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Xiao Y, Lv L, Xu Z, Zhou L, Lin Y, Lin Y, Guo J, Chen J, Ou Y, Lin L, Wu D. Correlation between peri-implant bone mineral density and primary implant stability based on artificial intelligence classification. Sci Rep 2024; 14:3009. [PMID: 38321110 PMCID: PMC10847140 DOI: 10.1038/s41598-024-52930-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 01/25/2024] [Indexed: 02/08/2024] Open
Abstract
Currently, the classification of bone mineral density (BMD) in many research studies remains rather broad, often neglecting localized changes in BMD. This study aims to explore the correlation between peri-implant BMD and primary implant stability using a new artificial intelligence (AI)-based BMD grading system. 49 patients who received dental implant treatment at the Affiliated Hospital of Stomatology of Fujian Medical University were included. Recorded the implant stability quotient (ISQ) after implantation and the insertion torque value (ITV). A new AI-based BMD grading system was used to obtain the distribution of BMD in implant site, and the bone mineral density coefficients (BMDC) of the coronal, middle, apical, and total of the 1 mm site outside the implant were calculated by model overlap and image overlap technology. Our objective was to investigate the relationship between primary implant stability and BMDC values obtained from the new AI-based BMD grading system. There was a significant positive correlation between BMDC and ISQ value in the coronal, middle, and total of the implant (P < 0.05). However, there was no significant correlation between BMDC and ISQ values in the apical (P > 0.05). Furthermore, BMDC was notably higher at implant sites with greater ITV (P < 0.05). BMDC calculated from the new AI-based BMD grading system could more accurately present the BMD distribution in the intended implant site, thereby providing a dependable benchmark for predicting primary implant stability.
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Affiliation(s)
- Yanjun Xiao
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, China
| | - Lingfeng Lv
- Fujian Provincial Engineering Research Center of Oral Biomaterial, Fujian Medical University, Fuzhou, 350001, China
| | - Zonghe Xu
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, China
| | - Lin Zhou
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, China
| | - Yanjun Lin
- Fujian Provincial Engineering Research Center of Oral Biomaterial, Fujian Medical University, Fuzhou, 350001, China
| | - Yue Lin
- Newland Digital Technology Co., Ltd., Fuzhou, Fujian, China
| | - Jianbin Guo
- Fujian Provincial Engineering Research Center of Oral Biomaterial, Fujian Medical University, Fuzhou, 350001, China
| | - Jiang Chen
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, China
| | - Yanjing Ou
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, China
| | - Lin Lin
- Newland Digital Technology Co., Ltd., Fuzhou, Fujian, China
| | - Dong Wu
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, China.
- Research Center of Dental and Craniofacial Implants, Fujian Medical University, Fuzhou, 350001, China.
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