Journal article
Mammographic density and cancer detection: does digital imaging challenge our current understanding?
Academic radiology, Vol.21(11), pp.1377-1385
11/2014
DOI: 10.1016/j.acra.2014.06.004
PMID: 25097013
Abstract
To investigate the impact of breast density on the performance of radiologists when mammograms are digitally acquired and displayed.
A total of 150 craniocaudal digital mammograms including 75 cases with cancer were examined by 14 radiologists divided into two groups: those who read more (six) and less (eight) than 2000 mammograms per year. Cases were classified as low or high mammographic density. For both types of cases, detection of cancers within and outside the dense fibroglandular tissue was investigated. The performance of radiologist was measured using jack-knife free-response receiver operating characteristic (JAFROC) figure of merit (FOM).
Radiologists with over 2000 annual reads had significantly higher JAFROC FOM (P = .03) for high (0.76) mammographic density compared to low (0.70) mammographic density cases. When lesions overlaid the fibroglandular tissue, cases with high mammographic density compared to low mammographic density displayed increased location sensitivity for all radiologists (P = .03) and for those radiologists reading more than 2000 mammograms annually (P = .04), whereas JAFROC FOMs increased for all radiologists (P = .05). No significant changes were observed when the lesion was outside the fibroglandular region.
Increased mammographic density improves the performance of experienced radiologists when using digital mammograms. This finding, which does not align with those previously reported for film screen systems, may be because of windowing/leveling opportunities available with digital images.
Details
- Title: Subtitle
- Mammographic density and cancer detection: does digital imaging challenge our current understanding?
- Creators
- Dana S Al Mousa - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, Australia. Electronic address: dalm3874@uni.sydney.edu.auClaudia Mello-Thoms - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, AustraliaElaine A Ryan - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, AustraliaWarwick B Lee - BreastScreen, Cancer Institute of NSW, NSW, AustraliaMariusz W Pietrzyk - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, AustraliaWarren M Reed - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, AustraliaRobert Heard - Discipline of Behavioural and Social Sciences in Health, Faculty of Health Sciences, University of Sydney, NSW, AustraliaAnn Poulos - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, AustraliaJennifer Tan - Sydney South West Area Health Services (SSWAHS), NSW, AustraliaYanpeng Li - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, AustraliaPatrick C Brennan - Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, NSW, Australia
- Resource Type
- Journal article
- Publication Details
- Academic radiology, Vol.21(11), pp.1377-1385
- Publisher
- United States
- DOI
- 10.1016/j.acra.2014.06.004
- PMID
- 25097013
- ISSN
- 1076-6332
- eISSN
- 1878-4046
- Language
- English
- Date published
- 11/2014
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology
- Record Identifier
- 9984051576002771
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