动态增强MRI时间信号强度曲线在卵巢良恶性肿瘤鉴别中的价值
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摘要
目的探讨动态增强MRI时间信号强度曲线(TIC)鉴别卵巢肿瘤良恶性的价值。方法收集2016年1月—2017年8月间于我院超声检查发现盆腔附件肿块的71例女性病人,年龄14～78岁,中位年龄52岁。所有病人行MRI常规及动态增强检查后经手术获得病理结果。利用工作站在肿块实性区和正常子宫外肌层设置兴趣区获取TIC,以子宫外肌层强化曲线为基准,对卵巢肿块实性区的TIC类型进行校正,分析曲线类型与良恶性卵巢肿瘤的关系。采用χ~2检验比较良恶性肿瘤间3种TIC类型差异。结果 71例病人中包括卵巢恶性肿瘤40例,良性肿瘤26例,交界性肿瘤5例。上述3种肿瘤的TIC类型的差异有统计学意义(P<0.05)。良性肿瘤以Ⅰ型TIC为主(73.1%),恶性肿瘤以Ⅲ型TIC为主(77.5%)。MRI+TIC鉴别肿瘤良恶性的敏感度、特异度、阳性预测值和阴性预测值较单独常规MRI检查各指标均有不同程度提高。结论动态增强MRI及其TIC对卵巢良恶性肿瘤具有重要的鉴别诊断价值。
Objective To investigate the value of time-signal intensity curve(TIC) derived from dynamic contrastenhanced(MRI) in the differentiation of benign and malignant ovarian tumors. Methods Seventy-one female patients(median age 52 years, range 14 to 78 years) with adnexal masses were evaluated in our study. The diagnosis was established based on ultrasound findings in our hospital during January 2016 to August 2017, and was confirmed by surgery and pathology. All female patients underwent routine MRI and dynamic contrast-enhanced MRI scanning. The TIC was acquired by setting the region of interest in the solid mass and the normal myometrium on workstation, and the types of TIC in the solid area of the ovarian tumors were corrected based on the myometrial enhancement curves. The correlation between TIC urve types and malignances of ovarian tumors were analyzed. Three TIC types of benign and malignant tumors were compared by chi-square test. Results The 71 patients included 40 cases with malignant ovarian cancers, 26 benign tumors and 5 borderline tumors. The TIC type was significantly different among the three types of ovarian tumors(P<0.005). The type Ⅰ curve was the main type in the benign group(73.1%), and the type Ⅲ curves in the malignant group(77.5%). The diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of MRI +TIC were all higher than those of routine MRI. Conclusion Dynamic contrast-enhanced MRI and TIC have important value in the differential diagnosis of malignant and benign ovarian tumors.
Objective To investigate the value of time-signal intensity curve(TIC) derived from dynamic contrastenhanced(MRI) in the differentiation of benign and malignant ovarian tumors. Methods Seventy-one female patients(median age 52 years, range 14 to 78 years) with adnexal masses were evaluated in our study. The diagnosis was established based on ultrasound findings in our hospital during January 2016 to August 2017, and was confirmed by surgery and pathology. All female patients underwent routine MRI and dynamic contrast-enhanced MRI scanning. The TIC was acquired by setting the region of interest in the solid mass and the normal myometrium on workstation, and the types of TIC in the solid area of the ovarian tumors were corrected based on the myometrial enhancement curves. The correlation between TIC urve types and malignances of ovarian tumors were analyzed. Three TIC types of benign and malignant tumors were compared by chi-square test. Results The 71 patients included 40 cases with malignant ovarian cancers, 26 benign tumors and 5 borderline tumors. The TIC type was significantly different among the three types of ovarian tumors(P<0.005). The type Ⅰ curve was the main type in the benign group(73.1%), and the type Ⅲ curves in the malignant group(77.5%). The diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of MRI +TIC were all higher than those of routine MRI. Conclusion Dynamic contrast-enhanced MRI and TIC have important value in the differential diagnosis of malignant and benign ovarian tumors.
引文
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[2]Kurmanr J,Carcangiu ML,Herrington CS,et al.WHO classification of tumors of female reproductive organs[M].Lyon:IARC,2014
[3]Mohaghegh P,Rockall AG.Imaging strategy forearly ovarian cancer:characterization of adnexal masses withconventional and advanced imaging techniques[J].Radiographics,2012,32:1751-1773.
[4]Kido A,Fujimoto K,Okada T,et al.Advanced MRI in malignant neoplasms of the uterus[J].J Magn Reson Imaging,2013,37:249-264.
