Abstract
Purpose
The authors sought to assess interobserver agreement in classifying mammography density according to quantitative Breast Imaging Reporting and Data System (BI-RADS) criteria.
Materials and methods
Six expert mammography readers were tested on a set of 100 mammograms. Interobserver agreement was determined according to the kappa statistic, adjusting for chance agreement, on a four-category (D1 vs. D2 vs. D3 vs. D4) or two-category (D1–2 vs. D3–4) basis. Agreement with a panel of 12 readers who had been tested on the same set in a previous study was also assessed.
Results
The six readers showed good agreement when compared in pairs [agreement on a four-category basis was substantial (kappa=0.60–0.80) for 13 pairs and almost perfect (kappa>0.80) for two pairs); agreement on a two-category basis was substantial for 12 pairs and almost perfect for three pairs) or compared with the panel (on a four-category basis, agreement was substantial for five of six readers and almost perfect for one; on a two-category basis, agreement was substantial for all readers).
Conclusions
In agreement with previous studies, visual classification of mammography density according to BI-RADS quantitative criteria was highly reproducible among readers; nevertheless, attribution to the “dense breast” (BI-RADS D3–4) category, which might be adopted as a determinant of different screening protocols (such as adjunct ultrasonography or yearly interval) varied among readers (range 6–15%). Controlled studies should be performed comparing visual with computer-density category attribution, the latter possibly being a better alternative due to its absolute reproducibility.
Riassunto
Obiettivo
Scopo del presente lavoro è stato verificare la riproducibilità interosservatore nel classificare la densità mammografica in base ai criteri della classificazione quantitative Breast Imaging Reporting and Data System (BI-RADS).
Materiali e metodi
Sei lettori esperti di mammografia sono stati testati su un set di 100 mammografie. La concordanza interosservatore è stata valutata mediante la statistica kappa, che aggiusta per la concordanza casuale, rispetto a quattro (D1 vs. D2 vs. D3 vs. D4) o due categorie (D1–2 vs. D3–4). È stata verificata anche la concordanza con un panel di 12 lettori che avevano valutato lo stesso set di mammografie in uno studio precedente.
Risultati
I sei lettori hanno mostrato una buona concordanza quando confrontati in coppie (concordanza sulla base di quattro categorie sostanziale (kappa=0,60–0,80) per 13 coppie e quasi perfetta (kappa>0,80) per due coppie; concordanza sulla base di due categorie sostanziale per 12 coppie, quasi perfetta per tre) o rispetto al panel (concordanza sulla base di quattro categorie sostanziale per 5/6 lettori e quasi perfetta per un lettore; concordanza sulla base di due categorie sostanziale per tutti i lettori).
Conclusioni
In accordo con precedenti studi la classificazione visuale della densità mammografica secondo i criteri BI-RADS è risultata altamente riproducibile tra i diversi lettori: ciò nonostante l’attribuzione della categoria seno denso (BI-RADS D3–4), che potrebbe essere adottata come determinante di protocolli di screening differenziati (aggiunta dell’ecografia, frequenza annuale) varia tra i lettori (in questo studio dal 6% al 15%). Necessitano studi controllati che confrontino la classificazione visuale con quella computerizzata, potendo quest’ultima essere una valida alternativa per la sua riproducibilità assoluta.
