Mammography and computerized decision systems: A review

Annals of the New York Academy of Sciences

Volumn 980, Issue , 2002, Pages 83-94

  Roque, Antônio C ^a   André, Túlio C S S ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Breast cancer; Computer aided diagnosis; Mammography

Indexed keywords

BREAST CALCIFICATION; BREAST CANCER; CANCER DIAGNOSIS; CLINICAL PRACTICE; COMPUTER ASSISTED DIAGNOSIS; CONFERENCE PAPER; DECISION SUPPORT SYSTEM; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; DIAGNOSTIC VALUE; HUMAN; MAMMOGRAPHY; RADIOLOGIST; SENSITIVITY AND SPECIFICITY;

EID: 0036972657     PISSN: 00778923     EISSN: None     Source Type: Book Series    
DOI: 10.1111/j.1749-6632.2002.tb04890.x     Document Type: Conference Paper

References (114)

1. KELSEY, J.L & L. BERNSTEIN. 1996. Epidemiology and prevention of breast cancer. Ann. Rev. Publ. Health 17: 47-67.
2. FERLAY, J., F. BRAY, P. PISANI & D.M. PARKIN. 2001. GLOBOCAN 2000: Cancer Incidence, Mortality and Prevalence Worldwide, Version 1.0. IARC CancerBase No. 5. IARCPress. Lyon, France.
3. AMERICAN CANCER SOCIETY. 2002. Cancer Facts and Figures 2002. American Cancer Society, Atlanta, GA.
4. GREENLEE, R.T., M.B. HILL-HARMON, T. MURRAY & M. THUN. 2001. Cancer statistics 2001. California Cancer J. Clin. 51: 15-35.
5. CIATTO, S., M. ROSELLI DEL TURCO & M. ZAPPA. 1995. The detectability of breast cancer by screening mammography. Br. J. Cancer 71: 337-346.
6. GETTY D.J., R.M. PICKETT, C.J. D'ORSI & J.A. SWETS. 1988. Enhanced interpretation of diagnostic images. Invest. Radiol. 23: 240-252.
7. DOI, K., H. MACMAHON, S. KATSURAGAWA, et al. 1997. Computer-aided diagnosis in radiology: potential and pitfalls. Eur. J. Radiol. 31: 97-109.
8. TE BRAKE, G.M., N. KARSSMEIJER & J.H.C.L. HENDRICKS. 1998. Automated detection of breast carcinomas not detected in a screening program. Radiol. 207: 465-471.
9. SHTERN, F., M.W. VANNIER, S.M. PIZER & D. WINFIELD. 1999. Report of the working group on digital mammography: computer-aided diagnosis and 3-D image analysis and display. Acad. Radiol. 6(Suppl. 5): S231-S237.
10. MOORE, S. 2001. Better breast cancer detection. IEEE Spectrum 38: 50-54.
11. SEMIGLAZOV, V.F., V.N. SAGAIDAK, V.M. MOOISENKO & E.A. MIKHAILOV. 1992. Study of the role of breast self-examination in the reduction of mortality from breast cancer: the Russian Federation/World Health Organization Study. Eur. J. Cancer. 29A: 2039-2046.
12. ELLMAN, R., S.M. MOSS, D. COLEMAN & J. CHAMBERLAIN. 1993. Breast self-examination programmes in the trial of early detection of breast cancer: ten year findings. Br. J. Cancer. 68: 208-212.
13. THOMAS, D.B., D.L. GAO, S.G. SELF, et al. 1997. Randomized trial of breast self-examination in Sahnghai: methodology and preliminary results. J. Natl. Cancer Inst. 89: 355-365.
14. PORTER, P.L., A.Y. EL-BASTAWISSI, M.T. MANDELSON, et al. 1999. Breast tumor characteristics as predictors of mammographic detection: comparison of interval- and screen-detected cancers. J. Natl. Cancer Inst. 91: 2020-2028.
15. MILLER, A.B., T. TO, C.J. BAINES & C. WALL. 2000. Canadian national breast screening study-2: 13-year results of a randomized trial in women aged 50-59 years. J. Natl. Cancer Inst. 92:1490-1499.
