Skip to main content

Computed Tomography for Imaging the Breast

Abstract

Despite the success of screening mammography contributing to the reduction of cancer mortality, a number of other imaging techniques are being studied for breast cancer screening. In our laboratory, a dedicated breast computed tomography (CT) system has been developed and is currently undergoing patient testing. The breast CT system is capable of scanning the breast with the woman lying prone on a tabletop, with the breast in the pendant position. A 360° scan currently requires 16.6 s, and a second scanner with a 9-second scan time is nearly operational. Extensive effort was placed on computing the radiation dose to the breast under CT geometry, and the scan parameters are selected to utilize the same radiation dose levels as two-view mammography. A total of 55 women have been scanned, ten healthy volunteers in a Phase I trial, and 45 women with a high likelihood of having breast cancer in a Phase II trial. The breast CT process leads to the production of approximately three hundred 512 × 512 images for each breast. Subjective evaluation of the breast CT images reveals excellent anatomical detail, good depiction of microcalcifications, and exquisite visualization of the soft tissue components of the tumor when contrasted against adipose tissues. The use of iodine contrast injection dramatically enhances the visualization of tumors. While a thorough scientific investigation based upon observer performance studies is in progress, initial breast CT images do appear promising and it is likely that breast CT will play some role in breast cancer imaging.

This is a preview of subscription content, access via your institution.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7

Abbreviations

CT:

computed tomography

MTF:

modulation transfer function

BIRADS:

breast imaging reporting and diagnosis system

References

  1. 1.

    Tabar L, Vitak B, Chen HH, Duffy SW, Yen MF, Chiang CF, et al. The Swedish Two-County Trial twenty years later. Updated mortality results and new insights from long-term follow-up. Radiol Clin North Am 2000;38:625–51.

    PubMed  CAS  Article  Google Scholar 

  2. 2.

    Pisani P, Forman D. Declining mortality from breast cancer in Yorkshire, 1983–1998: extent and causes. Br J Cancer 2004;90:652–6.

    PubMed  CAS  Article  Google Scholar 

  3. 3.

    Pisano ED, Parham CA. Digital mammography, sestamibi breast scintigraphy, and positron emission tomography breast imaging. Radiol Clin North Am 2000;38:861–9, (x).

    PubMed  CAS  Article  Google Scholar 

  4. 4.

    Jackson VP, Hendrick RE, Feig SA, Kopans DB. Imaging of the radiographically dense breast. Radiology 1993;188:297–301.

    PubMed  CAS  Google Scholar 

  5. 5.

    Yaffe MJ. What should the burden of proof be for acceptance of a new breast-cancer screening technique? Lancet 2004;364:1111–2.

    PubMed  Article  Google Scholar 

  6. 6.

    Kook SH, Kwag HJ. Value of contrast-enhanced power Doppler sonography using a microbubble echo-enhancing agent in evaluation of small breast lesions. J Clin Ultrasound 2003;31:227–38.

    PubMed  Article  Google Scholar 

  7. 7.

    Caruso G, Ienzi R, Cirino A, Salvaggio G, Campione M, Lagalla R, et al. Breast lesion characterization with contrast-enhanced US. Work in progress. Radiol Med (Torino) 2002;104:443–50.

    Google Scholar 

  8. 8.

    Melodelima D, Bamber JC, Duck FA, Shipley JA, Xu L. Elastography for breast cancer diagnosis using radiation force: system development and performance evaluation. Ultrasound Med Biol 2006;32:387–96.

    PubMed  Article  Google Scholar 

  9. 9.

    Cassano E, Rizzo S, Bozzini A, Menna S, Bellomi M. Contrast enhanced ultrasound of breast cancer. Cancer Imaging 2006;6:4–6.

    PubMed  CAS  Google Scholar 

  10. 10.

    Tohno E, Ueno E. Ultrasound (US) diagnosis of nonpalpable breast cancer. Breast Cancer 2005;12:267–71.

    PubMed  Article  Google Scholar 

  11. 11.

    Huang SW, Li PC. Ultrasonic computed tomography reconstruction of the attenuation coefficient using a linear array. IEEE Trans Ultrason Ferroelectr Freq Control 2005;52:2011–22.

