Can radiologists predict the presence of ductal carcinoma in situ and invasive breast cancer?

ATHENA Breast Health Initiative

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

OBJECTIVE. We hypothesize that radiologists' estimated percentage likelihood assessments for the presence of ductal carcinoma in situ (DCIS) and invasive cancer may predict histologic outcomes. MATERIALS AND METHODS. Two hundred fifty cases categorized as BI-RADS category 4 or 5 at four University of California Medical Centers were retrospectively reviewed by 10 academic radiologists with a range of 1-39 years in practice. Readers assigned BI-RADS category (1, 2, 3, 4a, 4b, 4c, or 5), estimated percentage likelihood of DCIS or invasive cancer (0-100%), and confidence rating (1 = low, 5 = high) after reviewing screening and diagnostic mammograms and ultrasound images. ROC curves were generated. RESULTS. Sixty-two percent (156/250) of lesions were benign and 38% (94/250) were malignant. There were 26 (10%) DCIS, 20 (8%) invasive cancers, and 48 (19%) cases of DCIS and invasive cancer. AUC values were 0.830-0.907 for invasive cancer and 0.731-0.837 for DCIS alone. Sensitivity of 82% (56/68), specificity of 84% (153/182), positive predictive value (PPV) of 66% (56/85), negative predictive value (NPV) of 93% (153/165), and accuracy of 84% ([56 + 153]/250) were calculated using an estimated percentage likelihood of 20% or higher as the prediction threshold for invasive cancer for the radiologist with the highest AUC (0.907; 95% CI, 0.864-0.951). Every 20% increase in the estimated percentage likelihood of invasive cancer increased the odds of invasive cancer by approximately two times (odds ratio, 2.4). For DCIS, using a threshold of 40% or higher, sensitivity of 81% (21/26), specificity of 79% (178/224), PPV of 31% (21/67), NPV of 97% (178/183), and accuracy of 80% ([21 + 178]/250) were calculated. Similarly, these values were calculated at thresholds of 2% or higher (BI-RADS category 4) and 95% or higher (BI-RADS category 5) to predict the presence of malignancy. CONCLUSION. Using likelihood estimates, radiologists may predict the presence of invasive cancer with fairly high accuracy. Radiologist-assigned estimated percentage likelihood can predict the presence of DCIS, albeit with lower accuracy than that for invasive cancer.

Original languageEnglish (US)
Pages (from-to)933-939
Number of pages7
JournalAmerican Journal of Roentgenology
Volume208
Issue number4
DOIs
StatePublished - Apr 1 2017

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Carcinoma, Intraductal, Noninfiltrating
Breast Neoplasms
Neoplasms
Area Under Curve
Radiologists
ROC Curve
Ultrasonography
Odds Ratio

Keywords

  • BI-RADS
  • Breast cancer
  • Digital mammography
  • Ductal carcinoma in situ
  • Invasive breast cancer
  • Kappa coefficients
  • ROC curves

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Can radiologists predict the presence of ductal carcinoma in situ and invasive breast cancer? / ATHENA Breast Health Initiative.

In: American Journal of Roentgenology, Vol. 208, No. 4, 01.04.2017, p. 933-939.