16. BARTON, M.B., R. HARRIS & S.W. FLETCHER. 1999. Does this patient have breast cancer? The screening clinical breast examination: should it be done? How? J. Am. Med. Assoc. 282: 1270-1280.
17. OLSEN, O. & P.C. GØTZSCHE. 2001. Cochrane review on screening for breast cancer with mammography. Lancet 358: 1340-1342.
18. MIETTINEN, O.S., C.I. HENSCHKE, M.W. PASMANTIER, et al. 2002. Mammographic screening: no reliable supporting evidence? Lancet 359: 404-406.
19. DUFFY, S.W., L. TABAR, G. FAGERBERG, et al. 1991. Breast screening, prognostic factors and survival: results from the Swedish two county study. Br. J. Cancer 64: 1133-1138.
20. KERLIKOWSKE, K. & J. BARCLAY. 1997. Outcomes of modern screening mammography. Monogr. Natl. Cancer Inst. 22: 105-111.
21. ALEXANDER, F.E., T.J. ANDERSON, H.K. BROWN, et al. 1999. 14 years of follow-up from the Edinburgh randomized trial of breast-cancer screening. Lancet 353: 1903-1908.
22. BLANKS, R.G., S.M. MOSS, C.E. MCGAHAN, et al. 2000. Effect of NHS breast screening programme on mortality from breast cancer in England and Wales, 1990-8: comparison of observed with predicted mortality. Br. Med. J. 321: 665-669.
23. DE KONING, H. J. 2000. Assessment of nationwide cancer screening programmes. Lancet 355: 80-81.
24. ERNSTER, V.L., J. BARCLAY, K. KERLIKOWSKE, et al. 1996. Incidence of and treatment for ductal carcinoma in situ of the breast. J. Am. Med. Assoc 275: 913-918.
25. HOWE, H.L., P.A. WINGO, M.J. THUN, et al. 2001. The annual report to the nation on the status of cancer (1973-1998), featuring cancers with recent increasing trends. J. Natl. Cancer Inst. 93: 824-842.
26. GARFINKEL, L., C.C. BORING & C.W. HEATH. 1994. Changing trends: an overview of breast cancer incidence and mortality. Cancer 74: 222-227.
27. MOODY-AYERS, S.Y., C.K. WELLS & A.R. FEINSTEIN. 2000. "Benign" tumors and "early detection" in mammography-screened patients of a natural cohort with breast cancer. Arch. Intern. Med. 160: 1109-1115.
28. KERLIKOWSKE, K.M., D.G. GRADY, J. BARCLAY, et al. 1996. Likelihhod ratios for modern screening mammography: risk of breast cancer based on age and mammographic interpretation. J. Am. Med. Assoc. 276: 39-43.
29. ROSENBERG, R.D., W.C. HUNT, M.R. WILLIAMSON, et al. 1998. Effects of breast density, ethnicity, and estrogen replacement therapy on screening mammography sensitivity and cancer stage at diagnosis: a review of 183, 134 screening mammograms in Albuquerque, New Mexico. Radiol. 209: 511-518.
30. BAINES, C.J. & R. DAYAN. 1999 A tangled web: factors likely to affect the efficacy of screening mammography. J. Natl. Cancer Inst. 91: 833-838.
31. SAARENMAA, I., T. SALMINEN, U. GEIGER, et al. 2001. The effect of age and density of the breast on the sensitivity of breast cancer diagnostic by mammography and ultrasonography. Breast Cancer Res. Treat. 67: 117-123.
32. BEAM, C.A., P.M. LAYDE & D.C. SULLIVAN 1996. Variability in the interpretation of screening mammograms by U.S. radiologists: findings from a national sample Arch. Intern. Med. 156: 209-213.
33. KERLIKOWSKE, K., D.G. GRADY, J. BARCLAY, et al. 1998. Variability and accuracy in mammographic interpretation using the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS). J. Natl. Cancer Inst. 90: 1801-1809.