    PubMed  Article  Google Scholar 

  12. 12.

    Agnese DM. Advances in breast imaging. Surg Technol Int 2005;14:51–6.

    PubMed  Google Scholar 

  13. 13.

    Palmer GM, Zhu C, Breslin TM, Xu F, Gilchrist KW, Ramanujam N. Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis. Appl Opt 2006;45:1072–8.

    PubMed  CAS  Article  Google Scholar 

  14. 14.

    Tromberg BJ, Cerussi A, Shah N, Compton M, Durkin A, Hsiang D, et al. Imaging in breast cancer: diffuse optics in breast cancer: detecting tumors in pre-menopausal women and monitoring neoadjuvant chemotherapy. Breast Cancer Res 2005;7:279–85.

    PubMed  Article  Google Scholar 

  15. 15.

    Durduran T, Choe R, Yu G, Zhou C, Tchou JC, Czerniecki BJ, et al. Diffuse optical measurement of blood flow in breast tumors. Opt Lett 2005;30:2915–7.

    PubMed  Article  Google Scholar 

  16. 16.

    Nioka S, Chance B. NIR spectroscopic detection of breast cancer. Technol Cancer Res Treat 2005;4:497–512.

    PubMed  CAS  Google Scholar 

  17. 17.

    Fantini S, Heffer EL, Pera VE, Sassaroli A, Liu N. Spatial and spectral information in optical mammography. Technol Cancer Res Treat 2005;4:471–82.

    PubMed  Google Scholar 

  18. 18.

    Tromberg BJ. Optical scanning and breast cancer. Acad Radiol 2005;12:923–4.

    PubMed  Article  Google Scholar 

  19. 19.

    Leach MO, Boggis CR, Dixon AK, Easton DF, Eeles RA, Evans DG, et al. Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS). Lancet 2005;365:1769–78.

    PubMed  CAS  Article  Google Scholar 

  20. 20.

    Choi BG, Kim HH, Kim EN, Kim BS, Han JY, Yoo SS, et al. New subtraction algorithms for evaluation of lesions on dynamic contrast-enhanced MR mammography. Eur Radiol 2002;12:3018–22.

    PubMed  Google Scholar 

  21. 21.

    Tuncbilek N, Unlu E, Karakas HM, Cakir B, Ozyilmaz F. Evaluation of tumor angiogenesis with contrast-enhanced dynamic magnetic resonance mammography. Breast J 2003;9:403–8.

    PubMed  Article  Google Scholar 

  22. 22.

    Sardanelli F, Giuseppetti GM, Panizza P, Bazzocchi M, Fausto A, Simonetti G, et al. Sensitivity of MRI versus mammography for detecting foci of multifocal, multicentric breast cancer in fatty and dense breasts using the whole-breast pathologic examination as a gold standard. AJR Am J Roentgenol 2004;183:1149–57.

    PubMed  Google Scholar 

  23. 23.

    Jatoi I. MRI in breast cancer management: potential for benefit and harm. Int J Fertil Womens Med 2005;50:281–4.

    PubMed  Google Scholar 

  24. 24.

    Bartella L, Morris EA. Advances in breast imaging: magnetic resonance imaging. Curr Oncol Rep 2006;8:7–13.

    PubMed  Google Scholar 

  25. 25.

    Galinsky D, Kisselgoff D, Sella T, Peretz T, Libson E, Sklair-Levy M. Effect of breast magnetic resonance imaging on the clinical management of breast cancer. Isr Med Assoc J 2005;7:700–3.

    PubMed  Google Scholar 

  26. 26.

    Buchanan CL, Morris EA, Dorn PL, Borgen PI, Van Zee KJ. Utility of breast magnetic resonance imaging in patients with occult primary breast cancer. Ann Surg Oncol 2005;12:1045–53.

    PubMed  Article  Google Scholar 

  27. 27.

    Lehman CD, Schnall MD. Imaging in breast cancer: magnetic resonance imaging. Breast Cancer Res 2005;7:215–9.

    PubMed  Article  Google Scholar 

  28. 28.

