バイオマーカーとしての声:良性および悪性声帯病変の探索分析
Phillip Jenkins1, Rylan Harrison2, Steven Bedrick1
1Division of Informatics, Clinical Epidemiology, Oregon Health and Science University, Portland, OR, United States.
Frontiers in digital health
|August 28, 2025
まとめ
音響比率 (HNR) のような声のバイオマーカーは 声帯の損傷を早期に検出するのに役立ちます この研究では,HNRと基本周波数が,特に男性において,良性および悪性病変を健康な声から区別することを発見しました.
科学分野:
- 喉科 喉科
- 音響分析
- バイオマーカーの発見
背景:
- 声帯の損傷は良性でも悪性でも 声の質に大きく影響し 深刻な健康被害をもたらします
- これらの病変の早期の非侵襲的検出は 患者の治療結果と診断のアクセシビリティを改善するために不可欠です
- 声の分析は喉の病変を特定するための 潜在的バイオマーカーです
研究 の 目的:
- 喉癌と良性声帯の病変を他の声の症状と健康な声の機能から最も区別できる音響的特徴を特定する.
- 早期の病変検出のための非侵襲的なバイオマーカーとしての声の有用性を評価する.
主な方法:
- 7つの診断コホートを含むBridge2AI-Voiceデータセットの分析
- 非パラメトリックな統計的方法を用いた音響特性の抽出と比較 (基本周波数,ジッター,ジミラー,HNR)
- 2段階の分析: (1) 喉癌,良性病変,健康な声; (2) 喉癌,良性病変,性音不全,声帯麻痺
主要な成果:
- 良性病変と健康な対照群/喉頭がんの間で,音響対騒音比 (HNR) と基本的頻度における有意な差異が見つかりました.
- これらの区別は,特にHNRとその変動性では,シスジェンダーの男性にも見られた.
- シスジェンダーの女性のサンプルサイズが限られ,統計的に有意な結果が出なかった.
結論:
- 音響比 (HNR),特にその変動性は,声帯の損傷の早期発見とモニタリングのための声ベースのマーカーとして有望である.
- 音声分析は,良性および悪性声帯の状態を区別するのに役立ちます.
- これらの発見とその臨床的応用を検証するために,より大規模で多様な集団でのさらなる研究が必要である.
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