34. BIRD, R.E., T.W. WALLACE, B.C. YANKASKAS. 1992. Analysis of cancers missed at screening mammography. Radiol. 184: 613-617.
35. VAN DUCK, J.A., A.L. VERBEEK, J.H.C.L. HENDRICKS & R. HOLLAND. 1993. The current detectability of cancer in a breast screening program. Cancer 72: 1933-1938.
36. GOERGEN, S.K., J. EVANS, G.P. COHEN & J.H. MACMILLAN. 1997. Characteristics of breast carcinomas missed by screening radiologists. Radiol. 204: 131-135.
37. MUSHLIN, A.I., R.W. KOUIDES & D.E. SHAPIRO. 1998. Estimating the accuracy of screening mammography: a meta-analysis. Am. J. Prevent. Med. 14: 143-153.
38. JACKSON, V.P., R.E. HENDRICK, S.A. FEIG & D.B. KOPANS. 1993. Imaging of the radiographically dense breast. Radiol. 188: 297-301.
39. BROWN, M.L., F. HOUN, E.A. SICKLES & L.G. KESSLER. 1995. Screening mammography in community practice: positive predictive value of abnormal findings and yield of follow-up diagnostic procedures. Am. J. Roentgenol. 165: 1373-1377.
40. KERLIKOWSKE, K., D. GRADY, J. BARCLAY, et al. 1993. Positive predictive value of screening mammography by age and family history of breast cancer. J. Am. Med. Assoc. 270: 2444-2450.
41. ELMORE, J.G., M.D. BARTON, V.M. MOCERI, et al. 1998. Ten-year risk of false-positive screening mammograms and clinical breast examinations. N. Engl. J. Med. 338: 1089-1096.
42. KOPANS, D.B. 1992. The positive predictive value of mammography. Am. J Roentgenol. 158: 521-526.
43. MAY, F.M., J.M. STORELLA, D.Z. SILVERSTONE & G. WYSHAK. 1988. Non palpable breast lesions: recommendations for biopsy based on suspicion of carcinoma at mammography. Radiol. 167: 353-358.
44. PHYSICIANS INSURERS ASSOCIATION OF AMERICA. 1995. Physicians Insurers Association of America Breast Cancer Study. Physicians Insurers Association of America. Washington, DC.
45. GRAM, I.T., E. LUND & S.E. SLENKER. 1990. Quality of life following a false-positive mammogram. Br. J. Cancer 62: 1018-1022.
46. LERMAN, C., B. TROCK, B.K. RIMER, et al. 1991. Psychological and behavioral implications of abnormal mammograms. Ann. Intern. Med. 114: 657-661.
47. SICKLES, E.A. 1991. Periodic mammography follow-up of probably benign lesions: results in 3,184 consecutive cases. Radiol. 179: 463-468.
48. VARAS, X., F. LEBORGNE & J.H. LEBORGNE. 1992. Non-palpable, probably benign lesions: role of follow-up mammography. Radiol. 184: 409-414.
49. ANTTINEN, I., M. PAMILO, M. SOIVA & M. ROIHA. 1993. Double reading of mammography screening films: one radiologist or two? Clin. Radiol. 48: 414-421.
50. THURFELL, K.A., A.A. LERNEVAL & A.H. TAUBE. 1994. Benefit of independent double reading in a population-based mammography screening program. Radiol. 191: 241-244.
51. HENDEE, W. R., C. BEAM & E. HENDRICK. 1999. Proposition: all mammograms should be double-read. Med. Phys. 26: 115-118.
52. FREER, T.W. & M.J. ULISSEY. 2001. Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center. Radiol. 220: 781-786.
53. SICKLES, E.A. 1998. Findings at mammographic screening on only one standard projection: outcomes analysis. Radiol. 208: 471-475.
54. AMERICAN COLLEGE OF RADIOLOGY. 2001. American College of Radiology Standard for Communication: Diagnostic Radiology. American College of Radiology. Reston, VA.
55. FEIG, S.A. 1988. Importance of supplementary mammographic views to diagnostic accuracy. Am. J. Roentgenol. 151: 40-41.
