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Can Radiologists Predict the Presence of Ductal Carcinoma In Situ and Invasive Breast Cancer?
Aminololama-Shakeri, Shadi; Flowers, Chris I; McLaren, Christine E; Wisner, Dorota J; de Guzman, Jade; Campbell, Joan E; Bassett, Lawrence W; Ojeda-Fournier, Haydee; Gerlach, Karen; Hargreaves, Jonathan; Elson, Sarah L; Retallack, Hanna; Joe, Bonnie N; Feig, Stephen A; Wells, Colin J.
Afiliação
  • Aminololama-Shakeri S; 1 Department of Radiology, University of California Davis, 4860 Y St, Ste 3100, Sacramento, CA 95817.
  • Flowers CI; 2 Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA.
  • McLaren CE; 3 Present address: Moffitt Cancer Center, Tampa, FL.
  • Wisner DJ; 4 Department of Epidemiology, University of California, Irvine, CA.
  • de Guzman J; 5 Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
  • Campbell JE; 6 Present address: Kaiser Permanente, San Rafael, CA.
  • Bassett LW; 7 Department of Radiology, University of California, San Diego, CA.
  • Ojeda-Fournier H; 8 Department of Radiological Sciences, University of California, Irvine, CA.
  • Gerlach K; 9 Breast Imaging Section, Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, CA.
  • Hargreaves J; 7 Department of Radiology, University of California, San Diego, CA.
  • Elson SL; 8 Department of Radiological Sciences, University of California, Irvine, CA.
  • Retallack H; 10 Present address: The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Joe BN; 1 Department of Radiology, University of California Davis, 4860 Y St, Ste 3100, Sacramento, CA 95817.
  • Feig SA; 5 Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
  • Wells CJ; 11 Present address: 23andMe, Inc., Mountain View, CA.
AJR Am J Roentgenol ; 208(4): 933-939, 2017 Apr.
Article em En | MEDLINE | ID: mdl-28199152
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Competência Clínica / Carcinoma Ductal de Mama / Radiologistas Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Competência Clínica / Carcinoma Ductal de Mama / Radiologistas Idioma: En Ano de publicação: 2017 Tipo de documento: Article