Research output: Contribution to journalArticle

@article{fa2161704d5948e8af4fd73b719ada6c,
title = "Can radiologists predict the presence of ductal carcinoma in situ and invasive breast cancer?",
abstract = "OBJECTIVE. We hypothesize that radiologists' estimated percentage likelihood assessments for the presence of ductal carcinoma in situ (DCIS) and invasive cancer may predict histologic outcomes. MATERIALS AND METHODS. Two hundred fifty cases categorized as BI-RADS category 4 or 5 at four University of California Medical Centers were retrospectively reviewed by 10 academic radiologists with a range of 1-39 years in practice. Readers assigned BI-RADS category (1, 2, 3, 4a, 4b, 4c, or 5), estimated percentage likelihood of DCIS or invasive cancer (0-100{\%}), and confidence rating (1 = low, 5 = high) after reviewing screening and diagnostic mammograms and ultrasound images. ROC curves were generated. RESULTS. Sixty-two percent (156/250) of lesions were benign and 38{\%} (94/250) were malignant. There were 26 (10{\%}) DCIS, 20 (8{\%}) invasive cancers, and 48 (19{\%}) cases of DCIS and invasive cancer. AUC values were 0.830-0.907 for invasive cancer and 0.731-0.837 for DCIS alone. Sensitivity of 82{\%} (56/68), specificity of 84{\%} (153/182), positive predictive value (PPV) of 66{\%} (56/85), negative predictive value (NPV) of 93{\%} (153/165), and accuracy of 84{\%} ([56 + 153]/250) were calculated using an estimated percentage likelihood of 20{\%} or higher as the prediction threshold for invasive cancer for the radiologist with the highest AUC (0.907; 95{\%} CI, 0.864-0.951). Every 20{\%} increase in the estimated percentage likelihood of invasive cancer increased the odds of invasive cancer by approximately two times (odds ratio, 2.4). For DCIS, using a threshold of 40{\%} or higher, sensitivity of 81{\%} (21/26), specificity of 79{\%} (178/224), PPV of 31{\%} (21/67), NPV of 97{\%} (178/183), and accuracy of 80{\%} ([21 + 178]/250) were calculated. Similarly, these values were calculated at thresholds of 2{\%} or higher (BI-RADS category 4) and 95{\%} or higher (BI-RADS category 5) to predict the presence of malignancy. CONCLUSION. Using likelihood estimates, radiologists may predict the presence of invasive cancer with fairly high accuracy. Radiologist-assigned estimated percentage likelihood can predict the presence of DCIS, albeit with lower accuracy than that for invasive cancer.",
keywords = "BI-RADS, Breast cancer, Digital mammography, Ductal carcinoma in situ, Invasive breast cancer, Kappa coefficients, ROC curves",
author = "{ATHENA Breast Health Initiative} and Shadi Aminololama-Shakeri and Flowers, {Chris I.} and McLaren, {Christine E.} and Wisner, {Dorota J.} and {De Guzman}, Jade and Campbell, {Joan E.} and Bassett, {Lawrence W.} and Haydee Ojeda-Fournier and Karen Gerlach and Hargreaves, {Jonathan B} and Elson, {Sarah L.} and Hanna Retallack and Joe, {Bonnie N.} and Feig, {Stephen A.} and Wells, {Colin J.}",
year = "2017",
month = "4",
day = "1",
doi = "10.2214/AJR.16.16073",
language = "English (US)",
volume = "208",
pages = "933--939",
journal = "American Journal of Roentgenology",
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T1 - Can radiologists predict the presence of ductal carcinoma in situ and invasive breast cancer?

AU - ATHENA Breast Health Initiative

AU - Aminololama-Shakeri, Shadi

AU - Flowers, Chris I.

AU - McLaren, Christine E.

AU - Wisner, Dorota J.

AU - De Guzman, Jade

AU - Campbell, Joan E.

AU - Bassett, Lawrence W.

AU - Ojeda-Fournier, Haydee

AU - Gerlach, Karen

AU - Hargreaves, Jonathan B

AU - Elson, Sarah L.

AU - Retallack, Hanna

AU - Joe, Bonnie N.

AU - Feig, Stephen A.

AU - Wells, Colin J.

