Abstract Details

MPNST are the leading cause of death in NF1 and most often arise from a pre-existing benign PNF. Short TI inversion recovery (STIR) sequences on MRI display tumor extent but do not permit accurate differentiation between PNF and MPNST. Furthermore, STIR sequences are not routinely acquired for certain body regions. T1-weighted pre-contrast (T1) sequences are more standardly obtained. We developed a radiomics model using STIR and T1 sequences to differentiate between NF1-associated PNF and MPNST.

Evaluate the performance of radiomics to classify plexiform neurofibromas (PNF) and malignant peripheral nerve sheath tumors (MPNST) in NF1

136 PNF and 91 MPNST from nine centers were segmented on STIR sequences (if available) or T2-weighted fat-saturated or T1-weighted fat-saturated post-contrast sequences. Segmentations were co-registered to T1 sequences. Standard pre-processing included N4 bias field correction, intensity normalization (mean 120 SI, SD 80 SI), and resampling (1 mm³ voxel resolution). 107 radiomic features were extracted from STIR- and T1-derived segmentations using PyRadiomics. We applied the Boruta algorithm and correlation removal for selection of important features. A Random Forest model was built using the top ten selected features. The data were divided into a training/validation and test set (7:3 ratio). Ten-fold cross-validation was performed and repeated 100 times. Model performance was evaluated using the AUC.

The AUC (95% confidence intervals) for the test set was 0.807 (0.694-0.921), 0.744 (0.614-0.875), and 0.836 (0.705-0.968) for the STIR, T1, and combined STIR+T1 model, respectively. For the STIR+T1 model, nine texture features and one shape feature were included in the model.

Using clinical MRIs, our radiomics models demonstrate high performance in classifying PNF and MPNST on STIR and STIR+T1 sequences. Our inclusion of multicenter MRIs enhances model generalizability. These models can potentially be integrated into the clinical workflow to help clinicians in the early identification of MPNST or pre-malignant atypical neurofibromas.