Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study

The intravoxel incoherent motion (IVIM) model of diffusion weighted imaging (DWI) provides imaging biomarkers for breast tumor characterization. It has been extensively applied for both diagnostic and prognostic goals in breast cancer, with increasing evidence supporting its clinical relevance. However, variable performance exists in literature owing to the heterogeneity in datasets and quantification methods.

This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p ), pseudo-diffusion (D_p ) and tissue diffusivity (D_t ). Pearson correlation (r) coefficients between software pairs were computed while logistic regression model was implemented to test malignancy detection and assess robustness of the IVIM metrics.

D_t and f_p maps generated from different software showed consistency across platforms while D_p maps were variable. The average correlation between the three software pairs at three different sites for 1_st order radiomics of IVIM parameters were D_tmin/D_tmax/D_tmean/D_tvariance/D_tskew/D_tkurt: 0.791/0.891/0.98/0.815/0.697/0.584; f_pmax/f_pmean/f_pvariance/f_pskew/f_pkurt: 0.615/0.871/0.679/0.541/0.433; D_pmax/D_pmean/D_pvariance/D_pskew/D_pkurt: 0.616/0.56/0.587/0.454/0.51. Correlation between least-squares algorithms were the highest. D_tmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. D_t metrics were highly diagnostic as well as consistent along with f_p metrics.

Multiple 1_st order radiomic features of D_t and f_p obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.