非前列腺实体瘤脑转移的psma靶向PET成像:系统综述。

IF 3.5 3区 医学 Q2 ONCOLOGY
Frontiers in Oncology Pub Date : 2025-03-17 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1553505
Sara Dall' Armellina, Gayane Aghakhanyan, Alessio Rizzo, Salvatore C Fanni, Giacomo Aringhieri, Lorenzo Faggioni, Dania Cioni, Emanuele Neri, Duccio Volterrani, Silvia Morbelli
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引用次数: 0

摘要

前列腺特异性膜抗原(PSMA)是一种跨膜糖蛋白,最初在前列腺癌(PCa)中发现,但也在各种实体肿瘤的新生血管中表达。最近,PSMA PET已成为一种有前途的工具,用于检测非前列腺癌的脑转移(BMs),除了传统的成像之外,还提供了诊断能力。本系统综述评估了psma靶向放射性药物在脑转移成像中的作用,强调了它们的比较诊断性能,并探索了它们在治疗应用中的潜力。方法:按照PRISMA指南对文献进行系统回顾。包括评估PSMA PET成像在鉴别非前列腺实体瘤脑转移(BMs)诊断准确性的研究。完整的研究文章和病例报告都被认为涵盖了当前证据的广度。使用QUADAS-2工具评估纳入研究的方法学质量,并对数据进行定性综合。结果:本综述包括23项研究,报告了77例来自不同原发恶性肿瘤的脑转移,包括肺、乳腺、唾液腺、甲状腺、肾脏和黑色素瘤。与传统成像方式(如对比增强MRI和[18F]FDG PET)相比,PSMA PET显示出高肿瘤与背景比(TBR),能够更好地检测脑转移。在放疗后病例中,PSMA PET能有效区分放射性坏死与肿瘤复发。此外,与传统的闪烁成像方法相比,PSMA PET在检测甲状腺转移方面表现出更高的灵敏度,这突出了其在标准技术无法产生结论性结果的情况下的潜力。结论:PSMA PET成像在改善非前列腺癌脑转移的诊断和治疗方面具有重要的前景。虽然其治疗应用仍未得到充分探索,但初步发现表明,将PSMA PET整合到个性化神经肿瘤治疗中有希望的途径。未来的研究应侧重于标准化成像方案,探索PSMA PET在不同肿瘤亚型中的应用,并验证其在临床决策中的作用,以最大限度地提高其对患者预后的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PSMA-targeted PET imaging for brain metastases from non-prostatic solid tumors: a systematic review.

Introduction: Prostate-Specific Membrane Antigen (PSMA) is a transmembrane glycoprotein initially identified in prostate cancer (PCa) but also expressed in the neovasculature of various solid tumors. Recently, PSMA PET has emerged as a promising tool for detecting brain metastases (BMs) from non-prostatic cancers, offering diagnostic capabilities in addition to conventional imaging. This systematic review evaluates the role of PSMA-targeted radiopharmaceuticals in imaging BMs, highlighting their comparative diagnostic performance and exploring their potential for theranostic applications.

Methods: A systematic review of the literature was conducted following PRISMA guidelines. Studies evaluating the diagnostic accuracy of PSMA PET imaging in identifying brain metastases (BMs) from non-prostatic solid tumors were included. Both full research articles and case reports were considered to capture the breadth of current evidence. The methodological quality of the included studies was assessed using the QUADAS-2 tool, and data were synthesized qualitatively.

Results: The review includes 23 studies reporting on 77 BMs from diverse primary malignancies, including lung, breast, salivary gland, thyroid, kidney, and melanoma. PSMA PET demonstrated high tumor-to-background ratios (TBR), enabling superior detection of BMs compared to conventional imaging modalities such as contrast-enhanced MRI and [18F]FDG PET. In post-radiotherapy cases, PSMA PET effectively differentiated radionecrosis from tumor recurrence. Moreover, PSMA PET demonstrated superior sensitivity in detecting thyroid metastases compared to traditional scintigraphy methods, highlighting its potential in cases where standard techniques yield inconclusive results.

Conclusions: PSMA PET imaging shows significant promise in improving the diagnosis and management of BMs from non-prostatic cancers. While its theranostic applications remain underexplored, initial findings suggest promising avenues for integrating PSMA PET into personalized neuro-oncology care. Future studies should focus on standardizing imaging protocols, exploring PSMA PET utility in diverse tumor subtypes, and validating its role in clinical decision-making to maximize its impact on patient outcomes.

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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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