Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography

JRCT ID: jRCT1060220021

Registered date:28/05/2022

Basic Information

• Recruitment status: Recruiting
• Health condition(s) or Problem(s) studied: Mandibular third molar
• Date of first enrollment: 08/03/2021
• Target sample size: 1279
• Study type: Observational

Outcome(s)

• Primary Outcome: Accuracy rate by deep learning of mandibular third molar and inferior alveolar nerve in panoramic X-ray photography with diagnosis by CT image as correct answer
• Secondary Outcome: Sensitivity / specificity / F1 value / AUC by deep learning of mandibular third molar and inferior alveolar nerve in panoramic X-ray photography with diagnosis by CT image as correct answer

Key inclusion & exclusion criteria

• Age minimum: >= 20age old
• Age maximum: Not applicable
• Gender: Both

Include criteria

1) Both panoramic radiographs and CT are taken.
2) The age is 20 years or older.
3) The mandibular third molar is present.

Exclude criteria

1) It is an unclear image.
2) Plates are inserted in the lower jaw during panoramic photography.

Related Information

• Primary Sponsor: Sukegawa Shintaro
• Secondary Sponsor: Hara Takeshi