Gliomas are the most common type of cancer to affect the brain, with more than half of all primary brain cancers diagnosed being gliomas. Developing from the glial cells in the brain and spinal cord, these cancers have the potential to be aggressive, and spread quickly throughout the brain and become a major clinical concern very quickly. Glioma cancers can be differentiated by the types of glial cells which the cancers stem from, namely astrocytoma, oligodendroglioma, and ependymomas, thus effectively imaging and diagnosing these cancers is of vital importance.
The primary treatment course for gliomas, much like many cancers, is surgical intervention to remove the cancerous tissues. With all organs preserving as much function post surgery is the primary concern, and with an organ like the brain this cannot be emphasized enough. Effective imaging techniques are vital preoperatively for the optimal planning of surgical interventions and subsequent procedures.
This research topic aims to bring together emerging studies in the field of cancer imaging that will go on to form the basis of future considerations, prognoses, and diagnoses relating to gliomas, and how postsurgical outcomes can be better predicted and planned for by cancer care teams.
We welcome Original Research, leading-edge Reviews and Clinical Trials related but not limited to the aspects below:
- Cancer imaging techniques used in prognosis of glioma
- Cancer imaging methods used for assessment preoperatively
- Prediction of postsurgical outcomes after surgical intervention of glioma
- Characterization of gliomas using cancer imaging techniques
- Novel methods, or refinements to existing methods in imaging gliomas
- Design and Development of molecular probes for imaging gliomas
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
Gliomas are the most common type of cancer to affect the brain, with more than half of all primary brain cancers diagnosed being gliomas. Developing from the glial cells in the brain and spinal cord, these cancers have the potential to be aggressive, and spread quickly throughout the brain and become a major clinical concern very quickly. Glioma cancers can be differentiated by the types of glial cells which the cancers stem from, namely astrocytoma, oligodendroglioma, and ependymomas, thus effectively imaging and diagnosing these cancers is of vital importance.
The primary treatment course for gliomas, much like many cancers, is surgical intervention to remove the cancerous tissues. With all organs preserving as much function post surgery is the primary concern, and with an organ like the brain this cannot be emphasized enough. Effective imaging techniques are vital preoperatively for the optimal planning of surgical interventions and subsequent procedures.
This research topic aims to bring together emerging studies in the field of cancer imaging that will go on to form the basis of future considerations, prognoses, and diagnoses relating to gliomas, and how postsurgical outcomes can be better predicted and planned for by cancer care teams.
We welcome Original Research, leading-edge Reviews and Clinical Trials related but not limited to the aspects below:
- Cancer imaging techniques used in prognosis of glioma
- Cancer imaging methods used for assessment preoperatively
- Prediction of postsurgical outcomes after surgical intervention of glioma
- Characterization of gliomas using cancer imaging techniques
- Novel methods, or refinements to existing methods in imaging gliomas
- Design and Development of molecular probes for imaging gliomas
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
