title: Diffusion tensor imaging: possible implications for radiotherapy treatment planning of patients with high-grade glioma.
abstract: OBJECTIVE
  Radiotherapy treatment planning for high-grade gliomas (HGG) is hampered by the inability to image peri-tumoural white-matter infiltration. Diffusion tensor imaging (DTI) is an imaging technique that seems to show white-matter abnormalities resulting from tumour infiltration that cannot be visualised by conventional computed tomography or magnetic resonance imaging (MRI). We propose a new term, the image-based high-risk volume (IHV) for such abnormalities, which are distinct from the gross-tumour volume (GTV). For IHV based on DTI, we use the term IHVDTI. This study assesses the value of DTI for the individualisation of radiotherapy treatment planning for patients with HGG.
  
  
  METHODS
  Seven patients with biopsy-proven HGG were included in a theoretical planning exercise, comparing standard planning techniques with individualised plans based on DTI. Standard plans were generated using a 2.5 cm clinical target volume (CTV) margin added to the GTV. For DTI-based plans, the CTV was generated by adding a 1 cm margin to the IHVDTI. Estimates of normal tissue complication probability (NTCP) were calculated and used to estimate the level of dose escalation that could be achieved using the DTI-based plans.
  
  
  RESULTS
  The use of DTI resulted in non-uniform margins being added to the GTV to encompass areas at high risk of tumour involvement, but, in six out of seven cases, the IHVDTI was encapsulated by the standard CTV margin. In all cases, DTI could be used to reduce the size of the planning-target volume (PTV) (mean 35%, range 18-46%), resulting in escalated doses (mean 67 Gy, range 64-74 Gy), with NTCP levels that matched the conventional treatment plans.
  
  
  CONCLUSIONS
  DTI can be used to individualise radiotherapy target volumes, and reduction in the CTV permits modest dose escalation without an increase in NTCP. DTI may also be helpful in stratifying patients according to the degree of white-matter infiltration.
authors.affiliation: Department of Oncology, University of Cambridge, UK. rajesh.jena@addenbrookes.nhs.uk
authors.forename: R
authors.initials: R
authors.lastname: Jena
authors.forename: S J
authors.initials: SJ
authors.lastname: Price
authors.forename: C
authors.initials: C
authors.lastname: Baker
authors.forename: S J
authors.initials: SJ
authors.lastname: Jefferies
authors.forename: J D
authors.initials: JD
authors.lastname: Pickard
authors.forename: J H
authors.initials: JH
authors.lastname: Gillard
authors.forename: N G
authors.initials: NG
authors.lastname: Burnet
mesh_terms: D000328:Adult; D001932:Brain Neoplasms / Q000401:mortality / Q000473:pathology / Q000532:radiotherapy*; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D005910:Glioma / Q000401:mortality / Q000473:pathology / Q000532:radiotherapy*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted