摘要
相關性。透過呼出氣體分析診斷喉部、口腔和咽部腫瘤是腫瘤學中一個很有前景的非侵入性研究方向。此方法基於癌細胞代謝不同於健康細胞的概念,這些差異可以表現為特定揮發性有機化合物 (VOC) 的形成或其濃度的變化。目的。研究感測氣體分析裝置和人工神經網路在早期 (I-II) 期和廣泛期 (III-IV) 上呼吸道癌症患者呼出氣體樣本研究中的診斷能力。材料和方法。研究納入了 78 名口腔癌、喉癌和喉咽癌患者以及 47 名健康志願者。該研究使用作者開發的診斷裝置分析了受試者的呼出氣體樣本,該裝置使用一組半導體感測器檢測吸入空氣中的揮發性化合物,然後對數據進行神經網路分析。結果。基於這些感測器的訊號,神經網路對各期上呼吸道惡性腫瘤患者進行了分類和識別。平均準確率為89%,特異性為85%,敏感度為97%。對於早期(I-II期)上呼吸道癌症,準確率、特異性和敏感度分別為85%、75%和90%。結論:無論早期或晚期患者,基於呼出氣樣本的上呼吸道癌症非侵入性診斷方法均具有較高的診斷準確率。
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