Impact of dynamic contrast-enhanced MRI in 1.5 T versus 3 T MRI for clinically significant prostate cancer detection

European Journal of Radiology(2022)

引用 3|浏览28
暂无评分
摘要
Purpose This study analyzes the value of dynamic contrast-enhanced MRI (DCE) of the prostate on 1.5 T and 3 T examinations in patients within PI-RADS category 4. Methods In this retrospective, bi-centric, cohort study all consecutive patients classified as PI-RADS 4 in mpMRI with 100 verified prostate cancers (PCa) in subsequent MRI/US-guided fusion biopsy were included for 1.5 T and 3 T, each. PCa detection in index lesions (IL) upgraded to PI-RADS 4 based on positive DCE findings was compared between 1.5 T and 3 T. Secondary objectives are subgroup analysis of PZ lesions and comparison of ISUP grade group distribution between 1.5 T and 3 T. Results In total, 293 patients within PI-RADS category 4, including 152 (mean 66 ± 8y; median PSA 6.4 ng/ml;116 PZ IL) in the 1.5 T group and 141 (mean 65 ± 8y; median PSA 7.2 ng/ml;100 PZ IL) in the 3 T group were included. Overall amount of PCa (66 % vs 71 %; p = 0.346) and portion of upgraded IL (28 % vs 21 %; p = 0.126) did not differ significantly. At 1.5 T PCa detection was higher in upgraded PZ lesions compared to 3 T (23 % vs 14 %; p = 0.048). The amount of upgraded PZ lesions with ISUP grade group 2–5 PCa was significantly higher at 1.5 T versus 3 T (13.8 % vs 4.0 %; p = 0.007). 33 % (11/33; 1.5 T) and 32 % (10/31; 3 T) of the ISUP grade group 1 PCa of the PZ lesions were detected in upgraded lesions (10% of all PZ index lesions, respectively). Conclusion DCE enabled the detection of a substantial amount of additional clinically significant PCa in prostate mpMRI at 1.5 T. The effect was smaller at 3 T and was accompanied in relation to 1.5 T by higher risk of overdiagnosis due to detection of additional low-risk PCa.
更多
查看译文
关键词
Prostatic Neoplasms,Multiparametric Magnetic Resonance Imaging,Dynamic contrast enhanced imaging,Magnetic Resonance Imaging, Interventional
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要