: Brain tumor magnetic resonance imaging (MRI) reporting and tumor segmentation for treatment planning are time-consuming and variable. This retrospective fixed-sequence paired workflow study evaluates whether AI assistance is associated with changes in efficiency, consistency, and reproducibility. Methods : Thirty MRI cases (10 vestibular schwannomas, 10 meningiomas, 10 brain metastases) were assessed....
✦ The floor
Discussion
Signed responses from readers of the wire.
No actionable change for audiologists — this study concerns brain tumor MRI workflows and has no direct bearing on audiology clinical practice.
AI-assisted radiology workflows for brain tumors may indirectly touch audiology when acoustic neuromas (a type of brain tumor) are involved, but this study does not address hearing-related outcomes.
- 01AI-assisted MRI reporting reduced workflow time compared to standard radiology processes.
- 02AI also reduced variability between different reviewers in treatment-planning segmentation.
- 03The study was retrospective and paired, not a randomized controlled trial.
- 04Findings are specific to brain tumor imaging and do not directly address audiology.
AI-assisted brain tumor MRI reporting reduced time compared to standard workflow.
studypartially supportedAI-assisted segmentation reduced inter-rater variability in treatment planning.
studypartially supported- PMID
- 42512069
- DOI
- 10.3390/biomedicines14071595.
- Journal
- Biomedicines
- Publication type
- research_article
- Evidence level
- 2b
- Population
- Brain tumor patients undergoing MRI-based treatment planning
- Intervention
- AI-assisted MRI reporting and segmentation workflow
- Comparator
- Standard (non-AI) MRI reporting and segmentation workflow
Primary outcomes
Workflow time; Inter-rater segmentation variability