Differentiation of triple-negative breast cancer from other subtypes through whole-tumor histogram analysis on multiparametric MR imaging

Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes

“…In the first study that investigated the utility of DWI radiomic signatures, Xie et al investigated DWI and DCE-MRI histogram features for the differentiation of TN from other molecular subtypes with AUCs up to 0.763 [25]. Histogram features do not provide textural information in terms of spatial relationships between the signal intensities of pixels/voxels across a region or volume of interest [35].…”

“…Nevertheless, little is known about radiomic signatures derived from DWI for breast cancer characterization: the small number of previous studies of radiomics of DWI primarily evaluated differentiation between benign and malignant lesions [22][23][24] or solely used histogram features for the differentiation of TN cancers vs. other breast cancer subtypes [25]. Moreover, the actual parameters used to perform DWI radiomics are not yet well established, i.e., whether only the actual solid tumor itself should be measured or if the inclusion of edema, necrosis, and inflammation is essential for the differentiation between subgroups [26,27].…”

Diffusion-weighted imaging of the breast—a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group

“…While the basic monoexponential diffusion model and resulting ADC values providing a simple and technically reproducible parameter are currently preferable in clinical practice, the working group explicitly acknowledges continuous developments in the field of DWI that hold promise and should be pursued in parallel with ADC standardization. For example, the heterogeneity of ADC values within lesions may be measured using histogram analysis and more advanced artificial intelligence techniques [75][76][77]. Furthermore, DWI techniques "beyond the ADC" [26], such as diffusion tensor imaging (DTI), which allows the analysis of diffusion anisotropy [78][79][80][81][82][83]; intravoxel incoherent motion (IVIM) imaging, which distinguishes between intravascular perfusion and extravascular microstructural diffusion components [84][85][86][87][88][89]; and non-Gaussian diffusion, which provides enhanced sensitivity to tissue complexity, for instance from the kurtosis model [11,[84][85][86][87][88][90][91][92][93], may enhance the value of DWI.…”

Breast Cancer Radiogenomics: Current Status and Future Directions

“…Contrast enhancement metrics have proven to be the most commonly identified imaging feature associated with radiogenomics outcomes (4)(5)(6)(7)(8)(9)(10). MRI also allows for the assessment of additional tumoral features via diffusion weighted imaging (DWI), which have been a promising area of investigation (11)(12)(13)(14)(15)(16). Since DWI measures the in vivo motion of water molecules, which reflects tissue cellularity, differences in tumoral genetics may be expressed in DWI metrics.…”

“…Since DWI measures the in vivo motion of water molecules, which reflects tissue cellularity, differences in tumoral genetics may be expressed in DWI metrics. More advanced exploratory MRI techniques such as multiparametric MRI which can include established MRI parameters like DCE, DWI, MR spectroscopy, as well as novel MRI parameters like sodium imaging or blood oxygen level-dependent MRI have just initially be explored (14,16,17). One notable limitation of the analysis of MRI datasets is that MRI is frequently performed in the setting of preoperative planning after an initial biopsy has been performed.…”