Applying a CAD-generated imaging marker to assess short-term breast cancer risk

Seyedehnafiseh Mirniaharikandehei; Ali Zarafshani; Morteza Heidari; Yunzhi Wang; Faranak Aghaei; Bin Zheng

doi:10.1117/12.2291527

27 February 2018 Applying a CAD-generated imaging marker to assess short-term breast cancer risk

Seyedehnafiseh Mirniaharikandehei, Ali Zarafshani, Morteza Heidari, Yunzhi Wang, Faranak Aghaei, Bin Zheng

Proceedings Volume 10575, Medical Imaging 2018: Computer-Aided Diagnosis; 105753F (2018) https://doi.org/10.1117/12.2291527
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

Although whether using computer-aided detection (CAD) helps improve radiologists’ performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all “prior” negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65±0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (p<0.01). Thus, the study showed that CAD-generated false-positives might provide a new quantitative imaging marker to help assess short-term breast cancer risk.

Citation Download Citation

Seyedehnafiseh Mirniaharikandehei, Ali Zarafshani, Morteza Heidari, Yunzhi Wang, Faranak Aghaei, and Bin Zheng "Applying a CAD-generated imaging marker to assess short-term breast cancer risk ", Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105753F (27 February 2018); https://doi.org/10.1117/12.2291527

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available