骨盤臓器の転倒の診断と画像ベースの評価における人工知能: スコーピングレビュー
Marian Botoncea1,2, Călin Molnar1,2, Vlad Olimpiu Butiurca1,2
1Faculty of Medicine, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, 540139 Targu Mures, Romania.
Medicina (Kaunas, Lithuania)
|August 28, 2025
まとめ
人工知能 (AI) は,医療画像を用いて骨盤臓器の転落 (POP) を診断するのに有望である. しかし,現在のAIアプリケーションは,臨床使用のためのさらなる検証と現実世界のテストを必要としています.
科学分野:
- 医療用イメージング
- 人工知能
- 骨盤床の障害
背景:
- 骨盤臓器の転落 (POP) は,正確な診断と治療計画を必要とする一般的な状態です.
- 医学的なイメージングは,POPを評価する上で重要な役割を果たします.
- 人工知能 (AI),特にディープラーニング (DL) は,医療画像分析において急速に進歩しているツールです.
研究 の 目的:
- 画像ベースの診断とPOPの解剖学的評価におけるAIアプリケーションに関する現在の証拠のスコーピングレビューを実施する.
- POPの評価に使用されるAIの方法論に関する発見を統合する.
主な方法:
- PRISMA-ScRのガイドラインに従って,PubMed,Scopus,Web of Science (2020年1月〜2025年4月) で包括的な文献検索が行われました.
- 対象となった研究は,POPの女性に対する超音波とMRIにAI (CNN,ViT,ハイブリッドモデル) を適用したものである.
- 8 件の研究は,入場基準を満たした.
主要な成果:
- AIは2D/3D超音波とMRIに適用され,セグメンテーション,ランドマークの局所化,および転倒の分類が行われました.
- コンボリューションニューラルネットワーク (CNN) とビジョントランスフォーマー (ViT) は高い診断精度を示した.
- 制限には,内部データセットへの依存,限られた解釈能力,外部検証や臨床展開の欠如が含まれます.
結論:
- AIは,医療画像分析により,POP診断を改善する大きな可能性を秘めています.
- 現在のAIアプリケーションは主に探索的で,さらなる開発が必要です.
- 将来の研究は,外部検証,標準化,説明可能なAI,および有用性を高める臨床実装に焦点を当てるべきです.
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