Open AccessReview
Review of Template-Based Neuroimaging Tools in Neuro-Oncology: Novel Insights
by
Jürgen Germann, Andrew Yang, Clement T. Chow, Brendan Santyr, Nardin Samuel, Artur Vetkas, Can Sarica, Gavin J. B. Elias, Mathew R. Voisin, Walter Kucharczyk, Gelareh Zadeh, Andres M. Lozano and Alexandre Boutet
Cited by 2 | Viewed by 2372
Abstract
Background: A common MRI reference space allows for easy communication of findings, and has led to high-impact discoveries in neuroscience. Brain MRI of neuro-oncology patients with mass lesions or surgical cavities can now be accurately transformed into reference space, allowing for a
[...] Read more.
Background: A common MRI reference space allows for easy communication of findings, and has led to high-impact discoveries in neuroscience. Brain MRI of neuro-oncology patients with mass lesions or surgical cavities can now be accurately transformed into reference space, allowing for a reliable comparison across patients. Despite this, it is currently seldom used in neuro-oncology, leaving analytic tools untapped. The aim of this study was to systematically review the neuro-oncology literature utilizing reference space.
Methods: A systematic review of the neuro-oncology publications was conducted according to PRISMA statement guidelines. Studies specially reporting the use of the Montreal Neurological Institute (MNI) reference space were included. Studies were categorized according to their type of input data and their contributions to the field. A sub-analysis focusing on connectomics and transcriptomics was also included.
Results: We identified only 101 articles that utilized the MNI brain in neuro-oncology research. Tumor locations (
n = 77) and direct electrocortical stimulation (
n = 19) were the most common source of data. A majority of studies (
n = 51) provided insights on clinical factors such as tumor subtype, growth progression, and prognosis. A small group of studies (
n = 21) have used the novel connectomic and transcriptomic tools.
Conclusions: Brain MRI of neuro-oncology patients can be accurately transformed to MNI space. This has contributed to enhance our understanding of a wide variety of clinical questions ranging from tumor subtyping to symptom mapping. Many advanced tools such as connectomics and transcriptomics remain relatively untapped, thereby hindering our knowledge of neuro-oncology.
Full article
►▼
Show Figures