aceSystematic Review of Artificial Intelligence in Pre-Implant Radiographic Imaging: A Structured Qualitative Synthesis of Performance Across Imaging Modalities and AI Architectures
Purpose: To evaluate contemporary evidence on artificial intelligence (AI) applied to radiographic imaging for pre-implant dental assessment and treatment planning, with emphasis on the distinction between technical algorithmic performance and clinically oriented planning outcomes. Materials and methods: Peer-reviewed original studies published from January 2021 through December 2025 were identified through PubMed/MEDLINE, the Cochrane Library, ScienceDirect, JSTOR, and supplementary searches. Eligible studies u…
AI tools applied to pre-implant radiographs, mostly CBCT, performed well on segmentation and anatomical analysis and frequently shortened workflow time.
Evidence for AI-driven implant positioning and outcome prediction is limited and heterogeneous, and most assessed studies carried a high risk of bias.
Heterogeneity prevented quantitative pooling, most assessable studies had high risk of bias, and evidence for autonomous positioning and outcome prediction is limited and needs external and prospective testing.
Evidence
- Peer-reviewedThe International Journal of Oral & Maxillofacial Implants2026-10-19
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Truvace Impact Record TRV-2026-1939, v1: “Systematic Review of Artificial Intelligence in Pre-Implant Radiographic Imaging: A Structured Qualitative Synthesis of Performance Across Imaging Modalities and AI Architectures.” Truvace, 2026-10-19. /record/TRV-2026-1939 (accessed at citation time). sha256 b470ce8f99fac06c…
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