56. SCOTT, S. & M. MORROW. 1999. Breast cancer: making the diagnosis. Surg. Clin. North Am. 79: 991-1005.
57. SHTERN, F. 1992. Digital mammography and related technologies: perspective from the National Cancer Institute. Radiol. 183: 629-630.
58. FEIG, S.A. & M.J. YAFFE. 1995. Digital mammography, computer-aided diagnosis and telemmamography. Radiol. Clin. North Am. 33: 1205-1230.
59. SCHMIDT, R.A. & R.M. NISHIKAWA. 1995. Clinical use of digital mammography: the present and the prospects. J. Dig. Imag. 8: 74-79.
60. CHAN, H.P., M.A. HELVIE, N. PETRICK, et al. 2001. Digital mammography: observer performance study of the effects of pixel size on the characterization of malignant and benign microcalcifications. Acad. Radiol. 8: 454-466.
61. LEWIN, J.M., R.E. HENDRICK, C.J. D'ORSI, et al. 2001. Comparison of full-field digital mammography with screen-film mammography for cancer detection: results of 4,945 paired examinations. Radiol. 218: 873-880.
62. BICK, U., F. DIEKMANN, S.D. GREBE & B. HAMM. 2000. Full field digital mammography: first clinical experiences. Presented at the European Congress of Radiology ECR2000. Vienna, Austria, March 5-10.
63. VENTA, L.A., R.E. HENDRICK, Y.T. ADLER, et al. 2001. Rates and causes of disagreement in interpretation of full-field digital mammography and film-screen mammography in a diagnostic setting. Am. J. Roentgenol. 176: 1241-1248.
64. VYBORNY, C.J. & M.L. GIGER. 1994. Computer vision and artificial intelligence in mammography. Am. J. Roentgenol. 162: 699-709.
65. KAHN, C.E., JR. 1993. Artificial intelligence and radiology decision support. In Digital Imaging. W.R. Hendee & J.H. Trueblood, Eds.: 281-300. Medical Physics Publishing, Madison.
66. CHAN, H.P., L.T. NIKLASON, D.M. IKEDA, et al. 1994. Digitization requirements in mammography: effects on computer-aided detection of microcalcifications. Med. Phys. 21: 1203-1211.
67. PHAM, D.L., C. XU & J.L. PRINCE. 2000. Current methods in medical image segmentation. Annu. Rev. Bioeng. 2: 315-337.
68. AZAR, F.A. 2000. Imaging techniques for detecting breast cancer: survey and perspectives. Technical Report MS-BE-00-02. Department of Bioengineering. University of Pennsylvania. Philadelphia, PA.
69. ANDRÉ, T.C.S.S. & A.C. ROQUE. 2000. A neural network system for the diagnosis of breast cancer. Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences-METMBS'00. F. Valafar, Ed.: 1-6. CSREA, Las Vegas.
70. TABAR, L. & P.B. DEAN. 1985. Teaching Atlas of Mammography, 2nd edit. Thieme Inc., New York.
71. KOPANS, D.B. 1989. Breast Imaging. JB Lippincott Co., Philadelphia.
72. MILLS, R.R., R. DAVIS & A.J. STACEY. 1976. The detection and significance of calcifications in the breast: a radiological and pathological study. Br. J. Radiol. 49: 12-26.
73. CHAN, H.P., K. DOI, S. GALHOTRA, et al. 1987. Image feature analysis and computer-aided diagnosis in digital radiography. 1. Automated detection of microcalcifications in mammography. Med. Phys. 14: 538-548.
74. FAM, B.W., S.L. OLSON, P.F. WINTER & F.J. SHOLTZ. 1988. Algorithm for the detection of fine clustered calcifications in mammograms. Radiol. 169: 333-337.
75. CHAN, H.P., K. DOI, C.J. VYBORNY, et al. 1990. Improvement in radiologists' detection of clustered microcalcifications on mammograms: the potential of computer-aided diagnosis. Invest. Radiol. 25: 1102-1110.
76. DAVIES, D.H. & D.I. DANCE. 1990. Automatic detection of clusters of calcifications in digital mammograms. Phys. Med. Biol. 35: 1111-1118.
