在进行新辅助化疗（NAC）后，术前检测病理完全缓解（pCR）有助于在手术后采用非手术治疗方法。我们开发了一种基于深度神经网络的人工智能（AI）引导的pCR评估方法，用于在手术前识别pCR。本研究对进行NAC后接受食管切除术的可切除性食管鳞状细胞癌（ESCC）患者进行了检验。根据pCR患者的数量，随机选取了同样数量的病理学反应者但没有pCR的患者和非反应者。使用深度神经网络分析内窥镜图像。使用包含20张照片的测试数据集进行验证。计算了AI和四个有经验的内窥镜医师的pCR评估的敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）。对于病理反应评估，使用了日本食管癌分级系统。该研究纳入了123名患者，包括41名pCR患者，同样数量的没有pCR的病理学反应者和非反应者[0级，5例（4%）；1a级，36例（30%）；1b级，21例（17%）；2级，20例（16%）；3级，41例（33%）]。在20个模型中，内窥镜反应（ER）检测的敏感性、特异性、PPV、NPV和准确性的中位数值分别为60%、81%、77%、67%和70%。类似地，内窥镜医师的这些中位数分别为43%、90%、85%、65%和66%。这个概念证明研究表明，NAC后的AI引导的内窥镜反应评估能够以中等准确度识别pCR。目前的AI算法可能通过谨慎的外部验证和进行前瞻性研究来指导ESCC患者包括原发肿瘤和淋巴结在内的个体化治疗策略，以证明这种诊断方法的临床价值。© 2023年。外科肿瘤学会。

Detecting pathological complete response (pCR) before surgery would facilitate nonsurgical approach after neoadjuvant chemotherapy (NAC). We developed an artificial intelligence (AI)-guided pCR evaluation using a deep neural network to identify pCR before surgery.This study examined resectable esophageal squamous cell carcinoma (ESCC) patients who underwent esophagectomy after NAC. The same number of histological responders without pCR and non-responders were randomly selected based on the number of pCR patients. Endoscopic images were analyzed using a deep neural network. A test dataset consisting of 20 photos was used for validation. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of AI and four experienced endoscopists' pCR evaluations were calculated. For pathological response evaluation, Japanese Classification of Esophageal Cancer was used.The study enrolled 123 patients, including 41 patients with pCR, the same number of histological responders without pCR, and non-responders [grade 0, 5 (4%); grade 1a, 36 (30%); grade 1b, 21 (17%); grade 2, 20 (16%); grade 3, 41 (33%)]. In 20 models, the median values of sensitivity, specificity, PPV, NPV, and accuracy for endoscopic response (ER) detection were 60%, 81%, 77%, 67%, and 70%, respectively. Similarly, the endoscopists' median of these was 43%, 90%, 85%, 65%, and 66%, respectively.This proof-of-concept study demonstrated that the AI-guided endoscopic response evaluation after NAC could identify pCR with moderate accuracy. The current AI algorithm might guide an individualized treatment strategy including nonsurgical approach in ESCC patients through prospective studies with careful external validation to demonstrate the clinical value of this diagnostic approach including primary tumor and lymph node.© 2023. Society of Surgical Oncology.