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使用计算机断层扫描诊断血管平滑肌脂肪瘤——建议将感兴趣区<或=-10 HU或4个相邻像素<或=-10 HU作为诊断阈值。

Diagnosis of angiomyolipoma using computed tomography-region of interest < or =-10 HU or 4 adjacent pixels < or =-10 HU are recommended as the diagnostic thresholds.

作者信息

Simpson E, Patel U

机构信息

Department of Radiology, St George's Hospital and Medical School, London, UK.

出版信息

Clin Radiol. 2006 May;61(5):410-6. doi: 10.1016/j.crad.2005.12.013.

Abstract

AIM

To study and compare the diagnostic accuracy of region of interest (ROI) density measurement and pixel mapping [computed tomography (CT) density of individual pixels] for the diagnosis of renal angiomyolipoma (AML) using CT.

MATERIALS AND METHODS

A study group of histologically proven AMLs was compared with a control group of histologically proven renal cell cancers, normal renal parenchyma, and simple renal cysts. The mean tissue density (ROI circle) and a pixel density map were recorded. The diagnostic accuracy of various thresholds of ROI and pixel mapping values were compared using receiver operating characteristic curves.

RESULTS

Twenty-two AMLs, 16 renal cell carcinomas (RCCs), 30 simple cysts, and 30 sites of renal parenchyma were evaluated. The mean (+/-1 SD) density of the AMLs was significantly lower [-15.2(20.8) units] than the three control groups [+36.0(8.1) units, +5.4(3.4) units and +22.2(46.5) units for RCC, renal cyst and parenchyma respectively; p < 0.001 (analysis of variance)]. The sensitivities and specificities of the ROI diagnostic thresholds of < or =0 units, < or =-10 units and < or =-20 units were 77 and 97%, 73 and 100% and 50 and 100%, respectively. Using pixel mapping [diagnostic thresholds of either a line of 4 pixels < or =-10 units or a square of 4 pixels < or =-10 units] the sensitivity improves to 86% with a specificity of 97%.

CONCLUSION

Although a ROI threshold value of < or =-10 units has a very high specificity (100% in the present study) the sensitivity is modest at only 73%. Pixel mapping is more sensitive for recognizing small clusters of fat. In practice, both methods can be recommended for the analysis of suspected AMLs. ROI density measurement is convenient when analysing large areas of suspected fat and < or =-10 units should be used as the diagnostic threshold. When faced with small lucent areas or indeterminate values after ROI analysis, pixel mapping is recommended using a line of 4 pixels < or =-10 units or a square of 4 pixels < or =-10 units as the discriminating thresholds.

摘要

目的

研究并比较感兴趣区(ROI)密度测量和像素映射[单个像素的计算机断层扫描(CT)密度]在使用CT诊断肾血管平滑肌脂肪瘤(AML)中的诊断准确性。

材料与方法

将经组织学证实的AML研究组与经组织学证实的肾细胞癌、正常肾实质和单纯肾囊肿对照组进行比较。记录平均组织密度(ROI圆)和像素密度图。使用受试者操作特征曲线比较ROI和像素映射值的各种阈值的诊断准确性。

结果

评估了22例AML、16例肾细胞癌(RCC)、30例单纯囊肿和30个肾实质部位。AML的平均(±1标准差)密度显著低于三个对照组[RCC、肾囊肿和肾实质分别为+36.0(8.1)单位、+5.4(3.4)单位和+22.2(46.5)单位;p<0.001(方差分析)]。ROI诊断阈值≤0单位、≤-10单位和≤-20单位的敏感性和特异性分别为77%和97%、73%和100%、50%和100%。使用像素映射[4像素线≤-10单位或4像素正方形≤-10单位的诊断阈值],敏感性提高到86%,特异性为97%。

结论

尽管ROI阈值≤-10单位具有非常高的特异性(本研究中为100%),但其敏感性仅为73%,较为一般。像素映射在识别小脂肪团方面更敏感。在实践中,两种方法均可推荐用于分析疑似AML。分析大面积疑似脂肪时,ROI密度测量方便,应使用≤-10单位作为诊断阈值。当面对小的透亮区域或ROI分析后不确定的值时,建议使用像素映射,以4像素线≤-10单位或4像素正方形≤-10单位作为鉴别阈值。

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