磁敏感成像判断大鼠肝细胞癌病理分级的价值

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目的探讨磁敏感成像(SWI)技术判断肝细胞癌(HCC)病理分级的可行性。方法建立大鼠HCC模型后,行SWI检查。完成扫描后处死大鼠,取相应病灶行病理学检查,以Edmondson-Steiner分级法作为划分HCC病理分级的标准。比较低级别和高级别HCC的瘤内磁敏感信号强度(intratumoral susceptibility signal intensity,ITSS)特征的差异,并探索ITSS特征对HCC病理分级的判断价值。结果成功建立48只大鼠HCC模型,最终纳入分析的HCC病灶共32个,包括低级别18个(低级别组)和高级别14个(高级别组)。2组的ITSS出现率比较差异无统计学意义(P=0.113);2组的ITSS构成成分不同(P=0.002),低级别组HCC的ITSS构成主要是微血管,而高级别组HCC的ITSS构成以出血为主。此外,2组的ITSS在肿瘤内所占比例也不同(P<0.001),高级别组的ITSS在肿瘤内所占比例高于低级别组。当ITSS在肿瘤内所占比例得分为2分时,即至少有1个层面所占比例≥50%时,ROC曲线下面积最大,此时其灵敏度和特异度分别为85.7%(95%CI:74.9%~96.5%)及94.4%(95%CI:83.6%~100%),曲线下面积为0.917。结论 SWI能够评价HCC内的ITSS特征,并有助于区分低级别与高级别HCC。 Objective To investigate the feasibility of magnetic susceptibility imaging (SWI) to determine the pathological grade of hepatocellular carcinoma (HCC). Methods After establishment of rat model of HCC, SWI examination was performed. After the completion of the scan, the rats were sacrificed and pathological examination was performed on the corresponding lesions. The Edmondson-Steiner grading method was used as a standard to classify the pathological grading of HCC. To compare the difference of intratumoral susceptibility signal intensity (ITSS) features between low-grade and high-grade HCC, and to explore the value of ITSS in judging the pathological grade of HCC. RESULTS: Forty-eight rat HCC models were successfully established. A total of 32 HCC lesions were finally included in the analysis, including 18 in the low-grade group (low-grade group) and 14 in the high-grade group (high-grade group). There was no significant difference in ITSS incidence between the two groups (P = 0.113). The two groups had different ITSS components (P = 0.002). The ITSS of the low-grade HCC was mainly composed of microvessels, while the ITSS of the high-grade HCC Mainly to bleeding. In addition, the proportion of ITSS in the two groups was also different (P <0.001), and the proportion of ITSS in the high-grade group was higher in the tumor than in the lower-grade group. When the ITSS score in the tumor was 2 points, ie, at least 1 level accounted for 50% or more, the area under the ROC curve was the largest with a sensitivity and specificity of 85.7% (95% CI: 74.9% -96.5%) and 94.4% (95% CI: 83.6% -100%) respectively. The area under the curve was 0.917. Conclusion SWI can evaluate the ITSS features in HCC and help to distinguish between low-grade and high-grade HCC.
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