Artificial intelligence-assisted screening for NTRK fusion-positive salivary gland tumors: A novel digital pathology workflow.
AI-powered microscopy accurately detects fusion mutations in salivary gland tumors, potentially replacing expensive traditional testing.
In a retrospective study of 273 salivary gland tumors validated against FISH gold standard, the Luigi-Oral AI image retrieval system achieved 85.7% sensitivity and 93.2% specificity for NTRK fusion detection. This digital pathology workflow may serve as a cost-effective IHC alternative for pre-screening patients who could benefit from TRK inhibitor therapy.
What the study was
- Study design
- Retrospective validation study of AI diagnostic tool
- Population
- Primary salivary gland tumors (n=273, single center, 2005-2023)
- Sample size
- 273
- Category
- Diagnostics
- Maturity
- Validated
- Journal
- Human Pathology
Why it surfaced
Novel AI pathology workflow for a clinically actionable genomic target (NTRK fusions) in a rare cancer; directly enables precision therapy access. Single-center retrospective limits generalizability.
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