aceMultimodal Visual Question Answering System for Survival Prognosis in PSMA-Targeted Radiopharmaceutical Therapy
Large language models show great promise for clinical decision support but generally lack medical imaging integration. Therefore, vision-language models have been proposed, but there is little evidence on their performance, particularly compared with conventional machine learning. Prostate-specific membrane antigen (PSMA)-targeted radiopharmaceutical therapy is a well-established treatment for metastatic castration-resistant prostate cancer (mCRPC), but it is still not known which patients will be good long-term…
A physician-inspired visual question answering model that integrates PSMA PET or SPECT images with clinical data predicted 24-month survival in mCRPC patients, outperforming other state-of-the-art approaches in this retrospective cohort.
The study is a retrospective proof of concept with only 110 patients, wide confidence intervals, and external accuracy reached only after few-shot fine-tuning; the authors call the results preliminary.
Evidence
- Peer-reviewedJournal of Nuclear Medicine2026-10-15
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Truvace Impact Record TRV-2026-1815, v1: “Multimodal Visual Question Answering System for Survival Prognosis in PSMA-Targeted Radiopharmaceutical Therapy.” Truvace, 2026-10-18. /record/TRV-2026-1815 (accessed at citation time). sha256 fdb240fdf5d19997…
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