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Optimising trajectory planning for stereotactic brain tumour biopsy using artificial intelligence: a systematic
Joachim Starup-Hansen1, Simon C Williams2,3, Jonathan P Funnell2,3
1Charing Cross Hospital, Imperial College NHS Healthcare Trust, London, United Kingdom.
Purpose:
Despite advances in technology, stereotactic brain tumour biopsy remains challenging due to the risk of injury to critical structures. Indeed, choosing the correct trajectory remains essential to patient safety. Artificial intelligence can be used to perform automated trajectory planning. We present a systematic review of automated trajectory planning algorithms for stereotactic brain tumour biopsies.
Methods:
A PRISMA adherent systematic review was conducted. Databases were searched using keyword combinations of 'artificial intelligence', 'trajectory planning' and 'brain tumours'. Studies reporting applications of artificial intelligence (AI) to trajectory planning for brain tumour biopsy were included.
Results:
All eight studies were in the earliest stage of the IDEAL-D development framework. Trajectory plans were compared through a variety of surrogate markers of safety, of which the minimum distance to blood vessels was the most common. Five studies compared manual to automated planning strategies and favoured automation in all cases. However, this comes with a significant risk of bias.
Conclusions:
This systematic review reveals the need for IDEAL-D Stage 1 research into automated trajectory planning for brain tumour biopsy. Future studies should establish the congruence between expected risk of algorithms and the ground truth through comparisons to real world outcomes.
Insights
Automated trajectory planning using artificial intelligence (AI) shows promise for safer stereotactic brain tumor biopsies. Further research is needed to validate AI algorithms against real-world outcomes.
Area of Science:
- Neurosurgery
- Medical Imaging
- Artificial Intelligence
Background:
- Stereotactic brain tumor biopsy is challenging due to risks to critical structures.
- Accurate trajectory planning is vital for patient safety in these procedures.
Purpose of the Study:
- To systematically review artificial intelligence (AI) algorithms for automated trajectory planning in stereotactic brain tumor biopsies.
- To assess the current stage of development and safety markers of these AI algorithms.
Main Methods:
- A PRISMA-compliant systematic review was performed.
- Searches included keywords like 'artificial intelligence', 'trajectory planning', and 'brain tumors'.
- Studies applying AI to trajectory planning for brain tumor biopsy were included.
Main Results:
- All eight included studies were in the early IDEAL-D development framework (Stage 1).
- Minimum distance to blood vessels was a common safety marker.
- Five studies favored automated planning over manual methods, but carried a risk of bias.
Conclusions:
- There is a need for IDEAL-D Stage 1 research into automated trajectory planning for brain tumor biopsy.
- Future studies must validate AI algorithm safety by comparing predicted risks with real-world outcomes.
