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癌症正电子发射断层成像技术的进展。

Advances in PET imaging of cancer.

机构信息

Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University of Tübingen, Tübingen, Germany.

Nuclear Medicine and Clinical Molecular Imaging, Department of Radiology, Eberhard Karls University of Tübingen, Tübingen, Germany.

出版信息

Nat Rev Cancer. 2023 Jul;23(7):474-490. doi: 10.1038/s41568-023-00576-4. Epub 2023 May 31.

Abstract

Molecular imaging has experienced enormous advancements in the areas of imaging technology, imaging probe and contrast development, and data quality, as well as machine learning-based data analysis. Positron emission tomography (PET) and its combination with computed tomography (CT) or magnetic resonance imaging (MRI) as a multimodality PET-CT or PET-MRI system offer a wealth of molecular, functional and morphological data with a single patient scan. Despite the recent technical advances and the availability of dozens of disease-specific contrast and imaging probes, only a few parameters, such as tumour size or the mean tracer uptake, are used for the evaluation of images in clinical practice. Multiparametric in vivo imaging data not only are highly quantitative but also can provide invaluable information about pathophysiology, receptor expression, metabolism, or morphological and functional features of tumours, such as pH, oxygenation or tissue density, as well as pharmacodynamic properties of drugs, to measure drug response with a contrast agent. It can further quantitatively map and spatially resolve the intertumoural and intratumoural heterogeneity, providing insights into tumour vulnerabilities for target-specific therapeutic interventions. Failure to exploit and integrate the full potential of such powerful imaging data may lead to a lost opportunity in which patients do not receive the best possible care. With the desire to implement personalized medicine in the cancer clinic, the full comprehensive diagnostic power of multiplexed imaging should be utilized.

摘要

分子成像在成像技术、成像探针和对比剂开发以及数据质量领域,以及基于机器学习的数据分析方面都取得了巨大的进展。正电子发射断层扫描(PET)及其与计算机断层扫描(CT)或磁共振成像(MRI)的结合作为一种多模态 PET-CT 或 PET-MRI 系统,在单次患者扫描中提供了丰富的分子、功能和形态学数据。尽管最近技术取得了进步,并且有数十种针对特定疾病的对比剂和成像探针可用,但在临床实践中,仅使用少数参数(如肿瘤大小或平均示踪剂摄取量)来评估图像。多参数体内成像数据不仅高度定量,还可以提供有关生理学、受体表达、代谢或肿瘤形态和功能特征(如 pH 值、氧合或组织密度)以及药物药效动力学的宝贵信息,以使用对比剂来测量药物反应。它还可以进一步定量映射和空间解析肿瘤间和肿瘤内异质性,深入了解肿瘤对靶向治疗干预的脆弱性。如果不能充分利用和整合这些强大成像数据的全部潜力,患者可能无法获得最佳治疗效果。为了在癌症临床中实施个性化医疗,应该充分利用多重成像的全面诊断能力。

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