PY - 2017/4/1

Y1 - 2017/4/1

N2 - OBJECTIVE. We hypothesize that radiologists' estimated percentage likelihood assessments for the presence of ductal carcinoma in situ (DCIS) and invasive cancer may predict histologic outcomes. MATERIALS AND METHODS. Two hundred fifty cases categorized as BI-RADS category 4 or 5 at four University of California Medical Centers were retrospectively reviewed by 10 academic radiologists with a range of 1-39 years in practice. Readers assigned BI-RADS category (1, 2, 3, 4a, 4b, 4c, or 5), estimated percentage likelihood of DCIS or invasive cancer (0-100%), and confidence rating (1 = low, 5 = high) after reviewing screening and diagnostic mammograms and ultrasound images. ROC curves were generated. RESULTS. Sixty-two percent (156/250) of lesions were benign and 38% (94/250) were malignant. There were 26 (10%) DCIS, 20 (8%) invasive cancers, and 48 (19%) cases of DCIS and invasive cancer. AUC values were 0.830-0.907 for invasive cancer and 0.731-0.837 for DCIS alone. Sensitivity of 82% (56/68), specificity of 84% (153/182), positive predictive value (PPV) of 66% (56/85), negative predictive value (NPV) of 93% (153/165), and accuracy of 84% ([56 + 153]/250) were calculated using an estimated percentage likelihood of 20% or higher as the prediction threshold for invasive cancer for the radiologist with the highest AUC (0.907; 95% CI, 0.864-0.951). Every 20% increase in the estimated percentage likelihood of invasive cancer increased the odds of invasive cancer by approximately two times (odds ratio, 2.4). For DCIS, using a threshold of 40% or higher, sensitivity of 81% (21/26), specificity of 79% (178/224), PPV of 31% (21/67), NPV of 97% (178/183), and accuracy of 80% ([21 + 178]/250) were calculated. Similarly, these values were calculated at thresholds of 2% or higher (BI-RADS category 4) and 95% or higher (BI-RADS category 5) to predict the presence of malignancy. CONCLUSION. Using likelihood estimates, radiologists may predict the presence of invasive cancer with fairly high accuracy. Radiologist-assigned estimated percentage likelihood can predict the presence of DCIS, albeit with lower accuracy than that for invasive cancer.

AB - OBJECTIVE. We hypothesize that radiologists' estimated percentage likelihood assessments for the presence of ductal carcinoma in situ (DCIS) and invasive cancer may predict histologic outcomes. MATERIALS AND METHODS. Two hundred fifty cases categorized as BI-RADS category 4 or 5 at four University of California Medical Centers were retrospectively reviewed by 10 academic radiologists with a range of 1-39 years in practice. Readers assigned BI-RADS category (1, 2, 3, 4a, 4b, 4c, or 5), estimated percentage likelihood of DCIS or invasive cancer (0-100%), and confidence rating (1 = low, 5 = high) after reviewing screening and diagnostic mammograms and ultrasound images. ROC curves were generated. RESULTS. Sixty-two percent (156/250) of lesions were benign and 38% (94/250) were malignant. There were 26 (10%) DCIS, 20 (8%) invasive cancers, and 48 (19%) cases of DCIS and invasive cancer. AUC values were 0.830-0.907 for invasive cancer and 0.731-0.837 for DCIS alone. Sensitivity of 82% (56/68), specificity of 84% (153/182), positive predictive value (PPV) of 66% (56/85), negative predictive value (NPV) of 93% (153/165), and accuracy of 84% ([56 + 153]/250) were calculated using an estimated percentage likelihood of 20% or higher as the prediction threshold for invasive cancer for the radiologist with the highest AUC (0.907; 95% CI, 0.864-0.951). Every 20% increase in the estimated percentage likelihood of invasive cancer increased the odds of invasive cancer by approximately two times (odds ratio, 2.4). For DCIS, using a threshold of 40% or higher, sensitivity of 81% (21/26), specificity of 79% (178/224), PPV of 31% (21/67), NPV of 97% (178/183), and accuracy of 80% ([21 + 178]/250) were calculated. Similarly, these values were calculated at thresholds of 2% or higher (BI-RADS category 4) and 95% or higher (BI-RADS category 5) to predict the presence of malignancy. CONCLUSION. Using likelihood estimates, radiologists may predict the presence of invasive cancer with fairly high accuracy. Radiologist-assigned estimated percentage likelihood can predict the presence of DCIS, albeit with lower accuracy than that for invasive cancer.

KW - BI-RADS

KW - Breast cancer

KW - Digital mammography

KW - Ductal carcinoma in situ

KW - Invasive breast cancer

KW - Kappa coefficients

KW - ROC curves

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