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References/Bibliografia
Wolfe JN (1976) Risk for breast cancer development determined by mammographic parenchimal pattern. Cancer 37:2486–2492
Ciatto S, Zappa M (1993) A prospective study of the value of mammographic patterns as indicators of breast cancer risk in a screening experience. Eur J Radiol 17:122–125
Brisson J, Diorio C, Masse B, (2003) Wolfe’s parenchymal pattern and percentage of the breast with mammographic densities: redundant or complementary classification? Cancer epidemiol Biomarkers Prev 12:728–732
Vachon CM, Kuni CC, Anderson K et al (2000) Association of mammographic defined percent breast density with epidemiologic risk factors for breast cancer (United States). Cancer Causes Control 11:653–662
Boyd NF, Dite GS, Stone J et al (2002) Heritability of mammographic density, a risk factor for breast cancer. New engl J Med 347:886–894
Ursin G, Ma H, Wu H et al (2003) Mammographic density and breast cancer in three ethnic groups. Cancer epidemiol Biomarkers Prev 12:332–338
Chen Z, Wuy AH, Gauderman WJ et al (2004) Does mammographic density reflect ethnic differences in breast cancer incidence rates? Am J epidemiol 159:140–147
Egan RL, Mosteller RC (1977) Breast cancer mammography patterns. Cancer 40:2087–2090
Ciatto S, Visioli C, Paci e, Zappa M (2004) Breast density as a determinant of interval cancer at mammographic screening. Br J Cancer 90:393–396
Peeters PH, Verbeek AL, Hendriks JH et al (1989) The occurrence of interval cancers in the Nijmegen screening programme. Br J Cancer 59:929–932
Young K, Wallis M, Blank R, Moss S (1997) Influence of number of views and mammographic film density on the detection of invasive cancers: results from the NHS Breast Screening Programme. Br J Radiol 70:482–488
Buist DSM, Porter PL, Lehman C et al (2004) Factors contributing to mammography failure in women aged 40–49 years. J Natl Cancer Inst 96:1432–1440
Caumo F, Vecchiato F, Pellegrini M et al (2009) Analysis of interval cancers observed in an Italian mammography screening programme (2000–2006). Radiol Med 114:907–914
Caumo F, Brunelli S, Zorzi M et al (2011) Benefits of double reading of screening mammograms: retrospective study on a consecutive series. Radiol Med 116:575–583
American College of Radiology (2003) The ACR Breast Imaging Reporting and Data System (BI-RADS American College of Radiology, Reston
Ciatto S, Bonardi R, Zappa M (2001) Impact of replacement hormone therapy in menopause on breast radiologic density and possible complications of mammography in the assessment of breast masses. Radiol Med 101:39–43
Boyd NF, Wolfson C, Moskowitz M et al (1986) Observer variation in the classification pf mammographic parenchymal patterns. J Chroinic Dis 39:465–472
Berg WA, Campassi C, Langenberg P, Sexton MJ (2000) Breast imaging reporting and data system: inter- and intraobserver variability in feature analysis and final assessment. AJR Am J Roentgenol 174:1769–1777
Vachon CM, Sellers TA, Vierkant RA et al (2002) Case control study of increased mammographic breast density response to hormone replacement therapy. Cancer epidemiol Biomarkers Prev 11:1382–1388
Zhou C, Chan HP, Petrick N et al (2001) Computerized image analysis estimation of breast density on mammograms. Med Phys 28:1056–1069
Ciatto S, Houssami N, Apruzzese A et al (2005) Categorizing breast mammographic density: intra- and interobserver reproducibility of BI-RADS density categories. Breast 14:269–275
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174
Rosselli Del Turco M, Mantellini P, Ciatto S et al (2007) Full-field digital versus screen-film mammography: comparative accuracy in concurrent screening cohorts. AJR Am J Roetgenol 189:860–866
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
Berg WA, Blume JD, Cormack JB et al (2008) Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. J Am Med Ass 299:2151–2163
Corsetti V, Houssami N, Ferrari A et al (2008) Breast screening with ultrasound in women with mammography-negative dense breasts: evidence on incremental cancer detection and false positives, and associated cost. Eur J Cancer 44:539–544
Corsetti V, Houssami N, Ghirardi M et al (2011) evidence of the effect of adjunct ultrasound screening in women with mammography-negative dense breasts: Interval breast cancers at 1year follow-up. eur J Cancer 47:1021–1026
Rafferty E, Smith A, Niklason L (2009) Comparison of three methods of estimating breast density: BI-RADS density scores using full field digital mammography, breast tomosynthesis, and volumetric breast density. Proffered paper at Rad Soc North Am, Chicago, USA: ssM01
Tuncbilek N, Sezer A, Uğr U et al (2009) Qualitative and quantitative analysis of fibroglandular tissue in the digital environment. Proffered paper at 10th National Congress of Breast Diseases, Izmir, Turkey
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Bernardi, D., Pellegrini, M., Di Michele, S. et al. Interobserver agreement in breast radiological density attribution according to BI-RADS quantitative classification. Radiol med 117, 519–528 (2012). https://doi.org/10.1007/s11547-011-0777-3
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DOI: https://doi.org/10.1007/s11547-011-0777-3