| 摘要: |
| 目的：评估智能3D超微血管成像测量的血管指数在腮腺多形性腺瘤（pleomorphic adenoma, PA）和Warthin瘤（Warthin’s tumor, WT）鉴别诊中的断价值。
方法：对88例腮腺肿块（PA 51例，WT 37例）进行灰阶超声、彩色多普勒（color doppler flow imaging, CDFI）超声和二维SMI、智能3D SMI、超声造影（contrast enhanced ultrasonography, CEUS）检查。评估PA和WT在灰阶超声特征（大小、形状、边界、回声、有无液化）、CDFI（血流分级、血管分布）和二维SMI（血流分级、血管分布），以及三维SMI（血管指数（vascular index, VI））的差异，通过受试者工作曲线（receiver working curve, ROC）及其曲线下面积评价不同检查方式在鉴别PA和WT上的诊断效能。
结果：PA和WT在外形、回声、是否有粗钙化均无统计学意义（P＞0.05），在血管分布类型及血流分级方面差异有统计学意义（P＜0.001）。超声造影时间-强度曲线（time intensity curve, TIC）分析显示：与PA组相比，WT组的峰值强度（peak intensity, PI）、峰值减半时间（half time to descent, DT/2）、120s 强度、曲线下面积（area under the cure, AUC）、半下降斜率（semi-descent slope, DS/2），差异有统计学意义（P＜0.05），而造影剂到达时间（arrive time, AT）、基准强度（baseline intensity, BI）、峰值时间（time to peak, TTP）、下降斜率（descending slope, DS）差异均无统计学意义（P＞0.05）。ROC曲线分析显示：PI＞36.16dB、DT/2＞65.42、120s 强度＞11.91dB、AUC＞2493.55、DS/2＞0.42是诊断WT的最佳临界值。当VI＞17.73时提示WT可能性大。应用智能3D SMI测得的VI对腮腺肿瘤病理类型的诊断准确性高于二维SMI、CDFI（P＜0.05），与超声造影无显著差异（P＞0.05）。
结论：智能3D SMI技术可作为一种非侵入性工具，有助于腮腺PA和WT的鉴别诊断，有望得到更广泛的应用。 |
| 关键词: 智能3D 超微血管成像技术 血管指数 腮腺肿瘤 超声造影 |
| DOI： |
| 投稿时间：2024-02-03修订日期：2024-03-25 |
| 基金项目: |
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| Objective: To evaluate the value of vascular index measured by smart 3D superb microvascular imaging in the differential diagnosis of parotid pleomorphic adenoma (PA) from Warthin |
| Chen Mingming,jiangshu,zhangjian,luyejun,zhangjinnan,xingwei |
| () |
| Abstract: |
| Objective: To evaluate the value of vascular index measured by smart 3D superb microvascular imaging in the differential diagnosis of parotid pleomorphic adenoma (PA) from Warthin""s tumor (WT).
Methods: Eighty-eight cases of parotid masses (51cases of PA and 37 cases of WT) were examined by gray scale ultrasound, Color Doppler flow imaging(CDFI), two-dimensional SMI, smart 3D superb microvascular imaging and contrast enhanced ultrasonography (CEUS). The differences in gray-scale ultrasound features (size, shape, boundary, echo, and liquefaction), CDFI (blood flow grade and vascular distribution), 2D SMI (blood flow grade and vascular distribution), and smart 3D SMI (vascular index (VI)) between PA and WT were evaluated. The diagnostic effectiveness of different tests in differentiating PA and WT was evaluated by receiver working curve (ROC) and its area under the curve.
Results: There were no significant differences between PA and WT in shape, echo and coarse calcification (P > 0.05), but there were significant differences in vascular distribution type and blood flow classification (P < 0.001). time intensity curve (TIC) analysis showed that: Compared with the PA group, the peak intensity (PI), half time to descent (DT/2), 120s intensity and area under the cure in WT group AUC, semi-descent slope (DS/2), the difference was statistically significant (P < 0.05). Contrast agent arrive time (AT), baseline intensity (BI), time to peak (TTP), descending slope, There was no statistical significance in DS (P > 0.05). ROC curve analysis showed that PI > 36.16dB, DT/2 > 65.42, 120s intensity > 11.91dB, AUC > 2493.55, DS/2 > 0.42 were the best critical values for the diagnosis of WT. If VI is > 17.73, it indicates that WT is more likely. The diagnostic accuracy of VI measured by intelligent 3D SMI for pathological types of parotid tumors was higher than that of 2D SMI and CDFI (P < 0.05), and there was no significant difference with CEUS (P > 0.05).
Conclusions: Intelligent 3D SMI technology can be used as a non-invasive tool for the differential diagnosis of parotid PA and WT, and is expected to be widely used. |
| Key words: Smart 3D superb microvascular imaging Contrast enhanced ultrasonography Vascular index Parotid neoplasms |
