Affiliations 

  • 1 Diagnostic Imaging and Radiotherapy, Faculty of Health Sciences, National University of Malaysia, Kuala Lumpur, Malaysia. Electronic address: azrulyahya@ukm.edu.my
  • 2 Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
World Neurosurg, 2019 Oct;130:e188-e198.
PMID: 31326352 DOI: 10.1016/j.wneu.2019.06.027

Abstract

BACKGROUND: Diffusion tensor imaging (DTI), which visualizes white matter tracts, can be integrated to optimize intracranial radiation therapy (RT) and radiosurgery (RS) treatment planning. This study aimed to systematically review the integration of DTI for dose optimization in terms of evidence of dose improvement, clinical parameter changes, and clinical outcome in RT/RS treatment planning.

METHODS: PubMed and Scopus electronic databases were searched based on the guidelines established by PRISMA to obtain studies investigating the integration of DTI in intracranial RT/RS treatment planning. References and citations from Google Scholar were also extracted. Eligible studies were extracted for information on changes in dose distribution, treatment parameters, and outcome after DTI integration.

RESULTS: Eighteen studies were selected for inclusion with 406 patients (median study size, 19; range: 2-144). Dose distribution, with or without DTI integration, described changes of treatment parameters, and the reported outcome of treatment were compared in 12, 7, and 10 studies, respectively. Dose distributions after DTI integration improved in all studies. Delivery time or monitor unit was higher after integration. In studies with long-term follow-up (median, >12 months), neurologic deficits were significantly fewer in patients with DTI integration.

CONCLUSIONS: Integrating DTI into RT/RS treatment planning improved dose distribution, with higher treatment delivery time or monitor unit as a potential drawback. Fewer neurologic deficits were found with DTI integration.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.