## 4 Discussion
### Limitations  
This study is subject to several important limitations. First, the small number of individual cases used in the RNAseq (\(n=13\) samples from an individual patient) and PDX mice (\(n=5\)) limit the generalizability and conclusiveness of these findings--these aspects in particular must be confirmed in follow-up reports applying similar methods. The GSEA presented in this study utilized samples from tract-associated samples related to the tumor versus non-tract-associated samples from within and nearby the tumor, but we did not directly sample from white matter tractography unrelated to the tumor, which would have been an additionally helpful negative control for interpreting our findings more conclusively. While challenging to accomplish in humans due to lacking clinical justification from sampling healthy tissue distant from the tumor, such studies could be performed in animal models; precise regional biopsy on such a small scale is challenging and was not immediately possible in the context of the current project. Further, the software used for analysis, DSI Studio, permits a range of tracking algorithm parameter selections for generating tractograms; those used here (angular threshold of 45\({}^{\circ}\) and maximum tract length of 300 mm for the historical cohort used in outcome analyses) were particularly permissive. Tumor ROI segmentation is also subject to possible bias especially when carried out manually based on a single co-registered MR sequence, given known limitations to distinguishing the tumor boundary on any single sequence; additional multi-modal segmentation tools have since emerged which could also be employed in future studies through more accurate segmentation [79; 80; 81]. While survival analyses yielded statistically significant results when conducted on \(n=66\) patients from a single center, the reproducibility of our findings should be evaluated with larger, multicenter cohorts. We included data from two institutions in the present study; however, the data presented from the primary enrollment cohort (\(n=7\)) should be considered as a pilot dataset; the MDA dataset serves as a larger dataset that qualitatively validates the observations of the smaller cohort, but must still be quantitatively compared with other similarly datasets to be generated in the future. The two cohorts could not be quantitatively compared in the present study owing to the small size of the principal enrollment cohort, limiting the ability of the current study to evaluate accuracy and within-group variability of results across different settings. A method which could be applied in future work to evaluate between-group variability in mouse or human imaging studies has been previously presented by [PERSON] et al. [82]. Methodologically, future studies should also investigate the effect of differences in post-processing software, tumor segmentation algorithms, image acquisition, and the timing of image acquisition. Further studies should also compare different dwMRI parameters while employing similar post-processing methods. Modifying the b-value, number of gradient directions, and other parameters could enable the optimization of the scan time required to achieve the same results. Finally, longitudinal studies employing serial QSI examinations to assess tumor recurrence over time would be an interesting follow-up study.