Li Yujia, Li Jian, Yang Jinhui, Xiao Ling, Zhou Ming, Cai Yi, Rominger Axel, Shi Kuangyu, Seifert Robert, Gao Xiaomei, Tang Yongxiang, Hu Shuo
Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Department of Urology, Disorders of Prostate Cancer Multidisciplinary Team, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Eur J Nucl Med Mol Imaging. 2025 Feb;52(3):913-924. doi: 10.1007/s00259-024-06949-7. Epub 2024 Oct 15.
The diagnostic evaluation of men with suspected prostate cancer (PCa) yet inconclusive MRI (PI-RADS ≤ 3) presents a common clinical challenge. [Ga]Ga-labelled prostate-specific membrane antigen ([Ga]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.
This study retrospective included 151 men with clinical suspicion of PCa and PI-RADS ≤ 3 MRI. All men underwent [Ga]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.
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.
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.
对于疑似前列腺癌（PCa）但MRI结果不确定（PI-RADS≤3）的男性进行诊断评估是一项常见的临床挑战。[镓]镓标记的前列腺特异性膜抗原（[镓]镓-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。我们旨在建立一个纳入PSMA-PET的诊断模型，以加强对PI-RADS≤3男性中csPCa的诊断过程。
本研究回顾性纳入了151例临床怀疑患有PCa且PI-RADS≤3 MRI的男性。所有男性均接受了[镓]镓-PSMA PET/CT扫描以及超声/MRI/PET融合引导下的活检。csPCa被定义为分级组≥2。对PSMA-PET扫描的PRIMARY评分进行了评估。开发了一个纳入PSMA-PET和前列腺特异性抗原（PSA）衍生参数的诊断模型。将其判别性能和临床实用性与传统方法进行了比较。使用五重交叉验证和1000次迭代进行内部验证。
在这个PI-RADS≤3队列中，PRIMARY评分、SUVmax和常规临床PSMA-PET评估检测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）。与基于PRIMARY评分或SUVmax的策略相比，包含PRIMARY评分、SUVmax和血清游离PSA/总PSA（fPSA/tPSA）的诊断模型实现了显著更高的AUC，为0.906（95%CI，0.851-0.961）（P<0.05），并且明显优于通常基于PSA密度的传统策略（P<0.001）。1000次迭代的平均五重交叉验证AUC为0.878（95%CI，0.820-0.954）。理论上，使用21.6%的阈值，该模型可以在该队列中避免78%的不必要活检，同时仅漏诊7.8%的csPCa病例。
已开发并验证了一种新的诊断模型，该模型纳入了PSMA-PET衍生指标——PRIMARY评分和SUVmax——以及血清fPSA/tPSA。与单个传统指标相比，该综合模型可以提高诊断准确性，辅助临床决策。它在减少PI-RADS≤3 MRI结果男性的不必要活检方面具有巨大潜力，值得进一步进行前瞻性和外部评估。
