自律型人工知能と AI 支援による人間の光学診断 (CADx-Prosp)
自律型人工知能と AI 支援による結腸直腸ポリープの人体光学診断: ランダム化比較試験
Computer-aided image-enhanced endoscopy can predict the nature of colorectal polyps with over 90% accuracy. This technology uses artificial intelligence (AI) to analyze video recordings of polyps, learning to make diagnoses in real-time. This means that doctors can get immediate predictions about small polyps during the procedure, reducing the need for separate pathology exams and saving costs, ultimately improving patient care.
Human and AI interactions are complex and a framework to reap synergistic effects CADx systems when used by humans to harness optimal performance needs to be established. AI solutions in medicine are usually developed to be used as assistive devices, however, then they rely on humans to correct AI errors. Optical polyp diagnosis is a complex task. Non experts usually achieve diagnostic accuracy in 70-80%. CADx systems have a similar diagnostic accuracy when used autonomously. Clinical evaluation of CADx systems showed that CADx assisted OD performs equally to the operator performance when using non CADx assisted OD. To harness a benefit of clinical CADx implementation we would have to find a way that synergies between human and CADx come into play to eliminate cases in which CADx assisted and/ or human OD results in low diagnostic accuracy and also addresses the problem of serrated polyp recognition.
調査の概要
詳細な説明
Our study hypothesis is that for CADx implementation, instead of using the high/low confidence framework, identifying cases with suboptimal diagnostic accuracy could be facilitated through identifying cases in which CADx and endoscopist disagreed in their diagnosis. Eliminating such cases might separate out cases with low accuracy when using CADx assisted OD. Since endoscopists have a high sensitivity but low specificity for serrated polyp OD, this framework will also allow us to implement a strategy to adequately manage serrated polyps found in the cohort.
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Daniel von Renteln, MD
- 電話番号：30912 514 890-8000
- メール：daniel.von.renteln.med@ssss.gouv.qc.ca
研究場所
-
-
Quebec
-
Montreal、Quebec、カナダ
- 募集
- Ghislaine Ahoua
-
コンタクト：
- Daniel von Renteln, MD
-
-
参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria:
- Indication for full colonoscopy.
Exclusion Criteria:
- Known inflammatory bowel disease
- Active colitis
- coagulopathy
- familial polyposis syndrome
- poor general health, defined as an American Society of Anesthesiologists class >3
- emergency colonoscopy
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
- 主な目的：診断
- 割り当て：なし
- 介入モデル：単一グループの割り当て
- マスキング：なし（オープンラベル）
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
|
他の：All participants
The endoscopist will make an optical diagnosis (OD) prediction for all small polyps (up to 10 mm) in white light (WL). Then, the endoscopist will make another OD prediction using image enhanced endoscopy (IEE) modes. After that, CADx will be activated in the IEE mode and a CADx prediction will be documented. Finally, after seeing the CADx prediction, the endoscopist will make a final prediction, which can agree or disagree with the autonomous CADx one. Polyps will be resected and sent to a pathology lab, where a pathologic diagnosis (blinded to the endoscopist's predictions) will be rendered. |
The CADx system will be used to predict the histopathology of the polyp detected. |
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 |
|---|---|---|
|
Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis
時間枠：up to 100 weeks
|
Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis , when histopathology results are used as the reference |
up to 100 weeks
|
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis
時間枠：up to 100 weeks
|
Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis, when histopathology results are used as the reference |
up to 100 weeks
|
|
Test characteristics, including recall, specificity, positive and negative predictive values (PPV/NPV), and particularly the NPV of rectosigmoid neoplastic polyps.
時間枠：up to 100 weeks
|
A ≥90% NPV will be used as a quality benchmark for a strategy to not resect such diminutive polyps. |
up to 100 weeks
|
|
Agreement of surveillance interval recommendations of AI-A and AI-H compared with the pathology-based recommendations
時間枠：up to 100 weeks
|
For surveillance interval assignment, the pathology results of concomitant polyps >5 mm (including multiple concomitant polyps of all sizes and histology) will be considered when calculating the surveillance interval recommendation. Surveillance recommendations will be based on the 2020 United States Multi Society Task Force Guidelines as is current standard of practice at our center. |
up to 100 weeks
|
|
Proportion of patients for whom an immediate surveillance recommendation can be directly provided for each approach, and how often histopathology-based polyp examination would have been avoided.
時間枠：up to 100 weeks
|
The potential cost-effectiveness of OD (either approaches) will be evaluated using the measured described above. |
up to 100 weeks
|
|
Variability of OD (AI-A and AI-H) across participating endoscopists.
時間枠：up to 100 weeks
|
Each participating endoscopist will conduct a similar number of optical diagnoses to assess endoscopist-related factors. |
up to 100 weeks
|
|
Cost-effectiveness of OD ((AI-A and AI-H)
時間枠：up to 100 weeks
|
A cost-effectiveness model will be applied to better quantify costs and understand cost impact including key cost drivers when generalized to a broader screening population. |
up to 100 weeks
|
協力者と研究者
捜査官
- 主任研究者：Daniel von Renteln, MD、University of Montreal Medical Center (CHUM)
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
- 2025-12306
- 2025 (米国 NIH グラント/契約)
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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