Clinical Validation of an Artificial Intelligence System for De-termining Fetal Lie and Position in 3rd Trimester
Clinical Validation of an Artificial Intelligence System for Determining Fetal Lie and Position in 3rd Trimester
調査の概要
詳細な説明
Accurate assessment of fetal lie and presentation during the third trimester is essential for obstetric management and delivery planning. Ultrasound is the gold standard for determining fetal orientation; however, the examination is highly operator-dependent and requires considerable experience to correctly identify fetal anatomy and orientation. Artificial intelligence (AI)-based navigational support systems have the potential to assist clinicians by providing real-time guidance during ultrasound examinations and improving the consistency of fetal orientation assessment.
The purpose of this study is to prospectively validate an AI-based navigational support system for determining fetal lie and presentation during routine third-trimester ultrasound examinations. The system analyzes blind ultrasound sweeps acquired along the maternal midline and automatically predicts fetal lie and presentation. AI-generated predictions will be compared with expert clinician assessment, which serves as the reference standard.
Eligible pregnant women attending third-trimester ultrasound examinations at the Fetal Medicine Department, Rigshospitalet, Slagelse - or Hillerød hospital, will be invited to participate. Following written informed consent, an expert clinician will first determine fetal lie and presentation as part of the routine ultrasound examination. The same clinician will subsequently acquire three blind ultrasound sweeps along the maternal midline. The AI navigational support system will analyze each sweep and generate predictions of fetal lie and presentation. All examinations will be completed within 5-10 minutes to minimize changes in fetal orientation between the clinical assessment and AI evaluation.
The primary objective is to evaluate the diagnostic performance of the AI system by comparing AI-generated predictions with expert clinician assessment. Primary outcome measures include overall diagnostic accuracy and agreement,
These findings will provide additional insight into the feasibility of implementing AI-assisted navigational support in routine obstetric ultrasound practice.
研究の種類
入学 (推定)
連絡先と場所
研究連絡先
- 名前：Mary Le Ngo, MD, MD
- 電話番号：+45 20773779
- メール：mary.van.anh.le.ngo.01@regionh.dk
研究場所
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Slagelse、デンマーク、3450
- まだ募集していません
- Slagelse Hospital, Department of Obstetrics and Gynecology
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コンタクト：
- Kathinka Nyborg, MD
- 電話番号：20773779
- メール：kany@regionsjaelland.dk
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Capital Region
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Hillerød、Capital Region、デンマーク、3400
- まだ募集していません
- Nordsjællands Hospital, Department of Obstetrics and Gynecology
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コンタクト：
- Gitte Hedermann, Associate Professor
- 電話番号：+2520773779
- メール：gitte.hedermann.christensen@regionh.dk
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København Ø
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Copenhagen、København Ø、デンマーク、2100
- 募集
- Rigshospitalet - Department of Obstetrics and Gynecology
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コンタクト：
- Martin Tolsgaard, professor,, Medical doctor, Ph.D
- 電話番号：+4520773779
- メール：martin.groennebaek.tolsgaard@regionh.dk
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参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
サンプリング方法
調査対象母集団
説明
Inclusion Criteria:
- Pregnant women aged ≥18 years.
- Singleton pregnancy.
- Gestational age ≥28+0 weeks.
- Fetus in longitudinal lie (cephalic or breech presentation) as determined by the routine clinical ultrasound examination.
- Able to understand Danish or English.
- Able and willing to provide written informed consent.
Exclusion Criteria:
- Multiple pregnancy.
- Fetus in transverse lie.
- Inability to provide written informed consent.
研究計画
研究はどのように設計されていますか？
デザインの詳細
コホートと介入
グループ/コホート |
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Prospective Clinical Validation Cohort
Pregnant women with singleton pregnancies in the third trimester (≥28+0 weeks' gestation) undergoing obstetric ultrasound examination.
Participants undergo three blind ultrasound sweeps, and AI-generated predictions of fetal lie and presentation are compared with expert clinician assessment.
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この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Diagnostic accuracy of the AI navigational support system for determining fetal lie and presentation.
時間枠：During the study ultrasound examination (approximately 5 minutes).
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Overall proportion of correct AI predictions of fetal lie and presentation compared with expert clinician assessment (reference standard).
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During the study ultrasound examination (approximately 5 minutes).
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Agreement between AI predictions and expert clinician assessment.
時間枠：During the study ultrasound examination.
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Agreement will be evaluated using Cohen's kappa coefficient.
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During the study ultrasound examination.
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協力者と研究者
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
キーワード
追加の関連 MeSH 用語
その他の研究ID番号
- P-2019-3101
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
IPD プランの説明
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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