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扩散加权成像在乳腺良恶性病变鉴别诊断中的价值 被引量:5

Value of Diffusion Weighted Imaging on the Diagnosis and Differential Diagnosis of Breast Diseases
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摘要 目的:探讨扩散加权成像(DWI)在乳腺疾病定性诊断中的作用。方法:对65例患者行MRI检查,扫描序列包括T1WI和T2WI平扫、DWI(选用b值为800和1000s/mm2)及动态增强(DCE)。结果:65例患者共发现68处病灶,其中恶性肿瘤37个,良性病灶31个,所有病例均经病理证实。b值为800和1000s/mm2时,ADC值大小排列顺序均为恶性肿瘤<良性病灶<正常腺体<囊肿。在这两种b值下,正常腺体、良性病灶及恶性肿瘤的ADC值两两比较均有统计学意义,同一类型组织的ADC值也均有统计学意义,且正常腺体和恶性肿瘤间差异有显著性意义。b值为800s/mm2、ADC值为0.734×10-3~0.760×10-3s/mm2时,以及b值为1000s/mm2,ADC值为0.724×10-3~0.752×10-3s/mm2时,DWI对恶性肿瘤的敏感度均可达到90%。结论:DWI在乳腺疾病的定性诊断中有较大优势,B值在800和1000s/mm2之间时,DWI能够较好地鉴别各类病灶。 Objective.. To investigate the value of diffusion weighted imaging (DWI) in the diagnosis and differential diagnosis of breast lesions. Methods: 65 patients were enrolled in the study. T1WI, T2WI, DWI and DCE-MRI were performed in order. B values of DWI were selected as 800 and 1000s/mm^2. Results:68 lesions were detected in the 65 patients, including 37 malignant tumors and 31 benign lesions. All the cases were verified by pathology. ADC values ranged as malignant tumor 〈 benign lesion 〈 normal tissue〈 cyst under the B values of both 800 and 1000s/mm^2. All the differences between malignant tumors and benign lesions, benign lesions and normal tissues, as well as normal tissues and malignant tumors under the two B values had statistical difference. Differences of the same tissues under the two B values also showed statistical significance. When ADC value is set between 0. 734 and 0. 760×10^-3 s/mm^2 under the B value of 800s/mm^2 ,sensitivity to Malignant tumors is 90% ;and when ADC value is set between 0. 724 and 0. 752×10^-3s/mm^2 under the B value of 1000s/mm^2 ,the same sensitivity can be obtained. Conclusion:DWI is advantageous in qualitative diagnosis of breast lesions. When B value is set between 800 and 1000s/mm^2 ,DWI can effectively differentiate different types of breast lesions.
出处 《放射学实践》 2007年第12期1262-1265,共4页 Radiologic Practice
关键词 乳腺肿瘤 乳腺疾病 磁共振成像 扩散加权成像 Breast neoplasms Breast diseases Magnetic resonance imaging Diffusion weighted imaging
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