Diagnostic accuracy of a five-point Likert scoring system for magnetic resonance imaging (MRI) evaluated according to results of MRI/ultrasonography image-fusion targeted biopsy of the prostate

根据前列腺磁共振成像/超声图像融合靶向活检的结果,评估五分制李克特评分系统在磁共振成像(MRI)诊断中的准确性

阅读:1

Abstract

OBJECTIVE: To evaluate the accuracy of a magnetic resonance imaging (MRI)-based Likert scoring system in the detection of clinically significant prostate cancer (CSPC), using MRI/ultrasonography (US) image-fusion targeted biopsy (FTB) as a reference standard. PATIENTS AND METHODS: We retrospectively reviewed 1218 MRI-detected lesions in 629 patients who underwent subsequent MRI/US FTB between October 2012 and August 2015. 3-Tesla MRI was independently reported by one of eight radiologists with varying levels of experience and scored on a five-point Likert scale. All lesions with Likert scores 1-5 were prospectively defined as targets for MRI/US FTB. CSPC was defined as Gleason score ≥7. RESULTS: The median patient age was 64 years, PSA level 6.97 ng/mL and estimated prostate volume 52.2 mL. Of 1218 lesions, 48% (n = 581) were rated as Likert 1-2, 35% (n = 428) were Likert 3 and 17% (n = 209) were Likert 4-5. For Likert scores 1-5, the overall cancer detection rates were 12%, 13%, 22%, 50% and 59%, respectively, and the CSPC detection rates were 4%, 4%, 12%, 33% and 48%, respectively. Grading using the five-point scale showed strong positive correlation with overall cancer detection rate (r = 0.949, P = 0.05) and CSPC detection rate (r = 0.944, P = 0.05). By comparison, in Likert 4-5 lesions, significant differences were noted in overall cancer detection rate (63% vs 35%; P = 0.001) and CSPC detection rate (47% vs 29%; P = 0.027) for the more experienced vs the less experienced radiologists. CONCLUSIONS: The detection rates of overall cancer and CSPC strongly correlated with the five-point grading of the Likert scale. Among radiologists with different levels of experience, there were significant differences in these cancer detection rates.

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。