Can Radiologists Predict the Presence of Ductal Carcinoma In Situ and Invasive Breast Cancer?
| Autor: | Colin J. Wells, Shadi Aminololama-Shakeri, Joan E. Campbell, Haydee Ojeda-Fournier, Jonathan B Hargreaves, Karen Gerlach, Dorota J. Wisner, Sarah L. Elson, Hanna Retallack, Stephen A. Feig, Jade de Guzman, Chris I. Flowers, Lawrence W. Bassett, Christine E. McLaren, Bonnie N. Joe |
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| Rok vydání: | 2017 |
| Předmět: |
Adult
Oncology medicine.medical_specialty Digital mammography Breast Neoplasms BI-RADS Sensitivity and Specificity Article California 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Breast cancer Internal medicine Radiologists Prevalence Humans Medicine Neoplasm Invasiveness Radiology Nuclear Medicine and imaging skin and connective tissue diseases Aged Aged 80 and over Observer Variation Invasive carcinoma Receiver operating characteristic business.industry Carcinoma Ductal Breast Ultrasound Reproducibility of Results General Medicine Middle Aged Ductal carcinoma medicine.disease 030220 oncology & carcinogenesis Female Clinical Competence Radiology business |
| Zdroj: | AJR Am J Roentgenol |
| ISSN: | 1546-3141 0361-803X |
| DOI: | 10.2214/ajr.16.16073 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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