目的：探讨肝细胞癌（Hepatocellular carcinoma，HCC）微血管浸润（Microvascular Invasion，MVI）的CT、MRI影像特征。方法：分析68例经手术病理证实的HCC患者的资料，术前行CT或MRI平扫及动态增强扫描，两名资深放射学专家对边缘模糊征象（局部外凸结节、局部包膜不完整、多结节融合、瘤内新月征）、瘤内动脉和低密度/信号环征象（Two-trait predictor of venous invasion，TTPVI）、门脉分支癌栓（Portal vein tumor thrombosis，PVTT）及弥散系数（Apparent diffusion coefficient，ADC）值进行观察判定，分析影像征象与病理上HCC微血管浸润的相关性，并采用受试者工作曲线（Receiver operator characteristics，ROC）比较边缘模糊、TTPVI以及PVTT对MVI的诊断性能。结果：两名资深放射学专家在判定影像征象上具有较一致的吻合率（K值均＞0.8）。边缘模糊、TTPVI及PVTT征象均与MVI的存在具有显著的相关性（P<0.001，P<0.001，P=0.037）；在ADC值分析中，MVI病灶组的ADC平均值明显小于非MVI病灶组（P<0.001）；在两位观察者的ROC曲线比较中，边缘模糊与TTPVI征象对MVI的判定性能均显著高于PVTT征象（P<0.001，P<0.001；P<0.001，P<0.001）。结论：HCC的CT及MR影像征象中，边缘模糊、TTPVI、PVTT以及ADC值等对判定MVI具有较明显的临床价值。
Abstract
Objective: To discuss the correlation between various imaging features and microvascular invasion(MVI) in hepatocellular carcinoma(HCC) by using CT and MR image. Methods: Sixty-eight HCC cases confirmed by pathology underwent CT and MR examinations. Two radiologists independently reviewed radiologic images to evaluate the following features for MVI: maximum diameter, tumor margins, two-trait predictor of venous invasion(TTPVI), portal vein tumor thrombosis(PVTT) and apparent diffusion coefficient(ADC). The correlation was analyzed for prediction of MVI based on imaging features of CT and MR. The receiver operator characteristics(ROC) curve was carried out to compare the diagnostic performance for non-smooth tumor margins, TTPVI and PVTT. Results: There were excellent agreement value of the two observes(all K value>0.8). Nonsmooth tumor margins, TTPVI and PVTT were all significantly related with MVI(P<0.001); The average ADC value of MVI group was significantly higher the non-MVI group(P<0.001); The area under ROC(AUROC) of nonsmooth margins and TTPVI were both significant higher than that of PVTT(P<0.001, respectively) according to observe 1 and 2. Conclusion: Nonsmooth tumor margins, TTPVI, PVTT and ADC value are high accuracy in the prediction of MVI in HCC.
关键词
肝肿瘤 /
体层摄影术 /
X线计算机 /
磁共振成像
Key words
Liver neoplasms /
Tomography, X-ray computed /
Magnetic resonance imaging
中图分类号：
Ｒ735.7
Ｒ814.42
Ｒ445.2
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1]Torre LA, Bray F, Siegel RL, et al. Global cancer statistics[J]. CA Cancer J Clin, 2015, 65(2): 87-108.
[2]Sumie S, Kuromatsu R, Okuda K, et al. Microvascular invasion in patients with hepatocellular carcinoma and its predictable clinicopathological factors[J]. Ann Surg Oncol, 2008, 15(5): 1375-1382.
[3]Lee EC, Kim SH, Park H, et al. Survival analysis after liver resection for hepatocellular carcinoma: A consecutive cohort of 1 002 patients[J]. J Gastroenterol Hepatol, 2017, 32(5): 1055-1063.
[4]Sumie S, Nakashima O, Okuda K, et al. The significance of classifying microvascular invasion in patients with hepatocellular carcinoma[J]. Ann Surg Oncol, 2014, 21(3): 1002-1009.
[5]晏耀文，饶圣祥，俞梦勇. 扩散加权成像在预测肝细胞肝癌微血管浸润的价值[J]. 临床放射学杂志，2016，35（1）：93-95.
[6]Wang WT, Yang L, Yang ZX, et al. Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging[J]. Radiology, 2017, 286(2): 571-580.
[7]Renzulli M, Brocchi S, Cucchetti A, et al. Can Current Preoperative Imaging Be Used to Detect Microvascular Invasion of Hepatocellular Carcinoma?[J]. Radiology, 2016, 279(2): 432-442.
[8]Chou CT, Chen RC, Lin WC, et al. Prediction of microvascular invasion of hepatocellular carcinoma: preoperative CT and histopathologic correlation[J]. AJR, 2014, 203(3): W253-W259.
[9]Segal E, Sirlin CB, Ooi C, et al. Decoding global gene expression programs in liver cancer by noninvasive imaging[J]. Nat Biotechnol, 2007, 25(6): 675-680.
[10]Bruix J, Gores GJ, Mazzaferro V. Hepato-cellular carcinoma: clinical frontiers and perspectives[J]. Gut, 2014, 63(5): 844-855.
[11]Llovet JM, Schwartz M, Mazzaferro V. Resection and liver transplantation for hepatocellular carcinoma[J]. Semin Liver Dis, 2005, 25(2): 181-200.
[12]Miyata R, Tanimoto A, Wakabayashi G, et al. Accuracy of preoperative prediction of microinvasion of portal vein in hepatocellular carcinoma using superparamagnetic iron oxide-enhanced magnetic resonance imaging and computed tomography during hepatic angiography[J]. J Gastroenterol, 2006, 41(10): 987-995.
[13]Zimmerman MA, Ghobrial RM, Tong MJ, et al. Recurrence of hepatocellular carcinoma following liver transplantation: a review of preoperative and postoperative prognostic indicators[J]. Arch Surg, 2008, 143(2): 182-188.
[14]Roayaie S, Blume IN, Thung SN, et al. A system of classifying microvascular invasion to predict outcome after resection in patients with hepatocellular carcinoma[J]. Gastroenterology, 2009, 137(3): 850-855.
[15]Chou CT, Chen RC, Lee CW, et al. Prediction of microvascular invasion of hepatocellular carcinoma by pre-operative CT imaging[J]. Br J Radiol, 2012, 85(1014): 778-783.
[16]Xu PJ, Yan FH, Wang JH, et al. Added value of breathhold diffusion-weighted MRI in detection of small hepatocellular carcinoma lesions compared with dynamic contrast-enhanced MRI alone using receiver operating characteristic curve analysis[J]. J Magn Reson Imaging, 2009, 29(2): 341-349.
[17]Park MJ, Kim YK, Lee MW, et al. Small hepatocellular carcinomas: improved sensitivity by combining gadoxetic acid-enhanced and diffusion-weighted MR imaging patterns[J]. Radiology, 2012, 264(3): 761-770.
[18]Suh YJ, Kim MJ, Choi JY, et al. Preoperative prediction of the microvascular invasion of hepatocellular carcinoma with diffusion-weighted imaging[J]. Liver Transpl, 2012, 18(10): 1171-1178.
PDF(1371 KB)
