Evaluation of an Automated Information Extraction Tool for Imaging Data Elements to Populate a Breast Cancer Screening Registry.
J Digit Imaging
; 28(5): 567-75, 2015 Oct.
Article
em En
| MEDLINE
| ID: mdl-25561069
ABSTRACT
Breast cancer screening is central to early breast cancer detection. Identifying and monitoring process measures for screening is a focus of the National Cancer Institute's Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) initiative, which requires participating centers to report structured data across the cancer screening continuum. We evaluate the accuracy of automated information extraction of imaging findings from radiology reports, which are available as unstructured text. We present prevalence estimates of imaging findings for breast imaging received by women who obtained care in a primary care network participating in PROSPR (n = 139,953 radiology reports) and compared automatically extracted data elements to a "gold standard" based on manual review for a validation sample of 941 randomly selected radiology reports, including mammograms, digital breast tomosynthesis, ultrasound, and magnetic resonance imaging (MRI). The prevalence of imaging findings vary by data element and modality (e.g., suspicious calcification noted in 2.6% of screening mammograms, 12.1% of diagnostic mammograms, and 9.4% of tomosynthesis exams). In the validation sample, the accuracy of identifying imaging findings, including suspicious calcifications, masses, and architectural distortion (on mammogram and tomosynthesis); masses, cysts, non-mass enhancement, and enhancing foci (on MRI); and masses and cysts (on ultrasound), range from 0.8 to1.0 for recall, precision, and F-measure. Information extraction tools can be used for accurate documentation of imaging findings as structured data elements from text reports for a variety of breast imaging modalities. These data can be used to populate screening registries to help elucidate more effective breast cancer screening processes.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
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Mamografia
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Sistema de Registros
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Armazenamento e Recuperação da Informação
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Sistemas de Informação em Radiologia
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Detecção Precoce de Câncer
Tipo de estudo:
Diagnostic_studies
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Guideline
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Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Female
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Humans
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article