title: Improving the efficacy of mammography screening: the potential and challenge of developing new computer-aided detection approaches.
abstract: In this editorial article, we share our visions of how to improve the efficacy of breast cancer screening using quantitative image feature analysis methods with the medical imaging research community. Although earlier cancer detection and treatment can help reduce the mortality rates of patients with breast cancer, the most existing long-term (or lifetime) risk models do not have clinically acceptable discriminatory power at the individual level to select women for current screening. Because of such a clinical dilemma and low efficacy of breast cancer screening, it is of great importance to establish a new and more effective personalized breast cancer screening paradigm. The new computer-aided detection (CAD) approach can be applied in two application fields: analyzing negative mammograms can provide useful information to assess cancer risk, and implementing case-based cancer risk scores can develop an adaptive CAD cueing method to yield higher sensitivity and lower false-positive detection rates.
authors.affiliation: a 1 Department of Electrical and Computer Engineering, University of Texas, El Paso, TX, 79968, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Qian
authors.forename: Wenqing
authors.initials: W
authors.lastname: Sun
authors.forename: Bin
authors.initials: B
authors.lastname: Zheng
mesh_terms: D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008403:Mass Screening / Q000379:methods*
keywords: beast cancer screening; cancer risk prediction model; computer-aided detection for breast cancer; early cancer detection and treatment; risk analysis