Application of dynamic contrast-enhanced MRI in differentiating malignant from benign ovarian tumors

LI Haiming; QIANG Jinwei; MA Fenghua; ZHAO Shuhui; XIA Ganlin; FENG Feng

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Application of dynamic contrast-enhanced MRI in differentiating malignant from benign ovarian tumors

更新时间：2025-12-15

- Application of dynamic contrast-enhanced MRI in differentiating malignant from benign ovarian tumors
- Vol. 25, Issue 1, Pages: 66-70(2016)
- 作者机构：
  
  1. 复旦大学附属金山医院影像科,上海,201508
  2. 江苏省南通市肿瘤医院放射科,江苏,南通,226361
  3. 复旦大学附属妇产科医院放射科,上海,200011
  4. 上海交通大学医学院附属新华医院放射科,上海,200092
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published Online：04 May 2016，
  
  Published：04 May 2016
- 稿件说明：
移动端阅览
李海明,强金伟,马风华,等. 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(1): 66-70
DOI：

李海明,强金伟,马风华,等. 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(1): 66-70 DOI：

摘要

目的：

探讨动态增强MRI(dynamic contrast-enhanced MRI，DCE-MRI)对卵巢良恶性肿瘤的诊断和鉴别诊断价值。

方法：

回顾性分析经手术和病理证实、含有实质成分的86例卵巢良恶性肿瘤(良性15个、恶性71个)的DCE-MRI资料。评价标准包括时间-强度曲线(time-intensity curve，TIC)类型(分为Ⅰ、Ⅱ、Ⅲ型)和3项半定量参数：增强幅度(enhancement amplitude，EA)、最大斜率(maximal slope，MS)及达峰值一半时间(time of half rising，THR)，比较良恶性肿瘤的差异。

结果：

恶性肿瘤中，TIC Ⅲ型59例(83%)、Ⅱ型12例(17%)，未见Ⅰ型；良性肿瘤中，TIC Ⅰ型5例(33%)、Ⅱ型10例(67%)，未见Ⅲ型；TIC类型在良恶性肿瘤中差异有统计学意义(

＜0.001)。恶性肿瘤的平均EA及MS值均大于良性肿瘤[(267.486.2)

.(220.290.5)，(11.06.3)

.(6.14.7)，

值分别为0.05和＜0.001

]

，而THR值则低于良性肿瘤[(32.87.6)s

. (55.515.4)s，

＜0.001)

]

。THR值是诊断效能最高的指标，受试者工作特性曲线的曲线下面积为89%。当THR＜45 s时，诊断灵敏度、特异度、准确率、阳性和阴性预测值分别为94%、80%、92%、96%和75%。

结论：

DCE-MRI的TIC类型及其3个半定量参数有助于卵巢良恶性肿瘤的鉴别。

Abstract

Objective:

To investigate the value of dynamic contrast-enhanced MRI (DCE-MRI) in the differential diagnosis of ovarian malignant and benign tumors.

Methods:

DCE-MRI data of 86 ovarian tumors with solid compositions (benign 15

malignant 71) confirmed by surgery and pathology were retrospectively analyzed. The patterns (Ⅰ

Ⅱ and Ⅲ) of time-intensity curve

(TIC) and three semi-quantitative parameters including enhancement amplitude (EA)

maximal slope (MS) and time of half rising (THR) were evaluated and compared between ovarian benign and malignant tumors.

Results:

Among malignant ovarian tumors

59 (83%) were type Ⅲ

12 (17%) were type Ⅱ

and no type Ⅰ. Among benign ovarian tumors

5 (33%) were typeⅠ

10 (67%) were type II

and no type Ⅲ. There was significant difference in TIC pattern between benign and malignant tumors (

0.001). The mean values of EA and MS in malignant ovarian tumors were significantly higher than those in benign tumors [(267.486.2)

. (220.290.5)

(11.06.3)

. (6.14.7);

=0.05 and

0.001

respectively

]

. Whereas the mean value of THR in malignant tumors was significantly lower than that in benign tumors [(32.87.6) s

. (55.515.4) s;

0.001

]

. THR was the best diagnostic indicator among three semiquantitative parameters

and the area under the receiver operating characteristic (ROC) curve was 89%. When the cutoff value of THR was 45 s

the sensitivity

specificity

accuracy

positive and negative predictive values were 94%

80%

92%

96% and 75%

respectively.

Conclusion:

TIC patterns and semi-quantitative parameters of DCE-MRI are helpful in distinguishing malignant from benign ovarian tumors.

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