MRI can detect cancer in the contralateral breast that is missed by mammography and clinical examination at the time of the initial breast-cancer diagnosis. (ClinicalTrials.gov number, NCT00058058 [ClinicalTrials.gov].).
The use of computer-aided detection is associated with reduced accuracy of interpretation of screening mammograms. The increased rate of biopsy with the use of computer-aided detection is not clearly associated with improved detection of invasive breast cancer.
Purpose:To retrospectively compare the accuracy of digital versus film mammography in population subgroups of the Digital Mammographic Imaging Screening Trial (DMIST) defined by combinations of age, menopausal status, and breast density, by using either biopsy results or follow-up information as the reference standard.
Materials andMethods:DMIST included women who underwent both digital and film screening mammography. Institutional review board approval at all participating sites and informed consent from all participating women in compliance with HIPAA was obtained for DMIST and this retrospective analysis. Areas under the receiver operating characteristic curve (AUCs) for each modality were compared within each subgroup evaluated (age Ͻ 50 vs 50 -64 vs Ն 65 years, dense vs nondense breasts at mammography, and pre-or perimenopausal vs postmenopausal status for the two younger age cohorts [10 new subgroups in toto]) while controlling for multiple comparisons (P Ͻ .002 indicated a significant difference). All DMIST cancers were evaluated with respect to mammographic detection method (digital vs film vs both vs neither), mammographic lesion type (mass, calcifications, or other), digital machine type, mammographic and pathologic size and diagnosis, existence of prior mammographic study at time of interpretation, months since prior mammographic study, and compressed breast thickness.
Results:Thirty-three centers enrolled 49 528 women. Breast cancer status was determined for 42 760 women, the group included in this study. Pre-or perimenopausal women younger than 50 years who had dense breasts at film mammography comprised the only subgroup for which digital mammography was significantly better than film (AUCs, 0.79 vs 0.54; P ϭ .0015). Breast Imaging Reporting and Data Systembased sensitivity in this subgroup was 0.59 for digital and 0.27 for film mammography. AUCs were not significantly different in any of the other subgroups. For women aged 65 years or older with fatty breasts, the AUC showed a nonsignificant tendency toward film being better than digital mammography (AUCs, 0.88 vs 0.70; P ϭ .0025).
Conclusion:Digital mammography performed significantly better than film for pre-and perimenopausal women younger than 50 years with dense breasts, but film tended nonsignificantly to perform better for women aged 65 years or older with fatty breasts.
We report pion-nucleon partial-wave amplitudes obtained from analysis of scattering data at pion laboratory momenta from 0.42 to 2.0 GeV/c. These partial-wave amplitudes have been analyzed using modified Breit-Wigner, coupled-channel parametrizations. The resulting resonances and their parameters are tabulated.
The physical characteristics of a clinical prototype amorphous silicon-based flat panel imager for full-breast digital mammography have been investigated. The imager employs a thin thallium doped CsI scintillator on an amorphous silicon matrix of detector elements with a pixel pitch of 100 microm. Objective criteria such as modulation transfer function (MTF), noise power spectrum, detective quantum efficiency (DQE), and noise equivalent quanta were employed for this evaluation. The presampling MTF was found to be 0.73, 0.42, and 0.28 at 2, 4, and 5 cycles/mm, respectively. The measured DQE of the current prototype utilizing a 28 kVp, Mo-Mo spectrum beam hardened with 4.5 cm Lucite is approximately 55% at close to zero spatial frequency at an exposure of 32.8 mR, and decreases to approximately 40% at a low exposure of 1.3 mR. Detector element nonuniformity and electronic gain variations were not significant after appropriate calibration and software corrections. The response of the imager was linear and did not exhibit signal saturation under tested exposure conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.