Accuracy and Interpretation Time of Computer-Aided Detection Among Novice and Experienced Breast MRI Readers

Abstract

OBJECTIVE The purpose of this study was to compare the diagnostic accuracy and interpretation times of breast MRI with and without use of a computer-aided detection (CAD) system by novice and experienced readers. SUBJECTS AND METHODS A reader study was undertaken with 20 radiologists, nine experienced and 11 novice. Each radiologist participated in two reading sessions spaced 6 months apart that consisted of 70 cases (27 benign, 43 malignant), read with and without CAD assistance. Sensitivity, specificity, negative predictive value, positive predictive value, and overall accuracy as measured by the area under the receiver operating characteristic curve (AUC) were reported for each radiologist. Accuracy comparisons across use of CAD and experience level were examined. Time to interpret and report on each case was recorded. RESULTS CAD improved sensitivity for both experienced (AUC, 0.91 vs 0.84; 95% CI on the difference, 0.04, 0.11) and novice readers (AUC, 0.83 vs 0.77; 95% CI on the difference, 0.01, 0.10). The increase in sensitivity was statistically higher for experienced readers (p = 0.01). Diagnostic accuracy, measured by AUC, for novices without CAD was 0.77, for novices with CAD was 0.79, for experienced readers without CAD was 0.80, and for experienced readers with CAD was 0.83. An upward trend was noticed, but the differences were not statistically significant. There were no significant differences in interpretation times. COCLUSIONS MRI sensitivity improved with CAD for both experienced readers and novices with no overall increase in time to evaluate cases. However, overall accuracy was not significantly improved. As the use of breast MRI with CAD increases, more attention to the potential contributions of CAD to the diagnostic accuracy of MRI is needed.

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

“…This work demonstrates the ability of DTI, scanned at 3 T at high spatial resolution (~8 mm 3 ), to measure in vivo the water diffusion tensor parameters in the entire fibroglandular tissue of both breasts. The ensemble of algorithms and software developed in the course of this study enabled analysis of the large DTI datasets and simultaneously view the diffusion parametric maps of the various diffusion coefficients, λ 1 , λ 2 , λ 3 , ADC and anisotropy indices λ 1 -λ 3 , and FA of all breast slices.…”

“…The insufficient sensitivity and specificity of these techniques, particularly for detecting lesions in dense breasts, has stimulated the development of other techniques including breast magnetic resonance imaging (MRI). Dynamic contrast enhanced (DCE) MRI has been established as a powerful tool for the detection and diagnosis of breast cancer 1,2 and is frequently facilitated by computer aided diagnosis means 3 . Currently it is used for special cases, such as high risk patients 4 , but not for routine screening, presumably because of the high costs, the need to use an injection of a contrast agent, the lack of standardization and the variable specificity in differentiating benign from malignant lesions ranging from low/moderate values 5,6 to high values that were obtained using combined mammography and DCE-MRI 7,8 .…”

Breast cancer molecular subtype classifier that incorporates MRI features

“…Systematic review and meta-analysis have demonstrated that clinical CAD systems do not influence the sensitivity or specificity of an experienced radiologist. 27,28 However, our results suggest that features extracted by the computer, imperceptible to the radiologists eye, may further our understanding of breast cancer molecular subtypes. Technology has allowed MRI to move beyond diagnosis, as shown by ours and other reports of extraction of histogram based features and use of fractal-based methods and/or multiparametric analysis that may offer further insight into a complex heterogeneous disease on a pixel-by-pixel level.…”

Radiogenomic Analysis of Breast Cancer: Luminal B Molecular Subtype Is Associated with Enhancement Dynamics at MR Imaging

“…Patients underwent T1-weighted precontrast and three to six postcontrast sequences with a gadolinium-based contrast agent. Because algorithms have not provided consistent benefits for experienced radiologists (31,32).…”