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Quantitative Measures Confirm the Inverse Relationship between Lesion Spiculation and Detection of Breast Masses
- Source :
- Academic Radiology. 20:576-580
- Publication Year :
- 2013
- Publisher :
- Elsevier BV, 2013.
-
Abstract
- Objective To identify specific mammographic appearances that reduce the mammographic detection of breast cancer. Materials and Methods This study received institutional board review approval and all readers gave informed consent. A set of 60 mammograms each consisting of craniocaudal and mediolateral oblique projections were presented to 129 mammogram Breastscreen readers. The images consisted of 20 positive cases with single and multicentric masses in 16 and 4 cases, respectively (resulting in a total of 24 cancers), and readers were asked to identify and locate the lesions. Each lesion was then ranked according to a detectability rating (ie, the number of observers who correctly located the lesion divided by the total number of observers), and this was correlated with breast density, lesion size, and various descriptors of lesion shape and texture. Results Negative and positive correlations between lesion detection and density (r = −0.64, P = .007) and size (r = 0.65, P = .005), respectively, were demonstrated. In terms of lesion size and shape, there were significant correlations between the probability of detection and area (r = 0.43, P = .04), perimeter (r = 0.66, P = .0004), lesion elongation (r = 0.49, P = .02), and lesion nonspiculation (r = 0.78, P Conclusions The results of this study have identified specific lesion characteristics associated with shape that may contribute to reduced cancer detection. Mammographic sensitivity may be adversely affected without appropriate attention to spiculation.
- Subjects :
- medicine.medical_specialty
Statistics as Topic
Breast Neoplasms
Cancer detection
Sensitivity and Specificity
Perimeter
Lesion
Breast cancer
medicine
Humans
Radiology, Nuclear Medicine and imaging
Breast density
Aged
Observer Variation
Lesion detection
business.industry
Reproducibility of Results
Middle Aged
medicine.disease
Radiographic Image Enhancement
Radiographic Image Interpretation, Computer-Assisted
Female
Radiology
medicine.symptom
business
Algorithms
Mammography
Subjects
Details
- ISSN :
- 10766332
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- Academic Radiology
- Accession number :
- edsair.doi.dedup.....9bbab3f4193897c351f0c9903ecff450
- Full Text :
- https://doi.org/10.1016/j.acra.2012.12.010