Related Experiment Video
Updated: Jun 3, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Optimization of time-to-peak analysis for differentiating malignant and benign breast lesions with dynamic
Fang Liu1, Anat Kornecki, Olga Shmuilovich
1Imaging Division, Lawson Health Research Institute, London, ON, Canada.
Rationale And Objectives:
The aim of this study was to investigate the feasibility of applying measures sensitive to time-to-peak (T(peak)) heterogeneity as indicators for malignancy on breast dynamic contrast-enhanced magnetic resonance imaging.
Materials And Methods:
The study included 39 benign and 97 malignant breast lesions from 103 patients. Lesions were automatically segmented by k-means clustering. Voxel-by-voxel T(peak) values were extracted using an empirical model. The pth percentile values (p = 10, 20…) of the T(peak) distribution within each lesion and the fractional and absolute hot spot volumes were determined, where the hot spot volume is the volume of tissue with T(peak) less than a threshold value. Using the area under the receiver-operating characteristic curve (AUC), these measures were tested as indicators for differentiating fibroadenomas from invasive lesions and from ductal carcinoma in situ, as well as for differentiating nonfibroadenoma benign lesions from these malignant lesions. Region of interest-based T(peak) measurements were also tested. Finally, the relationship between hot spot volume and lesion volume was investigated.
Results:
For differentiating fibroadenomas from malignant lesions, AUC values increased with decreasing values of p. At the optimal threshold (3 minutes), the hot spot volume provided high diagnostic performance (AUC ≥0.96 ± 0.02 for absolute hot spot volume). However, for differentiating nonfibroadenoma benign lesions from malignant lesions, AUC values were low. A significant correlation between absolute hot spot volume and lesion volume was found for malignant lesions and nonfibroadenoma benign lesions.
Conclusion:
Quantitative analysis of the T(peak) distribution can be optimized for diagnostic performance, providing indicators sensitive to intralesion T(peak) heterogeneity.
