In the last years, the treatment of primary and metastatic brain tumors has undergone several promising developments. Glioblastomas have been the focus of disruptive molecular and pharmacological research and re-shaping of treatment pathways and techniques has been facilitated thanks to novel therapeutic approaches.
Concurrently, neuroimaging MR techniques have also improved with the introduction of new sequences and further large-scale clinical validation of existing ones. New imaging scenarios and paradigms have emerged related to challenging imaging patterns of lesions during and after treatment, which comprise of residual/relapsing disease progression and response to treatment. This holds particularly true in gliomas undergoing immunotherapy but has also been described in metastases and CNS lymphomas.
PET imaging is also playing an important role, especially with the introduction of combined PET/MR scanners and radio-labelled amino-acid tracers that show the potential of integrated and selective imaging for differentiating disease progression from treatment-related effects.
Notably, artificial intelligence has revealed its potential in identifying imaging patterns related to outcomes in several neuroimaging techniques and is expected to play a major role as diagnostic surrogate to the human expertise.
This Research Topic's scope is to bring together clinical, radiological, and engineering knowledge for efficient brain tumor surveillance by means of MRI and PET neuroimaging.
It will mainly focus on the added value and improvement in neuroimaging by including advanced MR and PET techniques in identifying disease progression patterns and understanding the effect of different treatments on brain tissue.
Additionally, it will explore the potential role of artificial intelligence in this challenging diagnostic scenario.
Scope and information for Authors
We welcome manuscripts on the following subjects:
· Role of different MR techniques in identifying disease progression (gliomas, metastasis, lymphomas)
· Role of perfusion MRI (included ASL) and metabolic MRI incl. its timing and protocol design in the follow-up of treated gliomas
· Validation of MRI protocols for metastases treated with gamma-knife and stereotactic radiotherapy
· Added value and diagnostic advantages by utilizing PET imaging for the specific diagnostic scenario different PET tracers
· Applications of artificial intelligence in brain tumors imaging surveillance
In the last years, the treatment of primary and metastatic brain tumors has undergone several promising developments. Glioblastomas have been the focus of disruptive molecular and pharmacological research and re-shaping of treatment pathways and techniques has been facilitated thanks to novel therapeutic approaches.
Concurrently, neuroimaging MR techniques have also improved with the introduction of new sequences and further large-scale clinical validation of existing ones. New imaging scenarios and paradigms have emerged related to challenging imaging patterns of lesions during and after treatment, which comprise of residual/relapsing disease progression and response to treatment. This holds particularly true in gliomas undergoing immunotherapy but has also been described in metastases and CNS lymphomas.
PET imaging is also playing an important role, especially with the introduction of combined PET/MR scanners and radio-labelled amino-acid tracers that show the potential of integrated and selective imaging for differentiating disease progression from treatment-related effects.
Notably, artificial intelligence has revealed its potential in identifying imaging patterns related to outcomes in several neuroimaging techniques and is expected to play a major role as diagnostic surrogate to the human expertise.
This Research Topic's scope is to bring together clinical, radiological, and engineering knowledge for efficient brain tumor surveillance by means of MRI and PET neuroimaging.
It will mainly focus on the added value and improvement in neuroimaging by including advanced MR and PET techniques in identifying disease progression patterns and understanding the effect of different treatments on brain tissue.
Additionally, it will explore the potential role of artificial intelligence in this challenging diagnostic scenario.
Scope and information for Authors
We welcome manuscripts on the following subjects:
· Role of different MR techniques in identifying disease progression (gliomas, metastasis, lymphomas)
· Role of perfusion MRI (included ASL) and metabolic MRI incl. its timing and protocol design in the follow-up of treated gliomas
· Validation of MRI protocols for metastases treated with gamma-knife and stereotactic radiotherapy
· Added value and diagnostic advantages by utilizing PET imaging for the specific diagnostic scenario different PET tracers
· Applications of artificial intelligence in brain tumors imaging surveillance