[5]Li HM,Qiang JW,Ma FH,et al.The value of dynamic contrast-enhanced MRI in characterizing complex ovarian tumors[J].J Ovarian Res,2017,10:4.
[6]Petrillo A,Fusco R,Petrillo M,et al.DCE-MRI time-intensity curve visual inspection to assess pathological response after neoadjuvant therapy in locally advanced rectal cancer[J].Jpn J Radiol,2018,36:611-621.
[7]Thomassin-Naggara I,Dara觙E,Cuenod CA,et al Dynamic contrastenhanced magnetic resonance imaging:a useful tool for characterizing ovarian epithelial tumors[J].J Magn Reson Imaging,2008,28:111-120.
[8]李海明,强金伟.动态增强MRI在卵巢良恶性肿瘤鉴别中的价值[J].肿瘤影像学,2016,25:66-70.
[9]路丽,季倩,沈文.动态增强MRI对卵巢肿瘤的诊断价值及研究进展[J].国际医学放射学杂志,2014,37:130-133.
[10]袁涛,全冠民.卵巢肿瘤的高场功能MRI应用研究进展[J].国际医学放射学杂志,2015,38:143-147.
[11]Carter JS,Koopmeiners JS,Kuehn-Hajder JE,et al Quantitative multiparametric MRI of ovarian cancer[J].J Magn Reson Imaging,2013,38:1501-1509.
[12]何东峰,马大庆,靳二虎.动态增强MRI在鉴别乳腺良、恶性肿瘤和提示恶性肿瘤病理分级中的作用[J].中华放射学杂志,2012,46:1075-1078.
[13]方俊华,闵祥德,冯朝燕,等.磁共振灌注加权成像定量参数在前列腺外周带前列腺癌鉴别诊断中的价值[J].磁共振成像,2015,6:136-140.
[14]Patel N,Harris AL,Gleeson FV,et al.Clinical imaging of tumor angiogenesis[J].Future Oncol,2012,8:1443-1459.
[15]Kim DH,Sung B,Kim JA,et al.High VEGF serum values are associated with locoregional spread of gastroenteropancreatic neuroendocrine tumors(GEP-NETs)[J].Int J Oncol,2017,51:715-723.
[16]Guo XL,Li D,Sun K,et al.Inhibition of autophagy enhances anticancer effects of bevacizumab in hepatocarcinoma[J].J Mol Med(Berl),2013,91:473-483.
[17]Bennani-Baiti B.Baltzer PA.MR Imaging for diagnosis of malignancy in mammographic microcalcifcations:a systematic review and Meta-analysis[J].Radiology,2017,283:692-701.
[18]Thomassin-Naggara I,Aubert E,Rockall A,et al.Adnexal masses:development and preliminary validation of an MR imaging scoring system[J].Radiology,2013,267:432-443.
[19]Kazerooni AF,Malek M,Haghighatkhah H,Semiquantitative dynamic contrast-enhanced MRI for accurate classification of complex adnexal masses[J].J Magn Reson.Imaging,2017,45:418-427.
[20]Khalifa F,Soliman A,El-Baz A,et al.Models and methods for analyzing DCE-MRI:a review[J].Med Phys,2014,17:124-143.
[21]Kandukuri SR,Rao J.FIGO 2013 staging system for ovarian cancer:whatis new in comparison to the 1988 staging system[J].Curr Opin Obstet Gynecol,2015,27:48-52.
[22]郭永梅,黄云海,魏新华,等.3.0 T动态增强磁共振对卵巢肿瘤的半定量及定量分析研究[J].磁共振成像,2015,6:782-786.
[23]Dhanda S,Thakur M,Kerkar R,et al,Diffusion-weighted imaging of gynecologic tumors:diagnostic pearls and potential pitfalls[J].Radiographics,2014,34:1393-1416.
[24]Forstner R,Meissnitzer M,Cunha TM.Update on imaging of ovarian cancer[J].Curr Radiol Rep,2016,4:31.
[25]Van Calster B,Van Hoorde K,Valentin L,et al.Evaluating the risk of ovarian cancer before surgeryusing the ADNEX model to differentiate between benign,borderline,early and advanced stage invasive,and secondary metastatic tumours:prospective multicentre diagnostic study[J].BMJ,2014,349:g5920.
[26]Mansour SM,Saraya S,El-faissal Y.Semi-quantitative contrastenhanced MR analysis of indeterminate ovarian tumours:when to say malignancy[J].Br J Radiol,2015.DOI:10.1259/bjr.20150099.