Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107, Yanjiang West Road, Guangzhou, 510120, Guangdong, China.
Surg Endosc. 2018 Sep;32(9):3925-3935. doi: 10.1007/s00464-018-6132-1. Epub 2018 Feb 27.
To assist surgeons in identifying and preserving the parathyroid gland (PTG) in endoscopic thyroidectomy (ET), we have summarized the characteristics of the PTG and the surrounding tissues in ET by applying the Storz Professional Image Enhancement System (SPIES).
From November 2014 to May 2016, 182 patients with 613 suspected PTGs were included in our study. The shape, color, area, and density of surface blood vessels (SBVs); whether they were encapsulated with adipose tissue; and whether congestion was present during the operation were summarized. The κ coefficient of interobserver agreement in assessing the area and the density of SBVs of suspected PTGs with and without Spectra A (SA) and Spectra B (SB) modalities were calculated. Multiple binary logistic regression analyses were performed to determine the predictive value of different characteristics for detecting the PTG in ET with the application of SPIES.
With visual identification and histopathological results as reference standards, 291 targeted tissues were identified as PTGs, 256 as adipose tissue, 43 as lymph nodes, and 23 as thyroid tissue. The κ coefficients of interobserver agreement in assessing SBV density with or without the SA and SB modalities were 0.944 ± 0.013 and 0.859 ± 0.021, respectively, and those in assessing SBV area were 0.937 ± 0.014 and 0.841 ± 0.022, respectively. In the comparison between PTGs and other tissues, multiple binary logistic regression analysis revealed that shape, color, SBV density, congestion, and whether tissue was encapsulated with adipose tissue were independent predictive factors of PTGs.
With the application of SPIES, the shape, color, density of SBVs, adipose tissue encapsulation, and congestion were independent factors that predicted PTGs in ET. The SA and SB modalities of SPIES could improve the reliability of SBV density and area classifications in targeted tissues.
为了帮助外科医生在经内镜甲状腺切除术(ET)中识别和保护甲状旁腺(PTG),我们应用 Storz 专业图像增强系统(SPIES)总结了 ET 中 PTG 及其周围组织的特征。
从 2014 年 11 月至 2016 年 5 月,我们对 182 例 613 个疑似甲状旁腺的患者进行了研究。总结了表面血管(SBV)的形状、颜色、面积和密度;是否被脂肪组织包裹;以及手术过程中是否存在充血。使用 Spectra A(SA)和 Spectra B(SB)模式评估可疑甲状旁腺的 SBV 面积和密度的观察者间一致性 κ 系数进行了计算。进行了多项二项逻辑回归分析,以确定 SPIES 应用中不同特征对检测 ET 中甲状旁腺的预测价值。
以视觉识别和组织病理学结果为参考标准,291 个靶向组织被鉴定为甲状旁腺,256 个为脂肪组织,43 个为淋巴结,23 个为甲状腺组织。在使用或不使用 SA 和 SB 模式评估 SBV 密度的观察者间一致性 κ 系数分别为 0.944±0.013 和 0.859±0.021,在评估 SBV 面积的观察者间一致性 κ 系数分别为 0.937±0.014 和 0.841±0.022。在甲状旁腺与其他组织的比较中,多项二项逻辑回归分析显示,形状、颜色、SBV 密度、充血和是否被脂肪组织包裹是甲状旁腺的独立预测因素。
应用 SPIES 后,形状、颜色、SBV 密度、脂肪组织包裹和充血是 ET 中预测甲状旁腺的独立因素。SPIES 的 SA 和 SB 模式可提高靶向组织中 SBV 密度和面积分类的可靠性。