Proton MR spectroscopy and the detection of malignancy in ovarian masses

质子磁共振波谱法在卵巢肿块恶性肿瘤检测中的应用

阅读:2

Abstract

OBJECTIVE: To assess the impact of MR spectroscopy (MRS) on the detection of malignancy in ovarian masses. METHODS: This prospective work included 230 females that had 245 adnexal/ovarian masses. Tumours were spotted by preliminary pelvic ultrasound. Masses assessed by MRI, multi- or single-voxel spectroscopy. Patients' spectra were assessed for peaks of lactate (Lac, 1.31 ppm), lipid (Lip, 1.33 ppm), N-acetyl aspartate (2.0 ppm), acetone (A, 2.05 ppm), choline (Cho, 3.23 ppm) and creatinine (Cr, 3.4 ppm) and the mean values of the (Cho/Cr) ratios were performed by a semi-quantitative approach. The operative pathology served as the standard of reference. RESULTS: Cho peak twofold higher than the average noise level was detected in 72% of the malignant and only 5.4% of the benign masses with an accuracy of 83%. Adding lactate to the choline enhanced the accuracy to 93%. The mean Cho/Cr ratios of the malignant ovarian masses (2.8) were significantly higher than that of the benign ones (1.2) . We used a receiver operating characteristic curve to determine the best cut-off value (1.7) for the mean Cho/Cr ratio to discriminate malignancy with sensitivity: 81.2%, specificity: 93.3 %, positive-predictive value: 92.9 %, negative-predictive value: 82.4% and accuracy: 87.1%. CONCLUSION: The simultaneous presence of choline and lactate peaks in MRS examination of the ovarian masses minimizes the overlap between benign and malignant categories. N-acetyl aspartate and acetone are the metabolites for diagnosing complex cystic masses as benign teratoma, endomterioma and tubo- ovarian abscess. ADVANCES IN KNOWLEDGE: MRS is a non-contrast based and fast MR sequence that gives an idea about tissue components could be used to improve the sensitivity and the accuracy of detecting malignancy in ovarian masses.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。