    Chang CH, Sibala JL, Fritz SL, Dwyer SJ, III, Templeton AW. Specific value of computed tomographic breast scanner (CT/M) in diagnosis of breast diseases. Radiology 1979;132:647–52.

    PubMed  CAS  Google Scholar 

  29. 29.

    Chen B, Ning R. Cone-beam volume CT breast imaging: feasibility study. Med Phys 2002;29:755–70.

    PubMed  Article  Google Scholar 

  30. 30.

    McKinley RL, Tornai MP, Samei E, Bradshaw ML. Simulation study of a quasi-monochromatic beam for X-ray computed mammotomography. Med Phys 2004;31:800–13.

    PubMed  Article  Google Scholar 

  31. 31.

    Ning R, Tang X, Conover D, Yu R. Flat panel detector-based cone beam computed tomography with a circle-plus-two-arcs data acquisition orbit: preliminary phantom study. Med Phys 2003;30:1694–705.

    PubMed  Article  Google Scholar 

  32. 32.

    Ning R, Chen B, Yu R, Conover D, Tang X, Ning Y. Flat panel detector-based cone-beam volume CT angiography imaging: system evaluation. IEEE Trans Med Imaging 2000;19:949–63.

    PubMed  CAS  Article  Google Scholar 

  33. 33.

    Chen Z, Ning R. Forest representation of vessels in cone-beam computed tomographic angiography. Comput Med Imaging Graph 2005;29:1–14.

    PubMed  CAS  Article  Google Scholar 

  34. 34.

    Chen Z, Ning R. Breast volume denoising and noise characterization by 3D wavelet transform. Comput Med Imaging Graph 2004;28:235–46.

    PubMed  Article  Google Scholar 

  35. 35.

    Zhong J, Ning R, Conover D. Image denoising based on multiscale singularity detection for cone beam CT breast imaging. IEEE Trans Med Imaging 2004;23:696–703.

    PubMed  Article  Google Scholar 

  36. 36.

    Chen Z, Ning R. Why should breast tumour detection go three dimensional? Phys Med Biol 2003;48:2217–28.

    PubMed  Article  Google Scholar 

  37. 37.

    Chen B, Ning R. Cone-beam volume CT breast imaging: feasibility study. Med Phys 2002;29:755–70.

    PubMed  Article  Google Scholar 

  38. 38.

    Thacker SC, Glick SJ. Normalized glandular dose (DgN) coefficients for flat-panel CT breast imaging. Phys Med Biol 2004;49:5433–44.

    PubMed  Article  Google Scholar 

  39. 39.

    Gong X, Vedula AA, Glick SJ. Microcalcification detection using cone-beam CT mammography with a flat-panel imager. Phys Med Biol 2004;49:2183–95.

    PubMed  Article  Google Scholar 

  40. 40.

    Brzymialkiewicz CN, Tornai MP, McKinley RL, Bowsher JE. Evaluation of fully 3-D emission mammotomography with a compact cadmium zinc telluride detector. IEEE Trans Med Imaging 2005;24:868–77.

    PubMed  Article  Google Scholar 

  41. 41.

    McKinley RL, Tornai MP, Samei E, Bradshaw ML. Simulation study of a quasi-monochromatic beam for X-ray computed mammotomography. Med Phys 2004;31:800–13.

    PubMed  Article  Google Scholar 

  42. 42.

    Tornai MP, Bowsher JE, Jaszczak RJ, Pieper BC, Greer KL, Hardenbergh PH, et al. Mammotomography with pinhole incomplete circular orbit SPECT. J Nucl Med 2003;44:583–93.

    PubMed  Google Scholar 

  43. 43.

    Tu SJ, Shaw CC, Chen L. Noise simulation in cone beam CT imaging with parallel computing. Phys Med Biol 2006;51:1283–97.

    PubMed  Article  Google Scholar 

  44. 44.

    Suryanarayanan S, Karellas A, Vedantham S, Glick SJ, D’Orsi CJ, Baker SP, et al. Comparison of tomosynthesis methods used with digital mammography. Acad Radiol 2000;7:1085–97.

    PubMed  CAS  Article  Google Scholar 

  45. 45.

