Data Sheet 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.pdf

IntroductionThe 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.
MethodsThis 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 1st order radiomics of IVIM parameters perfusion fraction (fp), pseudo-diffusion (Dp) and tissue diffusivity (Dt). 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.
ResultsDt and fp maps generated from different software showed consistency across platforms while Dp maps were variable. The average correlation between the three software pairs at three different sites for 1st order radiomics of IVIM parameters were Dtmin/Dtmax/Dtmean/Dtvariance/Dtskew/Dtkurt: 0.791/0.891/0.98/0.815/0.697/0.584; fpmax/fpmean/fpvariance/fpskew/fpkurt: 0.615/0.871/0.679/0.541/0.433; Dpmax/Dpmean/Dpvariance/Dpskew/Dpkurt: 0.616/0.56/0.587/0.454/0.51. Correlation between least-squares algorithms were the highest. Dtmean 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. Dt metrics were highly diagnostic as well as consistent along with fp metrics.
DiscussionMultiple 1st order radiomic features of Dt and fp 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.