Assessing the accuracy of Ga-68-PSMA PET/CT compared with MRI in the initial diagnosis of prostate malignancy: A cohort analysis of 114 consecutive patients

JOURNAL OF MEDICAL IMAGING AND RADIATION ONCOLOGY(2022)

引用 1|浏览0
暂无评分
摘要
Introduction Prostate cancer diagnosis is shifting towards a minimally invasive approach, maintaining accuracy and efficacy while reducing morbidity. We aimed to assess if PSMA-Ga68 PET/CT can accurately grade and localise prostatic malignancy using objective methods, compared with pathology and MRI. Methods Retrospective analysis on 114 consecutive patients undergoing staging PSMA PET/CT scans over 12 months was carried out. The SUVmax and site of highest PSMA activity within the prostate gland were recorded. Pathology/biopsy review assessed maximum Gleason score (and location). MRI analysis assessed the highest PIRADS score and location. The grade, location and size of malignant tissue on biopsy, and PSA, were correlated with the SUVmax and the PIRADS score. Results SUVmax was significantly elevated in cases with PSA >= 10 (P = 0.003) and Gleason score >= 8 (P = 0.0002). SUVmax demonstrated equivalent sensitivity to MRI-PIRADS in predicting Gleason >= 8 disease, with higher specificity when tested under a high-specificity regime (SUVmax >= 10, PIRADS = 5, P = 0.002). Furthermore, the region of highest SUVmax was superior to MRI-PIRADS for localising the highest grade tumour region, correctly identifying 71% of highest grade regions compared to 54% with MRI (P = 0.015). Conclusion PSMA PET/CT is as effective as MRI in identifying high-grade prostate malignancy. Our findings also support previous studies in showing a significant relationship between SUVmax and Gleason grade. These benefits, along with the known advantage in identifying distant metastases and the reduced cost, further support the argument that PSMA PET/CT should be offered as an initial investigation in the workup of prostate cancer.
更多
查看译文
关键词
Ga-68-PSMA PET, CT, cancer, MRI, prostate
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