European Journal of Nuclear Medicine and Molecular Imaging ( IF 8.6 ) Pub Date : 2024-10-15 , DOI: 10.1007/s00259-024-06949-7 Yujia Li, Jian Li, Jinhui Yang, Ling Xiao, Ming Zhou, Yi Cai, Axel Rominger, Kuangyu Shi, Robert Seifert, Xiaomei Gao, Yongxiang Tang, Shuo Hu
Introduction
The diagnostic evaluation of men with suspected prostate cancer (PCa) yet inconclusive MRI (PI-RADS ≤ 3) presents a common clinical challenge. [68Ga]Ga-labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) positron emission tomography/computed tomography (PET/CT) has shown promise in identifying clinically significant PCa (csPCa). We aim to establish a diagnostic model incorporating PSMA-PET to enhance the diagnostic process of csPCa in PI-RADS ≤ 3 men.
Materials and Methods
This study retrospective included 151 men with clinical suspicion of PCa and PI-RADS ≤ 3 MRI. All men underwent [68Ga]Ga-PSMA PET/CT scans and ultrasound/MRI/PET fusion-guided biopsies. csPCa was defined as Grade Group ≥ 2. PRIMARY-scores from PSMA-PET scans were evaluated. A diagnostic model incorporating PSMA-PET and prostate-specific antigen (PSA)-derived parameters was developed. The discriminative performance and clinical utility were compared with conventional methods. Internal validation was conducted using a fivefold cross-validation with 1000 iterations.
Results
In this PI-RADS ≤ 3 cohort, areas-under-the-curve (AUCs) for detecting csPCa were 0.796 (95%CI, 0.738–0.853), 0.851 (95%CI, 0.783–0.918) and 0.806 (95%CI, 0.742–0.870) for PRIMARY-score, SUVmax and routine clinical PSMA-PET assessment, respectively. The diagnostic model comprising PRIMARY-score, SUVmax and serum free PSA/total PSA (fPSA/tPSA) achieved a significantly higher AUC of 0.906 (95%CI, 0.851–0.961) compared to strategies based on PRIMARY-score or SUVmax (P < 0.05) and markedly superior to conventional strategies typically based on PSA density (P < 0.001). The average fivefold cross-validated AUC with 1000 iterations was 0.878 (95%CI, 0.820–0.954). Theoretically, using a threshold of 21.6%, the model could have prevented 78% of unnecessary biopsies while missing only 7.8% of csPCa cases in this cohort.
Conclusions
A novel diagnostic model incorporating PSMA-PET derived metrics—PRIMARY-score and SUVmax—along with serum fPSA/tPSA, has been developed and validated. The integrated model may assist clinical decision-making with enhanced diagnostic accuracy over the individual conventional metrics. It has great potential to reduce unnecessary biopsies for men with PI-RADS ≤ 3 MRI results and warrants further prospective and external evaluations.
中文翻译:
使用基于 PSMA-PET 和 PSA 的新型模型来提高具有临床意义的前列腺癌的诊断准确性,并避免对 PI-RADS ≤ 3 MRI 男性进行不必要的活检
介绍
疑似前列腺癌 (PCa) 但 MRI (PI-RADS ≤ 3) 的男性的诊断评估是一个常见的临床挑战。[68加]Ga 标记的前列腺特异性膜抗原 ([68Ga]Ga-PSMA) 正电子发射断层扫描/计算机断层扫描 (PET/CT) 在识别具有临床意义的 PCa (csPCa) 方面显示出前景。我们的目标是建立一个结合 PSMA-PET 的诊断模型,以增强 3 名男性 PI-RADS ≤ csPCa 的诊断过程。
材料和方法
本研究回顾性研究纳入了 151 例临床疑似 PCa 和 PI-RADS ≤ 3 MRI 的男性。所有男性均接受了 [68Ga]Ga-PSMA PET/CT 扫描和超声/MRI/PET 融合引导活检。csPCa 被定义为 2 ≥ 级组。评估 PSMA-PET 扫描的 PRIMARY 评分。开发了一种包含 PSMA-PET 和前列腺特异性抗原 (PSA) 衍生参数的诊断模型。将鉴别性能和临床效用与传统方法进行比较。内部验证使用具有 1000 次迭代的 5 倍交叉验证进行。
结果
在这个 PI-RADS ≤ 3 队列中,检测 csPCa 的曲线下面积 (AUC) 分别为 0.796 (95%CI, 0.738–0.853)、0.851 (95%CI, 0.783–0.918) 和 0.806 (95%CI, 0.742–0.870) 对于主要评分、SUVmax 和常规临床 PSMA-PET 评估。与基于 PRIMARY 评分或 SUVmax 的策略相比,包括 PRIMARY 评分、SUVmax 和血清游离 PSA/总 PSA (fPSA/tPSA) 的诊断模型实现了 0.906 (95%CI,0.851–0.961) 的显著更高 AUC (P < 0.05),明显优于通常基于 PSA 密度的常规策略 (P < 0.001)。1000 次迭代的平均 5 倍交叉验证 AUC 为 0.878 (95% CI,0.820–0.954)。理论上,使用 21.6% 的阈值,该模型可以防止 78% 的不必要活检,同时在该队列中仅遗漏 7.8% 的 csPCa 病例。
结论
已经开发并验证了一种新的诊断模型,该模型结合了 PSMA-PET 衍生指标 — PRIMARY-score 和 SUVmax — 以及血清 fPSA/tPSA。该集成模型可以帮助临床决策,提高对单个常规指标的诊断准确性。它对 PI-RADS 男性的 3 ≤ MRI 结果减少不必要的活检具有巨大潜力,并需要进一步的前瞻性和外部评估。