aceArtificial intelligence in personalized internal dosimetry for radiopharmaceutical therapy: a narrative mini-review
Personalized internal radiation dosimetry supports individualized radiopharmaceutical therapy but remains difficult to implement because workflows require repeated quantitative imaging, segmentation, registration, kinetic modeling, and absorbed-dose calculation. This mini-review summarizes current evidence on artificial intelligence across the personalized dosimetry workflow and considers clinical readiness. A narrative PubMed search was completed in early 2026 and covered peer-reviewed studies published from 20…
Deep learning cut Y-90 SPECT reconstruction error and sped up image registration, easing workflow burdens that make individualized radiopharmaceutical dosimetry hard to implement.
AI-based clinical decision support for dosimetry rests mainly on retrospective, single-center evidence and still needs prospective, multicenter validation before routine clinical use.
The evidence for AI-based clinical decision support is mainly retrospective and single-center, and decision-support tools still need prospective, multicenter validation.
Evidence
- Peer-reviewedNuclear Medicine Communications2026-10-20
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Truvace Impact Record TRV-2026-2002, v1: “Artificial intelligence in personalized internal dosimetry for radiopharmaceutical therapy: a narrative mini-review.” Truvace, 2026-10-20. /record/TRV-2026-2002 (accessed at citation time). sha256 ff104b4ee9303c95…
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