predictive value of mammographic features and final assessment categories. AJR Am J Roentgenol 1998;171(1):35-40. (Pubitemid 28308645)
9. Orel SG, Kay N, Reynolds C, Sullivan DC. BI-RADS categorization as a predictor of malignancy. Radiology 1999;211(3):845-850. (Pubitemid 29249488)
10. Taplin SH, Ichikawa LE, Kerlikowske K, et al. Concordance of Breast Imaging Reporting and Data System assessments and management recommendations in screening mammography. Radiology 2002;222(2):529-535. (Pubitemid 34106131)
11. Varas X, Leborgne JH, Leborgne F, Mezzera J, Jaumandreu S, Leborgne F. Revisiting the mammographic follow-up of BI-RADS category 3 lesions. AJR Am J Roentgenol 2002;179(3):691-695. (Pubitemid 34919583)
12. Zonderland HM, Pope TL Jr, Nieborg AJ. The positive predictive value of the Breast Imaging Reporting and Data System (BI-RADS) as a method of quality assessment in breast imaging in a hospital population. Eur Radiol 2004;14(10):1743-1750. (Pubitemid 39386620)
13. Baker JA, Kornguth PJ, Lo JY, Williford ME, Floyd CE Jr. Breast cancer: prediction with artificial neural network based on BI-RADS standardized lexicon. Radiology 1995;196(3):817-822.
14. Ciatto S, Cataliotti L, Distante V. Nonpalpable lesions detected with mammography: review of 512 consecutive cases. Radiology 1987;165(1):99-102. (Pubitemid 17146989)
15. Hall FM, Storella JM, Silverstone DZ, Wyshak G. Nonpalpable breast lesions: recommendations for biopsy based on suspicion of carcinoma at mammography. Radiology 1988;167(2):353-358.
16. Helvie MA, Pennes DR, Rebner M, Adler DD. Mammographic follow-up of low-suspicion lesions: compliance rate and diagnostic yield. Radiology 1991;178(1):155-158.
17. Lehman CD, Rutter CM, Eby PR, White E, Buist DS, Taplin SH. Lesion and patient characteristics associated with malignancy after a probably benign finding on community practice mammography. AJR Am J Roentgenol 2008;190(2):511-515. (Pubitemid 351196625)
18. Sickles EA. Nonpalpable, circumscribed, noncalcified solid breast masses: likelihood of malignancy based on lesion size and age of patient. Radiology 1994;192(2):439-442. (Pubitemid 24233923)
19. Varas X, Leborgne F, Leborgne JH. Nonpalpable, probably benign lesions: role of follow-up mammography. Radiology 1992;184(2):409-414.
20. Vizcaíno I, Gadea L, Andreo L, et al. Short-term follow-up results in 795 nonpalpable probably benign lesions detected at screening mammography. Radiology 2001;219(2):475-483.
21. Egan RL. Breast imaging: diagnosis and morphology of breast diseases. Philadelphia, Pa: Saunders, 1988.
22. Homer MJ. Mammographic interpretation: a practical approach. 2nd ed. New York, NY: McGraw-Hill, Health Professions Division, 1997.
23. Cory RC, Linden SS. The mammographic density of breast cancer. AJR Am J Roentgenol 1993;160(2):418-419.
24. Jackson VP, Dines KA, Bassett LW, Gold RH, Reynolds HE. Diagnostic importance of the radiographic density of noncalcified breast masses: analysis of 91 lesions. AJR Am J Roentgenol 1991;157(1):25-28.
25. Burnside ES, Davis J, Costa VS, et al. Knowledge discovery from structured mammography reports using inductive logic programming. AMIA Annu Symp Proc 2005:96-100.
26. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33(1):159-174. (Pubitemid 8054849)
27. Berg WA, Campassi C, Langenberg P, Sexton MJ. Breast Imaging Reporting and Data System: inter- and intraobserver variability in feature analysis and final assessment. AJR Am J Roentgenol 2000;174(6):1769-1777.