Identification of Breast Cancer Using Integrated Information from MRI and Mammography
- Publication Date
- June 09, 2015
- Journal
- PLOS ONE
- Authors
- Shih Neng Yang, Fang Jing Li, Yen Hsiu Liao, Yueh Sheng Chen, et al
- Volume
- 10
- Issue
- 6
- Pages
- e0128404
- DOI
- https://dx.plos.org/10.1371/journal.pone.0128404
- Publisher URL
- http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0128404
- PubMed
- http://www.ncbi.nlm.nih.gov/pubmed/26056841
- PubMed Central
- http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4461246
- Europe PMC
- http://europepmc.org/abstract/MED/26056841
- Web of Science
- 000356349000020
- Scopus
- 84936805473
- Mendeley
- http://www.mendeley.com/research/identification-breast-cancer-using-integrated-information-mri-mammography-1
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Mendeley | Further Information
{"title"=>"Identification of Breast Cancer Using Integrated Information from MRI and Mammography.", "type"=>"journal", "authors"=>[{"first_name"=>"Shih-Neng", "last_name"=>"Yang"}, {"first_name"=>"Fang-Jing", "last_name"=>"Li"}, {"first_name"=>"Yen-Hsiu", "last_name"=>"Liao"}, {"first_name"=>"Yueh-Sheng", "last_name"=>"Chen"}, {"first_name"=>"Wu-Chung", "last_name"=>"Shen"}, {"first_name"=>"Tzung-Chi", "last_name"=>"Huang"}], "year"=>2015, "source"=>"PloS one", "identifiers"=>{"issn"=>"1932-6203", "pmid"=>"26056841", "doi"=>"10.1371/journal.pone.0128404"}, "id"=>"010aeeb5-5073-3162-a16b-3da3b54f4086", "abstract"=>"OBJECTIVES Integration of information from corresponding regions between the breast MRI and an X-ray mammogram could benefit the detection of breast cancer in clinical diagnosis. We aimed to provide a framework of registration from breast MRI to mammography and to evaluate the diagnosis using the combined information. MATERIALS AND METHODS 43 patients with 46 lesions underwent both MRI and mammography scans, and the interval between the two examinations was around one month. The distribution of malignant to benign lesions was 31/46 based on histological results. Maximum intensity projection and thin-plate spline methods were applied for image registration for MRI to mammography. The diagnosis using integrated information was evaluated using results of histology as the reference. The assessment of annotations and statistical analysis were performed by the two radiologists. RESULTS For the cranio-caudal view, the mean post-registration error between MRI and mammography was 2.2±1.9 mm. For the medio-lateral oblique view, the proposed approach performed even better with a mean error of 3.0±2.4 mm. In the diagnosis using MRI assessment with information of mammography, the sensitivity was 91.9±2.3% (29/31, 28/31), specificity 70.0±4.7% (11/15, 10/15), accuracy 84.8±3.1% (40/46, 38/46), positive predictive value 86.4±2.1% (29/33, 28/33) and negative predictive value 80.8±5.4% (11/13, 10/13). CONCLUSION MRI with the aid of mammography shows potential improvements of sensitivity, specificity, accuracy, PPV and NPV in clinical breast cancer diagnosis compared to the use of MRI alone.", "link"=>"http://www.mendeley.com/research/identification-breast-cancer-using-integrated-information-mri-mammography-1", "reader_count"=>8, "reader_count_by_academic_status"=>{"Researcher"=>3, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>1, "Student > Master"=>3}, "reader_count_by_user_role"=>{"Researcher"=>3, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>1, "Student > Master"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Engineering"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>1, "Computer Science"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Computer Science"=>{"Computer Science"=>3}, "Unspecified"=>{"Unspecified"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "group_count"=>2}Scopus | Further Information
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Relative Metric
{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}Loading … 

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