    Raptopoulos V, Baum JK, Hochman M, Karellas A, Houlihan MJ, D’Orsi CJ. High resolution CT mammography of surgical biopsy specimens. J Comput Assist Tomogr 1996;20:179–84.

    PubMed  CAS  Article  Google Scholar 

  46. 46.

    Gisvold JJ, Reese DF, Karsell PR. Computed tomographic mammography (CTM). AJR Am J Roentgenol 1979;133:1143–9.

    PubMed  CAS  Google Scholar 

  47. 47.

    McLeod RA, Gisvold JJ, Stephens DH, Beabout JW, Sheedy PF. Computed tomography of soft tissues and breast. Semin Roentgenol 1978;13:267–75.

    PubMed  CAS  Article  Google Scholar 

  48. 48.

    Gisvold JJ, Karsell PR, Reese EC. Clinical evaluation of computerized tomographic mammography. Mayo Clin Proc 1977;52:181–5.

    PubMed  CAS  Google Scholar 

  49. 49.

    Niklason LT, Christian BT, Niklason LE, Kopans DB, Castleberry DE, Opsahl-Ong BH, et al. Digital tomosynthesis in breast imaging. Radiology 1997;205:399–406.

    PubMed  CAS  Google Scholar 

  50. 50.

    Smith A. Full-field breast tomosynthesis. Radiol Manage 2005;27:25–31.

    PubMed  Google Scholar 

  51. 51.

    Wu T, Moore RH, Rafferty EA, Kopans DB. A comparison of reconstruction algorithms for breast tomosynthesis. Med Phys 2004;31:2636–47.

    PubMed  Article  Google Scholar 

  52. 52.

    Reiser I, Nishikawa RM, Giger ML, Wu T, Rafferty E, Moore RH, et al. Computerized detection of mass lesions in digital breast tomosynthesis images using two- and three dimensional radial gradient index segmentation. Technol Cancer Res Treat 2004;3:437–41.

    PubMed  CAS  Google Scholar 

  53. 53.

    Boone JM, Nelson TR, Lindfors KK, Seibert JA. Dedicated breast CT: radiation dose and image quality evaluation. Radiology 2001;221:657–67.

    PubMed  CAS  Google Scholar 

  54. 54.

    Boone JM, Shah N, Nelson TR. A comprehensive analysis of DgN (CT) coefficients for pendant-geometry cone-beam breast computed tomography. Med Phys 2004;31:226–35.

    PubMed  CAS  Article  Google Scholar 

  55. 55.

    Boone JM, Kwan AL, Seibert JA, Shah N, Lindfors KK, Nelson TR. Technique factors and their relationship to radiation dose in pendant geometry breast CT. Med Phys 2005;32:3767–76.

    PubMed  Article  Google Scholar 

  56. 56.

    Kwan AL, Boone JM, Shah N. Evaluation of X-ray scatter properties in a dedicated cone-beam breast CT scanner. Med Phys 2005;32:2967–75.

    PubMed  Article  Google Scholar 

  57. 57.

    Boone JM. Normalized glandular dose (DgN) coefficients for arbitrary X-ray spectra in mammography: computer-fit values of Monte Carlo derived data. Med Phys 2002;29:869–75.

    PubMed  Article  Google Scholar 

  58. 58.

    Kriege M, Brekelmans CT, Boetes C, Besnard PE, Zonderland HM, Obdeijn IM, et al. Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition. N Engl J Med 2004;351:427–37.

    PubMed  CAS  Article  Google Scholar 

Download references

Acknowledgments

This work was funded in part by grants from the National Cancer Institute (CA 89260) the National Institute for Biomedical Imaging and Bioengineering (EB 002138), and the California Breast Cancer Research Program (11-1B-0114).

Author information

Affiliations

Authors

Corresponding author

Correspondence to John M. Boone.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Boone, J.M., Kwan, A.L.C., Yang, K. et al. Computed Tomography for Imaging the Breast. J Mammary Gland Biol Neoplasia 11, 103–111 (2006). https://doi.org/10.1007/s10911-006-9017-1

Download citation

Keywords

  • Mammography
  • Cancer
  • Computed tomography
  • Radiation
  • Technology