77. KARSSEMEIJER, N. 1992. Stochastic model for automated detection of calcifications in digital mammograms. Imag. Vis. Comp. 10: 369-375.
78. DENGLER, J., S. BEHRENS & J.F. DESAGA. 1993. Segmentation of microcalcifications in mammograms. IEEE Trans. Med. Imag. 12: 634-642.
79. SHEN, L., R.M. RANGAYYAN & J.E.L. DESAUTELS. 1993. Application of shape analysis to mammographic calcifications. IEEE Trans. Med. Imag. 13: 263-274.
80. NISHIKAWA, R.M., M.L. GIGER, K. DOI, et al. 1993. Computer-aided detection of clustered microcalcifications: an improved method for grouping detected signals. Med. Phys. 20: 1661-1666.
81. LEFEBVRE, F. & H. BENALI. 1995. A fractal approach to the segmentation of microcalcifications in digital mammograms. Med. Phys. 22: 381-390.
82. CHAN, H.P., S.C. LO, B. SAHINER, et al. 1995. Computer-aided detection of mammographic microcalcifications: pattern recognition with an artificial neural network. Med. Phys. 22: 1555-1567.
83. ZHANG, W., K. DOI, M.L. GIGER, et al. 1996. An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms. Med. Phys. 23: 595-601.
84. STRICKLAND, R.N. & H.I. HAHN. 1996. Wavelet transforms for detecting microcalcifications in mammograms. IEEE Trans. Med. Imag. 15: 218-229.
85. BETAL, D., N. ROBERTS & G.H. WHITEHOUSE. 1997. Segmentation and numerical analysis of microcalcifications on mammograms using mathematical morphology. Br. J. Radiol. 70: 903-917.
86. BANKMAN, I.N., T. NIZIALEK, I. SIMON, et al. 1997. Segmentation algorithms for detecting microcalcifications in mammograms. IEEE Trans. Inf. Technol. Biomed. 1: 141-149.
87. QIAN, W., L.P. CLARKE, D. SONG & R.A. CLARK. 1998. Digital mammography: hybrid four-channel wavelet transform for microcalcification segmentation. Acad. Radiol. 5: 354-365.
88. ANASTASIO, M.A., H. YOSHIDA, R. NAGEL, et al. 1998. A genetic algorithm-based method for optimizing the performance of a computer-aided diagnosis scheme for detection of clustered microcalcifications in mammograms. Med. Phys. 25: 1613-1620.
89. SCHMIDT, F., E. SORATIN, C. SZEPESVARI, et al. 1999. An automatic method for the identification and interpretation of clustered microcalcifications in mammograms. Phys. Med. Biol. 44: 1231-1243.
90. BOTTEMA, M.J. & J.P. SLAVOTINEK. 2000. Detection and classification of lobular and DCIS (small cell) microcalcifications in digital mammograms. Patt. Recog. Lett, 21: 1209-1214.
91. BOCCIGNONE, G., A. CHIANESE & A. PICARIELLO. 2000. Computer aided detection of microcalcifications in digital mammograms. Comput. Biol. Med. 30: 267-286.
92. GAVRIELIDES, M.A., J.Y. LO, R. VARGAS-VORACEK & C.E. FLOYD, JR. 2000. Segmentation of suspicious clustered microcalcifications in mammograms. Med. Phys. 27: 13-22.
93. VELDKAMP, W.J., N. KARSSEMEIJER, J.D. OTTEN & J.H. HENDRICKS. 2000. Automated classification of clustered microcalcifications into malignant and benign types. Med. Phys. 27: 2600-2608.
94. MARKOPOULOS, C., E. KOUSKOS, K. KOUFOPOULOS, et al. 2001. Use of artificial neural networks (computer analysis) in the diagnosis of microcalcifications on mammography. Eur. J. Radiol. 39: 60-65.
