Li Y B, Sun L S, Sun Z P, Xie X Y, Zhang J Y, Zhang Z Y, Zhao Y P, Ma X C
Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China.
Central Laboratory, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China.
Beijing Da Xue Xue Bao Yi Xue Ban. 2020 Feb 18;52(1):83-89. doi: 10.19723/j.issn.1671-167X.2020.01.013.
To establish a Parotid Imaging Reporting and Data System (PI-RADS) for CT diagnosis of the parotid gland neoplasms and to investigate the clinical applicable value and feasibility of PI-RADS.
Patients who had been diagnosed with primary parotid gland neoplasms and had received surgical treatments in Peking University School and Hospital of Stomatology during the period of January 2013 to December 2016 were included in this study. The diagnoses were confirmed by the postoperative pathological examinations in all the patients. The CT imaging data of all patients were retrospectively reviewed and analyzed by two readers in consensus. Imaging characteristics related to the parotid neoplasms were extracted and quantified. Based on comprehensive analysis of the imaging characteristics, the probabilities of the benign and malignant neoplasms were evaluated and classified into six grades, PI-RADS 1-6 (PI-RADS 1: normal parotid gland; PI-RADS 2: confidently benign lesions; PI-RADS 3: probably benign lesions without confirmed evidence of malignancy; PI-RADS 4: suspected malignancy without sufficient evidence of malignancy; PI-RADS 5: confidently malignant lesions; PI-RADS 6: lesions with confirmed pathological evidence of malignancy).
A total of 897 patients with 1 003 parotid lesions were included. The lesions included 905 benign and 98 malignant lesions. The proportions of the malignancies in PI-RADS 2, PI-RADS 3, PI-RADS 4 and PI-RADS 5 according to the two readers in consensus were 0.4%, 5.7%, 35.5% and 96.7% respectively. The overall Cohen's Kappa test showed medium consistency between the two independent researchers (κ=0.614, P<0.001, 95%CI: 0.569-0.695). Pearson Chi-square test showed that the proportions of malignancies increased with the diagnostic PI-RADS grades (Cochran-Armitage trend test, Z=-15.579, P<0.001). The results of Pearson Chi-square tests showed significant differences between the grades [PI-RADS 2 and 3 (χ²=12.048, P=0.001); PI-RADS 3 and 4 (χ²=75.231, P<0.001); PI-RADS 4 and 5 (χ²=32.266, P<0.001)].
PI-RADS can be used to evaluate the risk of malignancy and will be helpful to improve the imaging diagnosis and clinical treatment of parotid gland neoplasms.
建立用于腮腺肿瘤CT诊断的腮腺影像报告和数据系统（PI-RADS），并探讨其临床应用价值及可行性。
纳入2013年1月至2016年12月期间在北京大学口腔医学院·口腔医院被诊断为原发性腮腺肿瘤并接受手术治疗的患者。所有患者的诊断均经术后病理检查证实。由两位阅片者对所有患者的CT影像数据进行回顾性分析并达成共识。提取并量化与腮腺肿瘤相关的影像特征。基于对影像特征的综合分析，评估良恶性肿瘤的概率并分为六个等级，即PI-RADS 1-6（PI-RADS 1：正常腮腺；PI-RADS 2：肯定为良性病变；PI-RADS 3：可能为良性病变但无恶性的确切证据；PI-RADS 4：怀疑为恶性但无足够恶性证据；PI-RADS 5：肯定为恶性病变；PI-RADS 6：有病理证实恶性的病变）。
共纳入897例患者的1003个腮腺病变。其中良性病变905个，恶性病变98个。两位阅片者达成共识后，PI-RADS 2、PI-RADS 3、PI-RADS 4和PI-RADS 5中恶性病变的比例分别为0.4%、5.7%、35.5%和96.7%。总体Cohen's Kappa检验显示两位独立研究者之间具有中等一致性（κ=0.614，P<0.001，95%CI：0.569-0.695）。Pearson卡方检验显示恶性病变比例随PI-RADS诊断等级升高而增加（ Cochr an-Armitage趋势检验，Z=-15.579，P<0.001）。Pearson卡方检验结果显示各等级之间存在显著差异[PI-RADS 2和3（χ²=12.048，P=0.001）；PI-RADS 3和4（χ²=75.231，P<0.001）；PI-RADS 4和5（χ²=32.266，P<0.001）]。
PI-RADS可用于评估恶性风险，有助于提高腮腺肿瘤的影像诊断及临床治疗水平。
