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      萤火虫成像联合应变弹性成像校正人工智能S-Detect技术对乳腺囊实性肿块良恶性的诊断价值

      Diagnostic Value of Micropure Imaging Combined with Strain Elastography in Correcting Artificial Intelligence S-Detect Technology for Benign and Malignant Breast Complex Cystic and Solid Masses

        摘要
      • 摘要:
        目的 探讨萤火虫成像（micropure imaging, MI）联合应变弹性成像（strain elastography, SE）校正人工智能（artificial intelligence, AI）S-Detect技术对乳腺囊实性肿块良恶性的诊断价值。
        方法 根据145个乳腺囊实性肿块的MI和SE的表现对其S-Detect诊断结果进行校正。以术后病理结果为金标准，计算校正前后的诊断敏感度、特异度、准确度，并绘制两组受试者操作特征（receiver operating characteristic, ROC）曲线，比较曲线下面积。
        结果 病理良性80个，恶性65个。S-Detect经过校正后，诊断敏感度、特异度、准确度以及ROC曲线下面积均较校正前有所提高。
        结论 MI与SE联合校正S-Detect的诊断结果，能够提高对乳腺囊实性肿块良恶性的诊断效能。

         

        Abstract:
        Objective To explore the diagnostic value of micropure imaging (MI) combined with strain elastography (SE) in correcting artificial intelligence (AI) S-Detect technology for benign and malignant breast complex cystic and solid masses.
        Methods The S-Detect diagnosis results were corrected based on the manifestations of MI and SE of the 145 breast complex cystic and solid masses. Postoperative pathological results were used as the gold standard to calculate the diagnostic sensitivity, specificity, and accuracy before and after correction. Additionally, receiver operating characteristic (ROC) curves were drawn for both groups, and the areas under the curves were compared.
        Results There were 80 benign and 65 malignant pathological results. After the correction of S-Detect, the diagnostic sensitivity, specificity, and accuracy, as well as the areas under the ROC curves, were all improved compared to before the correction.
        Conclusion Combining MI and SE to correct the diagnostic results of S-Detect can help improve the diagnostic efficacy of breast complex cystic and solid masses.

         

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