Hata K, Akiba S, Hata T, Miyazaki K
Department of Obstetrics and Gynecology, Shimane Medical University, Izumo, Japan.
Gynecol Oncol. 1998 Mar;68(3):256-62. doi: 10.1006/gyno.1998.4947.
Our objective was to improve the preoperative diagnosis of ovarian malignancy using a multivariate logistic regression analysis on the basis of demographic, serologic, gray-scale morphological, and Doppler variables.
One hundred seventy-one patients with ovarian tumors (120 benign, 51 malignant including 9 tumors of low malignant potential) were studied with transvaginal B-mode, color, and pulsed Doppler ultrasonography before surgery. Based on the gray-scale ultrasound imaging, each tumor was classified as a unilocular cyst, multilocular cyst, unilocular cyst with solid parts, multilocular cyst with solid parts, or solid tumor. Intratumoral blood flow velocity waveforms were recorded on all tumors except unilocular cyst and were evaluated for resistance index (RI) and peak systolic velocity (PSV). Serum CA 125 levels were also measured.
Twenty tumors were unilocular cysts and were all benign. Seventy tumors including all unilocular cysts which showed no flows were all benign. The remaining 101 tumors (50 benign, 51 malignant including 9 tumors of low malignant potential) presented intratumoral blood flows. Univariate and multivariate logistic regression analyses were conducted to identify variables predictive of ovarian malignancy in these 101 tumors. The variables included age, menstrual state, serum CA 125 levels, B-mode classification, RI, and PSV. In univariate analysis, menopause, the positivity of CA 125 (> or = 35 U/ml), and PSV larger than or equal to 10.4 cm/s were found to be significantly associated with malignant tumors. The PSV value of 10.4 cm/s was the median in benign tumors. Multivariate analysis showed that serum CA 125 levels (> or = 35 U/ml) (P = 0.002) and PSV (> or = 10.4 cm/s) (P < 0.001) were to be independent predictors of malignancy.
These results suggest that intratumoral PSV is the strongest means of differentiating benign from malignant ovarian tumors with suspicious gray-scale ultrasonographic findings.
我们的目的是基于人口统计学、血清学、灰阶形态学和多普勒变量，通过多因素逻辑回归分析来改善卵巢恶性肿瘤的术前诊断。
对171例卵巢肿瘤患者（120例良性，51例恶性，包括9例低恶性潜能肿瘤）在手术前进行经阴道B型、彩色和脉冲多普勒超声检查。根据灰阶超声成像，将每个肿瘤分类为单房囊肿、多房囊肿、有实性部分的单房囊肿、有实性部分的多房囊肿或实性肿瘤。除单房囊肿外，记录所有肿瘤的瘤内血流速度波形，并评估阻力指数（RI）和收缩期峰值速度（PSV）。同时测量血清CA 125水平。
20个肿瘤为单房囊肿，均为良性。70个肿瘤包括所有无血流的单房囊肿均为良性。其余101个肿瘤（50例良性，51例恶性，包括9例低恶性潜能肿瘤）呈现瘤内血流。对这101个肿瘤进行单因素和多因素逻辑回归分析，以确定预测卵巢恶性肿瘤的变量。变量包括年龄、月经状态、血清CA 125水平、B型分类、RI和PSV。单因素分析发现，绝经状态、CA 125阳性（≥35 U/ml）以及PSV大于或等于10.4 cm/s与恶性肿瘤显著相关。10.4 cm/s的PSV值是良性肿瘤的中位数。多因素分析显示，血清CA 125水平（≥35 U/ml）（P = 0.002）和PSV（≥10.4 cm/s）（P < 0.001）是恶性肿瘤的独立预测因素。
这些结果表明，对于灰阶超声检查结果可疑的卵巢肿瘤，瘤内PSV是区分良性与恶性的最强有力手段。
