核磁共振成像合并扩散加权成像在老年卵巢肿瘤中的诊断价值

Diagnostic value of MRI combined with diffusion-weighted imaging for ovarian tumors in the elderly

目的:研究核磁共振成像(MRI)和扩散加权成像(DWI)对老年卵巢肿瘤的诊断价值并讨论其临床意义。方法:回顾性分析2013年1月~2017年12月治疗的卵巢肿瘤患者130例,年龄60~78岁,手术前进行MRI及DWI扫描和CT检查。对卵巢肿瘤影像学表现和肿瘤表观弥散系数(ADC)值进行分析。以手术后组织病理学结果作为金标准,比较MRI及DWI与CT检查对卵巢肿瘤的诊断价值。结果:以组织病理学结果作为诊断依据,MRI诊断卵巢肿瘤良恶性的敏感性、特异性和准确性均明显高于CT检查(P<0.05),恶性卵巢肿瘤的ADC值(×10^-3mm^2/s)明显高于良性肿瘤(0.92±0.32vs1.52±0.31,P<0.05)。对卵巢肿瘤分期诊断的准确率,MRI及DWI也明显高于CT检查(89.2%vs80.0%,P<0.05)。结论:MRI及DWI对卵巢肿瘤良恶性、分期诊断的准确性明显高于CT检查,提示MRI及DWI对诊断老年卵巢肿瘤具有重要的临床意义。

Objective To study the value of magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in the diagnosis of ovarian tumors in the elderly,and to discuss its clinical significance.Methods A retrospective analysis was performed on the data of 130 patients who received treatment for ovarian tumors during January 2013 to December 2017.The patients aged from 60 to 78 years old.Before operation,all patients are scanned withMRI and DWI and received CT examination. The imaging findings and apparent diffusion coefficient (ADC) values of ovarian tumors were analyzed.Using the postoperative histopathological results as the gold standard,the values of MRI,DWI and CT in the diagnosis of ovarian tumors were evaluated. Results Based on the diagnostic criteria of histopathological results,the sensitivity,specificity and accuracy ofMRI in the diagnosis of benign and malignant ovarian tumors were significantly higher than those of CT (P<0.05).The ADC value (×10^-3 mm^2/s) of malignant ovarian tumors was significantly higher than that of benign ovarian tumors (0.92±0.32 vs 1.52±0.31,P<0.05).The accuracy rate ofMRI combined with DWI in the staging of ovarian tumors was significantly higher than that of CT (89.2%vs 80%, P<0.05).Conclusion The accuracy of MRI and DWI in the diagnosis of benign and malignant ovarian tumors is superior to that of CT,indicating thatMRI combined with DWI have important clinical significance in the diagnosis of ovarian tumors in the elderly.