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首页> 外文期刊>Chinese journal of academic radiology. >Multiparametric prostate MRI and structured reporting: benefits and challenges in the PI-RADS era
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Multiparametric prostate MRI and structured reporting: benefits and challenges in the PI-RADS era

机译：多参数前列腺MRI和结构化报告：Pi-Rads时代的好处和挑战

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Prostate cancer (PCa) is the second most frequent cancer diagnosis in men and the sixth leading cause of cancer death worldwide with increasing numbers globally. Therefore, differentiated diagnostic imaging and risk-adapted therapeutic approaches are warranted. Multiparametric magnetic resonance imaging (mpMRI) of the prostate supports the diagnosis of PCa and is currently the leading imaging modality for PCa detection, characterization, local staging and image-based therapy planning. Due to the combination of different MRI sequences including functional MRI methods such as diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI), mpMRI enables a high sensitivity and specificity for the detection of PCa. The rising demand for individualized treatment strategies requires methods to ensure reproducibility, completeness, and quality of prostate MRI report data. The PI-RADS (Prostate Imaging Reporting and Data System) 2.1 classification represents the classification system that is internationally recommended for MRI-based evaluation of clinically significant prostate cancer. PI-RADS facilitates clinical decision-making by providing clear reporting parameters based on clinical evidence and expert consensus. Combined with software-based solutions, structured radiology reports form the backbone to integrate results from radiomics analyses or Al-applications into radiological reports and vice versa. This review provides an overview of imaging methods for PCa detection and local staging while placing special emphasis on mpMRI of the prostate. Furthermore, the article highlights the benefits of software-based structured PCa reporting solutions implementing PI-RADS 2.1 for the integration of structured data into decision support systems, thereby paving the way for workflow automation in radiology.
机译：前列腺癌（PCA）是男性中第二大最常见的癌症诊断，是全球范围内癌症死亡的第六个主要原因，全球人数增加。因此，有必要进行区分诊断成像和适应风险的治疗方法。前列腺的多参数磁共振成像（MPMRI）支持PCA的诊断，目前是PCA检测，表征，局部分期和基于图像的治疗计划的领先成像方式。由于不同的MRI序列（包括功能性MRI方法）的组合，例如扩散加权成像（DWI）和动态对比增强MRI（DCE-MRI），MPMRI可以对检测PCA的检测具有高灵敏度和特异性。对个性化治疗策略的需求不断上升，需要方法来确保前列腺MRI报告数据的可重复性，完整性和质量。 PI-RADS（前列腺成像报告和数据系统）2.1分类代表了国际建议的分类系统，用于基于MRI的临床意义前列腺癌评估。 PI-RADS通过根据临床证据和专家共识提供明确的报告参数来促进临床决策。结合基于软件的解决方案，结构化放射学报告构成了将放射线分析或al-Applications的结果整合到放射学报告中的主链，反之亦然。这篇综述提供了用于PCA检测和局部分期的成像方法的概述，同时特别强调了前列腺的mpmri。此外，本文强调了基于软件的结构化PCA报告解决方案实施PI-RADS 2.1将结构化数据集成到决策支持系统中的好处，从而为放射学中的工作流程自动化铺平了道路。

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