## 3 Review Results
### DTI Modelled Tumoral Invasion  
Gliomas typically spread along the white matter tracts with tumour cells migrating with the orientation of the axons [32,33]. Typically, the tumoral core in high-grade tumours is defined as the contrast-enhancing tumour often with necrotic tissue within it [2]. However, glioma cells are found outside this core region due to the tumoral spread. As glioma cells migrate, it is thought to cause a loss of axonal integrity, leading to increased diffusivity and the T2 signal, and it is difficult to differentiate from vasogenic edema [34,35]. It has been suggested that diffusion imaging can improve the identification of non-enhancing tumour infiltration. For example, [PERSON] et al., 2009 find that the ADC is lower in the peritumour tissue of infiltrative tumours compared to non-infiltrative tumours [36]. Another study additionally found FA reductions in regions prior to visible tumour recurrence [35].  
Therefore, DTI has been proposed to improve the identification of peritumour infiltration by better characterising diffusion abnormalities. Several studies have used the p (isotropic) and q (anisotropic) maps which are derived from the diffusion tensor to identify tumour and peritumour infiltration as it is proposed that the tumour core has a reduced q and increased p and the infiltrative tumour has an increased p and unchanged q. Defining the infiltrative tumour with p and q maps has been suggested as a replacement for defining the CTV on standard anatomic imaging in order to reduce the overall radiation dose in  
Figure 4: Diagram displaying (**A**) Example without tractography dissected corticospinal tract (CST) included as an OAR, and (**B**) CST included as an OAR during dose planning, resulting in a reduced radiation dose.  
radiotherapy plans [24]. The CTV will typically need to be manually drawn; however, a study has proposed a semi-automated method that automatically expands the GTV drawn on the q map using a level set function on a p map [15].  
Another proposed method utilises FA maps to detect tumour infiltration, as FA has been found to be reduced in infiltrative regions. Study groups have used deep learning to correct FA maps for free water to increase FA maps' accuracy, finding that a model utilising these corrected FA maps could predict recurrence with an area under the curve (AUC) of 0.9 (compared to 0.77 with uncorrected maps) in a retrospective study [27]. The group additionally used the method to create the CTV and found that it correlated with the typical method of CTV definition, although it was larger in volume and adequately covered reoccurrences in follow-up scans [28].  
A limitation of using p and q maps or FA maps to expand the GTV is that they do not take directionality into account, and information on fibre orientation is not used. Some studies have used the whole tensor to predict tumour spread. An article used a 3D-based DTI model that uses the fibre orientation to predict glioma growth [25]. However, this study did not evaluate the model accuracy quantitatively. Another article used white matter path length function to map the shortest path along the WM from a given region back to the tumour core and expanded the GTV from this by 1, 2, or 3 cm to form an anisotropic CTV. However, this method is only displayed in two cases, and the results of a retrospective study using the software are awaited [26]. The group additionally released the software to be used openly, therefore making translational studies using the method much easier.  
Figure 5 shows a diagram showing how a DTI-guided anisotropic CTV could theoretically capture more areas of tumoral spread in gliomas by expanding along the WM.