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Wisner DJ, Feig S, Joe B, Hargreaves J, Ojeda-Fournier H, Bassett L, Aminololama-Shakeri S, DeGuzman JQ, Flowers CI, Campbell JE, Elson S, Retallack H, Wells C. Abstract P2-01-06: How much agreement can we expect on BI-RADS mammographic findings? Observer agreement among 10 expert mammographers. Cancer Res 2013. [DOI: 10.1158/0008-5472.sabcs13-p2-01-06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Purpose: To determine the agreement between expert readers on mammographic findings and calcification patterns.
Materials and Methods: Ten academic radiologists from 5 centers reviewed 250 de-identified mammographic cases without prior exams which were previously assessed as BI-RADS 4 or 5 with subsequent pathologic diagnosis by percutaneous or surgical biopsy. For benign cases diagnosed by percutaneous biopsy, 1 year of benign or negative imaging follow-up was required. Using standardized forms, each radiologist assessed the presence of any suspicious mammographic findings (microcalcifications, asymmetry (1-vew), focal asymmetry (2-view), architectural distortion), and the morphology (none, round/punctate, amorphous, coarse heterogeneous, fine pleomorphic, fine linear branching) and distribution (none, diffuse, regional, grouped, linear, segmental) of any identified microcalcifications. Agreement between radiologists for presence/absence of findings, morphology, and distribution of calcifications was determined by calculating the Kappa (k) coefficient with 95% confidence interval (95% CI). The kappa coefficient proposed strength of agreement is ≤0 = poor, .01-.20 = slight, .21-.40 = fair, .41-.60 = moderate, .61-.80 = substantial, and .81-1 = almost perfect, as established by Landis and Koch.1
Results: Of the 250 lesions, 156 (62%) were benign and 94 (38%) malignant. Agreement among the 10 expert readers was strongest for recognizing the presence/absence of calcifications (k = 0.82, 95% CI: 0.80-84), “almost perfect”). There was substantial agreement among the readers for the identification of a mass (k = 0.67, 95% CI: 0.66-69), whereas agreement was fair for the presence of a focal (2-view) asymmetry (k = 0.21, 95% CI: 0.1900.23) or architectural distortion (k = 0.28, 95%CI: 0.26-0.30). Agreement for asymmetries (1-view) was slight (k = 0.09, 95%CI: 0.08-0.11). Among the 6 categories of microcalcification distribution and morphology, reader agreement was moderate (distribution k = 0.60, 95%CI:0.59-0.61; morphology k = 0.51, 95%CI: 0.50-0.52).
Conclusion: When asked to characterize suspicious mammographic findings, this sampling of 10 expert academic breast imagers across 5 centers revealed varying strength of agreement for different findings, ranging from slight to almost perfect. Strongest agreement (“almost perfect”) was found for identifying the presence or absence of microcalcifications, although agreement drops to moderate when readers are asked to specify microcalcification morphology and distribution.
1 Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics.1977;33:159-174.
Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P2-01-06.
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Affiliation(s)
- DJ Wisner
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - S Feig
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - B Joe
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - J Hargreaves
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - H Ojeda-Fournier
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - L Bassett
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - S Aminololama-Shakeri
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - JQ DeGuzman
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - CI Flowers
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - JE Campbell
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - S Elson
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - H Retallack
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
| | - C Wells
- University of California, San Francisco, San Francisco, CA; University of California, Irvine, Irvine, CA; University of California, Davis, Davis, CA; University of California, San Diego, San Diego, CA; University of California, Los Angeles, Los Angeles, CA; Cancer Imaging Advisors, Tampa, FL
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Boone J, Chen L, Nosratieh A, Abbey C, Lindfors K, Aminololama-Shakeri S, Seibert J. TU-E-217BCD-03: Characterization of Anatomical Noise in Mammography, Tomosynthesis and Breast CT. Med Phys 2012; 39:3914. [PMID: 28518664 DOI: 10.1118/1.4735975] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE The role of breast density in cancer detection has been well characterized, and newer modalities such as breast tomosynthesis and breast CT (bCT) were developed to improve cancer detection in the dense breast by reducing anatomical complexity. Anatomical noise was characterized on a small cohort of patient images and compared across digital mammography, tomosynthesis, and bCT images. METHODS AND MATERIALS An IRB-approved and HIPPA-compliant clinical study was performed on women undergoing breast biopsy, and mammography, tomosynthesis, and bCT were performed on both breasts immediately prior to biopsy. A total of 23 women participated in this study, and the unaffected breast (no lesion) was evaluated. A total of 1000 regions of interest were sampled on each image data set, and the 2D noise power spectrum (NPS) was evaluated. This was radially averaged to produce a 1D NPS, and the NPS was fit to a power law: ln{NPS(f)} = alpha+betaxln(f), over an anatomically-relevant range of spatial frequencies. The slope, beta, was averaged across patients and compared between modalities and projections. RESULTS The value of beta was determined for bCT data sets, and they were 1.75 (0.424), 1.83 (0.352), and 1.79 (0.397), for the coronal, sagittal and axial views, respectively. For tomosynthesis, beta was 3.06 (0.361) and 3.10 (0.315) for the CC and MLO views, respectively. For mammography, these values were 3.17 (0.226) and 3.30 (0.236), for the CC and MLO views, respectively. The values of beta for breast CT were significantly different than those for tomosynthesis and mammography (p<0.001, all 12 comparisons). CONCLUSIONS The results of this investigation demonstrate that the anatomical complexity of the breast, as characterized by the parameter beta, is statistically similar between mammography and tomosynthesis, a somewhat surprising finding. The breast CT image data, however, demonstrate a statistically-significant reduction in beta across all projections. Funded in part by Hologic Corporation and by a grant from the National Institute of Biomedical Imaging and Bioengineering, EB002138.
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Affiliation(s)
- J Boone
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
| | - L Chen
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
| | - A Nosratieh
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
| | - C Abbey
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
| | - K Lindfors
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
| | - S Aminololama-Shakeri
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
| | - J Seibert
- UC Davis Medical Center, Sacramento, CA.,University of California, Davis, Sacramento, California.,University of California, Davis, Sacramento, CA.,University of California, Santa Barbara, CA.,University of California Davis, Sacramento, California.,University of California, Davis, Sacramento, California.,UC Davis Medical Center, Sacramento, CA
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