摘要
目的：探讨超声图像对卵巢恶性肿瘤诊断与鉴别诊断的价值与病理诊断符合率。方法：选择手术切除的卵巢恶性肿瘤患者185例，术前应用超声显像检测卵巢恶性肿瘤的声像图特征，并与术后病理诊断做对照。结果：本组185例患者共195个肿瘤，超声表现为囊性6个（6/195），占3%；囊实性141个（141/195），占72.3%；实性48个（48/195），占24.7%；血管分布特点为在肿瘤隔或实质成分的内部呈多血管弥漫分布，以束状、树枝状或彩球状血管网为主，实质中心部出现2～3级杂乱血流；与术后病理诊断符合率为95.7％。结论：超声图像对卵巢恶性肿瘤的诊断符合率较高，具有重要诊断价值，育龄妇女妇检时应常规进行卵巢超声检查。
Abstract
Objective: To study the value of the ultrasonography in the diagnosis and differential diagnosis of malignant ovarian tumors and the coincidence rate with pathological diagnosis. Methods: 185 patients with ovarian malignant tumor got resection. The ultrasonographic characteristics of ovarian malignant tumors before surgery were reviewed and correlated with pathological results after surgery. Results: A total of 185 patients with 195 tumors were collected into this study. Ultrasound showed cystic lesions in 6 (6/195), accounted for 3%; cystic-solid lesions in 141(141/195), accounted for 72.3%; mainly solid 48(48/195), accounted for 24.7%; the ultrasonic characteristics of ovarian malignant tumors were correlated with the postoperative pathological diagnosis. In malignant ovarian tumor there was rich vascular supply, multiple-vascellum distributed diffusively in the tumor or internal parenchymal ingredients, demonstrated as fasciculation, dendritic or ball shape vascular network, 2~3 grade disorder bloodstream in the center of parenchymal, the coincidence rate of the image features with postoperative pathological diagnosis was 95.7%. Conclusion: The coincidence rate of the ultrasound images of ovarian malignant tumors is high. Ultrasonography has important diagnostic value, women in reproductive age should carry out routine ovarian ultrasound inspection regularly.
关键词
卵巢肿瘤 /
超声检查 /
多普勒 /
彩色
Key words
Ovarian neoplasms /
Ultrasonography /
Doppler /
color
池秀玲;余彩茶;张品南;滕 慧;焦 岩;张 雯;袁吟迅.
卵巢恶性肿瘤的超声声像图特征与病理特点[J]. 中国临床医学影像杂志. 2014, 25(9): 642-644
CHI Xiu-ling;YU Cai-cha;ZHANG Pin-nan;TENG Hui;JIAO Yan;ZHANG Wen;YUAN Yin-xun.
The ultrasonographic features and pathological characteristics of ovarian malignant tumor[J]. Journal of China Clinic Medical Imaging. 2014, 25(9): 642-644
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