前列腺癌(prostate cancer,PCa)是全球男性中患病最多、致死率第二高的癌症.PCa神经微环境与肿瘤进展、手术根治程度及术后复发密切相关,但具体机制尚不明确.神经微环境中的神经密度(neural density,ND)、神经周围侵袭(perineural invasion,PNI)以及神经内分泌特征(neuroendocrine features,NEF)与TMPRSS2 ERG基因、单胺氧化酶A(monoamine oxidase A,MAOA)、核因子κB,神经营养因子以及神经肽Y(neuropeptide Y,NPY)等的表达密切相关.挖掘与该基因组学及蛋白组学相关的影像标志物可以早期识别PCa神经微环境从而影响临床诊疗方案.基于多参数磁共振成像(multiparameter magnetic resonance imaging,mp-MRI)影像组学特征可以识别PNI及NEF的潜在影像标志物.基于磁粒子成像技术(magnetic particle imaging,MPI)、深度神经网络(deep neural network,DNN)图像分类模型可以进行神经可视化.新兴神经影像技术弥散张量成像(diffusion tensor imaging,DTI)、扩散频谱成像(diffusion spectrum imaging,DSI)、神经突定向扩散与密度成像(neurite orientation dispersion and density imaging,NODDI)以及基于吩噁嗪的近红外荧光团的设计合成与神经成像技术,在显示及预测ND、PNI、NEF也蕴含着独特的价值.本文就PCa患者神经微环境潜在影像标志物的研究现状进行综述,以进一步揭示PCa神经微环境的神经生理机制,为后续诊疗过程及改善患者预后提供影像学依据.
Current status of potential magnetic resonance imaging markers in the neural microenvironment in prostate cancer patients
Prostate cancer (PCa) is the most prevalent and second deadliest cancer among men worldwide. The neural microenvironment of PCa is closely related to tumor progression,surgical curative degree,and postoperative recurrence,but the specific mechanism is not yet clear. The neural density (ND),perineural invasion (PNI),and neuroendocrine features (NEF) in the neural microenvironment are closely related to the expression of TMPRSS2 ERG gene,monoamine oxidase A (MAOA),nuclear factor kappa B,neurotrophic factors,and neuropeptide Y (NPY). Exploring imaging biomarkers related to genomics and proteomics can early identify the PCa neural microenvironment and affect clinical diagnosis and treatment plans. Based on the imaging omics features of multi-parameter magnetic resonance imaging (mp-MRI),potential imaging biomarkers for PNI and NEF can be identified. Neural visualization can be performed based on magnetic particle imaging (MPI) and deep neural network (DNN) image classification models. Emerging neuroimaging technologies such as diffusion tensor imaging (DTI),diffusion spectrum imaging (DSI),neurite orientation diffusion and density imaging (NODDI),and the design,synthesis,and neuroimaging of near-infrared fluorophores based on phenoxazine also hold unique value in displaying and predicting ND,PNI,and NEF. This article reviews the current research status of potential imaging biomarkers in the neural microenvironment of PCa patients,in order to further reveal the neurophysiological mechanisms of the PCa neural microenvironment and provide imaging evidence for subsequent diagnosis and treatment processes and improving patient prognosis.
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