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.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: 1 Department of Radiology, University of California Davis, 4860 Y St, Ste 3100, Sacramento, CA 95817.
authors.forename: Shadi
authors.initials: S
authors.lastname: Aminololama-Shakeri
authors.affiliation: 2 Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA.|3 Present address: Moffitt Cancer Center, Tampa, FL.
authors.forename: Chris I
authors.initials: CI
authors.lastname: Flowers
authors.affiliation: 4 Department of Epidemiology, University of California, Irvine, CA.
authors.forename: Christine E
authors.initials: CE
authors.lastname: McLaren
authors.affiliation: 5 Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.|6 Present address: Kaiser Permanente, San Rafael, CA.
authors.forename: Dorota J
authors.initials: DJ
authors.lastname: Wisner
authors.affiliation: 7 Department of Radiology, University of California, San Diego, CA.
authors.forename: Jade
authors.initials: J
authors.lastname: de Guzman
authors.affiliation: 8 Department of Radiological Sciences, University of California, Irvine, CA.
authors.forename: Joan E
authors.initials: JE
authors.lastname: Campbell
authors.affiliation: 9 Breast Imaging Section, Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, CA.
authors.forename: Lawrence W
authors.initials: LW
authors.lastname: Bassett
authors.affiliation: 7 Department of Radiology, University of California, San Diego, CA.
authors.forename: Haydee
authors.initials: H
authors.lastname: Ojeda-Fournier
authors.affiliation: 8 Department of Radiological Sciences, University of California, Irvine, CA.|10 Present address: The University of Texas MD Anderson Cancer Center, Houston, TX.
authors.forename: Karen
authors.initials: K
authors.lastname: Gerlach
authors.affiliation: 1 Department of Radiology, University of California Davis, 4860 Y St, Ste 3100, Sacramento, CA 95817.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Hargreaves
authors.affiliation: 5 Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.|11 Present address: 23andMe, Inc., Mountain View, CA.
authors.forename: Sarah L
authors.initials: SL
authors.lastname: Elson
authors.affiliation: 5 Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
authors.forename: Hanna
authors.initials: H
authors.lastname: Retallack
authors.affiliation: 5 Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
authors.forename: Bonnie N
authors.initials: BN
authors.lastname: Joe
authors.affiliation: 8 Department of Radiological Sciences, University of California, Irvine, CA.
authors.forename: Stephen A
authors.initials: SA
authors.lastname: Feig
authors.affiliation: 9 Breast Imaging Section, Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, CA.
authors.forename: Colin J
authors.initials: CJ
authors.lastname: Wells
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology*; D002140:California / Q000453:epidemiology; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging* / Q000473:pathology*; D002983:Clinical Competence / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D015588:Observer Variation; D015995:Prevalence; D000072177:Radiologists / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: BI-RADS; ROC curves; breast cancer; digital mammography; ductal carcinoma in situ; invasive breast cancer; kappa coefficients