MR扩散加权成像在宫颈癌诊断和分期中的应用价值  被引量:24

Application value of MR diffusion weighted imaging in diagnosis and staging of uterine cervical cancer

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作  者:周忠洁[1] 王小蓉[1] 赵晓君[1] 严志汉[1] 陈博[1] 蔡志胜[1] 

机构地区:[1]温州医科大学附属第二医院放射科,浙江温州325000

出  处:《医学影像学杂志》2013年第11期1752-1755,共4页Journal of Medical Imaging

摘  要:目的探讨磁共振扩散加权成像(DWI)在宫颈癌诊断的敏感性、分期的准确性及盆腔淋巴结转移的检出率和定性准确率中的应用价值。方法回顾性分析经术后病理证实的98例宫颈癌患者的影像资料,比较DWI联合常规MRI序列与单纯常规MRI序列在宫颈癌诊断、分期及盆腔淋巴结转移方面的差异。结果 DWI联合常规MRI序列对Ib期的漏诊率(1/20)低于单纯常规MRI序列漏诊率(5/20)。DWI联合常规MRI序列对IIb期分期准确率(21/23)高于单纯常规MRI序列准确率(14/23);其余各期分期,两者无明显差异。DWI联合常规MRI序列对盆腔淋巴结转移的检出率(135/148)和定性准确率(76/82)均高于单纯常规MRI序列的检出率(101/148)和定性准确率(56/82)。结论相对于常规MRI序列,DWI联合常规MRI序列对宫颈癌的诊断更敏感,IIb期分期更准确,盆腔淋巴结检出率和定性准确率更可靠。Objective To investigate the application value of MR diffusion weighted imaging (DWI) in diagnostic sensi- tivity, staging accuracy, detective rate and qualitative accuracy of pelvic metastatic lymph nodes of uterine cervical cancer (UCC). Methods Radiology materials of 98 cases of UCC diagnosed by postoperative pathology were analysed retrospec- tively and differences between DWI combined with routine MRI sequences and routine MRI sequences alone in UCC were compared. Results The misdiagnostic rate (1/20) of DWI combined with routine MRI sequences was lower than that (5/ 20) of routine MRI sequences alone. Accuracy (21/23) of DWI combined with routine MRI sequences in Iib-stage staging was higher than that (14/23) of routine MRI sequences alone; No significant differences were found in other stages" stag ing. Both detective rate (135/148) and qualitative accuracy (76/82) of DWI combined with routine MRI sequences in pel- vic metastatic lymph nodes were higher than that (101/148) and (56/82) of routine MRI sequences alone. Conclusion Compared with routine sequences, DWI combined with routine MRI sequences is more sensitive in diagnosis of UCC, more accurate in staging of IIb-stage, more reliable in detective rate and qualitative accuracy of pelvic metastatic lymph nodes.

关 键 词:宫颈癌 磁共振成像 扩散加权成像 

分 类 号:R737.3[医药卫生—肿瘤] R445.2[医药卫生—临床医学]

 

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