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Diagnostic performance of a near-infrared breast imaging system as adjunct to mammography versus X-ray mammography alone

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Abstract

Objectives

Radiologist reader performance for breast cancer detection using mammography plus Near-Infrared Breast Imaging (NIBI) was compared with mammography alone.

Methods

Two hundred seventy-six consecutive patients with suspected breast lesions underwent both mammography and NIBI. Four blinded radiologists independently first reviewed the mammograms alone. Readers subsequently reviewed the mammograms in combination with NIBI. The diagnostic benefit of NIBI as an adjunct to mammography was determined by performing receiver operating characteristics (ROC) analyses for each reader based on BI-RADS categories (Breast Imaging Reporting and Data System) and LOS (level of suspicion) scores. Additionally, a multireader-multicase (ROC) analysis of variance (ANOVA) was carried out.

Results

For the LOS-based analysis, the combination of mammography and NIBI resulted in a slightly larger area under the curve (AUC) for all four readers. The analysis based on BI-RADS categories also demonstrated a slight increase in AUC for three readers for the combination of mammography and NIBI compared with mammography alone. For the fourth reader, AUC was smaller for the combination compared with mammography alone. Neither for the separate ROC-analyses nor for the ANOVA, significant differences between the two methods were obtained.

Conclusions

The combination of mammography and NIBI did not perform significantly better than mammography alone.

Key Points

  • The intrinsic contrast provided by optical breast imaging may be inadequate

  • We found slightly (but nonsignificant) higher accuracy for optical imaging and mammography compared with mammography alone.

  • Contrast agents might be necessary to improve the performance of optical breast imaging

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References

  1. Jemal A, Siegel R, Ward E et al (2008) Cancer statistics, 2008. CA Canc J Clin 58:71–96

    Article  Google Scholar 

  2. Kalager M, Zelen M, Langmark F, Adami HO (2010) Effect of screening mammography on breast-cancer mortality in Norway. N Engl J Med 363:1203–1210

    Article  PubMed  CAS  Google Scholar 

  3. Tabar L, Duffy SW, Yen MF et al (2002) All-cause mortality among breast cancer patients in a screening trial: support for breast cancer mortality as an end point. J Med Screen 9:159–162

    Article  PubMed  CAS  Google Scholar 

  4. Otto SJ, Fracheboud J, Looman CW et al (2003) Initiation of population-based mammography screening in Dutch municipalities and effect on breast-cancer mortality: a systematic review. Lancet 361:1411–1417

    Article  PubMed  Google Scholar 

  5. Pisano ED, Gatsonis C, Hendrick E et al (2005) Diagnostic performance of digital versus film mammography for breast-cancer screening. N Engl J Med 353:1773–1783

    Article  PubMed  CAS  Google Scholar 

  6. Pisano ED, Hendrick RE, Yaffe MJ et al (2008) Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST. Radiology 246:376–383

    Article  PubMed  Google Scholar 

  7. Kuhl CK, Schrading S, Leutner CC et al (2005) Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer. J Clin Oncol 23:8469–8476

    Article  PubMed  Google Scholar 

  8. Hoey J (2002) Mammography screening among women aged 40–49 years shows no benefit. CMAJ 167:898

    PubMed  Google Scholar 

  9. (2009) Screening for breast cancer: U.S. preventive services task force recommendation statement. Ann Intern Med 151: 716–726

  10. Fredholm H, Eaker S, Frisell J, Holmberg L, Fredriksson I, Lindman H (2009) Breast cancer in young women: poor survival despite intensive treatment. PLoS One 4:e7695

    Article  PubMed  Google Scholar 

  11. Flobbe K, Bosch AM, Kessels AG et al (2003) The additional diagnostic value of ultrasonography in the diagnosis of breast cancer. Arch Intern Med 163:1194–1199

    Article  PubMed  Google Scholar 

  12. Bedrosian I, Mick R, Orel SG et al (2003) Changes in the surgical management of patients with breast carcinoma based on preoperative magnetic resonance imaging. Cancer 98:468–473

    Article  PubMed  Google Scholar 

  13. Brown ML, Houn F, Sickles EA, Kessler LG (1995) Screening mammography in community practice: positive predictive value of abnormal findings and yield of follow-up diagnostic procedures. AJR Am J Roentgenol 165:1373–1377

    PubMed  CAS  Google Scholar 

  14. Poplack SP, Tosteson AN, Grove MR, Wells WA, Carney PA (2000) Mammography in 53,803 women from the New Hampshire mammography network. Radiology 217:832–840

    PubMed  CAS  Google Scholar 

  15. Weissleder R, Pittet MJ (2008) Imaging in the era of molecular oncology. Nature 452:580–589

    Article  PubMed  CAS  Google Scholar 

  16. Tromberg BJ, Shah N, Lanning R et al (2000) Non-invasive in vivo characterization of breast tumors using photon migration spectroscopy. Neoplasia 2:26–40

    Article  PubMed  CAS  Google Scholar 

  17. Floery D, Helbich TH, Riedl CC et al (2005) Characterization of benign and malignant breast lesions with computed tomography laser mammography (CTLM): initial experience. Invest Radiol 40:328–335

    Article  PubMed  Google Scholar 

  18. Rinneberg H, Grosenick D, Moesta KT et al (2005) Scanning time-domain optical mammography: detection and characterization of breast tumors in vivo. Tech Canc Res Treat 4:483–496

