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AI-Assisted Versus Conventional Orthodontic Diagnosis and Treatment Planning (AI-OrthoDx)

2026年7月2日 更新者:Dr. Salah Mohammed Salem Ben Hafedh、Ben Hafeed Dental Center

Artificial Intelligence-Assisted Versus Conventional Orthodontic Diagnosis and Treatment Planning: A Prospective Paired Diagnostic-Agreement Study

This study compared an artificial intelligence-assisted orthodontic diagnostic workflow using WebCeph with a conventional clinician-based workflow.

The study included 120 new orthodontic patients treated at Ben Hafeed Dental Center in Sana'a, Yemen, between March 2024 and March 2026. For each participant, the researchers prepared a de-identified package of routine pretreatment records, including clinical findings, extraoral and intraoral photographs, panoramic and lateral cephalometric radiographs, and dental models or digital scans.

The same case package was independently assessed using both the artificial intelligence-assisted and conventional workflows. An independent panel of five expert orthodontists reviewed the cases and established the reference standard.

The main outcome was agreement with the expert panel for skeletal sagittal classification as Class I, Class II, or Class III. Other outcomes included orthodontic treatment-need grades, premolar extraction decisions, anchorage planning, appliance selection, and the time required to complete each diagnostic workflow.

Participation did not alter the routine orthodontic care provided to patients, and final clinical decisions remained the responsibility of the treating orthodontist.

研究概览

详细说明

This was a prospective paired diagnostic-agreement study conducted at Ben Hafeed Dental Center, Sana'a, Yemen, from March 2024 to March 2026.

A total of 120 eligible new orthodontic patients were included. Each participant contributed one standardized, de-identified pretreatment case package. Every case was evaluated using both an artificial intelligence-assisted workflow and a conventional clinician-based workflow, allowing direct within-case comparison.

The artificial intelligence-assisted workflow used WebCeph Premium, software version 2.0.3 (AssembleCircle Corp., Seongnam-si, Republic of Korea). The lateral cephalometric radiograph was uploaded to the software for automated anatomical landmark identification and generation of angular and linear cephalometric measurements. The original automated landmarks and measurements were recorded without manual correction. The reviewer interpreted the automated findings together with the remaining standardized pretreatment records and entered the required diagnostic and treatment-planning decisions.

For the conventional workflow, two calibrated orthodontists independently reviewed each case using routine clinical, photographic, radiographic, cephalometric, and dental-model assessment. Conventional cephalometric evaluation was performed using manual landmark identification through a local Dolphin Imaging-based workflow. When the two conventional orthodontists disagreed on an endpoint, a third calibrated orthodontist adjudicated the disputed decision.

The reference standard was established by an independent panel of five experienced orthodontists. Each expert independently reviewed the de-identified cases while blinded to the artificial intelligence-assisted and conventional workflow results. Reference decisions were established through majority agreement, with additional review and structured adjudication when required.

The primary endpoint was skeletal sagittal classification, categorized as Class I, Class II, or Class III. Secondary endpoints included the Index of Orthodontic Treatment Need Dental Health Component, the Index of Orthodontic Treatment Need Aesthetic Component, premolar extraction decision, anchorage-plan category, and primary appliance modality. Workflow duration was measured from the beginning of case assessment until all required decisions had been entered.

The study included 71 females and 49 males. The mean participant age was 20.3 years, with a standard deviation of 3.9 years and a range of 14 to 33 years.

The protocol was approved by the Yemen Dental Association under approval number 207. Written informed consent was obtained from adult participants. For minors, written parental or legal-guardian permission and participant assent were obtained.

研究类型

观察性的

注册 (实际的)

120

联系人和位置

本节提供了进行研究的人员的详细联系信息,以及有关进行该研究的地点的信息。

学习地点

      • Sanaa、也门
        • Ben Hafeed Dental Center

参与标准

研究人员寻找符合特定描述的人,称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

  • 孩子
  • 成人
  • 年长者

接受健康志愿者

不

取样方法

非概率样本

研究人群

The study population consisted of new orthodontic patients presenting for assessment at Ben Hafeed Dental Center in Sana'a, Yemen, from March 2024 to March 2026. Eligible participants were aged 12 years or older and had complete, good-quality routine pretreatment orthodontic records. Each enrolled participant contributed one standardized, de-identified case package that was assessed using both the AI-assisted and conventional diagnostic workflows.

