Feasibility study of artificial intelligence in immediate implant measurements and analysis in the mandibular molar region

doi:10.12337/zgkqzzxzz.2024.04.013

Abstract

Abstract: Objective To analyze and validate the feasibility of an artificial intelligence software, ITK-SNAP, in identifying the distance between mandibular molars and the inferior alveolar nerve canal. Methods The cone-beam CT (CBCT) image data of 100 college students were selected, and 30 cases were randomly selected as the experimental group, and the remaining 70 cases were used as the validation group together with the 30 cases in the experimental group. The distances from the apices of the mandibular molar roots and the tops of the alveolar septa to the inferior alveolar nerve canals were measured using CBCT image analysis software and ITK-SNAP, respectively. Results The differences in the distances between mandibular molars and the inferior alveolar nerve canals measured by CBCT and ITK-SNAP software were not statistically significant in intergroup comparisons (P>0.05), and had a high correlation with r>0 (correlation coefficients r were all greater than 0.9); in both males and females, the distances from the mesial apices, the distal apices, and the tops of the alveolar septa to the upper walls of the inferior alveolar nerve canals of the mandibular first molars were significantly greater than those of the second molars (P<0.05), and the distances from each point of the mandibular first molars to the upper walls of the inferior alveolar nerve canals were significantly greater than those of the second molars in both the right and left sides (P<0.05). Conclusion The artificial intelligence software ITK-SNAP for measuring the distance between mandibular molars and the mandibular canal is feasible, which provides a reference for the preoperative planning of immediate implant placement in the mandibular molar region.

Key words: Artificial intelligence, Mandibular canal, Mandibular molar, Image segmentation, Immediate implant placement

Zhao Wenbo, Li Xinru, Su Hang, Teng Weiwei, Cai Wenyu, Zhou Libo. Feasibility study of artificial intelligence in immediate implant measurements and analysis in the mandibular molar region[J]. Chinese Journal of Oral Implantology, 2024, 29(2): 178-183.

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