    Google Scholar 

  19. Cerussi A, Hsiang D, Shah N et al (2007) Predicting response to breast cancer neoadjuvant chemotherapy using diffuse optical spectroscopy. Proc Natl Acad Sci U S A 104:4014–4019

    Article  PubMed  CAS  Google Scholar 

  20. Poellinger A, Martin JC, Ponder SL et al (2008) Near-infrared laser computed tomography of the breast first clinical experience. Acad Radiol 15:1545–1553

    Article  PubMed  Google Scholar 

  21. Dorfman DD, Berbaum KS, Metz CE (1992) Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method. Invest Radiol 27:723–731

    Article  PubMed  CAS  Google Scholar 

  22. Dorfman DD, Berbaum KS, Lenth RV, Chen YF, Donaghy BA (1998) Monte Carlo validation of a multireader method for receiver operating characteristic discrete rating data: factorial experimental design. Acad Radiol 5:591–602

    Article  PubMed  CAS  Google Scholar 

  23. Hillis SL, Berbaum KS (2005) Monte Carlo validation of the Dorfman-Berbaum-Metz method using normalized pseudovalues and less data-based model simplification. Acad Radiol 12:1534–1541

    Article  PubMed  Google Scholar 

  24. Hillis SL, Berbaum KS (2004) Power estimation for the Dorfman-Berbaum-Metz method. Acad Radiol 11:1260–1273

    Article  PubMed  Google Scholar 

  25. Hillis SL, Berbaum KS, Metz CE (2008) Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis. Acad Radiol 15:647–661

    Article  PubMed  Google Scholar 

  26. Hillis SL (2007) A comparison of denominator degrees of freedom methods for multiple observer ROC analysis. Stat Med 26:596–619

    Article  PubMed  Google Scholar 

  27. Cerussi A, Shah N, Hsiang D, Durkin A, Butler J, Tromberg BJ (2006) In vivo absorption, scattering, and physiologic properties of 58 malignant breast tumors determined by broadband diffuse optical spectroscopy. J Biomed Opt 11:044005

    Article  PubMed  Google Scholar 

  28. Zhu Q, Hegde PU, Ricci A Jr et al (2010) Early-stage invasive breast cancers: potential role of optical tomography with US localization in assisting diagnosis. Radiology 256:367–378

    Article  PubMed  Google Scholar 

  29. Fang Q, Selb J, Carp SA et al (2011) Combined optical and X-ray tomosynthesis breast imaging. Radiology 258:89–97

    Article  PubMed  Google Scholar 

  30. Wells WA, Daghlian CP, Tosteson TD et al (2004) Analysis of the microvasculature and tissue type ratios in normal vs. benign and malignant breast tissue. Anal Quant Cytol Histol 26:166–174

    PubMed  Google Scholar 

  31. You SS, Jiang YX, Zhu QL et al (2010) US-guided diffused optical tomography: a promising functional imaging technique in breast lesions. Eur Radiol 20:309–317

    Article  PubMed  Google Scholar 

  32. Corlu A, Choe R, Durduran T et al (2007) Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans. Opt Express 15:6696–6716

    Article  PubMed  Google Scholar 

  33. Alacam B, Yazici B, Intes X, Nioka S, Chance B (2008) Pharmacokinetic-rate images of indocyanine green for breast tumors using near-infrared optical methods. Phys Med Biol 53:837–859

    Article  PubMed  Google Scholar 

  34. Poellinger A, Burock S, Grosenick D et al (2011) Breast cancer: early- and late-fluorescence near-infrared imaging with indocyanine green—a preliminary study. Radiology 258:409–416

    Article  PubMed  Google Scholar 

  35. van de Ven SM, Elias SG, Wiethoff AJ et al (2009) Diffuse optical tomography of the breast: preliminary findings of a new prototype and comparison with magnetic resonance imaging. Eur Radiol 19:1108–1113

    Article  PubMed  Google Scholar 

  36. van de Ven S, Elias S, Wiethoff A et al (2009) Diffuse optical tomography of the breast: initial validation in benign cysts. Mol Imag Biol 11:64–70

    Article  Google Scholar 

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Acknowledgement

S. Pinder is Director of Advanced Development, Imaging Diagnostic Systems, Inc., Fort Lauderdale, Florida, USA.

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Authors and Affiliations

  1. Department of Radiology, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany

    F. Collettini, J. C. Martin, F. Diekmann, E. Fallenberg, F. Engelken, T. J. Kroencke, B. Hamm & A. Poellinger

  2. Imaging Diagnostic Systems, Inc, 5307 NW 35th Terrace, Fort Lauderdale, FL, 33309, USA

    S. Ponder

  3. Department of Radiology, Charité, Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany

    A. Poellinger

Authors
  1. F. Collettini
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  2. J. C. Martin
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  4. E. Fallenberg
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  5. F. Engelken
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  6. S. Ponder
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  7. T. J. Kroencke
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  8. B. Hamm
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  9. A. Poellinger
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Correspondence to A. Poellinger.

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Collettini, F., Martin, J.C., Diekmann, F. et al. Diagnostic performance of a near-infrared breast imaging system as adjunct to mammography versus X-ray mammography alone. Eur Radiol 22, 350–357 (2012). https://doi.org/10.1007/s00330-011-2276-2

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  • DOI: https://doi.org/10.1007/s00330-011-2276-2

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