描述

Inclusion Criteria:

  1. New orthodontic patients aged 12 years or older.
  2. Availability of complete routine pretreatment records, including clinical examination data, standardized extraoral and intraoral photographs, panoramic and lateral cephalometric radiographs, and dental models or digital scans.
  3. Pretreatment records of sufficient quality to permit comprehensive orthodontic diagnosis and treatment planning.
  4. Provision of written informed consent by adult participants or written parental or legal-guardian permission, together with participant assent for minors, in accordance with applicable local requirements.

Exclusion Criteria:

  1. Cleft lip and/or palate or another craniofacial syndrome that substantially altered the routine orthodontic diagnostic pathway.
  2. A history of previous comprehensive fixed orthodontic treatment.
  3. Incomplete, poor-quality, or non-standardized records that prevented comprehensive orthodontic diagnosis and treatment planning.
  4. Refusal to participate or subsequent withdrawal of consent.

学习计划

本节提供研究计划的详细信息,包括研究的设计方式和研究的衡量标准。

研究是如何设计的?

设计细节

研究衡量的是什么?

主要结果指标

结果测量
措施说明
大体时间
Exact Agreement With the Expert Panel for Skeletal Sagittal Classification
大体时间:At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Proportion of participant cases in which the skeletal sagittal classification assigned by each diagnostic workflow exactly agreed with the expert-panel reference classification. Classification was categorized as Class I, Class II, or Class III. Agreement was reported separately for the AI-assisted and conventional workflows using percentage agreement and unweighted Cohen's kappa with 95% confidence intervals. Paired classification accuracy was compared using McNemar's test.
At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.

次要结果测量

结果测量
措施说明
大体时间
Agreement With the Expert Panel for IOTN Dental Health Component Grade
大体时间:At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Agreement between each workflow and the expert-panel reference grade for the Index of Orthodontic Treatment Need Dental Health Component, graded from 1 to 5. Outcomes included exact agreement, agreement within one grade, weighted Cohen's kappa with 95% confidence intervals, and absolute grade deviation.
At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Agreement With the Expert Panel for IOTN Aesthetic Component Grade
大体时间:At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Agreement between each workflow and the expert-panel reference grade for the Index of Orthodontic Treatment Need Aesthetic Component, graded from 1 to 10. Outcomes included exact agreement, agreement within one grade, weighted Cohen's kappa with 95% confidence intervals, and absolute grade deviation.
At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Diagnostic Accuracy for the Premolar Extraction Decision
大体时间:At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Accuracy of each workflow in classifying whether premolar extraction was indicated, using the expert-panel decision as the reference standard. Outcomes included sensitivity, specificity, positive predictive value, negative predictive value, overall accuracy, and unweighted Cohen's kappa with 95% confidence intervals.
At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Agreement With the Expert Panel for Anchorage-Plan Category
大体时间:At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Proportion of participant cases in which the anchorage-plan category assigned by each workflow agreed with the expert-panel reference decision. Categories were conventional anchorage, reinforced anchorage, or skeletal anchorage. Agreement was evaluated using percentage agreement and unweighted Cohen's kappa.
At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Agreement With the Expert Panel for Primary Appliance Modality
大体时间:At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Proportion of participant cases in which the primary appliance modality selected by each workflow agreed with the expert-panel reference decision. Categories were fixed appliance, clear aligner, or functional appliance. Agreement was evaluated using percentage agreement and unweighted Cohen's kappa.
At baseline pretreatment assessment; one case evaluation per workflow, completed within 1 day.
Time Required to Complete the Diagnostic and Treatment-Planning Workflow
大体时间:During the baseline diagnostic assessment; measured continuously from case opening to completion, within 1 day.
Total time in minutes from opening the standardized case package until all required diagnostic and treatment-planning decisions were entered. For the conventional workflow, the mean of the two initial orthodontists' assessment times was used. Third-rater adjudication time was excluded. The within-case paired difference between workflows was calculated.
During the baseline diagnostic assessment; measured continuously from case opening to completion, within 1 day.

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查,以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2024年3月3日

初级完成 (实际的)

2026年3月31日

研究完成 (实际的)

2026年3月31日

研究注册日期

首次提交

2026年7月2日

首先提交符合 QC 标准的

2026年7月2日

首次发布 (实际的)

2026年7月8日

研究记录更新

最后更新发布 (实际的)

2026年7月8日

上次提交的符合 QC 标准的更新

2026年7月2日

最后验证

2026年7月1日

更多信息

与本研究相关的术语

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

不

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