Differentiation of malignant tumours from granulomas by using dynamic [(18)F]-fluoro-L-α-methyltyrosine positron emission tomography

利用动态[(18)F]-氟-L-α-甲基酪氨酸正电子发射断层扫描鉴别恶性肿瘤和肉芽肿

阅读:1

Abstract

BACKGROUND: Previous clinical studies have revealed the potential of [(18)F]-fluoro-L-α-methyltyrosine ((18)F-FAMT) for the differential diagnosis of malignant tumours from sarcoidosis. However, one concern regarding the differential diagnosis with (18)F-FAMT is the possibility of false negatives given the small absolute uptake of (18)F-FAMT that has been observed in some malignant tumours. The aim of this study was to evaluate a usefulness of dynamic (18)F-FAMT positron emission tomography (PET) for differentiating malignant tumours from granulomas. METHODS: Rats bearing both granulomas (Mycobacterium bovis bacillus Calmette-Guérin (BCG)-induced) and tumours (C6 glioma cell-induced) underwent dynamic 2-deoxy-2-[(18)F]-fluoro-D-glucose ((18)F-FDG) PET and (18)F-FAMT PET for 120 min on consecutive days. Time-activity curves, static images, mean standardized uptake values (SUVs) and the SUV ratios (SUVRs; calculated by dividing SUV at each time point by that of 2 min after injection) were assessed. RESULTS: In tumours, (18)F-FAMT showed a shoulder peak immediately after the initial distribution followed by gradual clearance compared with granulomas. Although the mean SUV in the tumours (1.00 ± 0.10) was significantly higher than that in the granulomas (0.88 ± 0.12), a large overlap was observed. In contrast, the SUVR was markedly higher in tumours than in granulomas (50 min/2 min, 0.72 ± 0.06 and 0.56 ± 0.05, respectively) with no overlap. The dynamic patterns, SUVR, and mean SUV of (18)F-FDG in the granulomas were comparable to those in the tumours. CONCLUSIONS: Dynamic (18)F-FAMT and SUVR analysis might compensate for the current limitations and help in improving the diagnostic accuracy of (18)F-FAMT.

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。