95. NISHIKAWA, R.M., M.L. GIGER, R.A. SCHMIDT, et al. 1999. Prospective testing of a clinical mammography workstation for CAD: analysis of the first 10,000 cases. In Digital Mammography '98. N. Karssemeijer, M. Thijssen, J. Hendricks & L. Van Erning, Eds.: 395-400. Kluwer, Dordrecht, the Netherlands.
96. BURHENNE, L.J., S.A. WOOD, C.J. D'ORSI, et al. 2000. The potential contribution of computer-aided detection to the sensitivity of screening mammography. Radiol. 215: 554-562.
97. BIRDWELL, R.L., D.M. IKEDA, K.F. O'SHAUGHNESSY & E.A. SICKLES. 2001. Mammographic characteristics of 115 missed cancers later detected with screening mammography and the potential utility of computer-aided detection. Radiol. 219: 192-202.
98. LAI, S., X. LI & W. BISCHOF. 1989. On techniques for detecting circumscribed masses in mammograms. IEEE Trans. Med. Imag. 8: 377-386.
99. BRZAKOVIC D., X.M. LUO & P. BRZAKOVIC. 1990. An approach to automated detection of tumors in mammograms. IEEE Trans. Med. Imag. 9: 233-241.
100. YIN, F.F., M.L. GIGER, K. DOI, et al. 1991. Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images. Med. Phys. 18: 955-963.
101. KEGELMEYER, W.P. 1992. Computer detection of stellate lesions in mammograms. Proceedings of SPIE. 1660: 446-454. Society for Optical Engineering, Bellingham, WA.
102. KEGELMEYER, W.P., J.M. PRUNEDA, P.D. BOURLAND, et al. 1994. Computer-aided mammographic screening for spiculated lesions. Radiol. 191: 331-337.
103. LI, L., W. QIAN, L.P. CLARKE & R.A. CLARK. 1997. Digital mammography: computer-aided diagnosis method for mass detection with multiorientation and multiresolution wavelet transforms. Acad. Radiol. 4: 724-731.
104. MENDEZ, A.J., P.G. TAHOCES, M.J. LADO, et al. 1998. Computer-aided diagnosis: automatic detection of malignant masses in digitized mammograms. Med. Phys. 25: 957-964.
105. ZHENG, B., Y.H. CHANG, X.H. WANG, et al. 1999. Feature selection for computerized mass detection in digitized mammograms by using a genetic algorithm. Acad. Radiol. 6: 327-332.
106. MUDIGONDA, N.R., R.M. RANGAYYAN & J.E. DESAUTELS. 2000. Gradient and texture analysis for the classification of mammographic masses. IEEE Trans. Med. Imag. 19: 1032-1043.
107. TE BRAKE, G.M. & N. KARSSEMEIJER. 2001. Segmentation of suspicious densities in digital mammograms. Med. Phys. 28: 259-266.
108. LI, H., Y. WANG, K.J. LIU, et al. 2001. Computerized radiographic mass detection - part II: decision support by featured database visualization and modular neural networks. IEEE Trans. Med. Imag. 20: 302-313.
109. CHAN, H.P., B. SAHINER, M.A. HELVIE, et al. 1999. Improvement of radiologists' characterization of mammographic masses by using computer-aided diagnosis: an ROC study. Radiol. 212: 817-827.
110. BERNER, E.S., Ed. 1999. Clinical Decision Support Systems: Theory and Practice. Springer-Verlag, New York.
111. WU, Y., M.L. GIGER, K. DOI, et al. 1993. Artificial neural networks in mammography: application to decision making in the diagnosis of breast cancer. Radiol. 187: 81-87.
112. LO, J.Y., J.A. BAKER, P.J. KORNGUTH, et al. 1997. Predicting breast cancer invasion with artificial neural networks on the basis of mammographic features. Radiol. 203: 159-163.
113. HUO, Z., M.L. GIGER, C.J. VYBORNY, et al. 1998. Automated computerized classification of malignant and benign masses on digital mammograms. Acad. Radiol. 5: 155-168.
114. SAHINER, B., H.P. CHAN, N. PETRICK, et al. 1998. Computerized characterization of masses on mammograms: the rubber band straightening transform and texture analysis. Med. Phys. 25: 516-526.