[A comparative study of artificial intelligence nasal polyp classification based on whole-slide imaging and JESREC diagnostic criteria].

Objective: To explore the types and clinical characteristics of chronic rhinosinusitis with nasal polyps (CRSwNP) based on artificial intelligence and whole-slide imaging (WSI), and to explore the consistency of the diagnostic criteria of the Japanese epidemiological survey of refractory eosinophilic chronic rhinosinusitis (JESREC) in Chinese CRSwNP patients. Methods: The data of 136 patients with CRSwNP (101 males and 35 females, aging 14 to 70 years) who underwent endoscopic sinus surgery from 2018 to 2019 in the Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-sen University were analysed retrospectively. The preoperative clinical characteristics of patients were collected, such as visual analogue scale (VAS) of nasal symptoms, peripheral blood inflammatory cell count, total immunoglobulin E (IgE), Lund-Kennedy score and Lund-Mackay score. The proportion of inflammatory cells such as eosinophils, lymphocytes, plasma cells and neutrophils were calculated on the WSI of each patient through artificial intelligence chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0), and the specific type of nasal polyps was then obtained as eosinophilic CRSwNP (eCRSwNP) or non-eosinophilic CRSwNP (non-eCRSwNP). In addition, the JESREC diagnostic criteria was used to classify the nasal polyps, and the classification results were compared with the current gold standard for nasal polyps diagnosis (pathological diagnosis based on WSI). The accuracy, sensitivity and specificity of the diagnostic criteria of JESREC were evaluated. The data were expressed in M (Q1, Q3) and statistically analyzed by SPSS 17.0. Results: There was no significant difference between eCRSwNP and non-eCRSwNP in age distribution, gender, time of onset, total VAS score, Lund-Kennedy score or Lund-Mackay score. However, there was a significant difference in the ratio of nasal polyp inflammatory cells (eosinophils 40.5% (22.8%, 54.7%) vs 2.5% (1.0%, 5.3%), neutrophils 0.3% (0.1%, 0.7%) vs 1.3% (0.5%, 3.6%), lymphocytes 49.9% (39.3%, 65.9%) vs 82.0% (72.8%, 87.5%), plasma cells 5.1% (3.6%, 10.5%) vs 13.0% (7.4%, 16.3%), χ2 value was 9.91, 4.66, 8.28, 5.06, respectively, all P<0.05). In addition, eCRSwNP had a significantly higher level of proportion of allergic symptoms (nasal itching and sneezing), asthma, peripheral blood eosinophil and total IgE (all P<0.05). The overall accuracy, sensitivity and specificity of the JESREC diagnostic criteria was 74.3%, 81.3% and 64.3%, respectively. Conclusions: The eCRSwNP based on artificial intelligence and WSI has significant high level of allergic symptoms, asthma, peripheral blood eosinophils and total IgE, and the percentages of inflammatory cells in nasal polyps are different from that of non-eCRSwNP. The JESREC diagnostic criteria has good consistency in our research.目的： 探讨基于病理全玻片数字化图像（whole-slide imaging，WSI）的人工智能慢性鼻窦炎伴鼻息肉（CRSwNP）分型及其临床特征，同时探讨日本难治性嗜酸粒细胞性慢性鼻窦炎流行病学调查研究（Japanese epidemiological survey of refractory eosinophilic chronic rhinosinusitis，JESREC）诊断标准在本回顾性队列研究中的一致性。 方法： 回顾性分析中山大学附属第三医院耳鼻咽喉头颈外科2018—2019年接受鼻内镜手术的136例14~70岁的CRSwNP患者（男性101例，女性35例）。收集患者术前临床基本特征，如鼻部症状视觉模拟量表（VAS）评分、外周血炎性细胞计数、总免疫球蛋白（IgE）、Lund-Kennedy评分和Lund-Mackay评分等。通过第二代人工智能慢性鼻窦炎评估平台（artificial intelligence chronic rhinosinusitis evaluation platform 2.0，AICEP 2.0）计算每例患者WSI上的嗜酸粒细胞、淋巴细胞、浆细胞和中性粒细胞等炎性细胞比例，然后得出鼻息肉具体类型——嗜酸粒细胞性CRSwNP（eosinophilic CRSwNP，eCRSwNP）或非嗜酸粒细胞性CRSwNP（non-eosinophilic CRSwNP，non-eCRSwNP）。同时采用JESREC诊断标准进行鼻息肉分类，将所得分类结果与目前鼻息肉WSI诊断金标准（病理诊断）进行比较，评估该诊断标准的准确率、灵敏度及特异度。数据以M（Q1，Q3）表示，采用SPSS 17.0进行统计学分析。 结果： eCRSwNP和non-eCRSwNP患者在年龄分布、性别、病程、VAS评分、Lund-Kennedy评分和Lund-Mackay评分上的差异无统计学意义，而在鼻息肉炎性细胞比例上的差异有统计学意义［嗜酸粒细胞40.5%（22.8%，54.7%）比2.5%（1.0%，5.3%），中性粒细胞0.3%（0.1%，0.7%）比1.3%（0.5%，3.6%），淋巴细胞49.9%（39.3%，65.9%）比82.0%（72.8%，87.5%），浆细胞5.1%（3.6%，10.5%）比13.0%（7.4%，16.3%），χ²值分别为9.91、4.66、8.28、5.06，P值均<0.05］。此外，eCRSwNP患者的过敏症状（鼻痒和打喷嚏）和哮喘比例、外周血嗜酸粒细胞和血清总IgE水平均明显高于non-eCRSwNP患者（P值均<0.05）。JESREC诊断标准的总体准确率为74.3%，灵敏度为81.3%，特异度为64.3%。 结论： 基于人工智能和WSI诊断的eCRSwNP患者的过敏症状和哮喘比例、外周血嗜酸粒细胞和血清总IgE水平较高，鼻息肉中炎性细胞百分比与non-eCRSwNP患者存在差异。JESREC诊断标准在本回顾性队列研究中具有较好的一致性。.