title: An observer study comparing spot imaging regions selected by radiologists and a computer for an automated stereo spot mammography technique.
abstract: We are developing an automated stereo spot mammography technique for improved imaging of suspicious dense regions within digital mammograms. The technique entails the acquisition of a full-field digital mammogram, automated detection of a suspicious dense region within that mammogram by a computer aided detection (CAD) program, and acquisition of a stereo pair of images with automated collimation to the suspicious region. The latter stereo spot image is obtained within seconds of the original full-field mammogram, without releasing the compression paddle. The spot image is viewed on a stereo video display. A critical element of this technique is the automated detection of suspicious regions for spot imaging. We performed an observer study to compare the suspicious regions selected by radiologists with those selected by a CAD program developed at the University of Michigan. True regions of interest (TROIs) were separately determined by one of the radiologists who reviewed the original mammograms, biopsy images, and histology results. We compared the radiologist and computer-selected regions of interest (ROIs) to the TROIs. Both the radiologists and the computer were allowed to select up to 3 regions in each of 200 images (mixture of 100 CC and 100 MLO views). We computed overlap indices (the overlap index is defined as the ratio of the area of intersection to the area of interest) to quantify the agreement between the selected regions in each image. The averages of the largest overlap indices per image for the 5 radiologist-to-computer comparisons were directly related to the average number of regions per image traced by the radiologists (about 50% for 1 region/image, 84% for 2 regions/image and 96% for 3 regions/image). The average of the overlap indices with all of the TROIs was 73% for CAD and 76.8% +/- 10.0% for the radiologists. This study indicates that the CAD determined ROIs could potentially be useful for a screening technique that includes stereo spot mammography imaging.
authors.affiliation: Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-0030, USA. goodsitt@umich.edu
authors.forename: Mitchell M
authors.initials: MM
authors.lastname: Goodsitt
authors.forename: Heang-Ping
authors.initials: HP
authors.lastname: Chan
authors.forename: Justin T
authors.initials: JT
authors.lastname: Lydick
authors.forename: Chaitanya R
authors.initials: CR
authors.lastname: Gandra
authors.forename: Nelson G
authors.initials: NG
authors.lastname: Chen
authors.forename: Mark A
authors.initials: MA
authors.lastname: Helvie
authors.forename: Janet E
authors.initials: JE
authors.lastname: Bailey
authors.forename: Marilyn A
authors.initials: MA
authors.lastname: Roubidoux
authors.forename: Chintana
authors.initials: C
authors.lastname: Paramagul
authors.forename: Caroline E
authors.initials: CE
authors.lastname: Blane
authors.forename: Berkman
authors.initials: B
authors.lastname: Sahiner
authors.forename: Nicholas A
authors.initials: NA
authors.lastname: Petrick
mesh_terms: D055592:Biophysical Phenomena; D001703:Biophysics; D001943:Breast Neoplasms / Q000000981:diagnostic imaging; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods* / Q000706:statistics & numerical data; D015588:Observer Variation; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*