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

2026년 7월 2일 업데이트: 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.

연구 개요

상태

완전한

정황

상세 설명

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.

연구 유형

관찰

등록 (실제)

120

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 장소

  • 예멘
      • Sanaa, 예멘
        • Ben Hafeed Dental Center

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 어린이
  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

아니

샘플링 방법

비확률 샘플

연구 인구

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.

설명

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.

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Exact Agreement With the Expert Panel for Skeletal Sagittal Classification
기간: 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.

2차 결과 측정

결과 측정
측정값 설명
기간
Agreement With the Expert Panel for IOTN Dental Health Component Grade
기간: 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
기간: 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
기간: 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
기간: 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
기간: 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
기간: 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.

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

Ben Hafeed Dental Center

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (실제)

2024년 3월 3일

기본 완료 (실제)

2026년 3월 31일

연구 완료 (실제)

2026년 3월 31일

연구 등록 날짜

최초 제출

2026년 7월 2일

QC 기준을 충족하는 최초 제출

2026년 7월 2일

처음 게시됨 (실제)

2026년 7월 8일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 7월 8일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 7월 2일

마지막으로 확인됨

2026년 7월 1일

추가 정보

이 연구와 관련된 용어

키워드

추가 관련 MeSH 약관

기타 연구 ID 번호

  • BHDC-AIORT-2024-01
  • YDA-207 (기타 식별자: Yemen Dental Association)

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

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