Inoue Masaaki, Sano Toshiko, Watai Ryousuke, Ashikaga Ryuuichirou, Ueda Kazuki, Watatani Masahiro, Nishimura Yasumasa
Department of Radiology, Kinki University School of Medicine, 377-2 Ohno-Higashi, Osaka-Sayama, Osaka 589-8511, Japan.
AJR Am J Roentgenol. 2003 Sep;181(3):679-86. doi: 10.2214/ajr.181.3.1810679.
We sought to analyze the features of breast tumors as revealed on dynamic multidetector CT (MDCT), to develop descriptors for these features, and to compare the performance of MDCT with the performance of other techniques used in the depiction of tumors. SUBJECTS AND METHODS. MDCT was performed in 149 women with suspected breast tumors, and 173 breast lesions were detected. These breast lesions were classified as either mass or nonmass enhancing lesions. For mass lesions, the margin, shape, and enhancement patterns were evaluated. For nonmass enhancing lesions, the distribution of enhancement and the types of time-density curve patterns were evaluated. MDCT was compared with mammography and sonography as a method of revealing breast tumors.
Of the 173 breast lesions detected, 150 were mass lesions, 131 (87%) of which were malignant. Of the 23 nonmass enhancing lesions, 21 (91%) were malignant. The most highly predictive features for lesion malignancy were an irregular margin (100%), an irregular shape (99%), and rim enhancement (100%). Similar features were the most accurate signs of malignancy--a spiculated and irregular margin (90%). On time-density curves, the washout and plateau patterns showed high positive predictive value (93%) and sensitivity (91%) for malignancy. However, these patterns had low negative predictive value (42%) and specificity (48%). Seven breast lesions that could not be detected on mammography or sonography were identified on MDCT. MDCT more accurately revealed the margin of the tumor invasion in 11 breast tumors than did mammography or sonography.
The features revealed on MDCT can help to distinguish benign lesions from carcinomas. MDCT can add to the data obtained with mammography or sonography in patients with suspected breast tumors.
我们试图分析动态多排螺旋CT(MDCT)所显示的乳腺肿瘤特征,开发这些特征的描述符,并比较MDCT与用于肿瘤描绘的其他技术的性能。对象与方法。对149例疑似乳腺肿瘤的女性进行了MDCT检查,共检测到173个乳腺病变。这些乳腺病变分为肿块型或非肿块型强化病变。对于肿块型病变,评估其边缘、形态和强化模式。对于非肿块型强化病变,评估强化分布和时间-密度曲线模式类型。将MDCT与乳腺X线摄影和超声检查作为揭示乳腺肿瘤的方法进行比较。
在检测到的173个乳腺病变中,150个为肿块型病变,其中131个(87%)为恶性。在23个非肿块型强化病变中,21个(91%)为恶性。病变恶性的最具预测性特征是边缘不规则(100%)、形态不规则(99%)和边缘强化(100%)。类似特征是恶性的最准确征象——毛刺状和不规则边缘(90%)。在时间-密度曲线上,廓清型和平台型对恶性病变显示出较高的阳性预测值(93%)和敏感性(91%)。然而,这些模式的阴性预测值(42%)和特异性(48%)较低。在MDCT上发现了7个乳腺X线摄影或超声检查未能检测到的乳腺病变。MDCT比乳腺X线摄影或超声检查更准确地显示了11个乳腺肿瘤的肿瘤侵犯边缘。
MDCT所显示的特征有助于区分良性病变和癌。对于疑似乳腺肿瘤的患者,MDCT可以补充乳腺X线摄影或超声检查所获得的数据。